Topic Editors

Department of Electronic Engineering, Universidad Politécnica de Madrid, 28040 Madrid, Spain
Département Mathématiques, Université de Reims Champagne-Ardenne, 51454 Reims, France

Wireless Sensor Networks

Abstract submission deadline
closed (31 December 2022)
Manuscript submission deadline
closed (31 March 2023)
Viewed by
155229

Topic Information

Dear Colleagues,

In the past couple of decades, wireless communications have expanded at an extraordinary rate, permeating every environment. The M2M paradigm is generally referred to by the more common term of the Internet of things (IoT), and both terms are sometimes used interchangeably. The IoT is generally described as a system of interconnected objects (things) that are capable of communicating with each other over the Internet without human active intervention. A key infrastructure that provides support to the IoT paradigm is wireless sensor networks (WSNs). WSNs consist of a set of spatially distributed electronic devices, commonly called nodes, deployed in an area of interest that collect and share information gained from their surroundings. Depending on the application, WSNs can have a varying number of sensor nodes, stretching from a few units to dozens or even hundreds.

The potential fields of application of WSNs are essentially aligned to those of the IoT paradigm, ranging from home automation to industry and manufacturing control, transportation, vehicular networking, agriculture, commerce, and health and body monitoring.

Nodes in a WSN are generally composed of at least four modules in charge of four main functions: sensing, communication, energy supply, and control.

Wireless Sensor Networks comprise a set of major components, including:

  • WSN platforms;
  • Wearable devices;
  • WSN data management;
  • Cross-layer design;
  • WSN architectures and protocol stack;
  • Authentication, data security, and protection;
  • WSN and artificial intelligence, edge computing;
  • Energy harvesting.

This Topic aims to collect the results of research in these Wireless Sensor Network scenarios, as well as the results of similar research. The submission of papers concerning areas with a strong connection to engineering and industrial and manufacturing applications is strongly encouraged.

Dr. Alvaro Araujo Pinto
Dr. Hacene Fouchal
Topic Editors

Keywords

  • wireless sensor networks
  • internet of things
  • IoT
  • artificial intelligence
  • smart sensors
  • intelligent sensors
  • WSAN
  • wireless sensor and actuator networks
  • wearables
  • energy harvesting
  • edge computing
  • cross-layer optimization
  • QoS for WSN
  • low-energy techniques
  • hardware platforms

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Applied Sciences
applsci
2.7 4.5 2011 16.9 Days CHF 2400
Electronics
electronics
2.9 4.7 2012 15.6 Days CHF 2400
Information
information
3.1 5.8 2010 18 Days CHF 1600
Journal of Sensor and Actuator Networks
jsan
3.5 7.6 2012 20.4 Days CHF 2000
Sensors
sensors
3.9 6.8 2001 17 Days CHF 2600
Chips
chips
- - 2022 15.0 days * CHF 1000

* Median value for all MDPI journals in the second half of 2023.


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Published Papers (68 papers)

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35 pages, 785 KiB  
Review
On Wireless Sensor Network Models: A Cross-Layer Systematic Review
by Fernando Ojeda, Diego Mendez, Arturo Fajardo and Frank Ellinger
J. Sens. Actuator Netw. 2023, 12(4), 50; https://doi.org/10.3390/jsan12040050 - 30 Jun 2023
Cited by 7 | Viewed by 3215
Abstract
Wireless sensor networks (WSNs) have been adopted in many fields of application, such as industrial, civil, smart cities, health, and the surveillance domain, to name a few. Fateway and sensor nodes conform to WSN, and each node integrates processor, communication, sensor, and power [...] Read more.
Wireless sensor networks (WSNs) have been adopted in many fields of application, such as industrial, civil, smart cities, health, and the surveillance domain, to name a few. Fateway and sensor nodes conform to WSN, and each node integrates processor, communication, sensor, and power supply modules, sending and receiving information of a covered area across a propagation medium. Given the increasing complexity of a WSN system, and in an effort to understand, comprehend and analyze an entire WSN, different metrics are used to characterize the performance of the network. To reduce the complexity of the WSN architecture, different approaches and techniques are implemented to capture (model) the properties and behavior of particular aspects of the system. Based on these WSN models, many research works propose solutions to the problem of abstracting and exporting network functionalities and capabilities to the final user. Modeling an entire WSN is a difficult task for researchers since they must consider all of the constraints that affect network metrics, devices and system administration, holistically, and the models developed in different research works are currently focused only on a specific network layer (physical, link, or transport layer), making the estimation of the WSN behavior a very difficult task. In this context, we present a systematic and comprehensive review focused on identifying the existing WSN models, classified into three main areas (node, network, and system-level) and their corresponding challenges. This review summarizes and analyzes the available literature, which allows for the general understanding of WSN modeling in a holistic view, using a proposed taxonomy and consolidating the research trends and open challenges in the area. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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18 pages, 3643 KiB  
Article
Improving Accuracy of Real-Time Positioning and Path Tracking by Using an Error Compensation Algorithm against Walking Modes
by Jiale Gong, Ziyang Li, Mingzhu Chen, Hong Wang and Dongmo Hu
Sensors 2023, 23(12), 5417; https://doi.org/10.3390/s23125417 - 7 Jun 2023
Viewed by 1697
Abstract
Wide-range application scenarios, such as industrial, medical, rescue, etc., are in various demand for human spatial positioning technology. However, the existing MEMS-based sensor positioning methods have many problems, such as large accuracy errors, poor real-time performance and a single scene. We focused on [...] Read more.
Wide-range application scenarios, such as industrial, medical, rescue, etc., are in various demand for human spatial positioning technology. However, the existing MEMS-based sensor positioning methods have many problems, such as large accuracy errors, poor real-time performance and a single scene. We focused on improving the accuracy of IMU-based both feet localization and path tracing, and analyzed three traditional methods. In this paper, a planar spatial human positioning method based on high-resolution pressure insoles and IMU sensors was improved, and a real-time position compensation method for walking modes was proposed. To validate the improved method, we added two high-resolution pressure insoles to our self-developed motion capture system with a wireless sensor network (WSN) system consisting of 12 IMUs. By multi-sensor data fusion, we implemented dynamic recognition and automatic matching of compensation values for five walking modes, with real-time spatial-position calculation of the touchdown foot, enhancing the 3D accuracy of its practical positioning. Finally, we compared the proposed algorithm with three old methods by statistical analysis of multiple sets of experimental data. The experimental results show that this method has higher positioning accuracy in real-time indoor positioning and path-tracking tasks. The methodology can have more extensive and effective applications in the future. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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22 pages, 608 KiB  
Article
Improving Energy Efficiency in LoRaWAN Networks with Multiple Gateways
by Ali Loubany, Samer Lahoud, Abed Ellatif Samhat and Melhem El Helou
Sensors 2023, 23(11), 5315; https://doi.org/10.3390/s23115315 - 3 Jun 2023
Cited by 2 | Viewed by 1579
Abstract
LoRaWAN has imposed itself as a promising and suitable technology for massive machine-type communications. With the acceleration of deployment, improving the energy efficiency of LoRaWAN networks has become paramount, especially with the limitations of throughput and battery resources. However, LoRaWAN suffers from the [...] Read more.
LoRaWAN has imposed itself as a promising and suitable technology for massive machine-type communications. With the acceleration of deployment, improving the energy efficiency of LoRaWAN networks has become paramount, especially with the limitations of throughput and battery resources. However, LoRaWAN suffers from the Aloha access scheme, which leads to a high probability of collision at large scales, especially in dense environments such as cities. In this paper, we propose EE-LoRa, an algorithm to improve the energy efficiency of LoRaWAN networks with multiple gateways via spreading factor selection and power control. We proceed in two steps, where we first optimize the energy efficiency of the network, defined as the ratio between the throughput and consumed energy. Solving this problem involves determining the optimal node distribution among different spreading factors. Then, in the second step, power control is applied to minimize the transmission power at nodes without jeopardizing the reliability of communications. The simulation results show that our proposed algorithm greatly improves the energy efficiency of LoRaWAN networks compared to legacy LoRaWAN and relevant state-of-the-art algorithms. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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14 pages, 2706 KiB  
Article
Energy-Efficient Algorithms for Path Coverage in Sensor Networks
by Zhixiong Liu and Wei Zhou
Sensors 2023, 23(11), 5026; https://doi.org/10.3390/s23115026 - 24 May 2023
Cited by 1 | Viewed by 825
Abstract
Path coverage attracts many interests in some scenarios, such as object tracing in sensor networks. However, the problem of how to conserve the constrained energy of sensors is rarely considered in existing research. This paper studies two problems in the energy conservation of [...] Read more.
Path coverage attracts many interests in some scenarios, such as object tracing in sensor networks. However, the problem of how to conserve the constrained energy of sensors is rarely considered in existing research. This paper studies two problems in the energy conservation of sensor networks that have not been addressed before. The first problem is called the least movement of nodes on path coverage. It first proves the problem as NP-hard, and then uses curve disjunction to separate each path into some discrete points, and ultimately moves nodes to new positions under some heuristic regulations. The utilized curve disjunction technique makes the proposed mechanism unrestricted by the linear path. The second problem is called the largest lifetime on path coverage. It first separates all nodes into independent partitions by utilizing the method of largest weighted bipartite matching, and then schedules these partitions to cover all paths in the network by turns. We eventually analyze the energy cost of the two proposed mechanisms, and evaluate the effects of some parameters on performance through extensive experiments, respectively. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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20 pages, 1080 KiB  
Article
Reliability Evaluation for Chain Routing Protocols in Wireless Sensor Networks Using Reliability Block Diagram
by Oruba Alfawaz, Ahmed M. Khedr, Bader Alwasel and Walid Osamy
J. Sens. Actuator Netw. 2023, 12(2), 34; https://doi.org/10.3390/jsan12020034 - 10 Apr 2023
Viewed by 1721
Abstract
There are many different fields in which wireless sensor networks (WSNs) can be used such as environmental monitoring, healthcare, military, and security. Due to the vulnerability of WSNs, reliability is a critical concern. Evaluation of a WSN’s reliability is essential during the design [...] Read more.
There are many different fields in which wireless sensor networks (WSNs) can be used such as environmental monitoring, healthcare, military, and security. Due to the vulnerability of WSNs, reliability is a critical concern. Evaluation of a WSN’s reliability is essential during the design process and when evaluating WSNs’ performance. Current research uses the reliability block diagram (RBD) technique, based on component functioning or failure state, to evaluate reliability. In this study, a new methodology-based RBD, to calculate the energy reliability of various proposed chain models in WSNs, is presented. A new method called D-Chain is proposed, to form the chain starting from the nearest node to the base station (BS) and to choose the chain head based on the minimum distance D, and Q-Chain is proposed, to form the chain starting from the farthest node from the BS and select the head based on the maximum weight, Q. Each chain has three different arrangements: single chain/single-hop, multi-chain/single-hop, and multi-chain/multi-hop. Moreover, we applied dynamic leader nodes to all of the models mentioned. The simulation results indicate that the multi Q-Chain/single-hop has the best performance, while the single D-Chain has the least reliability in all situations. In the grid scenario, multi Q-Chain/single-hop achieved better average reliability, 11.12 times greater than multi D-Chain/single-hop. On the other hand, multi Q-Chain/single-hop achieved 6.38 times better average reliability than multi D-Chain/single-hop, in a random scenario. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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12 pages, 2045 KiB  
Article
Passive Backscatter Communication Scheme for OFDM-IM with Dynamic Carrier Activation
by Shibao Li and Rui Lu
Sensors 2023, 23(8), 3841; https://doi.org/10.3390/s23083841 - 9 Apr 2023
Viewed by 1373
Abstract
Multicarrier backscattering has been proposed to improve the communication rate, but the complex circuit structure of multicarrier backscattering devices requires more power consumption, resulting in devices far away from the radio frequency (RF) source without enough power to maintain communication, which greatly reduces [...] Read more.
Multicarrier backscattering has been proposed to improve the communication rate, but the complex circuit structure of multicarrier backscattering devices requires more power consumption, resulting in devices far away from the radio frequency (RF) source without enough power to maintain communication, which greatly reduces the limited communication range in backscattering. To solve this problem, this paper introduces carrier index modulation (IM) into orthogonal frequency division multiplexing (OFDM) backscattering and proposes a dynamic subcarrier activated OFDM-IM uplink communication scheme suitable for passive backscattering devices. When the existing power collection level of the backscatter device is detected, only a subset of carrier modulation is activated using part of the circuit modules to reduce the power threshold required for device activation. The activated subcarriers are mapped by a block-wise combined index using the look-up table method, which can not only transmit information using traditional constellation modulation but also carry additional information through the frequency domain carrier index. Monte Carlo experiments show that this scheme can effectively increase the communication distance and improve the spectral efficiency of low-order modulation backscattering when the power of the transmitting source is limited. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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22 pages, 1260 KiB  
Article
Three Level Recognition Based on the Average of the Phase Differences in Physical Wireless Parameter Conversion Sensor Networks and Its Effect to Localization with RSSI
by Toshi Ito, Masafumi Oda, Osamu Takyu, Mai Ohta, Takeo Fujii and Koichi Adachi
Sensors 2023, 23(6), 3308; https://doi.org/10.3390/s23063308 - 21 Mar 2023
Cited by 3 | Viewed by 1354
Abstract
In recent years, there have been increased demands for aggregating sensor information from several sensors owing to the spread of the Internet of Things (IoT). However, packet communication, which is a conventional multiple-access technology, is hindered by packet collisions owing to simultaneous access [...] Read more.
In recent years, there have been increased demands for aggregating sensor information from several sensors owing to the spread of the Internet of Things (IoT). However, packet communication, which is a conventional multiple-access technology, is hindered by packet collisions owing to simultaneous access by sensors and waiting time to avoid packet collisions; this increases the aggregation time. The physical wireless parameter conversion sensor network (PhyC-SN) method, which transmits sensor information corresponding to the carrier wave frequency, facilitates the bulk collection of sensor information, thereby reducing the communication time and achieving a high aggregation success rate. However, when more than one sensor transmits the same frequency simultaneously, the estimation accuracy of the number of accessed sensors deteriorates significantly because of multipath fading. Thus, this study focuses on the phase fluctuation of the received signal caused by the frequency offset inherent to the sensor terminals. Consequently, a new feature for detecting collisions is proposed, which is a case in which two or more sensors transmit simultaneously. Furthermore, a method to identify the existence of 0, 1, 2, or more sensors is established. In addition, we demonstrate the effectiveness of PhyC-SNs in estimating the location of radio transmission sources by utilizing three patterns of 0, 1, and 2 or more transmitting sensors. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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27 pages, 18092 KiB  
Article
A Pipe-Embeddable Impedance Sensor for Monitoring Water Leaks in Distribution Networks: Design and Validation
by Danilo Aparecido Carnevale Castillo and Marco Carminati
Sensors 2023, 23(6), 3117; https://doi.org/10.3390/s23063117 - 14 Mar 2023
Cited by 1 | Viewed by 1917
Abstract
Water leakage is one of main problems of distribution infrastructures, reaching unacceptable peaks of 50% of water lost in old networks in several countries. In order to address this challenge, we present an impedance sensor able to detect small water leaks (below 1 [...] Read more.
Water leakage is one of main problems of distribution infrastructures, reaching unacceptable peaks of 50% of water lost in old networks in several countries. In order to address this challenge, we present an impedance sensor able to detect small water leaks (below 1 L of released volume). The combination of real-time sensing and such a sensitivity allows for early warning and fast response. It relies on a set of robust longitudinal electrodes applied on the external surface of the pipe. The presence of water in the surrounding medium alters its impedance in a detectable way. We report detailed numerical simulations for the optimization of electrode geometry and sensing frequency (2 MHz), as well as the successful experimental proof in the laboratory of this approach for a pipe length of 45 cm. Moreover, we experimentally tested the dependence of the detected signal on the leak volume, temperature, and morphology of the soil. Finally, differential sensing is proposed and validated as a solution to reject drifts and spurious impedance variations due to environmental effects. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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22 pages, 5388 KiB  
Article
Energy Efficient Routing Protocol for an IoT-Based WSN System to Detect Forest Fires
by Ramesh Babu Pedditi and Kumar Debasis
Appl. Sci. 2023, 13(5), 3026; https://doi.org/10.3390/app13053026 - 27 Feb 2023
Cited by 13 | Viewed by 2426
Abstract
Around a third of the world’s surface area is covered with forests. This is about 4–5 billion hectares of land. We are losing an additional 3 million hectares of forest cover each year than we did in 2001. Hence, researchers worldwide have been [...] Read more.
Around a third of the world’s surface area is covered with forests. This is about 4–5 billion hectares of land. We are losing an additional 3 million hectares of forest cover each year than we did in 2001. Hence, researchers worldwide have been working on the identification and prevention of forest fires more aggressively. The wireless sensor network technology for forest fire detection was established as a result of the shortcomings of standard forest fire detection techniques in real time. This paper proposes an energy-aware Internet of Things (IoT) based Wireless Sensor Network (WSN) model with an efficient clustering and routing technique for forest fire detection. The proposed model is named Energy Efficient Routing Protocol (EERP). The model decreases the energy utilization in sensor nodes by minimizing idle listening in cluster heads. EERP also minimizes the transmission of redundant data by allowing only the sensor nodes close to an event to report the event. Furthermore, the model ensures that sensor nodes with low energy levels do not become cluster heads. EERP uses multi-hop routes to send data from source nodes to the Base Station. The performance of EERP is compared with that of some existing Medium Access Control (MAC) protocols in various scenarios. The simulation results prove that the proposed model reduces energy consumption in sensor nodes significantly. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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18 pages, 6524 KiB  
Article
Integrated Probe System for Measuring Soil Carbon Dioxide Concentrations
by Sammy Hassan, Ryan M. Mushinski, Tilahun Amede, Gary D. Bending and James A. Covington
Sensors 2023, 23(5), 2580; https://doi.org/10.3390/s23052580 - 26 Feb 2023
Cited by 2 | Viewed by 2327
Abstract
This article outlines the design and implementation of an internet-of-things (IoT) platform for the monitoring of soil carbon dioxide (CO2) concentrations. As atmospheric CO2 continues to rise, accurate accounting of major carbon sources, such as soil, is essential to inform [...] Read more.
This article outlines the design and implementation of an internet-of-things (IoT) platform for the monitoring of soil carbon dioxide (CO2) concentrations. As atmospheric CO2 continues to rise, accurate accounting of major carbon sources, such as soil, is essential to inform land management and government policy. Thus, a batch of IoT-connected CO2 sensor probes were developed for soil measurement. These sensors were designed to capture spatial distribution of CO2 concentrations across a site and communicate to a central gateway using LoRa. CO2 concentration and other environmental parameters, including temperature, humidity and volatile organic compound concentration, were logged locally and communicated to the user through a mobile (GSM) connection to a hosted website. Following three field deployments in summer and autumn, we observed clear depth and diurnal variation of soil CO2 concentration within woodland systems. We determined that the unit had the capacity to log data continuously for a maximum of 14 days. These low-cost systems have great potential for better accounting of soil CO2 sources over temporal and spatial gradients and possibly flux estimations. Future testing will focus on divergent landscapes and soil conditions. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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19 pages, 1036 KiB  
Article
Optimal Resource Allocation for 5G Network Slice Requests Based on Combined PROMETHEE-II and SLE Strategy
by Sujitha Venkatapathy, Thiruvenkadam Srinivasan, Han-Gue Jo and In-Ho Ra
Sensors 2023, 23(3), 1556; https://doi.org/10.3390/s23031556 - 31 Jan 2023
Cited by 2 | Viewed by 2392
Abstract
The network slicing of physical infrastructure is required for fifth-generation mobile networks to make significant changes in how service providers deliver and defend services in the face of evolving end-user performance requirements. To perform this, a fast and secure slicing technique is employed [...] Read more.
The network slicing of physical infrastructure is required for fifth-generation mobile networks to make significant changes in how service providers deliver and defend services in the face of evolving end-user performance requirements. To perform this, a fast and secure slicing technique is employed for node allocation and connection establishment, which necessitates the usage of a large number of domain applications across the network. PROMETHEE-II and SLE algorithms were used in this study’s approach to network design for node allocation and link construction, respectively. The PROMETHEE-II approach takes into account a variety of node characteristics while constructing a node importance rank array (NIRA), including the node capacity, bandwidth of neighboring connections, degree of the node, and proximity centrality among others. The SLE method is proposed to record all possible link configurations for the network slice request (NSR) nodes to guarantee that the shortest path array (SPA) of the NSR has a high acceptance rate. Performance metrics such as the service revenue and acceptance ratio were considered to evaluate the effectiveness of the suggested approach. The effectiveness of network slicing has been further examined under different infrastructure models to determine whether a small-world network structure is beneficial to 5G network. For each scenario, simulations were carried out and the results were compared to previously published findings from other sources. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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16 pages, 8102 KiB  
Article
Optimal Configuration for Monitoring Stations in a Wireless Localisation Network Based on Received Signal Strength Differences
by Mehdi Eshagh
Sensors 2023, 23(3), 1150; https://doi.org/10.3390/s23031150 - 19 Jan 2023
Viewed by 1348
Abstract
A smart city is a city equipped with many sensors communicating with each other for different purposes. Cybersecurity and signal security are important in such cities, especially for airports and harbours. Any signal interference or attack on the navigation of autonomous vehicles and [...] Read more.
A smart city is a city equipped with many sensors communicating with each other for different purposes. Cybersecurity and signal security are important in such cities, especially for airports and harbours. Any signal interference or attack on the navigation of autonomous vehicles and aircraft may lead to catastrophes and risks in people’s lives. Therefore, it is of tremendous importance to develop wireless security networks for the localisation of any radio frequency interferer in smart cities. Time of arrival, angle of arrival, time-difference of arrivals, received signal strength and received signal strength difference (RSSD) are known observables used for the localisation of a signal interferer. Localisation means to estimate the coordinates of an interferer from some established monitoring stations and sensors receiving such measurements from an interferer. The main goal of this study is to optimise the geometric configuration of the monitoring stations using a desired dilution of precision and/or variance-covariance matrix (VCM) for the transmitter’s location based on the RSSD. The required mathematical models are developed and applied to the Arlanda international airport of Sweden. Our numerical tests show that the same configuration is achieved based on dilution of precision and VCM criteria when the resolution of design is lower than 20 m in the presence of the same constraints. The choice of the pathloss exponent in the mathematical models of the RSSDs is not important for such low resolutions. Finally, optimisation based on the VCM is recommended because of its larger redundancy and flexibility in selecting different desired variances and covariances for the coordinates of the transmitter. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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23 pages, 9789 KiB  
Article
Towards Sustainable Distributed Sensor Networks: An Approach for Addressing Power Limitation Issues in WSNs
by Alaa Alaerjan
Sensors 2023, 23(2), 975; https://doi.org/10.3390/s23020975 - 14 Jan 2023
Cited by 6 | Viewed by 1910
Abstract
Distributed wireless sensor networks (WSNs) have been implemented in multiple applications. Those networks are intended to support the quality of operations and enhance applications’ productivity and safety. WSNs are constructed of a large amount of sensor nodes that are battery powered. Typically, wireless [...] Read more.
Distributed wireless sensor networks (WSNs) have been implemented in multiple applications. Those networks are intended to support the quality of operations and enhance applications’ productivity and safety. WSNs are constructed of a large amount of sensor nodes that are battery powered. Typically, wireless sensors are deployed in complex terrain which makes battery replacement extremely difficult. Therefore, it is critical to adopt an energy sustainability approach to enhance the lifetime of each sensor node since each node contributes to the lifetime of the entire WSN. In this work, we propose an approach to reduce power consumption in wireless sensors. The approach addresses power reduction in a sensor node at the sensing level, as well as the communication level. First, we propose configuring the microcontroller of the sensor to conserve energy based on the performed tasks. Then, we implement an interface to reduce consumed power by the radio module. Based on the approach, we carried out field experiments and we measure the improvement of power-consumption reduction. The results show that the approach contributes to saving up to 50% of the wasted energy at the sensor node and it improves communication reliability especially when the number of sensors in a network scales. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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24 pages, 12551 KiB  
Article
Efficient WSN Node Placement by Coupling KNN Machine Learning for Signal Estimations and I-HBIA Metaheuristic Algorithm for Node Position Optimization
by Bastien Poggi, Chabi Babatounde, Evelyne Vittori and Thierry Antoine-Santoni
Sensors 2022, 22(24), 9927; https://doi.org/10.3390/s22249927 - 16 Dec 2022
Cited by 5 | Viewed by 1702
Abstract
Wireless sensor network (WSN) deployment is an intensive field of research. In this paper, we propose a novel approach based on machine learning (ML) and metaheuristics (MH) for supporting decision-makers during the deployment process. We suggest optimizing node positions by introducing a new [...] Read more.
Wireless sensor network (WSN) deployment is an intensive field of research. In this paper, we propose a novel approach based on machine learning (ML) and metaheuristics (MH) for supporting decision-makers during the deployment process. We suggest optimizing node positions by introducing a new hybridized version of the “Hitchcock bird-inspired algorithm” (HBIA) metaheuristic algorithm that we named “Intensified-Hitchcock bird-inspired algorithm” (I-HBIA). During the optimization process, our fitness function focuses on received signal maximization between nodes and antennas. Signal estimations are provided by the machine learning “K Nearest Neighbors” (KNN) algorithm working with real measured data. To highlight our contribution, we compare the performances of the canonical HBIA algorithm and our I-HBIA algorithm on classical optimization benchmarks. We then evaluate the accuracy of signal predictions by the KNN algorithm on different maps. Finally, we couple KNN and I-HBIA to provide efficient deployment propositions according to actual measured signal on areas of interest. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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30 pages, 5199 KiB  
Article
SDA-RDOS: A New Secure Data Aggregation Protocol for Wireless Sensor Networks in IoT Resistant to DOS Attacks
by Murat Dener
Electronics 2022, 11(24), 4194; https://doi.org/10.3390/electronics11244194 - 15 Dec 2022
Cited by 3 | Viewed by 2343
Abstract
In a typical Wireless Sensor Network (WSN), thousands of sensor nodes can be distributed in the environment. Then, each sensor node transmits its detected data to the base station with the help of cooperation. In this type of network, data aggregation protocols are [...] Read more.
In a typical Wireless Sensor Network (WSN), thousands of sensor nodes can be distributed in the environment. Then, each sensor node transmits its detected data to the base station with the help of cooperation. In this type of network, data aggregation protocols are used to increase the network’s lifetime and reduce each sensor node’s communication load and energy consumption. With Data Clustering, the density of data circulating in the network is reduced, thus increasing the network’s life. Energy, delay, and efficiency are essential criteria in Data Clustering; however, security is another crucial aspect to be considered. A comprehensive solution for secure data clustering has yet to be seen when the literature is examined. In the solutions developed, data availability, which means that the WSN is resistant to Denial of Service (DOS) attacks, has been neglected too much, even though confidentiality, integrity, and authentication are met with different algorithms. This study developed a comprehensive, secure clustering protocol by considering all security requirements, especially data availability. The developed protocol uses the blowfish encryption algorithm, EAX mode, and RSA algorithm. The proposed protocol was theoretically analyzed, empirically evaluated, and simulated from many perspectives. Comparisons were made with LSDAR, SUCID, and OOP-MDCRP protocols. As a result of the study, a comprehensive security solution is provided and more successful results were obtained according to Energy Efficiency, Network Lifetime, Average Delay, and Packet delivery ratio criteria. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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41 pages, 2849 KiB  
Article
Recent Advances and Future Prospects of Using AI Solutions for Security, Fault Tolerance, and QoS Challenges in WSNs
by Walid Osamy, Ahmed M. Khedr, Ahmed Salim, Ahmed A. El-Sawy, Mohammed Alreshoodi and Ibrahim Alsukayti
Electronics 2022, 11(24), 4122; https://doi.org/10.3390/electronics11244122 - 10 Dec 2022
Cited by 4 | Viewed by 2068
Abstract
The increasing relevance and significant acceptance of Wireless Sensor Network (WSN) solutions have aided the creation of smart environments in a multitude of sectors, including the Internet of Things, and offer ubiquitous practical applications. We examine current research trends in WSN using Artificial [...] Read more.
The increasing relevance and significant acceptance of Wireless Sensor Network (WSN) solutions have aided the creation of smart environments in a multitude of sectors, including the Internet of Things, and offer ubiquitous practical applications. We examine current research trends in WSN using Artificial Intelligence (AI) technologies and the potential application of these methods for WSN improvement in this study. We emphasize the security, fault detection and tolerance, and quality of service (QoS) concerns in WSN, and provide a detailed review of current research that used different AI technologies to satisfy particular WSN objectives from 2010 to 2022. Specifically, this study’s purpose is to give a current review that compares various AI methodologies in order to provide insights for tackling existing WSN difficulties. Furthermore, there has been minimal existing related work concentrating employing AI approaches to solve security, fault detection and tolerance, and quality of service (QoS) concerns associated to WSN, and our goal is to fill the gap in existing studies. The application of AI solutions for WSN is the goal of this work, and we explore all parts of it in order to meet different WSN challenges such as security, fault detection and tolerance, and QoS. This will lead to an increased understanding of current AI applications in the areas of security, fault detection and tolerance, and QoS. Secondly, we present a comprehensive study and analysis of various AI schemes utilized in WSNs, which will aid the researchers in recognizing the most widely used techniques and the merits of employing various AI solutions to tackle WSN-related challenges. Finally, a list of open research issues has been provided, together with considerable bibliographic information, which provides useful recent research trends on the topics and encourages new research directions and possibilities. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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22 pages, 6781 KiB  
Article
An On-Site-Based Opportunistic Routing Protocol for Scalable and Energy-Efficient Underwater Acoustic Sensor Networks
by Rongxin Zhu, Xiwen Huang, Xiangdang Huang, Deshun Li and Qiuling Yang
Appl. Sci. 2022, 12(23), 12482; https://doi.org/10.3390/app122312482 - 6 Dec 2022
Cited by 5 | Viewed by 1326
Abstract
With the advancements in wireless sensor networks and the Internet of Underwater Things (IoUT), underwater acoustic sensor networks (UASNs) have attracted much attention, which has also been widely used in marine engineering exploration and disaster prevention. However, UASNs still face many challenges, including [...] Read more.
With the advancements in wireless sensor networks and the Internet of Underwater Things (IoUT), underwater acoustic sensor networks (UASNs) have attracted much attention, which has also been widely used in marine engineering exploration and disaster prevention. However, UASNs still face many challenges, including high propagation latency, limited bandwidth, high energy consumption, and unreliable transmission, influencing the good quality of service (QoS). In this paper, we propose a routing protocol based on the on-site architecture (SROA) for UASNs to improve network scalability and energy efficiency. The on-site architecture adopted by SROA is different from most architectures in that the data center is deployed underwater, which makes the sink nodes closer to the data source. A clustering method is introduced in SROA, which makes the network adapt to the changes in the network scale and avoid single-point failure. Moreover, the Q-learning algorithm is applied to seek optimal routing policies, in which the characteristics of underwater acoustic communication such as residual energy, end-to-end delay, and link quality are considered jointly when constructing the reward function. Furthermore, the reduction of packet retransmissions and collisions is advocated using a waiting mechanism developed from opportunistic routing (OR). The SROA realizes opportunistic routing to choose candidate nodes and coordinate packet forwarding among candidate nodes. The scalability of the proposed routing protocols is also analyzed by varying the network size and transmission range. According to the evaluation results, with the network scale ranging from 100 to 500, the SROA outperforms the existing routing protocols, extensively decreasing energy consumption and end-to-end delay. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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11 pages, 2385 KiB  
Communication
Wireless Heart Sensor for Capturing Cardiac Orienting Response for Prediction of Neurodevelopmental Delay in Infants
by Marcelo Aguilar-Rivera, Julie A. Kable, Lyubov Yevtushok, Yaroslav Kulikovsky, Natalya Zymak-Zakutnya, Iryna Dubchak, Diana Akhmedzhanova, Wladimir Wertelecki, Christina Chambers and Todd P. Coleman
Sensors 2022, 22(23), 9140; https://doi.org/10.3390/s22239140 - 25 Nov 2022
Cited by 1 | Viewed by 1449
Abstract
Early identification of infants at risk of neurodevelopmental delay is an essential public health aim. Such a diagnosis allows early interventions for infants that maximally take advantage of the neural plasticity in the developing brain. Using standardized physiological developmental tests, such as the [...] Read more.
Early identification of infants at risk of neurodevelopmental delay is an essential public health aim. Such a diagnosis allows early interventions for infants that maximally take advantage of the neural plasticity in the developing brain. Using standardized physiological developmental tests, such as the assessment of neurophysiological response to environmental events using cardiac orienting responses (CORs), is a promising and effective approach for early recognition of neurodevelopmental delay. Previous CORs have been collected on children using large bulky equipment that would not be feasible for widespread screening in routine clinical visits. We developed a portable wireless electrocardiogram (ECG) system along with a custom application for IOS tablets that, in tandem, can extract CORs with sufficient physiologic and timing accuracy to reflect the well-characterized ECG response to both auditory and visual stimuli. The sensor described here serves as an initial step in determining the extent to which COR tools are cost-effective for the early screening of children to determine who is at risk of developing neurocognitive deficits and may benefit from early interventions. We demonstrated that our approach, based on a wireless heartbeat sensor system and a custom mobile application for stimulus display and data recording, is sufficient to capture CORs from infants. The COR monitoring approach described here with mobile technology is an example of a desired standardized physiologic assessment that is a cost-and-time efficient, scalable method for early recognition of neurodevelopmental delay. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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18 pages, 4935 KiB  
Article
Blossom: Cluster-Based Routing for Preserving Privacy in Opportunistic Networks
by Benedikt Kluss, Samaneh Rashidibajgan and Thomas Hupperich
J. Sens. Actuator Netw. 2022, 11(4), 75; https://doi.org/10.3390/jsan11040075 - 16 Nov 2022
Viewed by 1664
Abstract
Opportunistic networks are an enabler technology for typologies without centralized infrastructure. Portable devices, such as wearable and embedded mobile systems, send relay messages to the communication range devices. One of the most critical challenges is to find the optimal route in these networks [...] Read more.
Opportunistic networks are an enabler technology for typologies without centralized infrastructure. Portable devices, such as wearable and embedded mobile systems, send relay messages to the communication range devices. One of the most critical challenges is to find the optimal route in these networks while at the same time preserving privacy for the participants of the network. Addressing this challenge, we presented a novel routing algorithm based on device clusters, reducing the overall message load and increasing network performance. At the same time, possibly identifying information of network nodes is eliminated by cloaking to meet privacy requirements. We evaluated our routing algorithm in terms of efficiency and privacy in opportunistic networks of traditional and structured cities, i.e., Venice and San Francisco by comparing our approach against the PRoPHET, First Contact, and Epidemic routing algorithms. In the San Francisco and Venice scenarios, Blossom improves messages delivery probability and outperforms PRoPHET, First Contact, and Epidemic by 46%, 100%, and 160% and by 67%, 78%, and 204%, respectively. In addition, the dropped messages probability in Blossom decreased 83% compared to PRoPHET and Epidemic in San Francisco and 91% compared to PRoPHET and Epidemic in Venice. Due to the small number of messages generated, the network overhead in this algorithm is close to zero. The network overhead can be significantly reduced by clustering while maintaining a reliable message delivery. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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20 pages, 2762 KiB  
Article
An Adaptive and Spectrally Efficient Multi-Channel Medium Access Control Protocol for Dynamic Ad Hoc Networks
by Abdurrahman Beg, Saud Mohammad Mostafa, AbdulAziz AbdulGhaffar, Tarek R. Sheltami and Ashraf Mahmoud
Sensors 2022, 22(22), 8666; https://doi.org/10.3390/s22228666 - 10 Nov 2022
Cited by 4 | Viewed by 1784
Abstract
Medium access control (MAC) protocols in ad hoc networks have evolved from single-channel independent transmission mechanisms to multi-channel concurrent mechanisms to efficiently manage the demands placed on modern networks. The primary aim of this study is to compare the performance of popular multi-channel [...] Read more.
Medium access control (MAC) protocols in ad hoc networks have evolved from single-channel independent transmission mechanisms to multi-channel concurrent mechanisms to efficiently manage the demands placed on modern networks. The primary aim of this study is to compare the performance of popular multi-channel MAC (MMAC) protocols under saturated network traffic conditions and propose improvements to the protocols under these conditions. A novel, dynamically adaptive MMAC protocol was devised to take advantage of the performance capabilities of the evaluated protocols in changing wireless ad hoc network conditions. A simulation of the familiar MAC protocols was developed based on a validated simulation of the IEEE 802.11 standard. Further, the behaviors and performances of these protocols are compared against the proposed MMAC protocols with a varying number of ad hoc stations and concurrent wireless channels in terms of throughput, Jain’s fairness index, and channel access delay. The results show that the proposed MMAC protocol, labeled E-SA-MMAC, outperforms the existing protocols in throughput by up to 11.9% under a constrained number of channels and in channel access delays by up to 18.3%. It can be asserted from these observations that the proposed approach provides performance benefits against its peers under saturated traffic conditions and other factors, such as the number of available wireless channels, and is suitable for dynamic ad hoc network deployments. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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18 pages, 1309 KiB  
Article
Optimized Routing by Combining Grey Wolf and Dragonfly Optimization for Energy Efficiency in Wireless Sensor Networks
by Hiba Apdalani Younus and Cemal Koçak
Appl. Sci. 2022, 12(21), 10948; https://doi.org/10.3390/app122110948 - 28 Oct 2022
Cited by 3 | Viewed by 1230
Abstract
The rapid development of technology has resulted in numerous sensors and devices for performing measurements in an environment. Depending on the scale and application, the coverage and size of a wireless sensor network (WSN) is decided. During the implementation, the energy consumption and [...] Read more.
The rapid development of technology has resulted in numerous sensors and devices for performing measurements in an environment. Depending on the scale and application, the coverage and size of a wireless sensor network (WSN) is decided. During the implementation, the energy consumption and life of the nodes in the WSN are affected by the continuous usage. Hence, in this study, we aimed to improve the lifespan of the WSN and reduce energy consumption by the nodes during the data transfer using a hybrid approach. The hybrid approach combines Grey Wolf Optimization (GWO) and Dragonfly Optimization (DFO) for exploring a global solution and optimizing the local solution to find the optimum route for the data transfer between the target node and the control center. The results show that the proposed approach has effective energy consumption corresponding to the load applied. Our proposed system scored high in the average residual energy by the number of rounds compared to other methods such as k-means, LEACH-C, CHIRON, and Optimal-CBR. The first dead node was found after 500 rounds, showing that the proposed model has nodes with better reliability. It also showed a comparative analysis of the transmission rate of a packet concerning mobility speed among various methods. The proposed method has the highest ratio at all mobility speeds, i.e., 99.3, 99.1, 99, 98.8, and 98.6, and our proposed system has the lowest computational time of all the evaluated methods, 6 s. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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9 pages, 1389 KiB  
Article
Detection Performance Evaluation for Marine Wireless Sensor Networks
by Qi Hu, Yaobo Liu, Ruoxin Mao and Chaoqun Yang
Electronics 2022, 11(20), 3367; https://doi.org/10.3390/electronics11203367 - 19 Oct 2022
Viewed by 1082
Abstract
Detection performance evaluation is one of the inevitable problems for marine wireless sensor networks (MWSNs) deployed for target detection. However, it is a very complicated problem since it associates many different aspects, such as emitter power, range, radar cross-section, weather, geography, working mode, [...] Read more.
Detection performance evaluation is one of the inevitable problems for marine wireless sensor networks (MWSNs) deployed for target detection. However, it is a very complicated problem since it associates many different aspects, such as emitter power, range, radar cross-section, weather, geography, working mode, and so on. Targeting this problem, this paper incorporates the Poisson point process model into describing the ranges from sensors to targets. The relationship between sensors and a target is built from the perspective of detection probabilities. Then, a new consistent, conservative target detection probability evaluation is derived within a CFAR framework, and the further global detection probability of the whole MWSN on the target is developed. Additionally, the rationality of this modeling approach is demonstrated via simulation results, which is in accord with the actual situation. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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16 pages, 5286 KiB  
Article
An Energy-Efficient Distributed Congestion Control Protocol for Wireless Multimedia Sensor Networks
by Uzma Majeed, Aqdas Naveed Malik, Nasim Abbas and Waseem Abbass
Electronics 2022, 11(20), 3265; https://doi.org/10.3390/electronics11203265 - 11 Oct 2022
Cited by 6 | Viewed by 1515
Abstract
Wireless multimedia sensor networks (WMSNs) generate a huge amount of multimedia data. Congestion is one of the most challenging open issues in WMSNs. Congestion causes low throughput, high packet loss and low energy efficiency. Congestion happens when the data carried by the network [...] Read more.
Wireless multimedia sensor networks (WMSNs) generate a huge amount of multimedia data. Congestion is one of the most challenging open issues in WMSNs. Congestion causes low throughput, high packet loss and low energy efficiency. Congestion happens when the data carried by the network surpasses the available capacity. This article presents an energy-efficient distributed congestion control protocol (DCCP) to mitigate congestion and improve end-to-end delay. Compared to the other protocols, the DCCP protocol proposed in this article can alleviate congestion by intelligently selecting the best path. First, congestion is detected by using two congestion indicators. Second, each node aggregates the received data and builds a traffic congestion map. The traffic congestion map is used to calculate the best path. Therefore, the traffic is balanced on different routes, which reduces the end-to-end delay. Finally, a rate controller is designed to prevent congestion in the network by sending a congestion notification message to a source node. After receiving a congestion notification message, the source node immediately adjusts its transmission rate. Experimental results based on raspberry pi sensor nodes show that the proposed DCCP protocol significantly improves network performance and is superior to existing modern congestion control protocols. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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28 pages, 7204 KiB  
Article
Investigation of Energy Cost of Data Compression Algorithms in WSN for IoT Applications
by Mukesh Mishra, Gourab Sen Gupta and Xiang Gui
Sensors 2022, 22(19), 7685; https://doi.org/10.3390/s22197685 - 10 Oct 2022
Cited by 4 | Viewed by 2040
Abstract
The exponential growth in remote sensing, coupled with advancements in integrated circuits (IC) design and fabrication technology for communication, has prompted the progress of Wireless Sensor Networks (WSN). WSN comprises of sensor nodes and hubs fit for detecting, processing, and communicating remotely. Sensor [...] Read more.
The exponential growth in remote sensing, coupled with advancements in integrated circuits (IC) design and fabrication technology for communication, has prompted the progress of Wireless Sensor Networks (WSN). WSN comprises of sensor nodes and hubs fit for detecting, processing, and communicating remotely. Sensor nodes have limited resources such as memory, energy and computation capabilities restricting their ability to process large volume of data that is generated. Compressing the data before transmission will help alleviate the problem. Many data compression methods have been proposed but mainly for image processing and a vast majority of them are not pertinent on sensor nodes because of memory impediment, energy utilization and handling speed. To overcome this issue, authors in this research have chosen Run Length Encoding (RLE) and Adaptive Huffman Encoding (AHE) data compression techniques as they can be executed on sensor nodes. Both RLE and AHE are capable of balancing compression ratio and energy utilization. In this paper, a hybrid method comprising RLE and AHE, named as H-RLEAHE, is proposed and further investigated for sensor nodes. In order to verify the efficacy of the data compression algorithms, simulations were run, and the results compared with the compression techniques employing RLE, AHE, H-RLEAHE, and without the use of any compression approach for five distinct scenarios. The results demonstrate the RLE’s efficiency, as it surpasses alternative data compression methods in terms of energy efficiency, network speed, packet delivery rate, and residual energy throughout all iterations. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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30 pages, 1038 KiB  
Article
Improving the Performance of Opportunistic Networks in Real-World Applications Using Machine Learning Techniques
by Samaneh Rashidibajgan and Thomas Hupperich
J. Sens. Actuator Netw. 2022, 11(4), 61; https://doi.org/10.3390/jsan11040061 - 26 Sep 2022
Cited by 2 | Viewed by 2340
Abstract
In Opportunistic Networks, portable devices such as smartphones, tablets, and wearables carried by individuals, can communicate and save-carry-forward their messages. The message transmission is often in the short range supported by communication protocols, such as Bluetooth, Bluetooth Low Energy, and Zigbee. These devices [...] Read more.
In Opportunistic Networks, portable devices such as smartphones, tablets, and wearables carried by individuals, can communicate and save-carry-forward their messages. The message transmission is often in the short range supported by communication protocols, such as Bluetooth, Bluetooth Low Energy, and Zigbee. These devices carried by individuals along with a city’s taxis and buses represent network nodes. The mobility, buffer size, message interval, number of nodes, and number of messages copied in such a network influence the network’s performance. Extending these factors can improve the delivery of the messages and, consequently, network performance; however, due to the limited network resources, it increases the cost and appends the network overhead. The network delivers the maximized performance when supported by the optimal factors. In this paper, we measured, predicted, and analyzed the impact of these factors on network performance using the Opportunistic Network Environment simulator and machine learning techniques. We calculated the optimal factors depending on the network features. We have used three datasets, each with features and characteristics reflecting different network structures. We collected the real-time GPS coordinates of 500 taxis in San Francisco, 320 taxis in Rome, and 196 public transportation buses in Münster, Germany, within 48 h. We also compared the network performance without selfish nodes and with 5%, 10%, 20%, and 50% selfish nodes. We suggested the optimized configuration under real-world conditions when resources are limited. In addition, we compared the performance of Epidemic, Prophet, and PPHB++ routing algorithms fed with the optimized factors. The results show how to consider the best settings for the network according to the needs and how self-sustaining nodes will affect network performance. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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15 pages, 4999 KiB  
Article
Applying an Integrated System of Cloud Management and Wireless Sensing Network to Green Smart Environments—Green Energy Monitoring on Campus
by Kuo-Hsiung Tseng, Meng-Yun Chung, Li-Hsien Chen and Ming-Yi Wei
Sensors 2022, 22(17), 6521; https://doi.org/10.3390/s22176521 - 29 Aug 2022
Cited by 5 | Viewed by 1626
Abstract
With increasing urbanization, the application of Internet of things (IoT) technology to city governance has become a trend in architecture, transportation, and healthcare management, making IoT applicable in various domains. This study used IoT to inspect green construction and adopted a front-end sensing [...] Read more.
With increasing urbanization, the application of Internet of things (IoT) technology to city governance has become a trend in architecture, transportation, and healthcare management, making IoT applicable in various domains. This study used IoT to inspect green construction and adopted a front-end sensing system, middle-end wireless transmission, and a back-end multifunctional system structure with cloud management. It integrated civil and electrical engineering to develop environmental monitoring technology and proposed a management information system for the implementation of green engineering. This study collected physical “measurements” of the greening environment on a campus. Ambient temperature and humidity were analyzed to explore the greening and energy-saving benefits of a green roof, a pervious road, and a photovoltaic roof. When the ambient temperature was below 25 °C, the solar panels had an insulation effect on the roof of the building during both 4:00–5:00 and 12:00–13:00, with an optimal insulation effect of 2.45 °C. When the ambient temperature was above 25 °C, the panels had a cooling effect on the roof of the building, whether during 4:00–5:00 or 12:00–13:00, with an optimal cooling effect of 5.77 °C. During the lower temperature period (4:00–5:00), the ecological terrace had an insulation effect on the space beneath, with an effect of approximately 1–3 °C and a mean insulation of 1.95 °C. During the higher temperature period (12:00–13:00), it presented a cooling effect on the space beneath, with an effect of approximately 0.5–9 °C and a mean cooling temperature of 5.16 °C. The cooling effect of the three greening areas on air and ground temperature decreased in the following order: pervious road > photovoltaic roof > ecological terrace. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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39 pages, 2721 KiB  
Review
Fault Tolerance Structures in Wireless Sensor Networks (WSNs): Survey, Classification, and Future Directions
by Ghaihab Hassan Adday, Shamala K. Subramaniam, Zuriati Ahmad Zukarnain and Normalia Samian
Sensors 2022, 22(16), 6041; https://doi.org/10.3390/s22166041 - 12 Aug 2022
Cited by 16 | Viewed by 3677
Abstract
The Industrial Revolution 4.0 (IR 4.0) has drastically impacted how the world operates. The Internet of Things (IoT), encompassed significantly by the Wireless Sensor Networks (WSNs), is an important subsection component of the IR 4.0. WSNs are a good demonstration of an ambient [...] Read more.
The Industrial Revolution 4.0 (IR 4.0) has drastically impacted how the world operates. The Internet of Things (IoT), encompassed significantly by the Wireless Sensor Networks (WSNs), is an important subsection component of the IR 4.0. WSNs are a good demonstration of an ambient intelligence vision, in which the environment becomes intelligent and aware of its surroundings. WSN has unique features which create its own distinct network attributes and is deployed widely for critical real-time applications that require stringent prerequisites when dealing with faults to ensure the avoidance and tolerance management of catastrophic outcomes. Thus, the respective underlying Fault Tolerance (FT) structure is a critical requirement that needs to be considered when designing any algorithm in WSNs. Moreover, with the exponential evolution of IoT systems, substantial enhancements of current FT mechanisms will ensure that the system constantly provides high network reliability and integrity. Fault tolerance structures contain three fundamental stages: error detection, error diagnosis, and error recovery. The emergence of analytics and the depth of harnessing it has led to the development of new fault-tolerant structures and strategies based on artificial intelligence and cloud-based. This survey provides an elaborate classification and analysis of fault tolerance structures and their essential components and categorizes errors from several perspectives. Subsequently, an extensive analysis of existing fault tolerance techniques based on eight constraints is presented. Many prior studies have provided classifications for fault tolerance systems. However, this research has enhanced these reviews by proposing an extensively enhanced categorization that depends on the new and additional metrics which include the number of sensor nodes engaged, the overall fault-tolerant approach performance, and the placement of the principal algorithm responsible for eliminating network errors. A new taxonomy of comparison that also extensively reviews previous surveys and state-of-the-art scientific articles based on different factors is discussed and provides the basis for the proposed open issues. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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10 pages, 1909 KiB  
Article
Localization Approach for Underwater Sensors in the Magnetic Silencing Facility Based on Magnetic Field Gradients
by Guohua Zhou, Yufen Wang, Kena Wu and Hanming Wang
Sensors 2022, 22(16), 6017; https://doi.org/10.3390/s22166017 - 12 Aug 2022
Cited by 3 | Viewed by 1420
Abstract
Localization of the underwater magnetic sensor arrays plays a pivotal role in the magnetic silencing facility. A localization approach is proposed for underwater sensors based on the optimization of magnetic field gradients in the inverse problem of localization. In the localization system, a [...] Read more.
Localization of the underwater magnetic sensor arrays plays a pivotal role in the magnetic silencing facility. A localization approach is proposed for underwater sensors based on the optimization of magnetic field gradients in the inverse problem of localization. In the localization system, a solenoid coil carrying direct current serves as the magnetic source. By measuring the magnetic field generated by the magnetic source in different positions, an objective function is established. The position vector of the sensor is determined by a novel multi-swarm particle swarm optimization with dynamic learning strategy. Without the optimization of the magnetic source’s positions, the sensors’ positions, especially in the z-axis direction, struggle to meet the requested localization. A strategy is proposed to optimize the positions of the magnetic source based on magnetic field gradients in the three directions of x, y and z axes. Compared with the former method, the model experiments show that the proposed method could achieve a 10 cm location error for the position type 2 sensor and meet the request of localization. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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36 pages, 590 KiB  
Article
Chaos-Enhanced Adaptive Hybrid Butterfly Particle Swarm Optimization Algorithm for Passive Target Localization
by Maja Rosić, Miloš Sedak, Mirjana Simić and Predrag Pejović
Sensors 2022, 22(15), 5739; https://doi.org/10.3390/s22155739 - 31 Jul 2022
Cited by 3 | Viewed by 1483
Abstract
This paper considers the problem of finding the position of a passive target using noisy time difference of arrival (TDOA) measurements, obtained from multiple transmitters and a single receiver. The maximum likelihood (ML) estimator’s objective function is extremely nonlinear and non-convex, making it [...] Read more.
This paper considers the problem of finding the position of a passive target using noisy time difference of arrival (TDOA) measurements, obtained from multiple transmitters and a single receiver. The maximum likelihood (ML) estimator’s objective function is extremely nonlinear and non-convex, making it impossible to use traditional optimization techniques. In this regard, this paper proposes the chaos-enhanced adaptive hybrid butterfly particle swarm optimization algorithm, named CAHBPSO, as the hybridization of butterfly optimization (BOA) and particle swarm optimization (PSO) algorithms, to estimate passive target position. In the proposed algorithm, an adaptive strategy is employed to update the sensory fragrance of BOA algorithm, and chaos theory is incorporated into the inertia weight of PSO algorithm. Furthermore, an adaptive switch probability is employed to combine global and local search phases of BOA with the PSO algorithm. Additionally, the semidefinite programming is employed to convert the considered problem into a convex one. The statistical comparison on CEC2014 benchmark problems shows that the proposed algorithm provides a better performance compared to well-known algorithms. The CAHBPSO method surpasses the BOA, PSO and semidefinite programming (SDP) algorithms for a broad spectrum of noise, according to simulation findings, and achieves the Cramer–Rao lower bound (CRLB). Full article
(This article belongs to the Topic Wireless Sensor Networks)
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24 pages, 1139 KiB  
Article
Hybrid Clustering and Routing Algorithm with Threshold-Based Data Collection for Heterogeneous Wireless Sensor Networks
by Muhammad Bilal, Ehsan Ullah Munir and Fawaz Khaled Alarfaj
Sensors 2022, 22(15), 5471; https://doi.org/10.3390/s22155471 - 22 Jul 2022
Cited by 7 | Viewed by 1988
Abstract
The concept of the internet of things (IoT) motivates us to connect bulk isolated heterogeneous devices to automate report generation without human interaction. Energy-efficient routing algorithms help to prolong the network lifetime of these energy-restricted smart devices that are connected by means of [...] Read more.
The concept of the internet of things (IoT) motivates us to connect bulk isolated heterogeneous devices to automate report generation without human interaction. Energy-efficient routing algorithms help to prolong the network lifetime of these energy-restricted smart devices that are connected by means of wireless sensor networks (WSNs). Current vendor-level advancements enable algorithm-level flexibility to design protocols to concurrently collect multiple application data while enforcing the reduction of energy expenditure to gain commercial success in the industrial stage. In this paper, we propose a hybrid clustering and routing algorithm with threshold-based data collection for heterogeneous wireless sensor networks. In our proposed model, homogeneous and heterogeneous nodes are deployed within specific regions. To reduce unnecessary data transmission, threshold-based conditions are presented to prevent unnecessary transmission when minor or no change is observed in the simulated and real-world applications. We further extend our proposed multi-hop model to achieve more network stability in dense and larger network areas. Our proposed model shows enhancement in terms of load balancing and end-to-end delay as compared to the other threshold-based energy-efficient routing protocols, such as the threshold-sensitive stable election protocol (TSEP), threshold distributed energy-efficient clustering (TDEEC), low-energy adaptive clustering hierarchy (LEACH), and energy-efficient sensor network (TEEN). Full article
(This article belongs to the Topic Wireless Sensor Networks)
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15 pages, 4040 KiB  
Article
Energy-Efficient Message Bundling with Delay and Synchronization Constraints in Wireless Sensor Networks
by Sihao Li, Kyeong Soo Kim, Linlin Zhang, Xintao Huan and Jeremy Smith
Sensors 2022, 22(14), 5276; https://doi.org/10.3390/s22145276 - 14 Jul 2022
Cited by 2 | Viewed by 1494
Abstract
In a wireless sensor network (WSN), reducing the energy consumption of battery-powered sensor nodes is key to extending their operating duration before battery replacement is required. Message bundling can save on the energy consumption of sensor nodes by reducing the number of message [...] Read more.
In a wireless sensor network (WSN), reducing the energy consumption of battery-powered sensor nodes is key to extending their operating duration before battery replacement is required. Message bundling can save on the energy consumption of sensor nodes by reducing the number of message transmissions. However, bundling a large number of messages could increase not only the end-to-end delays and message transmission intervals, but also the packet error rate (PER). End-to-end delays are critical in delay-sensitive applications, such as factory monitoring and disaster prevention. Message transmission intervals affect time synchronization accuracy when bundling includes synchronization messages, while an increased PER results in more message retransmissions and, thereby, consumes more energy. To address these issues, this paper proposes an optimal message bundling scheme based on an objective function for the total energy consumption of a WSN, which also takes into account the effects of packet retransmissions and, thereby, strikes the optimal balance between the number of bundled messages and the number of retransmissions given a link quality. The proposed optimal bundling is formulated as an integer nonlinear programming problem and solved using a self-adaptive global-best harmony search (SGHS) algorithm. The experimental results, based on the Cooja emulator of Contiki-NG, demonstrate that the proposed optimal bundling scheme saves up to 51.8% and 8.8% of the total energy consumption with respect to the baseline of no bundling and the state-of-the-art integer linear programming model, respectively. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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17 pages, 4273 KiB  
Article
Multi-Hop Routing Protocols for Oil Pipeline Leak Detection Systems
by Haneen Alhomyani, Mai Fadel, Nikos Dimitriou, Helen Bakhsh, Ghadah Aldabbagh and Samar Alkhuraiji
Electronics 2022, 11(13), 2078; https://doi.org/10.3390/electronics11132078 - 2 Jul 2022
Cited by 2 | Viewed by 1813
Abstract
In recent years, various applications have emerged requiring linear topologies of wireless sensor networks (WSN). Such topologies are used in pipeline (water/oil/gas) monitoring systems. The linear structure has a significant impact on network performance in terms of delay, throughput, and power consumption. Regarding [...] Read more.
In recent years, various applications have emerged requiring linear topologies of wireless sensor networks (WSN). Such topologies are used in pipeline (water/oil/gas) monitoring systems. The linear structure has a significant impact on network performance in terms of delay, throughput, and power consumption. Regarding communication efficiency, routing protocols play a critical role, considering the special requirements of linear topology and energy resources. Therefore, the challenge is to design effective routing protocols that can address the diverse requirements of the monitoring system. In this paper, we present various wireless communication technologies and existing leak detection systems. We review different routing protocols focusing on multi-hop hierarchical protocols, highlighting the limitations and design issues related to packet routing in linear pipeline leak detection networks. Additionally, we present a LoRa multi-hop model for monitoring aboveground oil pipelines. A set of model parameters are identified such as the distance between sensors. In addition, the paper determines some calculations to estimate traffic congestion and energy consumption. Several alternative model designs are investigated. The model is evaluated using different multi-hop communication scenarios, and we compare the data rate and energy to provide an energy-efficient and low-cost leak detection system. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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21 pages, 13011 KiB  
Article
Towards Self-Powered WSN: The Design of Ultra-Low-Power Wireless Sensor Transmission Unit Based on Indoor Solar Energy Harvester
by Fathi Mahdi Elsiddig Haroun, Siti Noratiqah Mohamad Deros, Ammar Ahmed Alkahtani and Norashidah Md Din
Electronics 2022, 11(13), 2077; https://doi.org/10.3390/electronics11132077 - 2 Jul 2022
Cited by 6 | Viewed by 2318
Abstract
The current revolution in communication and information technology is facilitating the Internet of Things (IoT) infrastructure. Wireless Sensor Networks (WSN) are a broad category of IoT applications. However, power management in WSN poses a significant challenge when the WSN is required to operate [...] Read more.
The current revolution in communication and information technology is facilitating the Internet of Things (IoT) infrastructure. Wireless Sensor Networks (WSN) are a broad category of IoT applications. However, power management in WSN poses a significant challenge when the WSN is required to operate for a long duration without the presence of a consistent power source. In this paper, we develop a batteryless, ultra-low-power Wireless Sensor Transmission Unit (WSTx) depending on the solar-energy harvester and LoRa technology. We investigate the feasibility of harvesting ambient indoor light using polycrystalline photovoltaic (PV) cells with a maximum power of 1.4 mW. The study provides comprehensive power management design details and a description of the anticipated challenges. The measured power consumption of the developed WSTx was 0.02109 mW during the sleep mode and 11.1 mW during the operation mode. The harvesting system can harvest energy up to 1.2 mW per second, where the harvested energy can power the WSTx for six hours with a maximum power efficiency of 85.714%. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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29 pages, 23999 KiB  
Article
HERO: Hybrid Effortless Resilient Operation Stations for Flash Flood Early Warning Systems
by Autanan Wannachai, Somrawee Aramkul, Benya Suntaranont, Yuthapong Somchit and Paskorn Champrasert
Sensors 2022, 22(11), 4108; https://doi.org/10.3390/s22114108 - 28 May 2022
Cited by 4 | Viewed by 2124
Abstract
Floods are the most frequent type of natural disaster. Flash floods are one of the most common types of floods, caused by rapid and excessive rainfall. Normally, when a flash flood occurs, the water of the upstream river increases rapidly and flows to [...] Read more.
Floods are the most frequent type of natural disaster. Flash floods are one of the most common types of floods, caused by rapid and excessive rainfall. Normally, when a flash flood occurs, the water of the upstream river increases rapidly and flows to the downstream watersheds. The overflow of water increasingly submerges villages in the drainage basins. Flash flood early warning systems are required to mitigate losses. Water level monitoring stations can be installed at upstream river areas. However, telemetry stations face several challenges because the upstream river areas are far away and lack of public utilities (e.g., electric power and telephone lines). This research proposes hybrid effortless resilient operation stations, named HERO stations, in the flash flood early warning system. The HERO station was designed and developed with a modular design concept to be effortlessly customized and maintained. The HERO station adapts its working operation against the environmental changes to maintain a long working period with high data sensing accuracy. Moreover, the HERO station can switch its communication mode between the centralized and decentralized communication modes to increase availability. The network of the HERO stations has already been deployed in the northern part of Thailand. It results in improvements of the telemetry station’s availability. The HERO stations can adapt to environmental changes. The flash flood early warning messages can be disseminated to the villagers to increase the flood preparation time and to reduce flash flood damage. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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21 pages, 11274 KiB  
Article
Long-Range Low-Power Multi-Hop Wireless Sensor Network for Monitoring the Vibration Response of Long-Span Bridges
by Eleonora Maria Tronci, Sakie Nagabuko, Hiroyuki Hieda and Maria Qing Feng
Sensors 2022, 22(10), 3916; https://doi.org/10.3390/s22103916 - 22 May 2022
Cited by 9 | Viewed by 2450
Abstract
Recently, vibration-based monitoring technologies have become extremely popular, providing effective tools to assess the health condition and evaluate the structural integrity of civil structures and infrastructures in real-time. In this context, battery-operated wireless sensors allow us to stop using wired sensor networks, providing [...] Read more.
Recently, vibration-based monitoring technologies have become extremely popular, providing effective tools to assess the health condition and evaluate the structural integrity of civil structures and infrastructures in real-time. In this context, battery-operated wireless sensors allow us to stop using wired sensor networks, providing easy installation processes and low maintenance costs. Nevertheless, wireless transmission of high-rate data such as structural vibration consumes considerable power. Consequently, these wireless networks demand frequent battery replacement, which is problematic for large structures with poor accessibility, such as long-span bridges. This work proposes a low-power multi-hop wireless sensor network suitable for monitoring large-sized civil infrastructures to handle this problem. The proposed network employs low-power wireless devices that act in the sub-GHz band, permitting long-distance data transmission and communication surpassing 1 km. Data collection over vast areas is accomplished via multi-hop communication, in which the sensor data are acquired and re-transmitted by neighboring sensors. The communication and transmission times are synchronized, and time-division communication is executed, which depends on the wireless devices to sleep when the connection is not necessary to consume less power. An experimental field test is performed to evaluate the reliability and accuracy of the designed wireless sensor network to collect and capture the acceleration response of the long-span Manhattan Bridge. Thanks to the high-quality monitoring data collected with the developed low-power wireless sensor network, the natural frequencies and mode shapes were robustly recognized. The monitoring tests also showed the benefits of the presented wireless sensor system concerning the installation and measuring operations. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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20 pages, 4060 KiB  
Article
A Wireless Underground Sensor Network Field Pilot for Agriculture and Ecology: Soil Moisture Mapping Using Signal Attenuation
by Srinivasa Balivada, Gregory Grant, Xufeng Zhang, Monisha Ghosh, Supratik Guha and Roser Matamala
Sensors 2022, 22(10), 3913; https://doi.org/10.3390/s22103913 - 21 May 2022
Cited by 10 | Viewed by 4627
Abstract
Wireless Underground Sensor Networks (WUSNs) that collect geospatial in situ sensor data are a backbone of internet-of-things (IoT) applications for agriculture and terrestrial ecology. In this paper, we first show how WUSNs can operate reliably under field conditions year-round and at the same [...] Read more.
Wireless Underground Sensor Networks (WUSNs) that collect geospatial in situ sensor data are a backbone of internet-of-things (IoT) applications for agriculture and terrestrial ecology. In this paper, we first show how WUSNs can operate reliably under field conditions year-round and at the same time be used for determining and mapping soil conditions from the buried sensor nodes. We demonstrate the design and deployment of a 23-node WUSN installed at an agricultural field site that covers an area with a 530 m radius. The WUSN has continuously operated since September 2019, enabling real-time monitoring of soil volumetric water content (VWC), soil temperature (ST), and soil electrical conductivity. Secondly, we present data collected over a nine-month period across three seasons. We evaluate the performance of a deep learning algorithm in predicting soil VWC using various combinations of the received signal strength (RSSI) from each buried wireless node, above-ground pathloss, the distance between wireless node and receive antenna (D), ST, air temperature (AT), relative humidity (RH), and precipitation as input parameters to the model. The AT, RH, and precipitation were obtained from a nearby weather station. We find that a model with RSSI, D, AT, ST, and RH as inputs was able to predict soil VWC with an R2 of 0.82 for test datasets, with a Root Mean Square Error of ±0.012 (m3/m3). Hence, a combination of deep learning and other easily available soil and climatic parameters can be a viable candidate for replacing expensive soil VWC sensors in WUSNs. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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24 pages, 4468 KiB  
Article
REIP: A Reconfigurable Environmental Intelligence Platform and Software Framework for Fast Sensor Network Prototyping
by Yurii Piadyk, Bea Steers, Charlie Mydlarz, Mahin Salman, Magdalena Fuentes, Junaid Khan, Hong Jiang, Kaan Ozbay, Juan Pablo Bello and Claudio Silva
Sensors 2022, 22(10), 3809; https://doi.org/10.3390/s22103809 - 17 May 2022
Cited by 5 | Viewed by 2875
Abstract
Sensor networks have dynamically expanded our ability to monitor and study the world. Their presence and need keep increasing, and new hardware configurations expand the range of physical stimuli that can be accurately recorded. Sensors are also no longer simply recording the data, [...] Read more.
Sensor networks have dynamically expanded our ability to monitor and study the world. Their presence and need keep increasing, and new hardware configurations expand the range of physical stimuli that can be accurately recorded. Sensors are also no longer simply recording the data, they process it and transform into something useful before uploading to the cloud. However, building sensor networks is costly and very time consuming. It is difficult to build upon other people’s work and there are only a few open-source solutions for integrating different devices and sensing modalities. We introduce REIP, a Reconfigurable Environmental Intelligence Platform for fast sensor network prototyping. REIP’s first and most central tool, implemented in this work, is an open-source software framework, an SDK, with a flexible modular API for data collection and analysis using multiple sensing modalities. REIP is developed with the aim of being user-friendly, device-agnostic, and easily extensible, allowing for fast prototyping of heterogeneous sensor networks. Furthermore, our software framework is implemented in Python to reduce the entrance barrier for future contributions. We demonstrate the potential and versatility of REIP in real world applications, along with performance studies and benchmark REIP SDK against similar systems. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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23 pages, 2705 KiB  
Article
Self-Stabilizing Capacitated Vertex Cover Algorithms for Internet-of-Things-Enabled Wireless Sensor Networks
by Yasin Yigit, Orhan Dagdeviren and Moharram Challenger
Sensors 2022, 22(10), 3774; https://doi.org/10.3390/s22103774 - 16 May 2022
Cited by 4 | Viewed by 2220
Abstract
Wireless sensor networks (WSNs) achieving environmental sensing are fundamental communication layer technologies in the Internet of Things. Battery-powered sensor nodes may face many problems, such as battery drain and software problems. Therefore, the utilization of self-stabilization, which is one of the fault-tolerance techniques, [...] Read more.
Wireless sensor networks (WSNs) achieving environmental sensing are fundamental communication layer technologies in the Internet of Things. Battery-powered sensor nodes may face many problems, such as battery drain and software problems. Therefore, the utilization of self-stabilization, which is one of the fault-tolerance techniques, brings the network back to its legitimate state when the topology is changed due to node leaves. In this technique, a scheduler decides on which nodes could execute their rules regarding spatial and temporal properties. A useful graph theoretical structure is the vertex cover that can be utilized in various WSN applications such as routing, clustering, replica placement and link monitoring. A capacitated vertex cover is the generalized version of the problem which restricts the number of edges covered by a vertex by applying a capacity constraint to limit the covered edge count. In this paper, we propose two self-stabilizing capacitated vertex cover algorithms for WSNs. To the best of our knowledge, these algorithms are the first attempts in this manner. The first algorithm is stabilized under an unfair distributed scheduler (that is, the scheduler which does not grant all enabled nodes to make their moves but guarantees the global progress of the system) at most O(n2) step, where n is the count of nodes. The second algorithm assumes 2-hop (degree 2) knowledge about the network and runs under the unfair scheduler, which subsumes the synchronous and distributed fair scheduler and stabilizes itself after O(n) moves in O(n) step, which is acceptable for most WSN setups. We theoretically analyze the algorithms to provide proof of correctness and their step complexities. Moreover, we provide simulation setups by applying IRIS sensor node parameters and compare our algorithms with their counterparts. The gathered measurements from the simulations revealed that the proposed algorithms are faster than their competitors, use less energy and offer better vertex cover solutions. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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19 pages, 21620 KiB  
Article
Multi-AP and Test Point Accuracy of the Results in WiFi Indoor Localization
by Shuyu Li, Sherif Welsen and Vladimir Brusic
Sensors 2022, 22(10), 3709; https://doi.org/10.3390/s22103709 - 12 May 2022
Cited by 3 | Viewed by 2272
Abstract
WiFi-based indoor positioning has attracted intensive research activities. While localization accuracy is steadily improving due to the application of advanced algorithms, the factors that affect indoor localization accuracy have not been sufficiently understood. Most localization algorithms used in changing indoor spaces are Angle-of-Arrival [...] Read more.
WiFi-based indoor positioning has attracted intensive research activities. While localization accuracy is steadily improving due to the application of advanced algorithms, the factors that affect indoor localization accuracy have not been sufficiently understood. Most localization algorithms used in changing indoor spaces are Angle-of-Arrival (AoA) based, and they deploy the conventional MUSIC algorithm. The localization accuracy can be achieved by algorithm improvements or joint localization that deploys multiple Access Points (APs). We performed an experiment that assessed the Test Point (TP) accuracy and distribution of results in a complex environment. The testing space was a 290 m2 three-room environment with three APs with 38 TPs. The joint localization using three APs was performed in the same test space. We developed and implemented a new algorithm for improved accuracy of joint localization. We analyzed the statistical characteristics of the results based on each TP and show that the local space-dependent factors are the key factors for localization accuracy. The most important factors that cause errors are distance, obstacles, corner locations, the location of APs, and the angular orientation of the antenna array. Compared with the well-known SpotFi algorithm, we achieved a mean accuracy (across all TPs) improvement of 46%. The unbiased joint localization median accuracy improved by 20% as compared to the best individual localization. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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18 pages, 3145 KiB  
Article
A Mathematical-Based Model for Estimating the Path Duration of the DSDV Routing Protocol in MANETs
by Saeed Salah, Raid Zaghal and Mada Abdeljawad
J. Sens. Actuator Netw. 2022, 11(2), 23; https://doi.org/10.3390/jsan11020023 - 12 May 2022
Cited by 7 | Viewed by 2362
Abstract
Mobile Ad Hoc Networks (MANETs) are kind of wireless networks where the nodes move in decentralized environments with a highly dynamic infrastructure. Many well-known routing protocols have been proposed, with each having its own design mechanism and its own strengths and weaknesses and [...] Read more.
Mobile Ad Hoc Networks (MANETs) are kind of wireless networks where the nodes move in decentralized environments with a highly dynamic infrastructure. Many well-known routing protocols have been proposed, with each having its own design mechanism and its own strengths and weaknesses and most importantly, each protocol being mainly designed for specific applications and scenarios. Most of the research studies in this field used simulation testbeds to analyze routing protocols. Very few contributions suggested the use of analytical studies and mathematical approaches to model some of the existing routing protocols. In this research, we have built a comprehensive mathematical-based model to analyze the Destination-Sequenced Distance Vector protocol (DSDV), one of the main widely deployed proactive protocols and studied its performance on estimating the path duration based on the concepts of the probability density function and the expected values to find the best approximation values in real scenarios. We have tested the validity of the proposed model using simulation scenarios implemented by the Network Simulator tool (NS3). The results extracted from both the mathematical model and the simulation have shown that the path duration is inversely proportional to both the speed of the node and the hop count. Furthermore, it had shown that the path duration estimated from the DSDV protocol is less than the actual path duration, due to the implementation of the settling time concept and keeping the “periodic routes’ update” parameter at a constant level, despite the fact that the node’s speed reduces the effective path utilization. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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22 pages, 1925 KiB  
Review
Technological Requirements and Challenges in Wireless Body Area Networks for Health Monitoring: A Comprehensive Survey
by Lisha Zhong, Shuling He, Jinzhao Lin, Jia Wu, Xi Li, Yu Pang and Zhangyong Li
Sensors 2022, 22(9), 3539; https://doi.org/10.3390/s22093539 - 6 May 2022
Cited by 22 | Viewed by 6517
Abstract
With the rapid growth in healthcare demand, an emergent, novel technology called wireless body area networks (WBANs) have become promising and have been widely used in the field of human health monitoring. A WBAN can collect human physical parameters through the medical sensors [...] Read more.
With the rapid growth in healthcare demand, an emergent, novel technology called wireless body area networks (WBANs) have become promising and have been widely used in the field of human health monitoring. A WBAN can collect human physical parameters through the medical sensors in or around the patient’s body to realize real-time continuous remote monitoring. Compared to other wireless transmission technologies, a WBAN has more stringent technical requirements and challenges in terms of power efficiency, security and privacy, quality of service and other specifications. In this paper, we review the recent WBAN medical applications, existing requirements and challenges and their solutions. We conducted a comprehensive investigation of WBANs, from the sensor technology for the collection to the wireless transmission technology for the transmission process, such as frequency bands, channel models, medium access control (MAC) and networking protocols. Then we reviewed its unique safety and energy consumption issues. In particular, an application-specific integrated circuit (ASIC)-based WBAN scheme is presented to improve its security and privacy and achieve ultra-low energy consumption. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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21 pages, 6730 KiB  
Article
Design and Implementation of a Multi-Hop Real-Time LoRa Protocol for Dynamic LoRa Networks
by Huu Phi Tran, Woo-Sung Jung, Dae-Seung Yoo and Hoon Oh
Sensors 2022, 22(9), 3518; https://doi.org/10.3390/s22093518 - 5 May 2022
Cited by 12 | Viewed by 2683
Abstract
Recently, LoRa (Long Range) technology has been drawing attention in various applications due to its long communication range and high link reliability. However, in industrial environments, these advantages are often compromised by factors such as node mobility, signal attenuation due to various obstacles, [...] Read more.
Recently, LoRa (Long Range) technology has been drawing attention in various applications due to its long communication range and high link reliability. However, in industrial environments, these advantages are often compromised by factors such as node mobility, signal attenuation due to various obstacles, and link instability due to external signal interference. In this paper, we propose a new multi-hop LoRa protocol that can provide high reliability for data transmission by overcoming those factors in dynamic LoRa networks. This study extends the previously proposed two-hop real-time LoRa (Two-Hop RT-LoRa) protocol to address technical aspects of dynamic multi-hop networks, such as automatic configuration of multi-hop LoRa networks, dynamic topology management, and updating of real-time slot schedules. It is shown by simulation that the proposed protocol achieves high reliability of over 97% for mobile nodes and generates low control overhead in topology management and schedule updates. The protocol was also evaluated in various campus deployment scenarios. According to experiments, it could achieve high packet delivery rates of over 97% and 95%, respectively, for 1-hop nodes and 2-hop nodes against node mobility. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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22 pages, 6035 KiB  
Article
Wake-Up Receiver-Based Routing for Clustered Multihop Wireless Sensor Networks
by Maximilian Weber, Ghofrane Fersi, Robert Fromm and Faouzi Derbel
Sensors 2022, 22(9), 3254; https://doi.org/10.3390/s22093254 - 23 Apr 2022
Cited by 5 | Viewed by 2288
Abstract
The Wireless Sensor Network (WSN) is one of the most promising solutions for the supervision of multiple phenomena and for the digitisation of the Internet of Things (IoT). The Wake-up Receiver (WuRx) is one of the most trivial and effective solutions for energy-constrained [...] Read more.
The Wireless Sensor Network (WSN) is one of the most promising solutions for the supervision of multiple phenomena and for the digitisation of the Internet of Things (IoT). The Wake-up Receiver (WuRx) is one of the most trivial and effective solutions for energy-constrained networks. This technology allows energy-autonomous on-demand communication for continuous monitoring instead of the conventional radio. The routing process is one of the most energy and time-consuming processes in WSNs. It is, hence, crucial to conceive an energy-efficient routing process. In this paper, we propose a novel Wake-up Receiver-based routing protocol called Clustered WuRx based on Multicast wake-up (CWM), which ensures energy optimisation and time-efficiency at the same time for indoor scenarios. In our proposed approach, the network is divided into clusters. Each Fog Node maintains the routes from each node in its cluster to it. When a sink requires information from a given node, it’s corresponding Fog Node uses a multicast wake-up mechanism to wake up the intended node and all the intermediate nodes that will be used in the routing process simultaneously. Measurement results demonstrate that our proposed approach exhibits higher energy efficiency and has drastic performance improvements in the delivery delay compared with other routing protocols. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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8 pages, 271 KiB  
Article
Stochastic Network Calculus-Aided Delay Analysis of Wireless-Power Line Mixed Networks
by Zheng Li, Haiming Hong, Lin Pang, Muyu Mei and Qinghai Yang
Electronics 2022, 11(9), 1326; https://doi.org/10.3390/electronics11091326 - 22 Apr 2022
Cited by 1 | Viewed by 1234
Abstract
In this paper, we investigate the delay performance of a wireless-power line mixed network via a stochastic network calculus (SNC)-based approach. The data transmission in this mixed network is modeled by a two-stage tandem queue, wherein the data is first relayed through a [...] Read more.
In this paper, we investigate the delay performance of a wireless-power line mixed network via a stochastic network calculus (SNC)-based approach. The data transmission in this mixed network is modeled by a two-stage tandem queue, wherein the data is first relayed through a wireless fading channel and then transmitted over a power line communication (PLC) system. The Rayleigh fading captures the wireless fading channel; whereas, the PLC channel gain is characterized by the log-normal distribution. The statistical characteristics of the service processes of both the wireless channel and PLC channel are derived. With any given traffic arrival and the service capability derived, the delay can be easily bounded via SNC. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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21 pages, 19063 KiB  
Article
A Novel Distributed Media Caching Technique for Seamless Video Streaming in Multi-Access Edge Computing Networks
by Emmanuel Osei-Mensah, Saqr Khalil Saeed Thabet, Chunbo Luo, Emelia Asiedu-Ayeh, Olusola Bamisile, Isaac Osei Nyantakyi and Humphrey Adun
Appl. Sci. 2022, 12(9), 4205; https://doi.org/10.3390/app12094205 - 21 Apr 2022
Cited by 1 | Viewed by 1708
Abstract
Online video is anticipated to be the largest fraction of all mobile network traffic aside from the huge processing tasks imposed on networks by the billions of IoT devices, causing unprecedented challenges to the current network architecture. Edge caching has been proposed as [...] Read more.
Online video is anticipated to be the largest fraction of all mobile network traffic aside from the huge processing tasks imposed on networks by the billions of IoT devices, causing unprecedented challenges to the current network architecture. Edge caching has been proposed as a highly promising technology to overcome this challenge by placing computational and data storage resources at the network edge to reduce latency and backhaul traffic. However, the edge resources are heavily constrained in their storage and computational capacities as large-scale deployments mean fairly distributing resources across the network. Addressing this limitation, we propose an edge video caching scheme that dynamically caches the first part of popularity-ranked video files on Multi-Edge Computing Access Node (MAN) servers envisioned to achieve higher cache hit ratios, lower latencies, and lower backhaul traffic. The concept of Regionally Organized Clouds (ROCs) with sufficient resources for file caching and compute-intensive tasks was introduced, and a formulation of the edge caching problem as an Integer Linear Programming (ILP) problem was made. Additionally, this study proposes a file view-time threshold for each cached video aimed at reducing the resource wastage caused when buffered contents are abandoned. Comparative evaluations of the proposed show its excellent performance over FIFO, Greedy, LFRU and TLRU schemes. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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20 pages, 1314 KiB  
Article
Wireless Lan Performance Enhancement Using Double Deep Q-Networks
by Khizra Asaf, Bilal Khan and Ga-Young Kim
Appl. Sci. 2022, 12(9), 4145; https://doi.org/10.3390/app12094145 - 20 Apr 2022
Cited by 3 | Viewed by 2295
Abstract
Due to the exponential growth in the use of Wi-Fi networks, it is necessary to study its usage pattern in dense environments for which the legacy IEEE 802.11 MAC (Medium Access Control) protocol was not specially designed. Although 802.11ax aims to improve Wi-Fi [...] Read more.
Due to the exponential growth in the use of Wi-Fi networks, it is necessary to study its usage pattern in dense environments for which the legacy IEEE 802.11 MAC (Medium Access Control) protocol was not specially designed. Although 802.11ax aims to improve Wi-Fi performance in dense scenarios due to modifications in the physical layer (PHY), however, MAC layer operations remain unchanged, and are not capable enough to provide stable performance in dense scenarios. Potential applications of Deep Learning (DL) to Media Access Control (MAC) layer of WLAN has now been recognized due to their unique features. Deep Reinforcement Learning (DRL) is a technique focused on behavioral sensitivity and control philosophy. In this paper, we have proposed an algorithm for setting optimal contention window (CW) under different network conditions called DRL-based Contention Window Optimization (DCWO). The proposed algorithm operates in three steps. In the initial step, Wi-Fi is being controlled by the 802.11 standards. In the second step, the agent makes the decisions concerning the value of CW after the TRAIN procedure for the proposed algorithm. The final phase begins after the training, defined by a time duration specified by the user. Now, the agent is fully trained, and no updates will be no longer received. Now the CW is updated via the OPTIMIZE process of DCWO. We have selected total network throughput, instantaneous network throughput, fairness index, and cumulative reward, and compared our proposed scheme DCWO with the Centralized Contention window Optimization with DRL (CCOD). Simulation results show that DCWO with Double Deep Q-Networks (DDQN) performs better than CCOD with (i) Deep Deterministic Policy Gradient (DDPG) and (ii) Deep Q-Network (DQN). More specifically, DCWO with DDQN gives on average 28% and 23% higher network throughput than CCOD in static and dynamic scenarios. Whereas in terms of instantaneous network throughput DCWO gives around 10% better results than the CCOD. DCWO achieves almost near to optimal fairness in static scenarios and better than DQN and DDPG with CCOD in dynamic scenarios. Similarly, while the cumulative reward achieved by DCWO is almost the same with CCOD with DDPG, the uptrend of DCWO is still encouraging. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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17 pages, 1301 KiB  
Article
FPGA-Based Autonomous GPS-Disciplined Oscillatorsfor Wireless Sensor Network Nodes
by Toan Quang The Bui, Arul Elango and René Jr. Landry
Sensors 2022, 22(9), 3135; https://doi.org/10.3390/s22093135 - 20 Apr 2022
Cited by 4 | Viewed by 2887
Abstract
Numerous devices in distributed wireless sensor arrays require a high-accuracy timing reference. Although the GPS-disciplined oscillators have been developed for decades, the hardware design still has performance limitations. In this context, we present the hardware implementation for a GPS-disciplined oscillator with an automatic [...] Read more.
Numerous devices in distributed wireless sensor arrays require a high-accuracy timing reference. Although the GPS-disciplined oscillators have been developed for decades, the hardware design still has performance limitations. In this context, we present the hardware implementation for a GPS-disciplined oscillator with an automatic adaptive drift correction algorithm, which is implemented in a low-cost, high-speed field-programmable gate array (FPGA) device. The system design and the hardware implementation are presented to demonstrate the advantages of the proposed oscillator. To verify this oscillator in real-time applications, we tested the device in multiple environments and compared it to state-of-the-art designs. The experimental results showed that our proposed device has a low cost and high performance. This device can achieve less than 80 ns and 356 ns in 1PPS signal drift in the indoor environment test and the outdoor environment test, respectively, after 24 h of working without a GPS signal. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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22 pages, 19376 KiB  
Article
An Intra-Vehicular Wireless Multimedia Sensor Network for Smartphone-Based Low-Cost Advanced Driver-Assistance Systems
by Christiaan M. Fourie and Hermanus Carel Myburgh
Sensors 2022, 22(8), 3026; https://doi.org/10.3390/s22083026 - 15 Apr 2022
Cited by 2 | Viewed by 2310
Abstract
Advanced driver-assistance system(s) (ADAS) are more prevalent in high-end vehicles than in low-end vehicles. Wired solutions of vision sensors in ADAS already exist, but are costly and do not cater for low-end vehicles. General ADAS use wired harnessing for communication; this approach eliminates [...] Read more.
Advanced driver-assistance system(s) (ADAS) are more prevalent in high-end vehicles than in low-end vehicles. Wired solutions of vision sensors in ADAS already exist, but are costly and do not cater for low-end vehicles. General ADAS use wired harnessing for communication; this approach eliminates the need for cable harnessing and, therefore, the practicality of a novel wireless ADAS solution was tested. A low-cost alternative is proposed that extends a smartphone’s sensor perception, using a camera-based wireless sensor network. This paper presents the design of a low-cost ADAS alternative that uses an intra-vehicle wireless sensor network structured by a Wi-Fi Direct topology, using a smartphone as the processing platform. The proposed system makes ADAS features accessible to cheaper vehicles and investigates the possibility of using a wireless network to communicate ADAS information in a intra-vehicle environment. Other ADAS smartphone approaches make use of a smartphone’s onboard sensors; however, this paper shows the application of essential ADAS features developed on the smartphone’s ADAS application, carrying out both lane detection and collision detection on a vehicle by using wireless sensor data. A smartphone’s processing power was harnessed and used as a generic object detector through a convolution neural network, using the sensory network’s video streams. The network’s performance was analysed to ensure that the network could carry out detection in real-time. A low-cost CMOS camera sensor network with a smartphone found an application, using Wi-Fi Direct, to create an intra-vehicle wireless network as a low-cost advanced driver-assistance system. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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19 pages, 1858 KiB  
Article
Research on Distributed Multi-Sensor Cooperative Scheduling Model Based on Partially Observable Markov Decision Process
by Zhen Zhang, Jianfeng Wu, Yan Zhao and Ruining Luo
Sensors 2022, 22(8), 3001; https://doi.org/10.3390/s22083001 - 14 Apr 2022
Cited by 3 | Viewed by 1479
Abstract
In the context of distributed defense, multi-sensor networks are required to be able to carry out reasonable planning and scheduling to achieve the purpose of continuous, accurate and rapid target detection. In this paper, a multi-sensor cooperative scheduling model based on the partially [...] Read more.
In the context of distributed defense, multi-sensor networks are required to be able to carry out reasonable planning and scheduling to achieve the purpose of continuous, accurate and rapid target detection. In this paper, a multi-sensor cooperative scheduling model based on the partially observable Markov decision process is proposed. By studying the partially observable Markov decision process and the posterior Cramer–Rao lower bound, a multi-sensor cooperative scheduling model and optimization objective function were established. The improvement of the particle filter algorithm by the beetle swarm optimization algorithm was studied to improve the tracking accuracy of the particle filter. Finally, the improved elephant herding optimization algorithm was used as the solution algorithm of the scheduling scheme, which further improved the algorithm performance of the solution model. The simulation results showed that the model could solve the distributed multi-sensor cooperative scheduling problem well, had higher solution performance than other algorithms, and met the real-time requirements. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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10 pages, 492 KiB  
Article
A Subspace Pre-Learning Strategy to Break the Interpose PUF
by Gaoxiang Li and Khalid T. Mursi
Electronics 2022, 11(7), 1049; https://doi.org/10.3390/electronics11071049 - 27 Mar 2022
Cited by 6 | Viewed by 1655
Abstract
Physical Unclonable Functions (PUFs) are promising security primitives for resource-constrained IoT devices. A critical aspect of PUF security research is to identify all potential security risks. This information about vulnerabilities is beneficial for both PUF developers and PUF-using application developers in terms of [...] Read more.
Physical Unclonable Functions (PUFs) are promising security primitives for resource-constrained IoT devices. A critical aspect of PUF security research is to identify all potential security risks. This information about vulnerabilities is beneficial for both PUF developers and PUF-using application developers in terms of designing new PUFs to mitigate existing risks and avoid vulnerable PUFs. Recently, a PUF structure called Interpose PUF (IPUF) was proposed, which claims to be resistant to reliability attacks and machine learning modeling attacks. Related studies on this secure PUF design have demonstrated that some IPUFs can still be broken, but large IPUFs may remain secure against all known modeling attacks. In addition, all these studies either focus on plain challenge–response pair attacks or require prior knowledge of IPUF architecture implementation. However, depending on the claim of attack resistance to reliability attacks, we can employ a different attack approach to break IPUFs. In this paper, we describe a subspace pre-learning-based attack method that can rapidly and accurately break the IPUFs that were treated as secure in the earlier study, revealing a vulnerability in IPUFs if the open interface conforms to the way challenge–response data are accessed by the subspace pre-learning-based attack method. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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17 pages, 3573 KiB  
Article
A Data Aggregation Approach Exploiting Spatial and Temporal Correlation among Sensor Data in Wireless Sensor Networks
by Lucy Dash, Binod Kumar Pattanayak, Sambit Kumar Mishra, Kshira Sagar Sahoo, Noor Zaman Jhanjhi, Mohammed Baz and Mehedi Masud
Electronics 2022, 11(7), 989; https://doi.org/10.3390/electronics11070989 - 23 Mar 2022
Cited by 21 | Viewed by 2861
Abstract
Wireless sensor networks (WSNs) have various applications which include zone surveillance, environmental monitoring, event tracking where the operation mode is long term. WSNs are characterized by low-powered and battery-operated sensor devices with a finite source of energy. Due to the dense deployment of [...] Read more.
Wireless sensor networks (WSNs) have various applications which include zone surveillance, environmental monitoring, event tracking where the operation mode is long term. WSNs are characterized by low-powered and battery-operated sensor devices with a finite source of energy. Due to the dense deployment of these devices practically it is impossible to replace the batteries. The finite source of energy should be utilized in a meaningful way to maximize the overall network lifetime. In the space domain, there is a high correlation among sensor surveillance constituting the large volume of the sensor network topology. Each consecutive observation constitutes the temporal correlation depending on the physical phenomenon nature of the sensor nodes. These spatio-temporal correlations can be efficiently utilized in order to enhance the maximum savings in energy uses. In this paper, we have proposed a Spatial and Temporal Correlation-based Data Redundancy Reduction (STCDRR) protocol which eliminates redundancy at the source level and aggregator level. The estimated performance score of proposed algorithms is approximately 7.2 when the score of existing algorithms such as the KAB (K-means algorithm based on the ANOVA model and Bartlett test) and ED (Euclidian distance) are 5.2, 0.5, respectively. It reflects that the STCDRR protocol can achieve a higher data compression rate, lower false-negative rate, lower false-positive rate. These results are valid for numeric data collected from a real data set. This experiment does not consider non-numeric values. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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18 pages, 2546 KiB  
Article
A Hybrid Routing Protocol Based on Naïve Bayes and Improved Particle Swarm Optimization Algorithms
by Xun Wang, Huarui Wu, Yisheng Miao and Huaji Zhu
Electronics 2022, 11(6), 869; https://doi.org/10.3390/electronics11060869 - 9 Mar 2022
Cited by 9 | Viewed by 2240
Abstract
Clustering of sensor nodes is a prominent method applied to wireless sensor networks (WSNs). In a cluster-based WSN scenario, the sensor nodes are assembled to generate clusters. The sensor nodes also have limited battery power. Therefore, energy efficiency in WSNs is crucial. The [...] Read more.
Clustering of sensor nodes is a prominent method applied to wireless sensor networks (WSNs). In a cluster-based WSN scenario, the sensor nodes are assembled to generate clusters. The sensor nodes also have limited battery power. Therefore, energy efficiency in WSNs is crucial. The load on the sensor node and its distance from the base station (BS) are the significant factors of energy consumption. Therefore, load balancing according to the transmission distance is necessary for WSNs. In this paper, we propose a hybrid routing algorithm based on Naïve Bayes and improved particle swarm optimization algorithms (HRA-NP). The cluster heads (CHs) are selected according to the CH conditional probability, which is estimated by the Naïve Bayes classifier. After the selection of the CHs, the multi-hop routing algorithm is applied to the CHs. The best routing path from each CH to the BS is obtained from an improved particle swarm optimization (PSO) algorithm. Simulations were conducted on evaluation factors such as energy consumption, active sensor nodes per round, the sustainability of the network, and the standard deviation of a load on the sensor node. It was observed that HRA-NP outperforms comparable algorithms, namely DUCF, ECRRS, and FC-RBAT, based on the evaluation factors. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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10 pages, 2437 KiB  
Article
Missing and Corrupted Data Recovery in Wireless Sensor Networks Based on Weighted Robust Principal Component Analysis
by Jingfei He, Yunpei Li, Xiaoyue Zhang and Jianwei Li
Sensors 2022, 22(5), 1992; https://doi.org/10.3390/s22051992 - 3 Mar 2022
Cited by 7 | Viewed by 2182
Abstract
Although wireless sensor networks (WSNs) have been widely used, the existence of data loss and corruption caused by poor network conditions, sensor bandwidth, and node failure during transmission greatly affects the credibility of monitoring data. To solve this problem, this paper proposes a [...] Read more.
Although wireless sensor networks (WSNs) have been widely used, the existence of data loss and corruption caused by poor network conditions, sensor bandwidth, and node failure during transmission greatly affects the credibility of monitoring data. To solve this problem, this paper proposes a weighted robust principal component analysis method to recover the corrupted and missing data in WSNs. By decomposing the original data into a low-rank normal data matrix and a sparse abnormal matrix, the proposed method can identify the abnormal data and avoid the influence of corruption on the reconstruction of normal data. In addition, the low-rankness is constrained by weighted nuclear norm minimization instead of the nuclear norm minimization to preserve the major data components and ensure credible reconstruction data. An alternating direction method of multipliers algorithm is further developed to solve the resultant optimization problem. Experimental results demonstrate that the proposed method outperforms many state-of-the-art methods in terms of recovery accuracy in real WSNs. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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24 pages, 5352 KiB  
Article
A Correlation-Based Anomaly Detection Model for Wireless Body Area Networks Using Convolutional Long Short-Term Memory Neural Network
by Albatul Albattah and Murad A. Rassam
Sensors 2022, 22(5), 1951; https://doi.org/10.3390/s22051951 - 2 Mar 2022
Cited by 12 | Viewed by 2723
Abstract
As the Internet of Healthcare Things (IoHT) concept emerges today, Wireless Body Area Networks (WBAN) constitute one of the most prominent technologies for improving healthcare services. WBANs are made up of tiny devices that can effectively enhance patient quality of life by collecting [...] Read more.
As the Internet of Healthcare Things (IoHT) concept emerges today, Wireless Body Area Networks (WBAN) constitute one of the most prominent technologies for improving healthcare services. WBANs are made up of tiny devices that can effectively enhance patient quality of life by collecting and monitoring physiological data and sending it to healthcare givers to assess the criticality of a patient and act accordingly. The collected data must be reliable and correct, and represent the real context to facilitate right and prompt decisions by healthcare personnel. Anomaly detection becomes a field of interest to ensure the reliability of collected data by detecting malicious data patterns that result due to various reasons such as sensor faults, error readings and possible malicious activities. Various anomaly detection solutions have been proposed for WBAN. However, existing detection approaches, which are mostly based on statistical and machine learning techniques, become ineffective in dealing with big data streams and novel context anomalous patterns in WBAN. Therefore, this paper proposed a model that employs the correlations that exist in the different physiological data attributes with the ability of the hybrid Convolutional Long Short-Term Memory (ConvLSTM) techniques to detect both simple point anomalies as well as contextual anomalies in the big data stream of WBAN. Experimental evaluations revealed that an average of 98% of F1-measure and 99% accuracy were reported by the proposed model on different subjects of the datasets compared to 64% achieved by both CNN and LSTM separately. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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10 pages, 4066 KiB  
Article
Combining 10 Matrix Pressure Sensor to Read Human Body’s Pressure in Sleeping Position in Relation with Decubitus Patients
by Hartono Pranjoto, Andrew Febrian Miyata and Lanny Agustine
J. Sens. Actuator Netw. 2022, 11(1), 16; https://doi.org/10.3390/jsan11010016 - 25 Feb 2022
Viewed by 2798
Abstract
This work uses piezoresistive matrix pressure sensors to map the human body’s pressure profile in a sleeping position. This study aims to detect the area with the highest pressure, to visualize the pressure profile into a heatmap, and to reduce decubitus by alerting [...] Read more.
This work uses piezoresistive matrix pressure sensors to map the human body’s pressure profile in a sleeping position. This study aims to detect the area with the highest pressure, to visualize the pressure profile into a heatmap, and to reduce decubitus by alerting the subject to changes in position. This research combines ten matrix pressure sensors to read a larger area. This work uses a Raspberry Pi 4 Model B with 8 GB memory as the data processor, and every sensor sheet uses ATMEGA 2560 as the sensor controller for data acquisition. Sensor calibration is necessary because each output must have the same value for the same weight value; the accuracy between different sensors is around 95%. After the calibration process, the output data must be smoothed to make visual representations more distinguishable. The areas with the highest pressure are the heel, tailbone, back, and head. When the subject’s weight increases, pressure on the tailbone and back increases, but that on the heel and head does not. The results of this research can be used to monitor people’s sleeping positions so that they can reduce the risk of decubitus. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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19 pages, 828 KiB  
Communication
Novel Cooperative Automatic Modulation Classification Using Vectorized Soft Decision Fusion for Wireless Sensor Networks
by Xiao Yan, Yan Zhang, Xiaoxue Rao, Qian Wang, Hsiao-Chun Wu and Yiyan Wu
Sensors 2022, 22(5), 1797; https://doi.org/10.3390/s22051797 - 24 Feb 2022
Cited by 5 | Viewed by 1668
Abstract
Cooperative automatic modulation classification (CAMC) using a swarm of sensors is intriguing nowadays as it would be much more robust than the conventional single-sensing-node automatic modulation classification (AMC) method. We propose a novel robust CAMC approach using vectorized soft decision fusion in this [...] Read more.
Cooperative automatic modulation classification (CAMC) using a swarm of sensors is intriguing nowadays as it would be much more robust than the conventional single-sensing-node automatic modulation classification (AMC) method. We propose a novel robust CAMC approach using vectorized soft decision fusion in this work. In each sensing node, the local Hamming distances between the graph features acquired from the unknown target signal and the training modulation candidate signals are calculated and transmitted to the fusion center (FC). Then, the global CAMC decision is made by the indirect vote which is translated from each sensing node’s Hamming-distance sequence. The simulation results demonstrate that, when the signal-to-noise ratio (SNR) was given by η0dB, our proposed new CAMC scheme’s correct classification probability Pcc could reach up close to 100%. On the other hand, our proposed new CAMC scheme could significantly outperform the single-node graph-based AMC technique and the existing decision-level CAMC method in terms of recognition accuracy, especially in the low-SNR regime. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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23 pages, 1363 KiB  
Article
Simple and Robust Log-Likelihood Ratio Calculation of Coded MPSK Signals in Wireless Sensor Networks for Healthcare
by Bo Xie, Congfang Ma, Haiqiong Li, Gaoyuan Zhang and Congzheng Han
Appl. Sci. 2022, 12(5), 2330; https://doi.org/10.3390/app12052330 - 23 Feb 2022
Cited by 1 | Viewed by 1610
Abstract
The simple and robust log-likelihood ratio (LLR) computation of coded Multiple Phase Shift Keying (MPSK) signals in Wireless Sensor Networks (WSNs) is considered under both phase noncoherent and Rayleigh fading channels for healthcare applications. We first simplify the optimal LLR for phase noncoherent [...] Read more.
The simple and robust log-likelihood ratio (LLR) computation of coded Multiple Phase Shift Keying (MPSK) signals in Wireless Sensor Networks (WSNs) is considered under both phase noncoherent and Rayleigh fading channels for healthcare applications. We first simplify the optimal LLR for phase noncoherent channel, the estimation of the instantaneous channel state information (CSI) for both the fading amplitude and the additive white Gaussian noise (AWGN) is successfully avoided, and the complexity-intensive process for zero-order Bessel function of the first kind is also perfectly eliminated. Furthermore, we also develop the simplified LLR under Rayleigh fading channel. Correspondingly, the variance estimation for both AWGN and the statistical characteristic of the fading amplitude is no longer required, and the complicated process for implementation of the exponential function is also successfully avoided. Compared to the calculation of optimal LLR with full complexity, the proposed method is implementation-friendly, which is practically desired for energy-limited WSNs. The simulations are developed in the context of low-density parity-check (LDPC) codes, and the corresponding results show that the detection performance is extremely close to that of the full-complexity LLR metrics. That is, the performance degradation is efficiently prevented, whereas complexity reduction is also successfully achieved. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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