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Special Issue "Sensor Systems for Internet of Things"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".

Deadline for manuscript submissions: closed (31 October 2019).

Special Issue Editors

Dr. Francisco Falcone
Website
Guest Editor
Department of Electrical, Electronic and Communication Engineering & Institute for Smart Cities (ISC), Public University of Navarre, 31006 Pamplona, Spain
Interests: wireless networks; performance evaluation; distributed systems; context-aware environments; IoT; next-generation wireless systems, Smart Health
Special Issues and Collections in MDPI journals
Prof. Dr. Jaime Lloret Mauri
Website
Guest Editor
Department of Communications, Polytechnic University of Valencia, Camino de Vera 46022, Valencia, Spain
Interests: network protocols; network algorithms; wireless sensor networks; ad hoc networks; multimedia streaming
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleague,

Internet of Things (IoT) technology makes it possible to gather data from everywhere and it can be used for any type of environment (e.g., cities, rural zones, etc.). Sensors and sensor networks allow all “things” to communicate directly with each other to share vital information, allowing us to have everything monitored and leading to better services. Moreover, accurate data is readily available to inform optimal decision making. The IoT enables a wide range of new capabilities and services. It changes how people go about their lives and their belongings. The scale of the IoT is set to have major economic, social, and environmental impacts, the intersection of which forms future sustainable growth.

This Special issue is an open call, but we encourage the submission of the best selected papers of the 5th International Conference on Internet of Things: Systems, Management and Security (IoTSMS 2018) held in Valencia, Spain on 15–18 October 2018 and 6th International Conference on Internet of Things: Systems, Management and Security (IoTSMS 2019) held in Granada, Spain on 22-25 October 2019. The scope of the Special Issue is placed on IoT development, analysis, and integration, with a focus on the role of sensor systems and information gathering and processing techniques of IoT ecosystems.

You are welcome to submit an unpublished original research work related to the theme of “Sensor Systems for Internet of Things”.

Prof. Dr. Francisco Falcone
Assoc. Prof. Dr. Jaime Lloret Mauri
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • sensor system architectures for IoT
  • communication in IoT
  • modeling of sensor systems in IoT applications
  • SDN and NFV support for sensors in IoT applications and systems
  • fog and edge support for IoT applications
  • 5G support for IoT data transmission
  • IoT for Smart Cities
  • energy management in IoT
  • green Internet of Things
  • data management and Big Data in IoT
  • security and privacy of IoT
  • reliability of IoT
  • applications of IoT
  • cloud computing for IoT
  • IoT for sustainable growth

Published Papers (11 papers)

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Research

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Open AccessArticle
A Low-Latency and Energy-Efficient Neighbor Discovery Algorithm for Wireless Sensor Networks
Sensors 2020, 20(3), 657; https://doi.org/10.3390/s20030657 - 24 Jan 2020
Abstract
Wireless sensor networks have been widely adopted, and neighbor discovery is an essential step to construct the networks. Most existing studies on neighbor discovery are designed on the assumption that either all nodes are fully connected or only two nodes compose the network. [...] Read more.
Wireless sensor networks have been widely adopted, and neighbor discovery is an essential step to construct the networks. Most existing studies on neighbor discovery are designed on the assumption that either all nodes are fully connected or only two nodes compose the network. However, networks are partially connected in reality: some nodes are within radio range of each other, while others are not. Low latency and energy efficiency are two common goals, which become even more challenging to achieve at the same time in partially connected networks. We find that the collision caused by simultaneous transmissions is the main obstruction of achieving the two goals. In this paper, we present an efficient algorithm called Panacea to address these challenges by alleviating collisions. To begin with, we design Panacea-NCD (Panacea no collision detection) for nodes that do not have a collision detection mechanism. When n is large, we show the discovery latency is bounded by O ( n · ln n ) for any duty cycle (the percentage time to turn on the radio), where each node has n neighbors on average. For nodes that can detect collisions, we then present Panacea-WCD which also bounds the latency within O ( n · ln n ) slots. Finally, we conduct extensive evaluations and the results also corroborate our analyses. Full article
(This article belongs to the Special Issue Sensor Systems for Internet of Things)
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Open AccessArticle
Extending the Battery Life of the ZigBee Routers and Coordinator by Modifying Their Mode of Operation
Sensors 2020, 20(1), 30; https://doi.org/10.3390/s20010030 - 19 Dec 2019
Cited by 1
Abstract
Wireless sensor networks proliferate more and more in all social scopes and sectors. Such networks are implemented in smart homes, smart cities, security systems, medical resources, agriculture, automotive industry, etc. Communication devices and sensors of such networks are powered with batteries: the enlarging [...] Read more.
Wireless sensor networks proliferate more and more in all social scopes and sectors. Such networks are implemented in smart homes, smart cities, security systems, medical resources, agriculture, automotive industry, etc. Communication devices and sensors of such networks are powered with batteries: the enlarging of battery life is a hot research topic. We focus on wireless sensor networks based on ZigBee technology. While sleep standard operation mode is defined for end devices, it is not the case for the rest of devices (routers and Coordinator), which usually always remain in active mode. We designed a formal optimization model for maximizing the enlarging of the battery life of routers and Coordinator, allowing us to delimit practical successful conditions. It was successfully tested with a standard ZigBee datasheet comprising technical data for sensors, routers, and coordinators. It was tested in a practical wireless sensor network assembly with XBee S2C devices. We derived, from the previous model, a novel but simple protocol of communication among routers and coordinators. It was tested in different use cases. We showed that when end devices generate traffic at regular intervals, the enlarging of the battery life of routers and Coordinator was possible only under certain use cases. Full article
(This article belongs to the Special Issue Sensor Systems for Internet of Things)
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Open AccessArticle
Implementation of Radiating Elements for Radiofrequency Front-Ends by Screen-Printing Techniques for Internet of Things Applications
Sensors 2019, 19(16), 3626; https://doi.org/10.3390/s19163626 - 20 Aug 2019
Cited by 1
Abstract
The advent of the Internet of Things (IoT) has led to embedding wireless transceivers into a wide range of devices, in order to implement context-aware scenarios, in which a massive amount of transceivers is foreseen. In this framework, cost-effective electronic and Radio Frequency [...] Read more.
The advent of the Internet of Things (IoT) has led to embedding wireless transceivers into a wide range of devices, in order to implement context-aware scenarios, in which a massive amount of transceivers is foreseen. In this framework, cost-effective electronic and Radio Frequency (RF) front-end integration is desirable, in order to enable straightforward inclusion of communication capabilities within objects and devices in general. In this work, flexible antenna prototypes, based on screen-printing techniques, with conductive inks on flexible low-cost plastic substrates is proposed. Different parameters such as substrate/ink characteristics are considered, as well as variations in fabrication process or substrate angular deflection in device performance. Simulation and measurement results are presented, as well as system validation results in a real test environment in wireless sensor network communications. The results show the feasibility of using screen-printing antenna elements on flexible low-cost substrates, which can be embedded in a wide array of IoT scenarios. Full article
(This article belongs to the Special Issue Sensor Systems for Internet of Things)
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Open AccessArticle
PALOT: Profiling and Authenticating Users Leveraging Internet of Things
Sensors 2019, 19(12), 2832; https://doi.org/10.3390/s19122832 - 25 Jun 2019
Cited by 1
Abstract
Continuous authentication was introduced to propose novel mechanisms to validate users’ identity and address the problems and limitations exposed by traditional techniques. However, this methodology poses several challenges that remain unsolved. In this paper, we present a novel framework, PALOT, that leverages IoT [...] Read more.
Continuous authentication was introduced to propose novel mechanisms to validate users’ identity and address the problems and limitations exposed by traditional techniques. However, this methodology poses several challenges that remain unsolved. In this paper, we present a novel framework, PALOT, that leverages IoT to provide context-aware, continuous and non-intrusive authentication and authorization services. To this end, we propose a formal information system model based on ontologies, representing the main source of knowledge of our framework. Furthermore, to recognize users’ behavioral patterns within the IoT ecosystem, we introduced a new module called “confidence manager”. The module is then integrated into an extended version of our early framework architecture, IoTCAF, which is consequently adapted to include the above-mentioned component. Exhaustive experiments demonstrated the efficacy, feasibility and scalability of the proposed solution. Full article
(This article belongs to the Special Issue Sensor Systems for Internet of Things)
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Open AccessArticle
Smart Cupboard for Assessing Memory in Home Environment
Sensors 2019, 19(11), 2552; https://doi.org/10.3390/s19112552 - 04 Jun 2019
Cited by 2
Abstract
Sensor systems for the Internet of Things (IoT) make it possible to continuously monitor people, gathering information without any extra effort from them. Thus, the IoT can be very helpful in the context of early disease detection, which can improve peoples’ quality of [...] Read more.
Sensor systems for the Internet of Things (IoT) make it possible to continuously monitor people, gathering information without any extra effort from them. Thus, the IoT can be very helpful in the context of early disease detection, which can improve peoples’ quality of life by applying the right treatment and measures at an early stage. This paper presents a new use of IoT sensor systems—we present a novel three-door smart cupboard that can measure the memory of a user, aiming at detecting potential memory losses. The smart cupboard has three sensors connected to a Raspberry Pi, whose aim is to detect which doors are opened. Inside of the Raspberry Pi, a Python script detects the openings of the doors, and classifies the events between attempts of finding something without success and the events of actually finding it, in order to measure the user’s memory concerning the objects’ locations (among the three compartments of the smart cupboard). The smart cupboard was assessed with 23 different users in a controlled environment. This smart cupboard was powered by an external battery. The memory assessments of the smart cupboard were compared with a validated test of memory assessment about face–name associations and a self-reported test about self-perceived memory. We found a significant correlation between the smart cupboard results and both memory measurement methods. Thus, we conclude that the proposed novel smart cupboard successfully measured memory. Full article
(This article belongs to the Special Issue Sensor Systems for Internet of Things)
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Open AccessArticle
The Lightweight Autonomous Vehicle Self-Diagnosis (LAVS) Using Machine Learning Based on Sensors and Multi-Protocol IoT Gateway
Sensors 2019, 19(11), 2534; https://doi.org/10.3390/s19112534 - 03 Jun 2019
Cited by 4
Abstract
This paper proposes the lightweight autonomous vehicle self-diagnosis (LAVS) using machine learning based on sensors and the internet of things (IoT) gateway. It collects sensor data from in-vehicle sensors and changes the sensor data to sensor messages as it passes through protocol buses. [...] Read more.
This paper proposes the lightweight autonomous vehicle self-diagnosis (LAVS) using machine learning based on sensors and the internet of things (IoT) gateway. It collects sensor data from in-vehicle sensors and changes the sensor data to sensor messages as it passes through protocol buses. The changed messages are divided into header information, sensor messages, and payloads and they are stored in an address table, a message queue, and a data collection table separately. In sequence, the sensor messages are converted to the message type of the other protocol and the payloads are transferred to an in-vehicle diagnosis module (In-VDM). The LAVS informs the diagnosis result of Cloud or road side unit(RSU) by the internet of vehicles (IoV) and of drivers by Bluetooth. To design the LAVS, the following two modules are needed. First, a multi-protocol integrated gateway module (MIGM) converts sensor messages for communication between two different protocols, transfers the extracted payloads to the In-VDM, and performs IoV to transfer the diagnosis result and payloads to the Cloud through wireless access in vehicular environment(WAVE). Second, the In-VDM uses random forest to diagnose parts of the vehicle, and delivers the results of the random forest as an input to the neural network to diagnose the total condition of the vehicle. Since the In-VDM uses them for self-diagnosis, it can diagnose a vehicle with efficiency. In addition, because the LAVS converts payloads to a WAVE message and uses IoV to transfer the WAVE messages to RSU or the Cloud, it prevents accidents in advance by informing the vehicle condition of drivers rapidly. Full article
(This article belongs to the Special Issue Sensor Systems for Internet of Things)
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Open AccessArticle
COSMOS: Collaborative, Seamless and Adaptive Sentinel for the Internet of Things
Sensors 2019, 19(7), 1492; https://doi.org/10.3390/s19071492 - 27 Mar 2019
Cited by 3
Abstract
The Internet of Things (IoT) became established during the last decade as an emerging technology with considerable potentialities and applicability. Its paradigm of everything connected together penetrated the real world, with smart devices located in several daily appliances. Such intelligent objects are able [...] Read more.
The Internet of Things (IoT) became established during the last decade as an emerging technology with considerable potentialities and applicability. Its paradigm of everything connected together penetrated the real world, with smart devices located in several daily appliances. Such intelligent objects are able to communicate autonomously through already existing network infrastructures, thus generating a more concrete integration between real world and computer-based systems. On the downside, the great benefit carried by the IoT paradigm in our life brings simultaneously severe security issues, since the information exchanged among the objects frequently remains unprotected from malicious attackers. The paper at hand proposes COSMOS (Collaborative, Seamless and Adaptive Sentinel for the Internet of Things), a novel sentinel to protect smart environments from cyber threats. Our sentinel shields the IoT devices using multiple defensive rings, resulting in a more accurate and robust protection. Additionally, we discuss the current deployment of the sentinel on a commodity device (i.e., Raspberry Pi). Exhaustive experiments are conducted on the sentinel, demonstrating that it performs meticulously even in heavily stressing conditions. Each defensive layer is tested, reaching a remarkable performance, thus proving the applicability of COSMOS in a distributed and dynamic scenario such as IoT. With the aim of easing the enjoyment of the proposed sentinel, we further developed a friendly and ease-to-use COSMOS App, so that end-users can manage sentinel(s) directly using their own devices (e.g., smartphone). Full article
(This article belongs to the Special Issue Sensor Systems for Internet of Things)
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Open AccessArticle
Management Platforms and Protocols for Internet of Things: A Survey
Sensors 2019, 19(3), 676; https://doi.org/10.3390/s19030676 - 07 Feb 2019
Cited by 9
Abstract
Internet of Things (IoT) management systems require scalability, standardized communication, and context-awareness to achieve the management of connected devices with security and accuracy in real environments. Interoperability and heterogeneity between hardware and application layers are also critical issues. To attend to the network [...] Read more.
Internet of Things (IoT) management systems require scalability, standardized communication, and context-awareness to achieve the management of connected devices with security and accuracy in real environments. Interoperability and heterogeneity between hardware and application layers are also critical issues. To attend to the network requirements and different functionalities, a dynamic and context-sensitive configuration management system is required. Thus, reference architectures (RAs) represent a basic architecture and the definition of key characteristics for the construction of IoT environments. Therefore, choosing the best technologies of the IoT management platforms and protocols through comparison and evaluation is a hard task, since they are difficult to compare due to their lack of standardization. However, in the literature, there are no management platforms focused on addressing all IoT issues. For this purpose, this paper surveys the available policies and solutions for IoT Network Management and devices. Among the available technologies, an evaluation was performed using features such as heterogeneity, scalability, supported technologies, and security. Based on this evaluation, the most promising technologies were chosen for a detailed performance evaluation study (through simulation and deployment in real environments). In terms of contributions, these protocols and platforms were studied in detail, the main features of each approach are highlighted and discussed, open research issues are identified as well as the lessons learned on the topic. Full article
(This article belongs to the Special Issue Sensor Systems for Internet of Things)
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Open AccessArticle
Economic Analysis of a Multi-Sided Platform for Sensor-Based Services in the Internet of Things
Sensors 2019, 19(2), 373; https://doi.org/10.3390/s19020373 - 17 Jan 2019
Abstract
A business model for sensor-based services is proposed where a platform creates a multi-sided market. The business model comprises a platform that serves as an intermediary between human users, app developers, and sensor networks, so that the users use the apps and the [...] Read more.
A business model for sensor-based services is proposed where a platform creates a multi-sided market. The business model comprises a platform that serves as an intermediary between human users, app developers, and sensor networks, so that the users use the apps and the apps process the data supplied by the sensor networks. The platform, acting as a monopolist, posts a fee for each of the three sides so as to maximize its profit. This business model intends to mimic the market-creating innovation that main mobile apps platforms have generated in the smartphone sector. We conduct an analysis of the profit maximization problem faced by the platform, show that optimum prices exist for any parameter value, and show that these prices always induce an equilibrium in the number of agents from each side that join the platform. We show that the relative strength of the value that advertisers attach to the users determines the platform price structure. Depending on the value of this relative strength, two alternative subsidizing strategies are feasible: to subsidize either the users’ subscription or the developers’ registration. Finally, all agents benefit from an increase in the population at any of the three sides. This result provides a rationale for incentivizing not only the user participation, but also the entry of developer undertakings and the deployment of wireless sensor network infrastructure. Full article
(This article belongs to the Special Issue Sensor Systems for Internet of Things)
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Open AccessArticle
LOADng-IoT: An Enhanced Routing Protocol for Internet of Things Applications over Low Power Networks
Sensors 2019, 19(1), 150; https://doi.org/10.3390/s19010150 - 03 Jan 2019
Cited by 8
Abstract
The Internet of Things (IoT) is an emerging paradigm that proposes the connection of objects to exchange information in order to reach a common objective. In IoT networks, it is expected that the nodes will exchange data between each other and with external [...] Read more.
The Internet of Things (IoT) is an emerging paradigm that proposes the connection of objects to exchange information in order to reach a common objective. In IoT networks, it is expected that the nodes will exchange data between each other and with external Internet services. However, due to deployment costs, not all the network devices are able to communicate with the Internet directly. Thus, other network nodes should use Internet-connected nodes as a gateway to forward messages to Internet services. Considering the fact that main routing protocols for low-power networks are not able to reach suitable performance in the displayed IoT environment, this work presents an enhancement to the Lightweight On-demand Ad hoc Distance-vector Routing Protocol—Next Generation (LOADng) for IoT scenarios. The proposal, named LOADng-IoT, is based on three improvements that will allow the nodes to find Internet-connected nodes autonomously and dynamically, decreasing the control message overhead required for the route construction, and reducing the loss of data messages directed to the Internet. Based on the performed assessment study, which considered several number of nodes in dense, sparse, and mobility scenarios, the proposed approach is able to present significant results in metrics related to quality-of-service, reliability, and energy efficiency. Full article
(This article belongs to the Special Issue Sensor Systems for Internet of Things)
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Review

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Open AccessReview
Wireless Sensor Networks for Big Data Systems
Sensors 2019, 19(7), 1565; https://doi.org/10.3390/s19071565 - 01 Apr 2019
Cited by 4
Abstract
Before discovering meaningful knowledge from big data systems, it is first necessary to build a data-gathering infrastructure. Among many feasible data sources, wireless sensor networks (WSNs) are rich big data sources: a large amount of data is generated by various sensor nodes in [...] Read more.
Before discovering meaningful knowledge from big data systems, it is first necessary to build a data-gathering infrastructure. Among many feasible data sources, wireless sensor networks (WSNs) are rich big data sources: a large amount of data is generated by various sensor nodes in large-scale networks. However, unlike typical wireless networks, WSNs have serious deficiencies in terms of data reliability and communication owing to the limited capabilities of the nodes. Moreover, a considerable amount of sensed data are of no interest, meaningless, and redundant when a large number of sensor nodes is densely deployed. Many studies address the existing problems and propose methods to overcome the limitations when constructing big data systems with WSN. However, a published paper that provides deep insight into this research area remains lacking. To address this gap in the literature, we present a comprehensive survey that investigates state-of-the-art research work on introducing WSN in big data systems. Potential applications and technical challenges of networks and infrastructure are presented and explained in accordance with the research areas and objectives. Finally, open issues are presented to discuss promising directions for further research. Full article
(This article belongs to the Special Issue Sensor Systems for Internet of Things)
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