Open AccessFeature PaperArticle
Athena: Towards Decision-Centric Anticipatory Sensor Information Delivery
J. Sens. Actuator Netw. 2018, 7(1), 5; doi:10.3390/jsan7010005 -
Abstract
The paper introduces a new direction in quality-of-service-aware networked sensing that designs communication protocols and scheduling policies for data delivery that are optimized specifically for decision needs. The work complements present decision monitoring and support tools and falls in the larger framework of
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The paper introduces a new direction in quality-of-service-aware networked sensing that designs communication protocols and scheduling policies for data delivery that are optimized specifically for decision needs. The work complements present decision monitoring and support tools and falls in the larger framework of decision-driven resource management. A hallmark of the new protocols is that they are aware of the inference structure used to arrive at decisions (from logical predicates), as well as the data (and data quality) that need to be furnished to successfully evaluate the unknowns on which these decisions are based. Such protocols can therefore anticipate and deliver precisely the right data, at the right level of quality, from the right sources, at the right time, to enable valid and timely decisions at minimum cost to the underlying network. This paper presents the decision model used and the protocol design philosophy, reviews the key recent results and describes a novel system, called Athena, that is the first to embody the aforementioned data delivery paradigm. Evaluation results are presented that compare the performance of decision-centric anticipatory information delivery to several baselines, demonstrating its various advantages in terms of decision timeliness, validity and network resources used. The paper concludes with a discussion of remaining future challenges in this emerging area. Full article
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Open AccessArticle
Real-Time Management of Groundwater Resources Based on Wireless Sensors Networks
J. Sens. Actuator Netw. 2018, 7(1), 4; doi:10.3390/jsan7010004 -
Abstract
Groundwater plays a vital role in the arid inland river basins, in which the groundwater management is critical to the sustainable development of area economy and ecology. Traditional sustainable management approaches are to analyze different scenarios subject to assumptions or to construct simulation–optimization
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Groundwater plays a vital role in the arid inland river basins, in which the groundwater management is critical to the sustainable development of area economy and ecology. Traditional sustainable management approaches are to analyze different scenarios subject to assumptions or to construct simulation–optimization models to obtain optimal strategy. However, groundwater system is time-varying due to exogenous inputs. In this sense, the groundwater management based on static data is relatively outdated. As part of the Heihe River Basin (HRB), which is a typical arid river basin in Northwestern China, the Daman irrigation district was selected as the study area in this paper. First, a simulation–optimization model was constructed to optimize the pumping rates of the study area according to the groundwater level constraints. Three different groundwater level constraints were assigned to explore sustainable strategies for groundwater resources. The results indicated that the simulation–optimization model was capable of identifying the optimal pumping yields and satisfy the given constraints. Second, the simulation–optimization model was integrated with wireless sensors network (WSN) technology to provide real-time features for the management. The results showed time-varying feature for the groundwater management, which was capable of updating observations, constraints, and decision variables in real time. Furthermore, a web-based platform was developed to facilitate the decision-making process. This study combined simulation and optimization model with WSN techniques and meanwhile attempted to real-time monitor and manage the scarce groundwater resource, which could be used to support the decision-making related to sustainable management. Full article
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Open AccessEditorial
Acknowledgement to Reviewers of Journal of Sensor and Actuator Networks in 2017
J. Sens. Actuator Netw. 2018, 7(1), 3; doi:10.3390/jsan7010003 -
Abstract
Peer review is an essential part in the publication process, ensuring that Journal of Sensor and Actuator Networks maintains high quality standards for its published papers.[...] Full article
Open AccessArticle
Development of Intelligent Core Network for Tactile Internet and Future Smart Systems
J. Sens. Actuator Netw. 2018, 7(1), 1; doi:10.3390/jsan7010001 -
Abstract
One of the main design aspects of the Tactile Internet system is the 1 ms end-to-end latency, which is considered as being the main challenge with the system realization. Forced by recent development and capabilities of the fifth generation (5G) cellular system, the
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One of the main design aspects of the Tactile Internet system is the 1 ms end-to-end latency, which is considered as being the main challenge with the system realization. Forced by recent development and capabilities of the fifth generation (5G) cellular system, the Tactile Internet will become a real. One way to overcome the 1 ms latency is to employ a centralized controller in the core of the network with a global knowledge of the system, together with the concept of network function virtualization (NFV). This is the idea behind the software defined networking (SDN). This paper introduces a Tactile Internet system structure, which employs SDN in the core of the cellular network and mobile edge computing (MEC) in multi-levels. The work is mainly concerned with the structure of the core network. The system is simulated over a reliable environment and introduces a round trip latency of orders of 1 ms. This can be interpreted by the reduction of intermediate nodes that are involved in the communication process. Full article
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Open AccessArticle
Bayesian-Optimization-Based Peak Searching Algorithm for Clustering in Wireless Sensor Networks
J. Sens. Actuator Netw. 2018, 7(1), 2; doi:10.3390/jsan7010002 -
Abstract
We propose a new peak searching algorithm (PSA) that uses Bayesian optimization to find probability peaks in a dataset, thereby increasing the speed and accuracy of clustering algorithms. Wireless sensor networks (WSNs) are becoming increasingly common in a wide variety of applications that
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We propose a new peak searching algorithm (PSA) that uses Bayesian optimization to find probability peaks in a dataset, thereby increasing the speed and accuracy of clustering algorithms. Wireless sensor networks (WSNs) are becoming increasingly common in a wide variety of applications that analyze and use collected sensing data. Typically, the collected data cannot be directly used in modern data analysis problems that adopt machine learning techniques because such data lacks additional information (such as data labels) specifying its purpose of users. Clustering algorithms that divide the data in a dataset into clusters are often used when additional information is not provided. However, traditional clustering algorithms such as expectation–maximization (EM) and k-means algorithms require massive numbers of iterations to form clusters. Processing speeds are therefore slow, and clustering results become less accurate because of the way such algorithms form clusters. The PSA addresses these problems, and we adapt it for use with the EM and k-means algorithms, creating the modified PSEM and PSk-means algorithms. Our simulation results show that our proposed PSEM and PSk-means algorithms significantly decrease the required number of clustering iterations (by 1.99 to 6.3 times), and produce clustering that, for a synthetic dataset, is 1.69 to 1.71 times more accurate than it is for traditional EM and enhanced k-means (k-means++) algorithms. Moreover, in a simulation of WSN applications aimed at detecting outliers, PSEM correctly identified the outliers in a real dataset, decreasing iterations by approximately 1.88 times, and PSEM was 1.29 times more accurate than EM at a maximum. Full article
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Open AccessArticle
Using Sensors to Study Home Activities
J. Sens. Actuator Netw. 2017, 6(4), 32; doi:10.3390/jsan6040032 -
Abstract
Understanding home activities is important in social research to study aspects of home life, e.g., energy-related practices and assisted living arrangements. Common approaches to identifying which activities are being carried out in the home rely on self-reporting, either retrospectively (e.g., interviews, questionnaires, and
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Understanding home activities is important in social research to study aspects of home life, e.g., energy-related practices and assisted living arrangements. Common approaches to identifying which activities are being carried out in the home rely on self-reporting, either retrospectively (e.g., interviews, questionnaires, and surveys) or at the time of the activity (e.g., time use diaries). The use of digital sensors may provide an alternative means of observing activities in the home. For example, temperature, humidity and light sensors can report on the physical environment where activities occur, while energy monitors can report information on the electrical devices that are used to assist the activities. One may then be able to infer from the sensor data which activities are taking place. However, it is first necessary to calibrate the sensor data by matching it to activities identified from self-reports. The calibration involves identifying the features in the sensor data that correlate best with the self-reported activities. This in turn requires a good measure of the agreement between the activities detected from sensor-generated data and those recorded in self-reported data. To illustrate how this can be done, we conducted a trial in three single-occupancy households from which we collected data from a suite of sensors and from time use diaries completed by the occupants. For sensor-based activity recognition, we demonstrate the application of Hidden Markov Models with features extracted from mean-shift clustering and change points analysis. A correlation-based feature selection is also applied to reduce the computational cost. A method based on Levenshtein distance for measuring the agreement between the activities detected in the sensor data and that reported by the participants is demonstrated. We then discuss how the features derived from sensor data can be used in activity recognition and how they relate to activities recorded in time use diaries. Full article
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Open AccessArticle
Addressing the Issue of Routing Unfairness in Opportunistic Backhaul Networks for Collecting Sensed Data
J. Sens. Actuator Netw. 2017, 6(4), 31; doi:10.3390/jsan6040031 -
Abstract
Widely deploying sensors in the environment and embedding them in physical objects is a crucial step towards realizing smart and sustainable cities. To cope with rising resource demands and limited budgets, opportunistic networks (OppNets) offer a scalable backhaul option for collecting delay-tolerant data
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Widely deploying sensors in the environment and embedding them in physical objects is a crucial step towards realizing smart and sustainable cities. To cope with rising resource demands and limited budgets, opportunistic networks (OppNets) offer a scalable backhaul option for collecting delay-tolerant data from sensors to gateways in order to enable efficient urban operations and services. While pervasive devices such as smartphones and tablets contribute significantly to the scalability of OppNets, closely following human movement patterns and social structure introduces network characteristics that pose routing challenges. Our study on the impact of these characteristics reveals that existing routing protocols subject a key set of devices to higher resource consumption, to which their users may respond by withdrawing participation. Unfortunately, existing solutions addressing this unfairness do not guarantee achievable throughput since they are not specifically designed for sensed data collection scenarios. Based on concepts derived from the study, we suggest design guidelines for adapting applicable routing protocols to sensed data collection scenarios. We also follow our design guidelines to propose the Fair Locality Aware Routing (FLARoute) technique. Evaluating FLARoute within an existing routing protocol confirms improved fairness and throughput under conditions that compromise the performance of existing solutions. Full article
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Open AccessArticle
Extended Batches Petri Nets Based System for Road Traffic Management in WSNs
J. Sens. Actuator Netw. 2017, 6(4), 30; doi:10.3390/jsan6040030 -
Abstract
One of the most critical issues in modern cities is transportation management. Issues that are encountered in this regard, such as traffic congestion, high accidents rates and air pollution etc., have pushed the use of Intelligent Transportation System (ITS) technologies in order to
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One of the most critical issues in modern cities is transportation management. Issues that are encountered in this regard, such as traffic congestion, high accidents rates and air pollution etc., have pushed the use of Intelligent Transportation System (ITS) technologies in order to facilitate the traffic management. Seen in this perspective, this paper brings forward a road traffic management system based on wireless sensor networks; it introduces the functional and deployment architecture of the system and focuses on the analysis component that uses a new extension of batches Petri nets for modeling road traffic flow. A real world implementation of visualization and data analysis components were carried out. Full article
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Open AccessArticle
Delegation Based User Authentication Framework over Cognitive Radio Networks
J. Sens. Actuator Netw. 2017, 6(4), 29; doi:10.3390/jsan6040029 -
Abstract
To address the ever increasing demand for wireless bandwidth, cognitive radio networks (CRNs) have been proposed to improve the efficiency of channel utilization. CRN permits unlicensed users to utilize the idle spectrum as long as it does not introduce interference to the primary
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To address the ever increasing demand for wireless bandwidth, cognitive radio networks (CRNs) have been proposed to improve the efficiency of channel utilization. CRN permits unlicensed users to utilize the idle spectrum as long as it does not introduce interference to the primary users due to the Federal Communications Commission’s recent regulatory policies. In this paper, we first identify some required distinctive security and privacy features for CRNs focused on ECMA-392, which is the first industrial standard for personal or portable devices in the television white spaces. After that, we propose a delegation based user authentication framework as a basic security and privacy module with full consideration of the required features over CRNs. The proposed framework provides privacy preserving yet accountable security within the CRN entities. Security and privacy analyses show that the proposed framework supports unlinkability, context privacy, anonymity, no registration and conditional traceability, which are the required security and privacy aspects in CRNs. Full article
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Open AccessFeature PaperArticle
Wearable-Based Human Activity Recognition Using an IoT Approach
J. Sens. Actuator Netw. 2017, 6(4), 28; doi:10.3390/jsan6040028 -
Abstract
This paper presents a novel system based on the Internet of Things (IoT) to Human Activity Recognition (HAR) by monitoring vital signs remotely. We use machine learning algorithms to determine the activity done within four pre-established categories (lie, sit, walk and jog). Meanwhile,
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This paper presents a novel system based on the Internet of Things (IoT) to Human Activity Recognition (HAR) by monitoring vital signs remotely. We use machine learning algorithms to determine the activity done within four pre-established categories (lie, sit, walk and jog). Meanwhile, it is able to give feedback during and after the activity is performed, using a remote monitoring component with remote visualization and programmable alarms. This system was successfully implemented with a 95.83% success ratio. Full article
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Open AccessArticle
A Social Environmental Sensor Network Integrated within a Web GIS Platform
J. Sens. Actuator Netw. 2017, 6(4), 27; doi:10.3390/jsan6040027 -
Abstract
We live in an era where typical measures towards the mitigation of environmental degradation follow the identification and recording of natural parameters closely associated with it. In addition, current scientific knowledge on the one hand may be applied to minimize the environmental impact
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We live in an era where typical measures towards the mitigation of environmental degradation follow the identification and recording of natural parameters closely associated with it. In addition, current scientific knowledge on the one hand may be applied to minimize the environmental impact of anthropogenic activities, whereas informatics on the other, playing a key role in this ecosystem, do offer new ways of implementing complex scientific processes regarding the collection, aggregation and analysis of data concerning environmental parameters. Furthermore, another related aspect to consider is the fact that almost all relevant data recordings are influenced by their given spatial characteristics. Taking all aforementioned inputs into account, managing such a great amount of complex and remote data requires specific digital structures; these structures are typically deployed over the Web on an attempt to capitalize existing open software platforms and modern developments of hardware technology. In this paper we present an effort to provide a technical solution based on sensing devices that are based on the well-known Arduino platform and operate continuously for gathering and transmitting of environmental state information. Controls, user interface and extensions of the proposed project rely on the Android mobile device platform (both from the software and hardware side). Finally, a crucial novel aspect of our work is the fact that all herein gathered data carry spatial information, which is rather fundamental for the successful correlation between pollutants and their place of origin. The latter is implemented by an interactive Web GIS platform operating oversight in situ and on a timeline basis. Full article
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Open AccessFeature PaperReview
Big Sensed Data Meets Deep Learning for Smarter Health Care in Smart Cities
J. Sens. Actuator Netw. 2017, 6(4), 26; doi:10.3390/jsan6040026 -
Abstract
With the advent of the Internet of Things (IoT) concept and its integration with the smart city sensing, smart connected health systems have appeared as integral components of the smart city services. Hard sensing-based data acquisition through wearables or invasive probes, coupled with
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With the advent of the Internet of Things (IoT) concept and its integration with the smart city sensing, smart connected health systems have appeared as integral components of the smart city services. Hard sensing-based data acquisition through wearables or invasive probes, coupled with soft sensing-based acquisition such as crowd-sensing results in hidden patterns in the aggregated sensor data. Recent research aims to address this challenge through many hidden perceptron layers in the conventional artificial neural networks, namely by deep learning. In this article, we review deep learning techniques that can be applied to sensed data to improve prediction and decision making in smart health services. Furthermore, we present a comparison and taxonomy of these methodologies based on types of sensors and sensed data. We further provide thorough discussions on the open issues and research challenges in each category. Full article
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Open AccessReview
Multi-Criteria Decision Analysis Methods in the Mobile Cloud Offloading Paradigm
J. Sens. Actuator Netw. 2017, 6(4), 25; doi:10.3390/jsan6040025 -
Abstract
Mobile cloud computing (MCC) is becoming a popular mobile technology that aims to augment local resources of mobile devices, such as energy, computing, and storage, by using available cloud services and functionalities. The offloading process is one of the techniques used in MCC
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Mobile cloud computing (MCC) is becoming a popular mobile technology that aims to augment local resources of mobile devices, such as energy, computing, and storage, by using available cloud services and functionalities. The offloading process is one of the techniques used in MCC to enhance the capabilities of mobile devices by moving mobile data and computation-intensive operations to cloud platforms. Several techniques have been proposed to perform and improve the efficiency and effectiveness of the offloading process, such as multi-criteria decision analysis (MCDA). MCDA is a well-known concept that aims to select the best solution among several alternatives by evaluating multiple conflicting criteria, explicitly in decision making. However, as there are a variety of platforms and technologies in mobile cloud computing, it is still challenging for the offloading process to reach a satisfactory quality of service from the perspective of customers’ computational service requests. Thus, in this paper, we conduct a literature review that leads to a better understanding of the usability of the MCDA methods in the offloading operation that is strongly reliant on the mobile environment, network operators, and cloud services. Furthermore, we discuss the challenges and opportunities of these MCDA techniques for offloading research in mobile cloud computing. Finally, we recommend a set of future research directions in MCDA used for the mobile cloud offloading process. Full article
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Open AccessArticle
Localization in Wireless Sensor Networks: A Survey on Algorithms, Measurement Techniques, Applications and Challenges
J. Sens. Actuator Netw. 2017, 6(4), 24; doi:10.3390/jsan6040024 -
Abstract
Localization is an important aspect in the field of wireless sensor networks (WSNs) that has developed significant research interest among academia and research community. Wireless sensor network is formed by a large number of tiny, low energy, limited processing capability and low-cost sensors
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Localization is an important aspect in the field of wireless sensor networks (WSNs) that has developed significant research interest among academia and research community. Wireless sensor network is formed by a large number of tiny, low energy, limited processing capability and low-cost sensors that communicate with each other in ad-hoc fashion. The task of determining physical coordinates of sensor nodes in WSNs is known as localization or positioning and is a key factor in today’s communication systems to estimate the place of origin of events. As the requirement of the positioning accuracy for different applications varies, different localization methods are used in different applications and there are several challenges in some special scenarios such as forest fire detection. In this paper, we survey different measurement techniques and strategies for range based and range free localization with an emphasis on the latter. Further, we discuss different localization-based applications, where the estimation of the location information is crucial. Finally, a comprehensive discussion of the challenges such as accuracy, cost, complexity, and scalability are given. Full article
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Open AccessArticle
ABORt: Acknowledgement-Based Opportunistic Routing Protocol for High Data Rate Multichannel WSNs
J. Sens. Actuator Netw. 2017, 6(4), 23; doi:10.3390/jsan6040023 -
Abstract
The ease of deployment and the auto-configuration capabilities of Wireless Sensor Networks (WSNs) make them very attractive in different domains like environmental, home automation or heath care applications. The use of multichannel communications in WSNs helps to improve the overall performance of the
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The ease of deployment and the auto-configuration capabilities of Wireless Sensor Networks (WSNs) make them very attractive in different domains like environmental, home automation or heath care applications. The use of multichannel communications in WSNs helps to improve the overall performance of the network. However, in heavy traffic scenarios, routing protocols should be adapted to allow load balancing and to avoid losing data packets due to congestion and queue overflow. In this paper, we present an Acknowledgement-Based Opportunistic Routing (ABORt) protocol designed for high data rate multichannel WSNs. It is a low overhead protocol that does not rely on synchronization for control traffic exchange during the operational phase of the network. ABORt is an opportunistic protocol that relies on link layer acknowledgements to disseminate routing metrics, which helps to reduce overhead. The performance of ABORt is evaluated using the Cooja simulator and the obtained results show that ABORt has a high packet delivery ratio with reduced packet end-to-end delay compared to two single channel routing protocols and two multichannel routing protocols that use number of hops and expected transmission count as routing metrics. Full article
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Open AccessArticle
Energy Efficient Hardware and Improved Cluster-Tree Topology for Lifetime Prolongation in ZigBee Sensor Networks
J. Sens. Actuator Netw. 2017, 6(4), 22; doi:10.3390/jsan6040022 -
Abstract
In wireless sensor networks, building energy-efficient systems is one of the major challenges. In such networks, nodes are usually supplied by low power and small batteries. Many factors are involved in the energy consumption, and this issue may be considered as a cross-layer
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In wireless sensor networks, building energy-efficient systems is one of the major challenges. In such networks, nodes are usually supplied by low power and small batteries. Many factors are involved in the energy consumption, and this issue may be considered as a cross-layer problem, from the hardware architecture to the application layer. This paper aims at presenting a hybrid solution for sensor networks based on two main aspects. The first one is the hardware architecture, where we present a prototype of a sensor node we designed. This node proved its efficiency in terms of energy consumption. The second aspect is related to the topology construction and presents a new topology control algorithm based on graph computing. Thus, our system consists of a real indoor application for temperature and humidity monitoring, applicable to home automation or industrial monitoring. We performed the experiments using a set of sensor nodes deployed over a building and proved the efficiency of the system in terms of energy consumption, network lifetime and data delivery. Full article
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Open AccessFeature PaperArticle
The Sensor Network Calculus as Key to the Design of Wireless Sensor Networks with Predictable Performance
J. Sens. Actuator Netw. 2017, 6(3), 21; doi:10.3390/jsan6030021 -
Abstract
In this article, we survey the sensor network calculus (SensorNC), a framework continuously developed since 2005 to support the predictable design, control and management of large-scale wireless sensor networks with timing constraints. It is rooted in the deterministic network calculus, which it instantiates
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In this article, we survey the sensor network calculus (SensorNC), a framework continuously developed since 2005 to support the predictable design, control and management of large-scale wireless sensor networks with timing constraints. It is rooted in the deterministic network calculus, which it instantiates for WSNs, as well as it generalizes it in some crucial aspects, as for instance in-network processing. Besides presenting these core concepts of the SensorNC, we also discuss the advanced concept of self-modeling of WSNs and efficient tool support for the SensorNC. Furthermore, several applications of the SensorNC methodology, like sink and node placement, as well as TDMA design, are displayed. Full article
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Open AccessArticle
User-Generated Services Composition in Smart Multi-User Environments
J. Sens. Actuator Netw. 2017, 6(3), 20; doi:10.3390/jsan6030020 -
Abstract
The increasing complexity shown in Smart Environments, together with the spread of social networks, is increasingly moving the role of users from simple information and services consumers to actual producers. In this work, we focus on security issues raised by a particular kind
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The increasing complexity shown in Smart Environments, together with the spread of social networks, is increasingly moving the role of users from simple information and services consumers to actual producers. In this work, we focus on security issues raised by a particular kind of services: those generated by users. User-Generated Services (UGSs) are characterized by a set of features that distinguish them from conventional services. To cope with UGS security problems, we introduce three different policy management models, analyzing benefits and drawbacks of each approach. Finally, we propose a cloud-based solution that enables the composition of multiple UGSs and policy models, allowing users’ devices to share features and services in Internet of Things (IoT) based scenarios. Full article
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Open AccessArticle
Enhanced IoT-Based End-To-End Emergency and Disaster Relief System
J. Sens. Actuator Netw. 2017, 6(3), 19; doi:10.3390/jsan6030019 -
Abstract
In this paper, we present a new enhancement for an emergency and disaster relief system called Critical and Rescue Operations using Wearable Wireless sensors networks (CROW2). We address the reliability challenges in setting up a wireless autonomous communication system in order
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In this paper, we present a new enhancement for an emergency and disaster relief system called Critical and Rescue Operations using Wearable Wireless sensors networks (CROW2). We address the reliability challenges in setting up a wireless autonomous communication system in order to offload data from the disaster area (rescuers, trapped victims, civilians, media, etc.) back to a command center. The proposed system connects deployed rescuers to extended networks and the Internet. CROW2 is an end-to-end system that runs the recently-proposed Optimized Routing Approach for Critical and Emergency Networks (ORACE-Net) routing protocol. The system integrates heterogeneous wireless devices (Raspberry Pi, smart phones, sensors) and various communicating technologies (WiFi IEEE 802.11n, Bluetooth IEEE 802.15.1) to enable end-to-end network connectivity, which is monitored by a cloud Internet-of-Things platform. First, we present the CROW2 generic system architecture, which is adaptable to various technologies integration at different levels (i.e., on-body, body-to-body, off-body). Second, we implement the ORACE-Net protocol on heterogeneous devices including Android-based smart phones and Linux-based Raspberry Pi devices. These devices act as on-body coordinators to collect information from on-body sensors. The collected data is then pushed to the command center thanks to multi-hop device-to-device communication. Third, the overall CROW2 system performance is evaluated according to relevant metrics including end-to-end link quality estimation, throughput and end-to-end delay. As a proof-of-concept, we validate the system architecture through deployment and extracted experimental results. Finally, we highlight motion detection and links’ unavailability prevention based on the recorded data where the main factors (i.e., interference and noise) that affect the performance are analyzed. Full article
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Open AccessArticle
A New Approach to Estimating the Path Loss in Underground Wireless Sensor Networks
J. Sens. Actuator Netw. 2017, 6(3), 18; doi:10.3390/jsan6030018 -
Abstract
Unlike terrestrial Wireless Sensor Networks (WSNs), communication between buried nodes in WUSNs happens through the ground. Due to the complexity of soil, accurate estimation of the underground signal attenuation is challenging. Existing path loss models mainly rely on semi-empirical and empirical mixing models
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Unlike terrestrial Wireless Sensor Networks (WSNs), communication between buried nodes in WUSNs happens through the ground. Due to the complexity of soil, accurate estimation of the underground signal attenuation is challenging. Existing path loss models mainly rely on semi-empirical and empirical mixing models for calculating the dielectric properties of the soil. In this paper, two existing models for estimating the path loss in soil (i.e., the CRIM-Fresnel and Modified-Friis models) are compared with measurements obtained at three locations. In addition, an improved method is proposed for estimating the path loss based on a new approach for calculating the dielectric properties of soil from Time Domain Reflectometry (TDR) measurements. The proposed approach calculates the complex permittivity values from TDR waveform based on a new modified method and subsequently use them as inputs into the Modified-Friis model. The results from the field trials were compared with the proposed method and the existing models. The results of this comparison showed that the proposed estimation technique provides a better estimation of Radio Frequency (RF) attenuation than the existing models. It also eliminates the need to take samples back to the laboratory by providing in situ calculation of attenuation based on TDR. Full article
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