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Section “Sensor Networks”: 10th Anniversary

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

Deadline for manuscript submissions: closed (31 March 2022) | Viewed by 43578

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Special Issue Editors

Dr. Davide Brunelli

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Department of Industrial Engineering, University of Trento, I-38123 Trento, Italy
Interests: energy harvesting; ultra-low-power sensors; IoT; energy-neutral devices
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Prof. Dr. Francesca Cuomo

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Guest Editor

Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, Rome, Italy
Interests: vehicular and sensor networks; low power wide area networks and IoT; cognitive radio networks; multimedia networking; energy saving in the Internet and in the wireless system
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Prof. Dr. Luca Catarinucci

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Guest Editor

Department of Innovation Engineering, University of Salento in Lecce, 73100 Lecce, Italy
Interests: RFID; sensors; antenna design; NFC; 3D-printing in RFID/Electronics
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Dr. Gregor Klančar

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Guest Editor

Laboratory of Control Systems and Cybernetics, Faculty of Electrical Engineering, University of Ljubljana, 1000 Ljubljana, Slovenia
Interests: autonomous mobile robots; motion control; trajectory tracking; path planning; localization; multiagent systems
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Dr. Matteo Nardello

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Guest Editor

Department of Industrial Engineering, University of Trento, I-38123 Trento, Italy
Interests: signal processing; embedded electronic systems; Internet of Thing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The year 2021 marks the 10th anniversary of the Section “Sensor Networks” in the journal Sensors. We have published more than 4000 papers and have more than 140 Section Board Editors. We are extremely grateful to all the scholars who have over the years contributed to the section’s success for their time and effort.

We would like to take this opportunity to celebrate the ten years of the Section “Sensor Networks” with this Special Issue, which will collect high-quality reviews and articles.

We invite submissions of original papers capable of looking ahead in the next ten years. At the same time, we believe it of strategic importance to examine the most significant recent achievements in the field. Thus, we invite review articles on the most influential technologies in the field, which represent the basis of current “sensor networks” applications today.

The Special Issue covers wide hot topics related to Sensor Networks. We are pleased to invite you to submit your manuscripts. Both comprehensive reviews (preferred) and original research articles are welcomed. Topics include but are not limited to:

Terrestrial sensor networks;
Underground sensor networks;
Underwater sensor networks;
Mobile sensor networks;
Smart sensor networks;
IoT networks;
Sensor networks and unmanned vehicles;
Protocols and algorithms of sensor networks;
Energy, management, and control of sensor networks;
Resource allocation, services, and fault tolerance in sensor networks;
Performance, simulation, and modeling of sensor networks;
Security and monitoring of sensor networks;
Sensor circuits and sensor devices;
Radio issues in wireless sensor networks;
Energy-neutral applications;
Deployments and implementations of sensor networks;
RFID sensors;
Antenna design.

Dr. Davide Brunelli
Prof. Dr. Francesca Cuomo
Prof. Dr. Luca Catarinucci
Dr. Gregor Klancar
Dr. Matteo Nardello
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 submissions that pass pre-check are 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 2600 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.

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Published Papers (11 papers)

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Research

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17 pages, 3155 KiB

Open AccessArticle

Sensors Allocation and Observer Design for Discrete Bilateral Teleoperation Systems with Multi-Rate Sampling

by Amir Aminzadeh Ghavifekr, Roberto De Fazio, Ramiro Velazquez and Paolo Visconti

Sensors 2022, 22(7), 2673; https://doi.org/10.3390/s22072673 - 30 Mar 2022

Cited by 2 | Viewed by 1999

Abstract

This study addresses sensor allocation by analyzing exponential stability for discrete-time teleoperation systems. Previous studies mostly concentrate on the continuous-time teleoperation systems and neglect the management of significant practical phenomena, such as data-swap, the effect of sampling rates of samplers, and refresh rates of actuators on the system’s stability. A multi-rate sampling approach is proposed in this study, given the isolation of the master and slave robots in teleoperation systems which may have different hardware restrictions. This architecture collects data through numerous sensors with various sampling rates, assuming that a continuous-time controller stabilizes a linear teleoperation system. The aim is to assign each position and velocity signals to sensors with different sampling rates and divide the state vector between sensors to guarantee the stability of the resulting multi-rate sampled-data teleoperation system. Sufficient Krasovskii-based conditions will be provided to preserve the exponential stability of the system. This problem will be transformed into a mixed-integer program with LMIs (linear matrix inequalities). These conditions are also used to design the observers for the multi-rate teleoperation systems whose estimation errors converge exponentially to the origin. The results are validated by numerical simulations which are useful in designing sensor networks for teleoperation systems. Full article

(This article belongs to the Special Issue Section “Sensor Networks”: 10th Anniversary)

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21 pages, 1456 KiB

Open AccessArticle

LoRaWAN Behaviour Analysis through Dataset Traffic Investigation

by Pietro Spadaccino, Francesco Giuseppe Crinó and Francesca Cuomo

Sensors 2022, 22(7), 2470; https://doi.org/10.3390/s22072470 - 23 Mar 2022

Cited by 14 | Viewed by 3561

Abstract

The large development of Internet of Things technologies is increasing the use of smart-devices to solve and support several real-life issues. In many cases, the aim is to move toward systems that, even if significant demands are not required in terms of quantity of exchanged data, they should be very reliable in terms of battery life and signal coverage. Networks that have these characteristics are the Low Power WAN (LPWAN). One of the most interesting LPWAN is LoRaWAN. LoRaWAN is a network with four principal components: end-devices, gateways, network servers, and application servers. It uses a LoRa physical layer to exchange messages between end-devices and gateways that forward these messages, through classic TCP/IP protocol, to the network server. In this work, we analyse LoRa and LoRaWAN by looking at its transmission characteristics and network behaviour, respectively, explaining the role of its components and showing the message exchange. This analysis is performed through the exploration of a dataset taken from the literature collecting real LoRaWAN packets. The goal of the work is twofold: (1) to investigate, under different perspectives, how a LoRaWAN works and (2) to provide software tools that can be used in several other LoraWAN datasets to measure the network behaviour. We carry out six different analyses to look at the most important features of LoRaWAN. For each analysis we present the adopted measurement strategy as well as the obtained results in the specific use case. Full article

(This article belongs to the Special Issue Section “Sensor Networks”: 10th Anniversary)

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22 pages, 4429 KiB

Open AccessArticle

IoT Device Integration and Payment via an Autonomic Blockchain-Based Service for IoT Device Sharing

by Anas Dawod, Dimitrios Georgakopoulos, Prem Prakash Jayaraman, Ampalavanapillai Nirmalathas and Udaya Parampalli

Sensors 2022, 22(4), 1344; https://doi.org/10.3390/s22041344 - 10 Feb 2022

Cited by 12 | Viewed by 2764

Abstract

The Internet of Things (IoT) incorporates billions of IoT devices (e.g., sensors, cameras, wearables, smart phones, as well as other internet-connected machines in homes, vehicles, and industrial plants), and the number of such connected IoT devices is currently growing rapidly. This paper proposes a novel Autonomic Global IoT Device Discovery and Integration Service (which we refer to as aGIDDI) that permits IoT applications to find IoT devices that are owned and managed by other parties in IoT (which we refer to as IoT device providers), integrate them, and pay for using their data observations. aGIDDI incorporates a suite of interacting sub-services supporting IoT device description, query, integration, payment (via a pay-as-you-go payment model), and access control that utilise a special-purpose blockchain to manage all information needed for IoT applications to find, pay and use the IoT devices they need. The paper describes aGIDDI’s novel protocol that allows any IoT application to discover and automatically integrate and pay for IoT devices and their data that are provided by other parties. The paper also presents aGIDDI’s architecture and proof-of-concept implementation, as well as an experimental evaluation of the performance and scalability of aGIDDI in variety of IoT device integration and payment scenarios. Full article

(This article belongs to the Special Issue Section “Sensor Networks”: 10th Anniversary)

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20 pages, 10570 KiB

Open AccessEditor’s ChoiceArticle

Motion Capture Sensor-Based Emotion Recognition Using a Bi-Modular Sequential Neural Network

by Yajurv Bhatia, ASM Hossain Bari, Gee-Sern Jison Hsu and Marina Gavrilova

Sensors 2022, 22(1), 403; https://doi.org/10.3390/s22010403 - 5 Jan 2022

Cited by 15 | Viewed by 4040

Abstract

Motion capture sensor-based gait emotion recognition is an emerging sub-domain of human emotion recognition. Its applications span a variety of fields including smart home design, border security, robotics, virtual reality, and gaming. In recent years, several deep learning-based approaches have been successful in solving the Gait Emotion Recognition (GER) problem. However, a vast majority of such methods rely on Deep Neural Networks (DNNs) with a significant number of model parameters, which lead to model overfitting as well as increased inference time. This paper contributes to the domain of knowledge by proposing a new lightweight bi-modular architecture with handcrafted features that is trained using a RMSprop optimizer and stratified data shuffling. The method is highly effective in correctly inferring human emotions from gait, achieving a micro-mean average precision of 0.97 on the Edinburgh Locomotive Mocap Dataset. It outperforms all recent deep-learning methods, while having the lowest inference time of 16.3 milliseconds per gait sample. This research study is beneficial to applications spanning various fields, such as emotionally aware assistive robotics, adaptive therapy and rehabilitation, and surveillance. Full article

(This article belongs to the Special Issue Section “Sensor Networks”: 10th Anniversary)

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25 pages, 10476 KiB

Open AccessArticle

Two-Hop Energy Consumption Balanced Routing Algorithm for Solar Insecticidal Lamp Internet of Things

by Xuanchen Guo, Lei Shu, Xing Yang, Edmond Nurellari, Kailiang Li, Bangsong Du and Heyang Yao

Sensors 2022, 22(1), 154; https://doi.org/10.3390/s22010154 - 27 Dec 2021

Cited by 4 | Viewed by 2863

Abstract

Due to the sparsity deployment of nodes, the full connection requirement, and the unpredictable electromagnetic interference on communication caused by high voltage pulse current of Solar Insecticidal Lamps Internet of Things (SIL-IoTs), a Two-Hop Energy Consumption Balanced routing algorithm (THECB) is proposed in this research work. THECB selects next-hop nodes according to 1-hop and 2-hop neighbors’ information. In addition, the greedy forwarding mechanism is expressed in the form of probability; that is, each neighbor node is given a weight between 0 and 1 according to the distance. THECB reduces the data forwarding traffic of nodes whose discharge numbers are relatively higher than those of other nodes so that the unpredictable electromagnetic interference on communication can be weakened. We compare the energy consumption, energy consumption balance, and data forwarding traffic over various discharge numbers, network densities, and transmission radius. The results indicate that THECB achieves better performance than Two-Phase Geographic Greedy Forwarding plus (TPGFPlus), which ignores the requirement of the node-disjoint path. Full article

(This article belongs to the Special Issue Section “Sensor Networks”: 10th Anniversary)

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19 pages, 5489 KiB

Open AccessArticle

Dynamic Adjustment of Weighted GCC-PHAT for Position Estimation in an Ultrasonic Local Positioning System

by José Manuel Villadangos, Jesús Ureña, Juan Jesús García-Domínguez, Ana Jiménez-Martín, Álvaro Hernández and Mª Carmen Pérez-Rubio

Sensors 2021, 21(21), 7051; https://doi.org/10.3390/s21217051 - 24 Oct 2021

Cited by 5 | Viewed by 3533

Abstract

Ultrasonic local positioning systems (ULPS) have been brought to the attention of researchers as one of the possibilities that can be used for indoor localization. Acoustic systems combine a suitable trade-off between precision, ease of development, and cost. This work proposes a method for measuring the time of arrival of encoded emissions from a set of ultrasonic beacons, which are used to implement an accurate ULPS. This method uses the generalized cross-correlation technique with PHAT filter and weighting factor β (GCC-PHAT-β). To improve the performance of the GCC-PHAT-β in encoded emission detection, the employment is proposed of mixed-medium multiple-access techniques, based on code division and time division multiplexing of beacon emissions (CDMA and TDMA respectively), and to dynamically adjust the PHAT filter weighting factor. The receiver position is obtained by hyperbolic multilateration from the time differences of arrival (TDoA) between a reference beacon and the rest, thus avoiding the need for receiver synchronization. The results show how the dynamic adaptation of the weighting factor significantly reduces positioning errors from 20 cm to 2 cm in 80% of measurements. The simulated and real experiments prove that the proposed algorithms improve the performance of the ULPS in situations with lower signal-to-noise ratios (SNR) than 0 dB and in environments where the multipath effect makes it difficult to correctly detect the encoded ultrasonic emissions. Full article

(This article belongs to the Special Issue Section “Sensor Networks”: 10th Anniversary)

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16 pages, 1021 KiB

Open AccessArticle

GPS-Free, Error Tolerant Path Planning for Swarms of Micro Aerial Vehicles with Quality Amplification ^‡

by Michel Barbeau, Joaquin Garcia-Alfaro, Evangelos Kranakis and Fillipe Santos

Sensors 2021, 21(14), 4731; https://doi.org/10.3390/s21144731 - 10 Jul 2021

Cited by 3 | Viewed by 2165

Abstract

We present an error tolerant path planning algorithm for Micro Aerial Vehicle (MAV) swarms. We assume navigation without GPS-like techniques. The MAVs find their path using sensors and cameras, identifying and following a series of visual landmarks. The visual landmarks lead the MAVs towards their destination. MAVs are assumed to be unaware of the terrain and locations of the landmarks. They hold a priori information about landmarks, whose interpretation is prone to errors. Errors are of two types, recognition or advice. Recognition errors follow from misinterpretation of sensed data or a priori information, or confusion of objects, e.g., due to faulty sensors. Advice errors are consequences of outdated or wrong information about landmarks, e.g., due to weather conditions. Our path planning algorithm is cooperative. MAVs communicate and exchange information wirelessly, to minimize the number of recognition and advice errors. Hence, the quality of the navigation decision process is amplified. Our solution successfully achieves an adaptive error tolerant navigation system. Quality amplification is parameterized with respect to the number of MAVs. We validate our approach with theoretical proofs and numeric simulations. Full article

(This article belongs to the Special Issue Section “Sensor Networks”: 10th Anniversary)

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Review

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28 pages, 2452 KiB

Open AccessReview

Modeling Radio Wave Propagation for Wireless Sensor Networks in Vegetated Environments: A Systematic Literature Review

by Alexis Barrios-Ulloa, Paola Patricia Ariza-Colpas, Hernando Sánchez-Moreno, Alejandra Paola Quintero-Linero and Emiro De la Hoz-Franco

Sensors 2022, 22(14), 5285; https://doi.org/10.3390/s22145285 - 15 Jul 2022

Cited by 24 | Viewed by 4697

Abstract

The use of wireless sensor networks (WSN) for monitoring variables in agricultural environments and natural forests has been increasing in recent years. However, the sizing of these systems is affected by the inaccuracy of the radio wave propagation models used, leading to possible increased costs and measurement errors. This systematic literature review (SLR) aims to identify propagation models widely used in WSN deployments in agricultural or naturally vegetated environments and their effectiveness in estimating signal losses. We also identified today’s wireless technologies most used in precision agriculture (PA) system implementations. In addition, the results of studies focused on the development of new propagation models for different environments are evaluated. Scientific and technical analysis is presented based on articles consulted in different specialized databases, which were selected according to different combinations of criteria. The results show that, in most of the application cases, vegetative models present high error values when estimating attenuation. Full article

(This article belongs to the Special Issue Section “Sensor Networks”: 10th Anniversary)

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44 pages, 726 KiB

Open AccessEditor’s ChoiceReview

Data Gathering Techniques in WSN: A Cross-Layer View

by Omer Gurewitz, Mark Shifrin and Efi Dvir

Sensors 2022, 22(7), 2650; https://doi.org/10.3390/s22072650 - 30 Mar 2022

Cited by 19 | Viewed by 6358

Abstract

Wireless sensor networks (WSNs) have taken a giant leap in scale, expanding their applicability to a large variety of technological domains and applications, ranging from the Internet of things (IoT) for smart cities and smart homes to wearable technology healthcare applications, underwater, agricultural and environmental monitoring and many more. This expansion is rapidly growing every passing day in terms of the variety, heterogeneity and the number of devices which such applications support. Data collection is commonly the core application in WSN and IoT networks, which are typically composed of a large variety of devices, some constrained by their resources (e.g., processing, storage, energy) and some by highly diverse demands. Many challenges span all the conceptual communication layers, from the Physical to the Applicational. Many novel solutions devised in the past do not scale well with the exponential growth in the population of the devices and need to be adapted, revised, or new innovative solutions are required to comply with this massive growth. Furthermore, recent technological advances present new opportunities which can be leveraged in this context. This paper provides a cross-layer perspective and review of data gathering in WSN and IoT networks. We provide some background and essential milestones that have laid the foundation of many subsequent solutions suggested over the years. We mainly concentrate on recent state-of-the-art research, which facilitates the scalable, energy-efficient, cost-effective, and human-friendly functionality of WSNs and the novel applications in the years to come. Full article

(This article belongs to the Special Issue Section “Sensor Networks”: 10th Anniversary)

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24 pages, 10918 KiB

Open AccessReview

Concise Historic Overview of Strain Sensors Used in the Monitoring of Civil Structures: The First One Hundred Years

by Branko Glisic

Sensors 2022, 22(6), 2397; https://doi.org/10.3390/s22062397 - 20 Mar 2022

Cited by 42 | Viewed by 5259

Abstract

Strain is one of the most frequently monitored parameters in civil structural health monitoring (SHM) applications, and strain-based approaches were among the first to be explored and applied in SHM. There are multiple reasons why strain plays such an important role in SHM: strain is directly related to stress and deflection, which reflect structural performance, safety, and serviceability. Strain field anomalies are frequently indicators of unusual structural behaviors (e.g., damage or deterioration). Hence, the earliest concepts of strain sensing were explored in the mid-XIX century, the first effective strain sensor appeared in 1919, and the first onsite applications followed in the 1920′s. Today, one hundred years after the first developments, two generations of strain sensors, based on electrical and fiber-optic principles, firmly reached market maturity and established themselves as reliable tools applied in strain-based SHM. Along with sensor developments, the application methods evolved: the first generation of discrete sensors featured a short gauge length and provided a basis for local material monitoring; the second generation greatly extended the applicability and effectiveness of strain-based SHM by providing long gauge and one-dimensional (1D) distributed sensing, thus enabling global structural and integrity monitoring. Current research focuses on a third generation of strain sensors for two-dimensional (2D) distributed and quasi-distributed sensing, based on new advanced technologies. On the occasion of strain sensing centenary, and as an homage to all researchers, practitioners, and educators who contributed to strain-based SHM, this paper presents an overview of the first one hundred years of strain sensing technological progress, with the objective to identify relevant transformative milestones and indicate possible future research directions. Full article

(This article belongs to the Special Issue Section “Sensor Networks”: 10th Anniversary)

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15 pages, 400 KiB

Open AccessReview

Air–Oxygen Blenders for Mechanical Ventilators: A Literature Review

by Gabryel F. Soares, Otacílio M. Almeida, José W. M. Menezes, Sergei S. A. Kozlov and Joel J. P. C. Rodrigues

Sensors 2022, 22(6), 2182; https://doi.org/10.3390/s22062182 - 11 Mar 2022

Cited by 4 | Viewed by 4307

Abstract

Respiratory diseases are one of the most common causes of death in the world and this recent COVID-19 pandemic is a key example. Problems such as infections, in general, affect many people and depending on the form of transmission they can spread throughout the world and weaken thousands of people. Two examples are severe acute respiratory syndrome and the recent coronavirus disease. These diseases have mild and severe forms, in which patients gravely affected need ventilatory support. The equipment that serves as a basis for operation of the mechanical ventilator is the air–oxygen blender, responsible for carrying out the air–oxygen mixture in the proper proportions ensuring constant supply. New blender models are described in the literature together with applications of control techniques, such as Proportional, Integrative and Derivative (PID); Fuzzy; and Adaptive. The results obtained from the literature show a significant improvement in patient care when using automatic controls instead of manual adjustment, increasing the safety and accuracy of the treatment. This study presents a deep review of the state of the art in air–oxygen benders, identifies the most relevant characteristics, performs a comparison study considering the most relevant available solutions, and identifies open research directions in the topic. Full article

(This article belongs to the Special Issue Section “Sensor Networks”: 10th Anniversary)

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