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Applications of Wireless Sensor Networks: Innovations and Future Trends

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A special issue of Journal of Sensor and Actuator Networks (ISSN 2224-2708). This special issue belongs to the section "Wireless Control Networks".

Deadline for manuscript submissions: 30 June 2025 | Viewed by 12458

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Special Issue Editors

Dr. Dionisis Kandris

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microSENSES Laboratory, Department of Electrical and Electronics Engineering, University of West Attica, 12244 Athens, Greece
Interests: algorithmic study of wireless sensor networks in terms of routing protocols; energy efficiency; congestion avoidance; coverage maximization; multiobjective optimization
Special Issues, Collections and Topics in MDPI journals

Dr. Eleftherios Anastasiadis

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Guest Editor

microSENSES Laboratory, Department of Electrical and Electronics Engineering, University of West Attica, 12244 Athens, Greece
Interests: algorithm design; approximation algorithms; algorithmic mechanism design; game theory; optimization algorithms for wireless sensor networks
Special Issues, Collections and Topics in MDPI journals

Dr. Purav Shah

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Guest Editor

School of Science and Technology, Department of Computer and Communications Engineering, Middlesex University London, The Burroughs, London NW4 4BT, UK
Interests: wireless sensor networks; Internet of Things (IoT); intelligent transportation systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Wireless Sensor Networks (WSNs), thanks to the combined utilization of their sensor nodes, have the ability to monitor the ambient conditions in areas of interest of almost any kind and size. For this reason, although initially conceived to be used solely in the military domain, WSNs nowadays not only are the basis of the Internet of Things (IoT), but also support an ever-growing range of applications.

Simultaneously, emergent advances in several scientific regions seem to be appropriate to enhance the capabilities of WSNs even more, hence initiating promising research trends.

The aim of this Special Issue is to host scientific articles that are associated with the state of the art, standards, experimentations, implementations, new research proposals, and case studies regarding applications of WSNs and relevant scientific innovations and research trends. Invited papers have to be original and neither published nor under review in any other conference or journal. Potential topics of this Special Issue include, but are not limited to, the following:

Environmental applications of WSNs;
Applications of WSNs in flora and fauna;
Applications of WSNs in Industry 4.0;
Urban applications of WSNs;
Applications of WSNs in healthcare;
Military applications of WSNs;
WSNs for smart cities;
WSNs for smart home;
Computational Intelligence for WSNs;
Smart WSNs for IoT;
Edge Computing in WSNs;
Energy Sustainability in WSNs;
Energy Efficiency in WSNs;
Energy Harvesting in WSNs;
Wireless Energy Transfer in WSNs.

Prof. Dr. Dionisis Kandris
Dr. Eleftherios Anastasiadis
Dr. Purav Shah
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. Journal of Sensor and Actuator Networks 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

Wireless Sensor Networks (WSNs)
healthcare applications
environmental applications
military applications
athletic applications
agricultural applications
structural health monitoring
environmental monitoring applications
industrial applications
smart life applications
habitat applications
power system applications

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Published Papers (11 papers)

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Research

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33 pages, 1438 KiB

Open AccessArticle

Mental Disorder Assessment in IoT-Enabled WBAN Systems with Dimensionality Reduction and Deep Learning

by Damilola Olatinwo, Adnan Abu-Mahfouz and Hermanus Myburgh

J. Sens. Actuator Netw. 2025, 14(3), 49; https://doi.org/10.3390/jsan14030049 - 7 May 2025

Viewed by 169

Abstract

Mental health is an important aspect of an individual’s overall well-being. Positive mental health is correlated with enhanced cognitive function, emotional regulation, and motivation, which, in turn, foster increased productivity and personal growth. Accurate and interpretable predictions of mental disorders are crucial for effective intervention. This study develops a hybrid deep learning model, integrating CNN and BiLSTM applied to EEG data, to address this need. To conduct a comprehensive analysis of mental disorders, we propose a two-tiered classification strategy. The first tier classifies the main disorder categories, while the second tier classifies the specific disorders within each main disorder category to provide detailed insights into classifying mental disorder. The methodology incorporates techniques to handle missing data (kNN imputation), class imbalance (SMOTE), and high dimensionality (PCA). To enhance clinical trust and understanding, the model’s predictions are explained using local interpretable model-agnostic explanations (LIME). Baseline methods and the proposed CNN–BiLSTM model were implemented and evaluated at both classification tiers using PSD and FC features. On unseen test data, our proposed model demonstrated a 3–9% improvement in prediction accuracy for main disorders and a 4–6% improvement for specific disorders, compared to existing methods. This approach offers the potential for more reliable and explainable diagnostic tools for mental disorder prediction. Full article

(This article belongs to the Special Issue Applications of Wireless Sensor Networks: Innovations and Future Trends)

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36 pages, 28868 KiB

Open AccessArticle

Lower-Complexity Multi-Layered Security Partitioning Algorithm Based on Chaos Mapping-DWT Transform for WA/SNs

by Tarek Srour, Mohsen A. M. El-Bendary, Mostafa Eltokhy, Atef E. Abouelazm, Ahmed A. F. Youssef and Ali M. El-Rifaie

J. Sens. Actuator Netw. 2025, 14(2), 36; https://doi.org/10.3390/jsan14020036 - 31 Mar 2025

Viewed by 478

Abstract

The resource limitations of Low-Power Wireless Networks (LP-WNs), such as Wireless Sensor Networks (WSNs), Wireless Actuator/Sensor Networks (WA/SNs), and Internet of Things (IoT) outdoor applications, restrict the utilization of the error-performance-enhancing techniques and the use of the powerful and robust security tools. Therefore, these LP-WN applications require special techniques to satisfy the requirements of a low data loss rate and satisfy the security requirements while considering the accepted level of complexity and power efficiency of these techniques. This paper focuses on proposing a power-efficient, robust cryptographic algorithm for the WA/SNs. The lower-complexity cryptographic algorithm is proposed, based on merging the data composition tools utilizing data transforms and chaos mapping techniques. The decomposing tool is performed by the various data transforms: Discrete Cosine Transform (DCT), Discrete Cosine Wavelet (DWT), Fast Fourier Transform (FFT), and Walsh Hadamard Transform (WHT); the DWT performs better with efficient complexity. It is utilized to separate the plaintext into the main portion and side information portions to reduce more than 50% of complexity. The main plaintext portion is ciphered in the series of cryptography to reduce the complexity and increase the security capabilities of the proposed algorithm by two chaos mappings. The process of reduction saves complexity and is employed to feed the series of chaos cryptography without increasing the complexity. The two chaos mappings are used, and two-dimensional (2D) chaos logistic maps are used due to their high sensitivity to noise and attacks. The chaos 2D baker map is utilized due to its high secret key managing flexibility and high sensitivity to initial conditions and plaintext dimensions. Several computer experiments are demonstrated to evaluate the robustness, reliability, and applicability of the proposed complexity-efficient crypto-system algorithm in the presence of various attacks. The results prove the high suitability of the proposed lower-complexity crypto-system for WASN and LP-WN applications due to its robustness in the presence of attacks and its power efficiency. Full article

(This article belongs to the Special Issue Applications of Wireless Sensor Networks: Innovations and Future Trends)

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24 pages, 3015 KiB

Open AccessArticle

Robust Distributed Collaborative Beamforming for WSANs in Dual-Hop Scattered Environments with Nominally Rectangular Layouts

by Oussama Ben Smida, Sofiène Affes, Dushantha Jayakody and Yoosuf Nizam

J. Sens. Actuator Netw. 2025, 14(2), 32; https://doi.org/10.3390/jsan14020032 - 19 Mar 2025

Viewed by 359

Abstract

We introduce a robust distributed collaborative beamforming (RDCB) approach for addressing channel estimation challenges in dual-hop transmissions within wireless sensor and actuator networks (WSANs) of K nodes. WSANs enhance wireless communication by reducing data transmission, latency, and energy consumption while optimizing network load through integrated sensing and actuation. The source S transmits signals to the WSAN, where nodes relay them to the destination D using beamforming weights to minimize noise and preserve signal integrity. These weights depend on channel state information (CSI), where estimation errors degrade performance. We develop RDCB solutions for three first-hop propagation scenarios—monochromatic [line-of-sight (LoS)] or “M”, bichromatic (moderately scattered) or “B”, and polychromatic (highly scattered) or “P”—while assuming a monochromatic LoS or “M” link for the second hop between the nodes and the far-field destination. Termed MM-RDCB, BM-RDCB, and PM-RDCB, respectively (“X” and “Y” in XY-RDCB—for X

\in {M, B, P}

and Y

\in {M}

—refer to the chromatic natures of the first- and second-hop channels, respectively, to which a specific RDCB solution is tailored), these solutions leverage asymptotic approximations for large K values and the nodes’ geometric symmetries. Our distributed solutions allow local weight computation, enhancing spectral and power efficiency. Simulation results show significant improvements in the signal-to-noise ratio (SNR) and robustness versus WSAN node placement errors, making the solutions well suited for emerging 5G and future 5G+/6G and Internet of Things (IoT) applications for different challenging environments. Full article

(This article belongs to the Special Issue Applications of Wireless Sensor Networks: Innovations and Future Trends)

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26 pages, 552 KiB

Open AccessArticle

A Proactive Charging Approach for Extending the Lifetime of Sensor Nodes in Wireless Rechargeable Sensor Networks

by Omar Banimelhem and Shifa’a Bani Hamad

J. Sens. Actuator Netw. 2025, 14(2), 26; https://doi.org/10.3390/jsan14020026 - 3 Mar 2025

Viewed by 657

Abstract

Although wireless sensor networks (WSNs) have a wide range of applications, their efficient utilization is still limited by the sensor node battery life. To overcome this issue, wireless power transfer technology (WPT) has recently been used to wirelessly charge sensor nodes and extend their lifespan. This technique paved the way to develop a wireless rechargeable sensor network (WRSN) in which a mobile charger (MC) is employed to recharge the sensor nodes. Several wireless charging technologies have been proposed in this field, but they are all tied up in two classes: periodic and on-demand strategies. This paper proposes a proactive charging method as a new charging strategy that anticipates the node’s need for energy in advance based on factors such as the node’s remaining energy, energy consumption rate, and the distance to the MC. The goal is to prevent sensor nodes from depleting their energy before the arrival of the MC. Unlike conventional methods where nodes have to request energy, the proactive charging strategy identifies the nodes that need energy before they reach a critical state. Simulation results have demonstrated that the proactive charging approach using a single MC can significantly improve the network lifespan by 500% and outperform the Nearest Job Next with Preemption (NJNP) and First Come First Serve (FCFS) techniques in terms of the number of survival nodes by 300% and 650%, respectively. Full article

(This article belongs to the Special Issue Applications of Wireless Sensor Networks: Innovations and Future Trends)

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29 pages, 883 KiB

Open AccessArticle

Energy-Efficient and Secure Double RIS-Aided Wireless Sensor Networks: A QoS-Aware Fuzzy Deep Reinforcement Learning Approach

by Sarvenaz Sadat Khatami, Mehrdad Shoeibi, Reza Salehi and Masoud Kaveh

J. Sens. Actuator Netw. 2025, 14(1), 18; https://doi.org/10.3390/jsan14010018 - 10 Feb 2025

Cited by 1 | Viewed by 1013

Abstract

Wireless sensor networks (WSNs) are a cornerstone of modern Internet of Things (IoT) infrastructure, enabling seamless data collection and communication for many IoT applications. However, the deployment of WSNs in remote or inaccessible locations poses significant challenges in terms of energy efficiency and secure communication. Sensor nodes, with their limited battery capacities, require innovative strategies to minimize energy consumption while maintaining robust network performance. Additionally, ensuring secure data transmission is critical for safeguarding the integrity and confidentiality of IoT systems. Despite various advancements, existing methods often fail to strike an optimal balance between energy efficiency and quality of service (QoS), either depleting limited energy resources or compromising network performance. This paper introduces a novel framework that integrates double reconfigurable intelligent surfaces (RISs) into WSNs to enhance energy efficiency while ensuring secure communication. To jointly optimize both RIS phase shift matrices, we employ a fuzzy deep reinforcement learning (FDRL) framework that integrates reinforcement learning (RL) with fuzzy logic and long short-term memory (LSTM)-based architecture. The RL component learns optimal actions by iteratively interacting with the environment and updating Q-values based on a reward function that prioritizes both energy efficiency and secure communication. The LSTM captures temporal dependencies in the system state, allowing the model to make more informed predictions about future network conditions, while the fuzzy logic layer manages uncertainties by using optimized membership functions and rule-based inference. To explore the search space efficiently and identify optimal parameter configurations, we use the advantage of the multi-objective artificial bee colony (MOABC) algorithm as an optimization strategy to fine-tune the hyperparameters of the FDRL framework while simultaneously optimizing the membership functions of the fuzzy logic system to improve decision-making accuracy under uncertain conditions. The MOABC algorithm enhances convergence speed and ensures the adaptability of the proposed framework in dynamically changing environments. This framework dynamically adjusts the RIS phase shift matrices, ensuring robust adaptability under varying environmental conditions and maximizing energy efficiency and secure data throughput. Simulation results validate the effectiveness of the proposed FDRL-based double RIS framework under different system configurations, demonstrating significant improvements in energy efficiency and secrecy rate compared to existing methods. Specifically, quantitative analysis demonstrates that the FDRL framework improves energy efficiency by 35.4%, the secrecy rate by 29.7%, and RSMA by 27.5%, compared to the second-best approach. Additionally, the model achieves an R² score improvement of 12.3%, confirming its superior predictive accuracy. Full article

(This article belongs to the Special Issue Applications of Wireless Sensor Networks: Innovations and Future Trends)

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19 pages, 3253 KiB

Open AccessArticle

Optimization of Crop Yield in Precision Agriculture Using WSNs, Remote Sensing, and Atmospheric Simulation Models for Real-Time Environmental Monitoring

by Vincenzo Barrile, Clemente Maesano and Emanuela Genovese

J. Sens. Actuator Netw. 2025, 14(1), 14; https://doi.org/10.3390/jsan14010014 - 30 Jan 2025

Viewed by 1358

Abstract

Due to the increasing demand for agricultural production and the depletion of natural resources, the rational and efficient use of resources in agriculture becomes essential. Thus, Agriculture 4.0 or precision agriculture (PA) was born, which leverages advanced technologies such as Geographic Information Systems (GIS), Artificial Intelligence (AI), sensors and remote sensing techniques to optimize agricultural practices. This study focuses on an innovative approach integrating data from different sources, within a GIS platform, including data from an experimental atmospheric simulator and from a wireless sensor network, to identify the most suitable areas for future crops. In addition, we also calculate the optimal path of a drone for crop monitoring and for a farm machine for agricultural operations, improving efficiency and sustainability in relation to agricultural practices and applications. Expected and obtained results of the conducted study in a specific area of Reggio Calabria (Italy) include increased accuracy in agricultural planning, reduced resource and pesticide use, as well as increased yields and more sustainable management of natural resources. Full article

(This article belongs to the Special Issue Applications of Wireless Sensor Networks: Innovations and Future Trends)

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16 pages, 12220 KiB

Open AccessFeature PaperArticle

An Intelligent Water Level Estimation System Considering Water Level Device Gauge Image Recognition and Wireless Sensor Networks

by Chihiro Yukawa, Tetsuya Oda, Takeharu Sato, Masaharu Hirota, Kengo Katayama and Leonard Barolli

J. Sens. Actuator Netw. 2025, 14(1), 13; https://doi.org/10.3390/jsan14010013 - 30 Jan 2025

Viewed by 1017

Abstract

The control of water levels in various environments is very important for predicting flooding and mitigating flood damages. Generally, water level device gauges are used to measure water levels, but the structural setting of reservoirs presents significant challenges for the installation of water level device gauges. Therefore, the solution to this problem is to apply image recognition methods using water level device gauges. In this paper, we present an intelligent water level estimation system considering water level device gauge image recognition and a Wireless Sensor Network (WSN). We carried out experiments in a water reservoir to evaluate the proposed system. From the experimental results, we found that the proposed system can estimate the water level via the object recognition of numbers and symbols on the water level device gauge. Full article

(This article belongs to the Special Issue Applications of Wireless Sensor Networks: Innovations and Future Trends)

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13 pages, 833 KiB

Open AccessArticle

Low-Complexity Ultrasonic Flowmeter Signal Processor Using Peak Detector-Based Envelope Detection

by Myeong-Geon Yu and Dong-Sun Kim

J. Sens. Actuator Netw. 2025, 14(1), 12; https://doi.org/10.3390/jsan14010012 - 30 Jan 2025

Cited by 1 | Viewed by 892

Abstract

Ultrasonic flowmeters are essential sensor devices widely used in remote metering systems, smart grids, and monitoring systems. In these environments, a low-power design is critical to maximize energy efficiency. Real-time data collection and remote consumption monitoring through remote metering significantly enhance network flexibility and efficiency. This paper proposes a low-complexity structure that ensures an accurate time-of-flight (ToF) estimation within an acceptable error range while reducing computational complexity. The proposed system utilizes Hilbert envelope detection and a differentiator-based parallel peak detector. It transmits and collects data through ultrasonic transmitter and receiver transducers and is designed for seamless integration as a node into wireless sensor networks (WSNs). The system can be involved in various IoT and industrial applications through high energy efficiency and real-time data transmission capabilities. The proposed structure was validated using the MATLAB software, with an LPG gas flowmeter as the medium. The results demonstrated a mean relative deviation of 5.07% across a flow velocity range of 0.1–1.7 m/s while reducing hardware complexity by 78.9% compared to the conventional FFT-based cross-correlation methods. This study presents a novel design integrating energy-efficient ultrasonic flowmeters into remote metering systems, smart grids, and industrial monitoring applications. Full article

(This article belongs to the Special Issue Applications of Wireless Sensor Networks: Innovations and Future Trends)

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33 pages, 4796 KiB

Open AccessArticle

Edge Computing-Aided Dynamic Wireless Charging and Trip Planning of UAVs

by Palwasha W. Shaikh and Hussein T. Mouftah

J. Sens. Actuator Netw. 2025, 14(1), 8; https://doi.org/10.3390/jsan14010008 - 16 Jan 2025

Viewed by 1311

Abstract

In today’s era of rapid technological advancement, unmanned aerial vehicles (UAVs) are transforming sectors such as remote delivery, surveillance, and disaster response. However, challenges related to energy consumption and operational efficiency continue to hinder their broader adoption. To address these issues, this study proposes an integrated system design combining dynamic wireless charging (DWC), intelligent trip planning, and intelligent edge computing (IEC). The proposed system leverages IEC for local data processing to reduce latency and optimize energy management, 6G networks for real-time vehicle-to-infrastructure (V2I) communication, and DWC to enable efficient, on-the-go energy replenishment. Additionally, a dynamic arrival management algorithm is introduced to minimize UAV wait times to enhance operational efficiency. Simulations of this system demonstrated significant improvements: larger UAVs achieved an average charging efficiency of 91.2%, while smaller UAVs achieved 92.75%, with dynamic arrival management reducing wait times by an average of 1.5 min for smaller UAVs and 5.0 min for larger UAVs. These findings underscore the system’s effectiveness in optimizing UAV operations and charging efficiency. This integrated approach offers a scalable framework to enhance UAV capabilities and sets a benchmark for future advancements in operational efficiency and charging technology for urban and environmental applications. Full article

(This article belongs to the Special Issue Applications of Wireless Sensor Networks: Innovations and Future Trends)

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73 pages, 5355 KiB

Open AccessReview

Key Enabling Technologies for 6G: The Role of UAVs, Terahertz Communication, and Intelligent Reconfigurable Surfaces in Shaping the Future of Wireless Networks

by Wagdy M. Othman, Abdelhamied A. Ateya, Mohamed E. Nasr, Ammar Muthanna, Mohammed ElAffendi, Andrey Koucheryavy and Azhar A. Hamdi

J. Sens. Actuator Netw. 2025, 14(2), 30; https://doi.org/10.3390/jsan14020030 - 17 Mar 2025

Cited by 1 | Viewed by 3354

Abstract

Sixth-generation (6G) wireless networks have the potential to transform global connectivity by supporting ultra-high data rates, ultra-reliable low latency communication (uRLLC), and intelligent, adaptive networking. To realize this vision, 6G must incorporate groundbreaking technologies that enhance network efficiency, spectral utilization, and dynamic adaptability. Among them, unmanned aerial vehicles (UAVs), terahertz (THz) communication, and intelligent reconfigurable surfaces (IRSs) are three major enablers in redefining the architecture and performance of next-generation wireless systems. This survey provides a comprehensive review of these transformative technologies, exploring their potential, design challenges, and integration into future 6G ecosystems. UAV-based communication provides flexible, on-demand communication in remote, harsh areas and is a vital solution for disasters, self-driving, and industrial automation. THz communication taking place in the 0.1–10 THz band reveals ultra-high bandwidth capable of a data rate of multi-gigabits per second and can avoid spectrum bottlenecks in conventional bands. IRS technology based on programmable metasurface allows real-time wavefront control, maximizing signal propagation and spectral/energy efficiency in complex settings. The work provides architectural evolution, active current research trends, and practical issues in applying these technologies, including their potential contribution to the creation of intelligent, ultra-connected 6G networks. In addition, it presents open research questions, possible answers, and future directions and provides information for academia, industry, and policymakers. Full article

(This article belongs to the Special Issue Applications of Wireless Sensor Networks: Innovations and Future Trends)

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36 pages, 570 KiB

Open AccessReview

Network Diffusion Algorithms and Simulators in IoT and Space IoT: A Systematic Review

by Charbel Mattar, Jacques Bou Abdo, Jacques Demerjian and Abdallah Makhoul

J. Sens. Actuator Netw. 2025, 14(2), 27; https://doi.org/10.3390/jsan14020027 - 4 Mar 2025

Cited by 1 | Viewed by 1230

Abstract

Network diffusion algorithms and simulators play a critical role in understanding how information, data, and malware propagate across various network topologies in Internet of Things and Space IoT configurations. This paper conducts a systematic literature review (SLR) of the key diffusion algorithms and network simulators utilized in studies over the past decade. The review focuses on identifying the algorithms and simulators employed, their strengths and limitations, and how their performance is evaluated under different IoT network topologies. Common network simulators, such as NS-3, Cooja, and OMNeT++ are explored, highlighting their features, scalability, and suitability for different IoT network scenarios. Additionally, network diffusion algorithms, including epidemic, cascading, and threshold models, are analyzed in terms of their effectiveness, complexity, and applicability in IoT environments with diverse network topologies. This SLR aims to provide a comprehensive reference for researchers and practitioners when selecting appropriate tools and methods for simulating and analyzing network diffusion across IoT and Space IoT configurations. Full article

(This article belongs to the Special Issue Applications of Wireless Sensor Networks: Innovations and Future Trends)

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