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Security and Smart Applications in IoT and Wireless Sensor and Actuator Networks

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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 September 2025 | Viewed by 23249

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Special Issue Editors

Dr. Donald Elmazi

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Guest Editor

Computer Engineering Department, Faculty of Computer Science, University Metropolitan Tirana, 1003 Tirana, Albania
Interests: next generations networks; IoT; intelligent algorithms

Dr. Elis Kulla

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Guest Editor

Department of System Management, Faculty of Information Engineering, Fukuoka Institute of Technology, Fukuoka 811-0295, Japan
Interests: mobile ad-hoc networks; wireless sensor networks; ad-hoc vehicular networks; mesh networks; fuzzy logic; genetic algorithms; machine learning

Special Issue Information

Dear Colleagues,

In an era defined by rapid technological advancement, the Internet of Things (IoT) has emerged as a transformative force, reshaping the way we interact with the world around us. At the heart of this technological revolution lies the seamless integration of smart applications within IoT ecosystems, which are interconnected through Wireless Sensors and Actor Networks (WSAN). This convergence of cutting-edge technologies has not only accelerated the development of innovative solutions but has also redefined our understanding of connectivity, efficiency, and automation in various domains, from home automation to industrial processes, healthcare, and environmental monitoring.

The concept of IoT revolves around the interconnection of everyday objects, devices, and systems through the Internet, enabling them to collect, transmit, and exchange data in real time. Wireless sensors play a pivotal role in this network, as they are the eyes and ears of the IoT, collecting data from the physical world. These sensors are equipped with a multitude of capabilities, including data acquisition, processing, and communication, making them the building blocks of smart applications that enhance our daily lives. Actors in this context refer to the entities capable of taking actions based on the data collected and processed by sensors. These can be machines, robots, algorithms, or even humans. WSANs represent the synergy between sensors and actors, forming a dynamic, self-organizing system that can respond to changing conditions, thereby offering greater intelligence and autonomy to IoT applications. This dynamic interaction between sensors and actors is the key to enabling smart, context-aware decision making and automation in various domains.

In this era of connectivity, the potential applications of smart systems in IoT and WSANs are boundless. From smart homes that adjust their environment based on your preferences to industrial setups that optimize processes and maintenance, and from precision agriculture that ensures sustainable food production to healthcare systems that monitor patients' health in real time, the IoT and WSANs are revolutionizing the way we live, work, and play.

This exploration of smart applications in the IoT and WSANs delves into the principles, technologies, and the wide array of domains where they are making a significant impact. As we journey through this dynamic landscape, we will uncover the ways in which these interconnected systems are shaping our future and propelling us into an era of unprecedented convenience, efficiency, and sustainability.

The topics covered include, but are not limited to, the following:

Simulations and experiments;
Energy management;
Routing efficiency;
Optimization algorithms;
Applications;
Security and privacy;
Data aggregation techniques;
Cloud infrastructure;
Internet of Everything (IoE);
Intelligent algorithms.

This Special Issue aims to provide novel ideas related to these topics, providing insight into the technologies that are transforming our future.

Dr. Donald Elmazi
Dr. Elis Kulla
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

security and privacy
Internet of Everything (IoE)
intelligent algorithms
Internet of Things (IoT)
Actuator Networks

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Published Papers (10 papers)

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Research

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25 pages, 2027 KiB

Open AccessArticle

Priority-Based Data Flow Control for Long-Range Wide Area Networks in Internet of Military Things

by Rachel Kufakunesu, Herman C. Myburgh and Allan De Freitas

J. Sens. Actuator Netw. 2025, 14(2), 43; https://doi.org/10.3390/jsan14020043 - 16 Apr 2025

Viewed by 243

Abstract

The Internet of Military Things (IoMT) is transforming defense operations by enabling the seamless integration of sensors and actuators for the real-time transmission of critical data in diverse military environments. End devices (EDs) collect essential information, including troop locations, health metrics, equipment status, and environmental conditions, which are processed to enhance situational awareness and operational efficiency. In scenarios involving large-scale deployments across remote or austere regions, wired communication systems are often impractical and cost-prohibitive. Wireless sensor networks (WSNs) provide a cost-effective alternative, with Long-Range Wide Area Network (LoRaWAN) emerging as a leading protocol due to its extensive coverage, low energy consumption, and reliability. Existing LoRaWAN network simulation modules, such as those in ns-3, primarily support uniform periodic data transmissions, limiting their applicability in critical military and healthcare contexts that demand adaptive transmission rates, resource optimization, and prioritized data delivery. These limitations are particularly pronounced in healthcare monitoring, where frequent, high-rate data transmission is vital but can strain the network’s capacity. To address these challenges, we developed an enhanced sensor data sender application capable of simulating priority-based traffic within LoRaWAN, specifically targeting use cases like border security and healthcare monitoring. This study presents a priority-based data flow control protocol designed to optimize network performance under high-rate healthcare data conditions while maintaining overall system reliability. Simulation results demonstrate that the proposed protocol effectively mitigates performance bottlenecks, ensuring robust and energy-efficient communication in critical IoMT applications within austere environments. Full article

(This article belongs to the Special Issue Security and Smart Applications in IoT and Wireless Sensor and Actuator Networks)

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19 pages, 2620 KiB

Open AccessArticle

A Zero-Trust Multi-Processor Reporter-Verifier Design of Edge Devices for Firmware Authenticity in Internet of Things and Blockchain Applications

by Ananda Maiti and Alexander A. Kist

J. Sens. Actuator Netw. 2025, 14(2), 35; https://doi.org/10.3390/jsan14020035 - 31 Mar 2025

Viewed by 285

Abstract

Firmware authenticity and integrity during upgrades are critical security factors in Internet of Things (IoT) applications in the age of edge artificial intelligence (AI). Data from IoT applications are vital for business decisions. Any unintended or malicious change in data can adversely impact the goals of an IoT application. Several studies have focused on using blockchain to ensure the authentication of IoT devices and the integrity of data once the data are in the blockchain. Firmware upgrades on IoT edge devices have also been investigated with blockchain applications, with a focus on eliminating external threats during firmware upgrades on IoT devices. In this paper, we propose a new IoT device design that works against internal threats by preventing malicious codes from device manufacturers. In IoT applications that monitor critical data, it is important to ensure that the correct firmware reporting honest data is running on the devices. As devices are owned and operated by a small group of application stakeholders, this multiprocessor design extracts the firmware periodically and checks whether it matches the signatures of the expected firmware designed for the business goals of the IoT applications. The test results show that there is no significant increase in code, disruption, or power consumption when implementing such a device. This scheme provides a hardware-oriented solution utilizing processor-to-processor communication protocols and is an alternative to running lightweight blockchain on IoT edge devices. Full article

(This article belongs to the Special Issue Security and Smart Applications in IoT and Wireless Sensor and Actuator Networks)

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11 pages, 894 KiB

Open AccessArticle

Optimizing Sensor Locations for Electrodermal Activity Monitoring Using a Wearable Belt System

by Riley Q. McNaboe, Youngsun Kong, Wendy A. Henderson, Xiaomei Cong, Aolan Li, Min-Hee Seo, Ming-Hui Chen, Bin Feng and Hugo F. Posada-Quintero

J. Sens. Actuator Netw. 2025, 14(2), 31; https://doi.org/10.3390/jsan14020031 - 18 Mar 2025

Viewed by 300

Abstract

Wearable devices for continuous health monitoring in humans are constantly evolving, yet the signal quality may be improved by optimizing electrode placement. While the commonly used locations to measure electrodermal activity (EDA) are at the fingers or the wrist, alternative locations, such as the torso, need to be considered when applying an integrated multimodal approach of concurrently recording multiple bio-signals, such as the monitoring of visceral pain symptoms like those related to irritable bowel syndrome (IBS). This study aims to quantitatively determine the EDA signal quality at four torso locations (mid-chest, upper abdomen, lower back, and mid-back) in comparison to EDA signals recorded from the fingers. Concurrent EDA signals from five body locations were collected from twenty healthy participants as they completed a Stroop Task and a Cold Pressor task that elicited salient autonomic responses. Mean skin conductance (meanSCL), non-specific skin conductance responses (NS.SCRs), and sympathetic response (TVSymp) were derived from the torso EDA signals and compared with signals from the fingers. Notably, TVSymp recorded from the mid-chest location showed significant changes between baseline and Stroop phase, consistent with the TVSymp recorded from the fingers. A high correlation (0.77–0.83) was also identified between TVSymp recorded from the fingers and three torso locations: mid-chest, upper abdomen, and lower back locations. While the fingertips remain the optimal site for EDA measurement, the mid-chest exhibited the strongest potential as an alternative recording site, with the upper abdomen and lower back also demonstrating promising results. These findings suggest that torso-based EDA measurements have the potential to provide reliable measurement of sympathetic neural activities and may be incorporated into a wearable belt system for multimodal monitoring. Full article

(This article belongs to the Special Issue Security and Smart Applications in IoT and Wireless Sensor and Actuator Networks)

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26 pages, 6009 KiB

Open AccessArticle

Enhancing Campus Environment: Real-Time Air Quality Monitoring Through IoT and Web Technologies

by Alfiandi Aulia Rahmadani, Yan Watequlis Syaifudin, Budhy Setiawan, Yohanes Yohanie Fridelin Panduman and Nobuo Funabiki

J. Sens. Actuator Netw. 2025, 14(1), 2; https://doi.org/10.3390/jsan14010002 - 25 Dec 2024

Viewed by 1674

Abstract

Nowadays, enhancing campus environments through mitigations of air pollutions is an essential endeavor to support academic achievements, health, and safety of students and staffs in higher educational institutes. In laboratories, pollutants from welding, auto repairs, or chemical experiments can drastically degrade the air quality in the campus, endangering the respiratory and cognitive health of students and staffs. Besides, in universities in Indonesia, automobile emissions of harmful substances such as carbon monoxide (CO), nitrogen dioxide (NO₂), and hydrocarbon (HC) have been a serious problem for a long time. Almost everybody is using a motorbike or a car every day in daily life, while the number of students is continuously increasing. However, people in many campuses including managements do not be aware these problems, since air quality is not monitored. In this paper, we present a real-time air quality monitoring system utilizing Internet of Things (IoT) integrated sensors capable of detecting pollutants and measuring environmental conditions to visualize them. By transmitting data to the SEMAR IoT application server platform via an ESP32 microcontroller, this system provides instant alerts through a web application and Telegram notifications when pollutant levels exceed safe thresholds. For evaluations of the proposed system, we adopted three sensors to measure the levels of CO, NO₂, and HC and conducted experiments in three sites, namely, Mechatronics Laboratory, Power and Emission Laboratory, and Parking Lot, at the State Polytechnic of Malang, Indonesia. Then, the results reveal Good, Unhealthy, and Dangerous for them, respectively, among the five categories defined by the Indonesian government. The system highlighted its ability to monitor air quality fluctuations, trigger warnings of hazardous conditions, and inform the campus community. The correlation of the sensor levels can identify the relationship of each pollutant, which provides insight into the characteristics of pollutants in a particular scenario. Full article

(This article belongs to the Special Issue Security and Smart Applications in IoT and Wireless Sensor and Actuator Networks)

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29 pages, 2096 KiB

Open AccessArticle

Efficient Zero-Knowledge Proofs for Set Membership in Blockchain-Based Sensor Networks: A Novel OR-Aggregation Approach

by Oleksandr Kuznetsov, Emanuele Frontoni, Marco Arnesano and Kateryna Kuznetsova

J. Sens. Actuator Netw. 2024, 13(6), 78; https://doi.org/10.3390/jsan13060078 - 14 Nov 2024

Viewed by 1438

Abstract

Blockchain-based sensor networks offer promising solutions for secure and transparent data management in IoT ecosystems. However, efficient set membership proofs remain a critical challenge, particularly in resource-constrained environments. This paper introduces a novel OR-aggregation approach (where “OR” refers to proving that an element equals at least one member of a set without revealing which one) for zero-knowledge set membership proofs, tailored specifically for blockchain-based sensor networks. We provide a comprehensive theoretical foundation, detailed protocol specification, and rigorous security analysis. Our implementation incorporates optimization techniques for resource-constrained devices and strategies for integration with prominent blockchain platforms. Extensive experimental evaluation demonstrates the superiority of our approach over existing methods, particularly for large-scale deployments. Results show significant improvements in proof size, generation time, and verification efficiency. The proposed OR-aggregation technique offers a scalable and privacy-preserving solution for set membership verification in blockchain-based IoT applications, addressing key limitations of current approaches. Our work contributes to the advancement of efficient and secure data management in large-scale sensor networks, paving the way for wider adoption of blockchain technology in IoT ecosystems. Full article

(This article belongs to the Special Issue Security and Smart Applications in IoT and Wireless Sensor and Actuator Networks)

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30 pages, 3145 KiB

Open AccessArticle

Create a Realistic IoT Dataset Using Conditional Generative Adversarial Network

by Miada Almasre and Alanoud Subahi

J. Sens. Actuator Netw. 2024, 13(5), 62; https://doi.org/10.3390/jsan13050062 - 3 Oct 2024

Viewed by 1647

Abstract

The increased use of Internet of Things (IoT) devices has led to greater threats to privacy and security. This has created a need for more effective cybersecurity applications. However, the effectiveness of these systems is often limited by the lack of comprehensive and balanced datasets. This research contributes to IoT security by tackling the challenges in dataset generation and providing a valuable resource for IoT security research. Our method involves creating a testbed, building the ‘Joint Dataset’, and developing an innovative tool. The tool consists of two modules: an Exploratory Data Analysis (EDA) module, and a Generator module. The Generator module uses a Conditional Generative Adversarial Network (CGAN) to address data imbalance and generate high-quality synthetic data that accurately represent real-world network traffic. To showcase the effectiveness of the tool, the proportion of imbalance reduction in the generated dataset was computed and benchmarked to the BOT-IOT dataset. The results demonstrated the robustness of synthetic data generation in creating balanced datasets. Full article

(This article belongs to the Special Issue Security and Smart Applications in IoT and Wireless Sensor and Actuator Networks)

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18 pages, 1703 KiB

Open AccessArticle

Hybrid Encryption Model for Secured Three-Phase Authentication Protocol in IoT

by Amr Munshi and Bandar Alshawi

J. Sens. Actuator Netw. 2024, 13(4), 41; https://doi.org/10.3390/jsan13040041 - 17 Jul 2024

Cited by 3 | Viewed by 1616

Abstract

The Internet of things (IoT) has recently received a great deal of attention, and there has been a large increase in the number of IoT devices owing to its significance in current communication networks. In addition, the validation of devices is an important concern and a major safety demand in IoT systems, as any faults in the authentication or identification procedure will lead to threatening attacks that cause the system to close. In this study, a new, three-phase authentication protocol in IoT is implemented. The initial phase concerns the user registration phase, in which encryption takes place with a hybrid Elliptic Curve Cryptography (ECC)–Advanced Encryption Standard (AES) model with an optimization strategy, whereby key generation is optimally accomplished via a Self-Improved Aquila Optimizer (SI-AO). The second and third phases include the login process and the authentication phase, in which information flow control-based authentication is conducted. Finally, decryption is achieved based on the hybrid ECC–AES model. The employed scheme’s improvement is established using various metrics. Full article

(This article belongs to the Special Issue Security and Smart Applications in IoT and Wireless Sensor and Actuator Networks)

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18 pages, 834 KiB

Open AccessArticle

A Multi-Agent Reinforcement Learning-Based Grant-Free Random Access Protocol for mMTC Massive MIMO Networks

by Felipe Augusto Dutra Bueno, Alessandro Goedtel, Taufik Abrão and José Carlos Marinello

J. Sens. Actuator Netw. 2024, 13(3), 30; https://doi.org/10.3390/jsan13030030 - 30 Apr 2024

Cited by 1 | Viewed by 1962

Abstract

The expected huge number of connected devices in Internet of Things (IoT) applications characterizes the massive machine-type communication (mMTC) scenario, one prominent use case of beyond fifth-generation (B5G) systems. To meet mMTC connectivity requirements, grant-free (GF) random access (RA) protocols are seen as a promising solution due to the small amount of data that MTC devices usually transmit. In this paper, we propose a GF RA protocol based on a multi-agent reinforcement learning approach, applied to aid IoT devices in selecting the least congested RA pilots. The rewards obtained by the devices in collision cases resemble the congestion level of the chosen pilot. To enable the operation of the proposed method in a realistic B5G network scenario and aiming to reduce signaling overheads and centralized processing, the rewards in our proposed method are computed by the devices taking advantage of a large number of base station antennas. Numerical results demonstrate the superior performance of the proposed method in terms of latency, network throughput, and per-device throughput compared with other protocols. Full article

(This article belongs to the Special Issue Security and Smart Applications in IoT and Wireless Sensor and Actuator Networks)

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18 pages, 1189 KiB

Open AccessArticle

Fast Multi-User Searchable Encryption with Forward and Backward Private Access Control

by Salim Sabah Bulbul, Zaid Ameen Abduljabbar, Duaa Fadhel Najem, Vincent Omollo Nyangaresi, Junchao Ma and Abdulla J. Y. Aldarwish

J. Sens. Actuator Netw. 2024, 13(1), 12; https://doi.org/10.3390/jsan13010012 - 2 Feb 2024

Cited by 2 | Viewed by 2395

Abstract

Untrusted servers are servers or storage entities lacking complete trust from the data owner or users. This characterization implies that the server hosting encrypted data may not enjoy full trust from data owners or users, stemming from apprehensions related to potential security breaches, unauthorized access, or other security risks. The security of searchable encryption has been put into question by several recent attacks. Currently, users can search for encrypted documents on untrusted cloud servers using searchable symmetric encryption (SSE). This study delves deeply into two pivotal concepts of privacy within dynamic searchable symmetric encryption (DSSE) schemes: forward privacy and backward privacy. The former serves as a safeguard against the linkage of recently added documents to previously conducted search queries, whereas the latter guarantees the irretrievability of deleted documents in subsequent search inquiries. However, the provision of fine-grained access control is complex in existing multi-user SSE schemes. SSE schemes may also incur high computation costs due to the need for fine-grained access control, and it is essential to support document updates and forward privacy. In response to these issues, this paper suggests a searchable encryption scheme that uses simple primitive tools. We present a multi-user SSE scheme that efficiently controls access to dynamically encrypted documents to resolve these issues, using an innovative approach that readily enhances previous findings. Rather than employing asymmetric encryption as in comparable systems, we harness low-complexity primitive encryption tools and inverted index-based DSSE to handle retrieving encrypted files, resulting in a notably faster system. Furthermore, we ensure heightened security by refreshing the encryption key after each search, meaning that users are unable to conduct subsequent searches with the same key and must obtain a fresh key from the data owner. An experimental evaluation shows that our scheme achieves forward and Type II backward privacy and has much faster search performance than other schemes. Our scheme can be considered secure, as proven in a random oracle model. Full article

(This article belongs to the Special Issue Security and Smart Applications in IoT and Wireless Sensor and Actuator Networks)

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Review

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26 pages, 2233 KiB

Open AccessReview

Transformative Technologies in Digital Agriculture: Leveraging Internet of Things, Remote Sensing, and Artificial Intelligence for Smart Crop Management

by Fernando Fuentes-Peñailillo, Karen Gutter, Ricardo Vega and Gilda Carrasco Silva

J. Sens. Actuator Netw. 2024, 13(4), 39; https://doi.org/10.3390/jsan13040039 - 8 Jul 2024

Cited by 41 | Viewed by 10428

Abstract

This paper explores the potential of smart crop management based on the incorporation of tools like digital agriculture, which considers current technological tools applied in agriculture, such as the Internet of Things (IoT), remote sensing, and artificial intelligence (AI), to improve crop production efficiency and sustainability. This is essential in the context of varying climatic conditions that affect the availability of resources for agriculture. The integration of tools such as IoT and sensor networks can allow farmers to obtain real-time data on their crops, assessing key health factors, such as soil conditions, plant water status, presence of pests, and environmental factors, among others, which can finally result in data-based decision-making to optimize irrigation, fertilization, and pest control. Also, this can be enhanced by incorporating tools such as drones and unmanned aerial vehicles (UAVs), which can increase monitoring capabilities through comprehensive field surveys and high-precision crop growth tracking. On the other hand, big data analytics and AI are crucial in analyzing extensive datasets to uncover patterns and trends and provide valuable insights for improving agricultural practices. This paper highlights the key technological advancements and applications in smart crop management, addressing challenges and barriers to the global adoption of these current and new types of technologies and emphasizing the need for ongoing research and collaboration to achieve sustainable and efficient crop production. Full article

(This article belongs to the Special Issue Security and Smart Applications in IoT and Wireless Sensor and Actuator Networks)

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