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Trends and Prospects for Wireless Sensor Networks and IoT

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A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: 20 December 2025 | Viewed by 14374

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Special Issue Editors

Prof. Dr. Octavian Fratu

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Department of Telecommunications, University Politehnica of Bucharest, 060042 Bucharest, Romania
Interests: internet of things; mobile communications; wireless networks; communications security; radio propagation
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Simona Halunga

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Guest Editor

Department of Telecommunications, University Politehnica of Bucharest, 060042 Bucharest, Romania
Interests: signal processing; internet of things; mobile communications; wireless systems; communications security
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Dr. Albena Mihovska

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Guest Editor

Department of Business Development and Technology, Aarhus University, 7400 Herning, Denmark
Interests: 5G/6G systems; mobile communications; IoT; radio access networks
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Vladimir Poulkov

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Guest Editor

Faculty of Telecommunications, Technical University of Sofia, 1000 Sofia, Bulgaria
Interests: mobile communications; radio access network; spectrum sensing

Special Issue Information

Dear Colleagues,

The use of the wireless sensor networks (WSN), especially as part of the so-called Internet of Things (IoT) systems and applications, has experienced an exponential growth during recent years. More and more monitoring and management systems are using such approaches, including robotic systems, automated systems and a variety of others. This period has seen the accomplishment of a continuous integration between sensing devices, communication and management networks and automated systems. This trend is driven not only by progress in computing and sensing technologies, such as technological progress in low-energy consumption and energy harvesting, but also in the new capabilities offered by the new communications systems generations, such as 5 / 6G systems that are currently under development. This has given additional support with the increase in automated systems capabilities, based on new achievements in artificial intelligence (AI) and augmented reality (AR) achievements. Additionally, it is expected that all these trends will be accelerated by the economic crisis caused by the COVID-19 pandemic and the overloading of supply chains. Moreover, the impact of the present war in the Eastern Europe and the tensions from East Asia are accelerating the developments in the areas of green technology and enhanced energy management.

Targeting all the elements highlighted above, the present Special Issue intends to contribute to dealing with the challenges in and evolutions of wireless sensor networks (WSN) and Internet of Things (IoT) technologies and their applications.

Prof. Dr. Octavian Fratu
Prof. Dr. Simona Halunga
Dr. Albena Mihovska
Prof. Dr. Vladimir Poulkov
Guest Editors

Manuscript Submission Information

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Keywords

wireless sensor networks (WSN)
Internet of Things (IoT)
low-power wide-area networks (LPWAN)
5G & 6G Cellular WSN
ultra-reliable and low-latency communication (URLLC)
critical infrastructure
smart applications
edge/fog computing

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Published Papers (10 papers)

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Research

35 pages, 17275 KiB

Open AccessArticle

Performance Analysis of Downlink 5G Networks in Realistic Environments

by Aymen I. Zreikat and Hunseok Kang

Appl. Sci. 2025, 15(8), 4526; https://doi.org/10.3390/app15084526 - 19 Apr 2025

Viewed by 257

Abstract

Fifth-generation (5G) networks are the fifth generation of mobile networks and are regarded as a global standard, following 1G, 2G, 3G, and 4G networks. Fifth-generation, with its large available bandwidth provided by mmWave, not only provides the end user with higher spectrum efficiency, massive capacity, low latency, and high speed but is also a network designed to connect virtually everyone and everything together, including machines, objects, and devices. Therefore, studies of such systems’ performance evaluation and capacity bounds are critical for the research community. Furthermore, the performance of these systems should be investigated in realistic contexts while considering signal strength and restricted uplink power to maintain system coverage and capacity, which are also affected by the environment and the value of the service factor parameter. However, any proposed application should include a multiservice case to reflect the true state of 5G systems. As an extension of previous work, the capacity bounds for 5G networks are derived and analyzed in this research, considering both single and multiservice cases with mobility. In addition, the influence of different parameters on network performance, such as the interference, service factor, and non-orthogonality factors, and cell radii, is also discussed. The numerical findings and analysis reveal that the type of environment and service factor parameters have the greatest influence on system capacity and coverage. Subsequently, it is shown that the investigated parameters have a major impact on cell performance and therefore can be considered key indicators for mobile designers and operators to consider in planning and designing future networks. To validate these findings, some results are evaluated against ITU-T standards, while others are compared with related studies from the literature. Full article

(This article belongs to the Special Issue Trends and Prospects for Wireless Sensor Networks and IoT)

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20 pages, 41816 KiB

Open AccessArticle

The 3D Gaussian Splatting SLAM System for Dynamic Scenes Based on LiDAR Point Clouds and Vision Fusion

by Yuquan Zhang, Guangan Jiang, Mingrui Li and Guosheng Feng

Appl. Sci. 2025, 15(8), 4190; https://doi.org/10.3390/app15084190 - 10 Apr 2025

Viewed by 1508

Abstract

This paper presents a novel 3D Gaussian Splatting (3DGS)-based Simultaneous Localization and Mapping (SLAM) system that integrates Light Detection and Ranging (LiDAR) and vision data to enhance dynamic scene tracking and reconstruction. Existing 3DGS systems face challenges in sensor fusion and handling dynamic objects. To address these, we introduce a hybrid uncertainty-based 3D segmentation method that leverages uncertainty estimation and 3D object detection, effectively removing dynamic points and improving static map reconstruction. Our system also employs a sliding window-based keyframe fusion strategy that reduces computational load while maintaining accuracy. By incorporating a novel dynamic rendering loss function and pruning techniques, we suppress artifacts such as ghosting and ensure real-time operation in complex environments. Extensive experiments show that our system outperforms existing methods in dynamic object removal and overall reconstruction quality. The key innovations of our work lie in its integration of hybrid uncertainty-based segmentation, dynamic rendering loss functions, and an optimized sliding window strategy, which collectively enhance robustness and efficiency in dynamic scene reconstruction. This approach offers a promising solution for real-time robotic applications, including autonomous navigation and augmented reality. Full article

(This article belongs to the Special Issue Trends and Prospects for Wireless Sensor Networks and IoT)

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32 pages, 3433 KiB

Open AccessArticle

A Blockchain Network Communication Architecture Based on Information-Centric Networking

by Yufei Zhou, Rui Han and Yang Li

Appl. Sci. 2025, 15(6), 3340; https://doi.org/10.3390/app15063340 - 19 Mar 2025

Viewed by 413

Abstract

Blockchain technology, as a distributed ledger technology, is becoming increasingly popular in various fields. However, the performance limitations of blockchain networks hinder their further development. Existing research on optimizing blockchain communication mechanisms based on P2P networks is constrained by the end-to-end transmission principles of TCP/IP networks, which lead to network congestion and bandwidth wastage during large-scale blockchain content distribution. Meanwhile, studies on ICN-based blockchain systems primarily focus on blockchain communication protocol implementation and compatibility within ICN/NDN networks. However, research on blockchain communication mechanisms in hybrid IP/ICN networking environments remains limited, failing to fully leverage ICN’s advantages to enhance the communication efficiency of existing blockchain P2P networks. To address this issue, this paper proposes BLOCK-ICN, an ICN-based blockchain network communication architecture compatible with IP networks. BLOCK-ICN enables ICN nodes with computing and storage capabilities to deploy blockchain applications, while maintaining compatibility with P2P networks. By leveraging ICN multicast technology, the architecture provides relay acceleration services for blockchain data dissemination. Specifically, in terms of network topology, BLOCK-ICN classifies network domains based on delay information provided by an enhanced resolution system and establishes select domain gateways based on data flow forwarding dependencies, thereby constructing a hierarchical and structured relay network topology. Regarding the broadcast protocol, ICN nodes perform parallel broadcasting via ICN multicast, and upon receiving messages, they further disseminate them to P2P nodes, reducing the overall network broadcast latency and bandwidth consumption. We extended SimBlock to implement and evaluate BLOCK-ICN. Simulation results demonstrated that, in a Bitcoin network with 16,000 nodes and an ICN node ratio of 1%, the broadcast delays for propagating blockchain data to 90% and 50% of the network were reduced by 25% and 33.2%, respectively, compared to Bitcoin. Full article

(This article belongs to the Special Issue Trends and Prospects for Wireless Sensor Networks and IoT)

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19 pages, 1237 KiB

Open AccessArticle

Cyberattack Detection Systems in Industrial Internet of Things (IIoT) Networks in Big Data Environments

by Abdullah Orman

Appl. Sci. 2025, 15(6), 3121; https://doi.org/10.3390/app15063121 - 13 Mar 2025

Cited by 1 | Viewed by 1168

Abstract

The rapid expansion of the Industrial Internet of Things (IIoT) has revolutionized industrial automation and introduced significant cybersecurity challenges, particularly for supervisory control and data acquisition (SCADA) systems. Traditional intrusion detection systems (IDSs) often struggle to effectively identify and mitigate complex cyberthreats, such as denial-of-service (DoS) and distributed denial-of-service (DDoS) attacks. This study proposes an advanced IDS framework integrating machine learning, deep learning, and hybrid models to enhance cybersecurity in IIoT environments. Using the WUSTL-IIoT-2021 dataset, multiple classification models—including decision tree, random forest, multilayer perceptron (MLP), convolutional neural networks (CNNs), and hybrid deep learning architectures—were systematically evaluated based on key performance metrics, including accuracy, precision, recall, and F1 score. This research introduces several key innovations. First, it presents a comparative analysis of machine learning, deep learning, and hybrid models within a unified experimental framework, offering a comprehensive evaluation of various approaches. Second, while existing studies frequently favor hybrid models, findings from this study reveal that the standalone MLP model outperforms other architectures, achieving the highest detection accuracy of 99.99%. This outcome highlights the critical role of dataset-specific feature distributions in determining model effectiveness and calls for a more nuanced approach when selecting detection models for IIoT cybersecurity applications. Additionally, the study explores a broad range of hyperparameter configurations, optimizing model effectiveness for IIoT-specific intrusion detection. These contributions provide valuable insights for developing more efficient and adaptable IDS solutions in IIoT networks. Full article

(This article belongs to the Special Issue Trends and Prospects for Wireless Sensor Networks and IoT)

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19 pages, 1137 KiB

Open AccessArticle

Secure Cryptographic Key Encapsulation and Recovery Scheme in Noisy Network Conditions

by Dina Ghanai Miandoab, Michael Logan Garrett, Mahafujul Alam, Saloni Jain, Sareh Assiri and Bertrand Cambou

Appl. Sci. 2025, 15(5), 2732; https://doi.org/10.3390/app15052732 - 4 Mar 2025

Viewed by 539

Abstract

In this study, we present the Response-Based Key Encapsulation Mechanism (R-KEM), an ephemeral key encapsulation and recovery scheme tailored for cryptographic systems in high-noise, high-jamming network environments. By adopting the Challenge–Response Pair (CRP) mechanism for both key encapsulation and authentication, R-KEM eliminates the need to store secret keys on the device, favoring on-demand key generation. By maintaining only encrypted data on the device, R-KEM significantly enhances security, ensuring that in the event of an attack, no sensitive information can be compromised. Its novel error-correcting strategy efficiently corrects 20 to 23 bits of errors promptly, eliminating the need for redundant helper data and fuzzy extractors. R-KEM is ideally suited for terminal devices with constrained computational resources. Our comprehensive performance analysis underscores R-KEM’s ability to recover error-free cryptographic keys in noisy networks, offering a superior alternative to conventional methods that struggle to maintain secure data transmission under such challenges. This work not only demonstrates R-KEM’s efficacy but also paves the way for more resilient cryptographic systems in noise-prone environments. Full article

(This article belongs to the Special Issue Trends and Prospects for Wireless Sensor Networks and IoT)

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31 pages, 622 KiB

Open AccessArticle

A Survey on Energy Drainage Attacks and Countermeasures in Wireless Sensor Networks

by Joon-Ku Lee, You-Rak Choi, Beom-Kyu Suh, Sang-Woo Jung and Ki-Il Kim

Appl. Sci. 2025, 15(4), 2213; https://doi.org/10.3390/app15042213 - 19 Feb 2025

Viewed by 657

Abstract

Owing to limited resources, implementing conventional security components in wireless sensor networks (WSNs) rather than wireless networks is difficult. Because most sensor nodes are typically powered by batteries, the battery power should be sufficiently long to prevent the shortening of the network lifetime. Therefore, many studies have focused on detecting and avoiding energy drainage attacks in WSNs. However, a survey paper has yet to be published for energy drain attacks in WSNs since 2019. Therefore, we present a novel comprehensive survey paper for energy drainage attacks in WSNs. First, we address an overview of WSNs and their security issues. Next, we explain the methodology for this study and explain the existing approaches for energy drainage attacks in layered architectures. Based on the results of this analysis, open issues and further research directions are presented. Full article

(This article belongs to the Special Issue Trends and Prospects for Wireless Sensor Networks and IoT)

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26 pages, 24035 KiB

Open AccessArticle

Indoor Walking Trajectory Estimation Using Mobile Device Sensors for Hand-Held and Hand-Swinging Modes

by Yuta Izutsu and Nobuyoshi Komuro

Appl. Sci. 2025, 15(3), 1195; https://doi.org/10.3390/app15031195 - 24 Jan 2025

Viewed by 663

Abstract

We propose an indoor location estimation method using sensors of mobile devices. First, we perform attitude estimation using each sensor. This estimation is used to estimate the attitude of the mobile device with respect to the earth. Based on the acceleration and other information obtained from the attitude estimation, we then estimate the step detection, step length, and direction of the step. Finally, the location is calculated using all the estimation results. To eliminate the need to hold the mobile device in place during the estimation process, the method is configured so that estimates may be performed while walking, while looking at the screen, and while walking and holding the device in one hand. As the proposed method does not use indoor location fingerprinting or machine learning, real-time estimation can be performed. Although the accuracy could be higher, our experimental results show that the proposed method is able to effectively estimate the location and walking trajectory. Full article

(This article belongs to the Special Issue Trends and Prospects for Wireless Sensor Networks and IoT)

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24 pages, 2534 KiB

Open AccessArticle

Emotion Estimation Using Noncontact Environmental Sensing with Machine and Deep Learning Models

by Tsumugi Isogami and Nobuyoshi Komuro

Appl. Sci. 2025, 15(2), 721; https://doi.org/10.3390/app15020721 - 13 Jan 2025

Viewed by 890

Abstract

This paper presents a method for estimating arousal and emotional valence levels using non-contact environmental sensing, addressing challenges such as discomfort from long-term device wear and privacy concerns associated with facial image analysis. We employed environmental data to develop machine learning models, including Random Forest, Gradient Boosting Decision Trees, and the deep learning model CNN-LSTM, and evaluated their accuracy in estimating emotional states. The results indicate that decision tree-based methods, particularly Random Forest, are highly effective for estimating emotional states from environmental data. Full article

(This article belongs to the Special Issue Trends and Prospects for Wireless Sensor Networks and IoT)

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27 pages, 4401 KiB

Open AccessArticle

Timing Analyses in FWE Evaluation

by Maria Sîrbu-Drăgan, Diana Brînaru and Simona Halunga

Appl. Sci. 2023, 13(24), 13008; https://doi.org/10.3390/app132413008 - 6 Dec 2023

Viewed by 1045

Abstract

This paper presents several conclusions based on time domain analysis of the simulation results of several transmission lines that use frequency-dependent dielectrics, highlighting the fiberglass effect on performance. The matching conditions of the circuit are checked based on a Smith chart simulation that represents the magnitude of the reflection coefficient via scattering parameters. A time domain analysis is provided by means of the eye diagram, which allows the study of the rise and fall time, jitter, and eye height and width of the two materials considered to be appropriate for the examination of composite substrates: one conventional substrate, FR4, and one more oriented to high-speed design constraints, N4000-13. Time domain analyses highlight the effect of increasing the rate for our purpose on the composite substrate for coupled or single-ended interconnections or routes on PCBs. Full article

(This article belongs to the Special Issue Trends and Prospects for Wireless Sensor Networks and IoT)

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25 pages, 3376 KiB

Open AccessArticle

Intelligent Jammer on Mobile Network LTE Technology: A Study Case in Bucharest

by Cristian Capotă, Mădălin Popescu, Eduard-Marian Bădulă, Simona Halunga, Octavian Fratu and Mircea Popescu

Appl. Sci. 2023, 13(22), 12286; https://doi.org/10.3390/app132212286 - 13 Nov 2023

Cited by 2 | Viewed by 5794

Abstract

The purpose of this study was to develop a laboratory model that enables the monitoring of communications carried out through mobile phones and their blocking in cases where it is prohibited. The main goal was to realise an intelligent jammer that blocks only illicit communications. The jammer was built with a software-defined radio (SDR) that can be found on the market and is accessible from a financial point of view. This study consisted of an analysis of the behaviour of mobile phones and mobile networks using the long-term evolution (LTE) of UMTS technologies so that the jamming technique can disrupt the communication of the cellular mobile system by using the software-defined radio and Python ecosystem. Because the 5G standalone (5G SA) is not yet implemented in Romania, we could not start developing a laboratory model for jamming this technology. When 5G SA is implemented, we will adapt this intelligent jamming solution to the new technology. Full article

(This article belongs to the Special Issue Trends and Prospects for Wireless Sensor Networks and IoT)

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