Special Issues
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Advanced Localization and Multi-Sensor Fusion in WSN, IoT & VANET

Submission Deadline: 31 May 2026 View: 818 Submit to Special Issue

Guest Editor(s)

Dr. Tanveer Ahmad

Email: tahmad01@ucy.ac.cy

Affiliation: Computer science and Engineering, University of Cyprus, Nicosia, 2109, Cyprus

Homepage:

Research Interests: WSN/ UWSN localization, positioning, navigation, routing, security, and protocols, navigation and path planning for agricultural vehicles in uncertain terrain


Dr. Muhammad Usman Hadi

Email: m.hadi@ulster.ac.uk

Affiliation: School of Engineering, Ulster University, Belfast BT15 1ED, United Kingdom

Homepage:

Research Interests: IoT, optical communication, wireless communication, UAV/drones, 5G and beyond 5G particularly time sensitive networks, microwave photonics, RoF systems, devices for telecommunications, and wireless sensor networks


Summary

Precise localization and smart multi-sensor data integration are now essential drivers for the upcoming generation of smart, connected systems. As Wireless Sensor Networks (WSN), the Internet of Things (IoT), and Vehicular Ad Hoc Networks (VANET) expand, the need for accurate, real-time, and context-aware localization services is accelerating. The integration of these technologies supports various vital applications such as intelligent transportation, smart city infrastructure, autonomous navigation, environmental monitoring, and industrial operations automation. However, attaining precise localization and reliable sensor fusion continues to be challenging because of environmental changes, communication issues, energy restrictions, and varied network structures. Combining data from multiple sensors like GPS, LiDAR, UWB, cameras, and inertial sensors provides a promising way to improve accuracy, fault tolerance, and scalability. Additionally, incorporating artificial intelligence, edge computing, and cloud analytics further boosts the adaptability and intelligence of the localization process systems.


This Special Issue aims to provide a platform for researchers, engineers, and practitioners to share innovative approaches, theoretical advancements, and experimental studies addressing the challenges of localization and sensor fusion in WSN, IoT, and VANET environments. We invite contributions that present novel methodologies, algorithms, frameworks, and real-world implementations to advance the state of the art in this rapidly evolving field.

Topics include (but are not limited to):
• Localization techniques for WSN, IoT, and VANET systems
• Hybrid and cooperative localization methods
• Multi-sensor data fusion algorithms
• Machine learning and AI-driven localization solutions
• Edge and cloud-assisted localization architectures
• Ultra-wideband (UWB), RFID, GPS, and LiDAR-based positioning
• Time synchronization and distance estimation techniques
• Energy-efficient and low-latency localization protocols
• Localization in mobile, dynamic, and harsh environments
• Privacy and security in localization systems
• Performance evaluation and benchmarking of localization methods


Keywords

localization techniques, sensor fusion, wireless sensor networks (WSN),Internet of things (IoT), vehicular ad hoc networks (VANET), Multi-sensor integration, AI-driven localization

Published Papers


  • Open Access

    ARTICLE

    Performance Evaluation of Malicious Node Detection and Mitigation of IoT-Based Trust Model for Wireless Sensor Network

    Anil Kumar, Abhay Bhatia, Amit Singh, Preeti Rani, Vincent Omollo Nyangaresi, Mahendihasan S. Heera
    CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2026.076553
    (This article belongs to the Special Issue: Advanced Localization and Multi-Sensor Fusion in WSN, IoT & VANET)
    Abstract The Internet of Things (IoT) enables seamless real-time monitoring and data exchange across distributed and heterogeneous environments with wireless sensor networks (WSNs). The open architecture and resource constraints of wireless sensor networks (WSNs) make them highly vulnerable to internal security threats caused by malicious or compromised nodes, particularly in Internet of Things (IoT) environments. To address this issue, we proposed Dynamic Trust Evaluation Model (DTEM), designed to provide a secure, scalable, and efficient framework for IoT-based WSNs. The proposed model identifies the role of trust management in routing, data aggregation, and intrusion detection, including trust-based… More >

  • Open Access

    ARTICLE

    iPAFAR: An Adaptive Pareto-Based NS-AAA Energy-Stable Fuzzy Clustering and Routing Framework for Smart City IoT-Enabled WSNs

    Bhanu Talwar, Puneet Thapar, Tahani Alsubait, Mai Alduailij, Ateeq Ur Rehman, Salil Bharany
    CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2026.080977
    (This article belongs to the Special Issue: Advanced Localization and Multi-Sensor Fusion in WSN, IoT & VANET)
    Abstract Wireless Sensor Networks (WSNs) play a vital role in smart city Internet of Things (IoT) applications, including environmental monitoring, intelligent transportation, and infrastructure management. However, limited battery capacity, uneven energy consumption, and inefficient clustering and routing mechanisms significantly reduce network lifetime, reliability, and scalability, especially in large-scale IoT deployments. Traditional routing protocols often rely on single-objective optimization or static clustering strategies, which fail to maintain long-term energy balance and stable communication performance. To address these challenges, this paper proposes iPAFAR, a Pareto-based multi-objective clustering and routing framework designed for IoT-enabled WSNs. The proposed model formulates… More >

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