Efficient Continuous Object Tracking With Fog-Assisted Boundary Detection in IoT-Enabled WSN

Ishaq N. Ullah A. Mushtaq M. Khashan O.A. Hussain M. Ghani A.
2026 Institute of Electrical and Electronics Engineers Inc.

IEEE Sensors Journal
2026 #26 Issue 5 7780 - 7792 pp.

Continuous object tracking in the Internet of Things (IoT)-enabled wireless sensor networks (WSNs) requires fast, energy-efficient boundary detection, especially for dynamic phenomena such as toxic gas leakage or wildfire spread. However, existing approaches often rely on cloudcentric processing, resulting in high transmission delays and excessive energy consumption due to large-scale node activation. This article proposes boundary detection of continuous objects (BDCO), a fog-assisted scheme that reduces communication overhead and improves boundary accuracy. BDCO organizes the network into grid-based clusters where the cluster head (CH) filters anomalous data using a selective aggregation mechanism and forwards only relevant boundary-related information to the fog node (FN). The FN then applies a convex hull-based boundary estimation model, enabling precise boundary formulation while minimizing node activation. The proposed scheme is implemented in NS-2.35 and demonstrates substantial improvements in energy consumption (3.00E+06), service delay (22 ms), end-to-end delay (33 ms), packet loss ratio (3.0), and boundary accuracy (0.85) compared to existing approaches. Overall, the BDCO scheme provides a more energy-efficient and delay-aware solution for real-time BDCO in an IoT-enabled WSN environment.

Boundary detection , cluster head (CH) , continuous object tracking , data aggregation , fog computing , Internet of Things (IoT) , wireless sensor networks (WSNs)

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Department of Computer Science, National University of Modern Languages (NUML), Islamabad, 44000, Pakistan
Research and Innovation Centers, Rabdan Academy, Abu Dhabi, United Arab Emirates
University of Sharjah, College of Business Administration (COBA), Sharjah, United Arab Emirates
Nazarbayev University, School of Engineering and Digital Sciences, Department of Computer Science, Astana, 010000, Kazakhstan

Department of Computer Science
Research and Innovation Centers
University of Sharjah
Nazarbayev University

10 лет помогаем публиковать статьи Международный издатель

Книга Публикация научной статьи Волощук 2026 Book Publication of a scientific article 2026