T-Tracking: An Energy-Aware Distributed Approach for Face-Based Target Monitoring

Abstract

In monitoring applications, detecting and tracking targets within mobile Wireless Sensor Networks (WSNs) is a critical and challenging task. This paper introduces a novel distributed tracking framework, known as Target Tracking (T-Tracking), designed to enhance monitoring accuracy while optimizing energy efficiency. The framework focuses on a specific concept termed the polygon face, where nodes are grouped based on their ability to communicate within defined boundaries. Within each polygon face, the brink detection algorithm is employed to identify edges formed by node pairs that offer the highest coverage. To ensure energy-efficient operation, nodes are dynamically selected based on their energy levels and sensing capabilities using a decentralized decision-making process. The proposed system effectively addresses common challenges such as coverage gaps, node failures, and energy depletion. When a target moves beyond the current coverage area or when monitoring nodes approach low energy levels, the tracking system activates a query mechanism to identify the optimal replacement node. This selection is based on a comparative evaluation of energy reserves and sensing range, ensuring continuous and reliable monitoring. By selecting the most suitable node in real-time, t-Tracking maintains high tracking quality (QoT), minimizes communication overhead, and extends the overall network lifetime. The framework is particularly beneficial for applications in surveillance, security, and mobile object tracking in complex environments.