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Energy-Efficient Object Detection and Tracking Framework for Wireless Sensor Network.

Jayashree Dev1, Jibitesh Mishra2

  • 1Department of Information Technology, Odisha University of Technology and Research, Bhubaneswar 751003, India.

Sensors (Basel, Switzerland)
|January 21, 2023
PubMed
Summary

This study introduces the Energy Efficient Object Detection and Tracking Framework (EEODTF) for wireless sensor networks (WSNs). EEODTF enhances energy efficiency without compromising object detection and localization accuracy.

Keywords:
energy efficiencyobject detectionobject localizationobject trackingwireless sensor network

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Network Engineering

Background:

  • Object detection and tracking in wireless sensor networks (WSNs) face challenges balancing network lifetime and accuracy.
  • Existing methods often increase node density or limit tracking scope, neglecting system cost and localization precision.

Purpose of the Study:

  • To propose a novel framework, the Energy Efficient Object Detection and Tracking Framework (EEODTF), for heterogeneous WSNs.
  • To minimize energy consumption in mobile object tracking while maintaining high detection and localization accuracy.

Main Methods:

  • The EEODTF framework employs node optimization, mobile node trajectory optimization, node clustering, data reporting optimization, and detection optimization.
  • Heterogeneous WSNs are utilized to achieve energy efficiency.

Main Results:

  • The EEODTF framework demonstrates superior energy efficiency compared to existing models.
  • Performance was evaluated against the Energy Efficient Tracking and Localization of Object (EETLO) and Particle-Swarm-Optimization-based Energy Efficient Target Tracking Model (PSOEETTM).

Conclusions:

  • The proposed EEODTF effectively balances energy efficiency and tracking accuracy in WSNs.
  • EEODTF offers a significant improvement in energy conservation for object detection and tracking applications.