Urvashi Saraswat

Work place: Department of Computer Science and Engineering, Harcourt Butler Technical University, Kanpur-208002, India

E-mail: urvashi.saraswat28@gmail.com


Research Interests: Sensor, Wireless Networks


Urvashi Saraswat (Corresponding author)* received M.Tech degree in Computer Science and Engineering from Dr. APJ Abdul Kalam Technical University in 2017. She is currently pursuing her Ph.D. degree with Harcourt Butler Technical University, Kanpur, Uttar Pradesh, India. Her research interests include tracking and coverage problems in Wireless Sensor Networks, Internet of Things, and Distributed Networks.

Author Articles
Hybrid Energy Regulated Constant Gain Kalman-Filter for Optimized Target Detection and Tracking in Wireless Sensor Networks

By Urvashi Saraswat Anita Yadav Abhishek Bhatia

DOI: https://doi.org/10.5815/ijcnis.2023.05.04, Pub. Date: 8 Oct. 2023

Wireless Sensor Networks (WSNs) are one of the most researched areas worldwide as the wide-scale networks possess low cost, are small in size, consume low power, and can be deployed in various environments. Among various applications of WSNs, target tracking is a highly demanding and broadly investigated application of wireless sensor networks. The parameter of accurate tracking is restricted because of the limited resources present in the wireless sensor networks, noise of the network, environmental factors, and faulty sensor nodes. Our work aims to enhance the accuracy of the tracking process as well as energy utilization by combing the mechanism of clustering with the prediction. Here, we present a hybrid energy-regulated constant gain Kalman filter-based target detection and tracking method, which is an algorithm to make the best use of energy and enhance precision in tracking. Our proposed algorithm is compared with the existing approaches where it is observed that the proposed technique possesses efficient energy utilization by decreasing the transference of unimportant data within the sensor network, achieving accurate results.

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