Gudla Mohan Sathwik

Work place: School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, TN 632014, India

E-mail: mohansathwikgudla857@gmail.com

Website:

Research Interests: Machine Learning, Data Mining

Biography

Gudla Mohan Sathwik is pursuing his B. Tech. in Computer Science Engineering at SCOPE, Vellore Institute of Technology, Vellore, TN, India. His research interests include but are not limited to algorithm design and analysis, data mining, machine learning, optimization, and IoT.

Author Articles
An Energy-Efficient Wireless Sensor Network (EE-WSN) for Hazard and Crack Detection in Coal Mines

By Kakelli Anil Kumar Saurav Ranjan Gudla Mohan Sathwik Tanmay Agrawal Riiju Jagetiya

DOI: https://doi.org/10.5815/ijwmt.2024.04.02, Pub. Date: 8 Aug. 2024

This paper presents a detailed study focused on the utilization of energy-efficient wireless sensor networks (WSNs) specifically designed for hazard and crack detection in coal mines. The primary objective of this research is to develop a WSN system that operates on low power consumption, enabling real-time monitoring of hazardous conditions and cracks within coal mines. The proposed system incorporates energy-efficient methods and protocols to minimize power usage and prolong the lifespan of sensor nodes. The study encompasses the complete design and implementation of a prototype WSN system, followed by a thorough evaluation of its performance within a simulated environment. The obtained results demonstrate the effectiveness of the proposed system in detecting hazards and cracks in real-time while consuming minimal power. Consequently, this research underscores the potential of energy-efficient WSNs to enhance the safety and efficiency of coal mining operations. Moreover, the findings of this study have broader implications, as they can serve as a foundation for the development of similar systems applicable to other hazardous environments, including oil rigs, nuclear power plants, and forest fires. By adopting the energy-efficient WSN approach outlined in this research, these industries can benefit from improved safety measures and enhanced operational efficiency.

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