Arvind Kumar Sharma
Papers
1
Total Citations
17
H-Index
1
About
Arvind Kumar Sharma is a researcher at the forefront of applying artificial intelligence and sensor-based automation to public health challenges, particularly in pandemic response. His most-cited work, "Automation Monitoring With Sensors For Detecting Covid Using Backpropagation Algorithm" (2021, 17 citations), addresses a critical gap during the COVID-19 crisis: the inability to efficiently track infected individuals and their locations in real time. Sharma proposed an innovative system that integrates sensor networks with a backpropagation neural network to automate the detection and monitoring of COVID-19 cases, offering a data-driven solution for rapid identification and containment. This contribution is especially significant in the context of India, where sudden surges in infections overwhelmed manual tracking efforts. By combining hardware sensors with machine learning, Sharma’s work demonstrates a practical pathway for using intelligent automation to mitigate viral spread and reduce human losses. His research bridges the gap between theoretical AI models and real-world deployment in crisis scenarios, making it a valuable reference for scholars working at the intersection of IoT, neural networks, and epidemiology.
Research Focus
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Top Papers
- 1