Machine Learning, Deep Learning, Internet of Things, Wireless Sensor Networks, Ad-hoc Networks, Cyber-Physical Systems

Publications:

1. V. Agarwal, S. Tapaswi, P. Chanak and N. Kumar, Intelligent Emergency Evacuation System for Industrial Environments Using IoT-Enabled WSNs,” in IEEE Transactions on Instrumentation and Measurement, vol. 72, pp. 1-12, 2023, Art no. 9514612, doi:10.1109/TIM.2023.3328071.

2. V. Agarwal, S. Tapaswi and P. Chanak, “Intelligent Fault-Tolerance Data Routing Scheme for IoT-Enabled WSNs,” in IEEE Internet of Things Journal, vol. 9, no. 17, pp. 16332-16342, 1 Sept., 2022, doi: 10.1109/JIOT.2022.3151501.

3. A. Jindal, V. Agarwal and P. Chanak, “Emergency Evacuation System for Clogging-Free and Shortest-Safe Path Navigation With IoT-Enabled WSNs,” in IEEE Internet of Things Journal, vol. 9, no. 13, pp. 10424-10433, 1 July, 2022, doi: 10.1109/JIOT.2021.3123189.

4. V. Agarwal, S. Tapaswi and P. Chanak, “Energy-Efficient Mobile Sink-Based Intelligent Data Routing Scheme for Wireless Sensor Networks,” in IEEE Sensors Journal, vol. 22, no. 10, pp. 9881-9891, 15 May, 2022, doi: 10.1109/JSEN.2022.3164944.

5. V. Agarwal, S. Tapaswi, and P. Chanak, “A Survey on Path Planning Techniques for Mobile Sink in IoT-Enabled Wireless Sensor Networks”, Wireless Personal Communication 119, 211–238 (2021). https://doi.org/10.1007/s11277-021-08204-w.

6. Dheeraj Pal, Alok Jain, Aradhana Saxena, Vaibhav Agarwal (2016). Comparing Various Classifier Techniques for Efficient Mining of Data. In: Proceedings of the International Congress on Information and Communication Technology. Advances in Intelligent Systems and Computing, vol 439. Springer, Singapore. https://doi.org/10.1007/978-981-10-0755-2_21.