Abstract: In this paper, a Machine Learning-enabled intelligent navigation system is presented. It will recommend routes in a road network by minimizing source to destination distance by choosing right shortest path between source to destination , it also take care and avoids categorically marked COVID-19 hotspots. The Q-Learning based system takes the source and destination as inputs from the users and recommends a safe and shorter path for traveling. It reduces the risk of getting exposed to the contaminated zones and contracting the virus by bypassing the red covid19 hotspot zones.
Keywords: Reinforcement Learning, IoT, Intelligent Navigation System, Route Planning, Q-Learning, Covid19 Hotspot
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DOI:
10.17148/IJARCCE.2021.10810
[1] Sudip Mitra, Shree Sarkar, "Cov-INS | Intelligent Navigation System to Avoid Infected Covid-19 Areas with Reinforcement Learning and Internet of Things," International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2021.10810
