Routing problem of mesh remote sensor IoT networks

Wireless Sensor Networks (WSNs) consist of autonomous sensors that monitor environmental factors such as temperature, humidity, sound, and pressure. These networks are important for applications such as environmental monitoring, smart cities, industrial automation and information gathering. As IoT devices continue to proliferate, addressing the challenges of energy efficiency, scalability, and reliability has become increasingly important. This paper proposes an innovative reinforcement learning (RL)-based routing algorithm designed to enhance the energy efficiency of remote sensor IoT networks. The study outlines the mechanism for implementing this algorithm and the anticipated results.