AI-Powered Autonomous Robots for Large-Scale Warehouse Cleaning and Maintenance with IoT Integration

Efficient and autonomous cleaning solutions are of greatest significance in the dynamic world of warehouse management. This research introduces a novel method for cleaning and maintaining large-scale warehouses using Reinforcement Learning (RL) algorithms, which combine autonomous robots powered by artificial intelligence (AI) with Internet of Things (IoT) technology. The dust level, floor cleanliness, and obstructions in a warehouse may be monitored in real time with the help of the proposed system's IoT sensors. Using this information as input, autonomous robots train in an RL framework to optimize their cleaning tactics in response to changing operational needs and environmental variables. With the help of the RL algorithm, robots can make smart decisions, greatly enhancing their cleaning abilities and reducing the need for human interaction. Using simulations and case studies shows how this method may work, highlighting how it could increase cleaning precision, operational effectiveness, and resource allocation. It highlights the potential of AI and the IoT to improve warehouse maintenance procedures and this method for further developments in autonomous robotic systems.