부산대학교 도서관

Rapid Electric Vehicle (EV) adoption has increased the need for efficient and safe charging infrastructure. This research proposes a unique strategy that combines Reinforcement Learning (RL) and Internet of Things (loT) technologies to improve EV charging system real-time payment processing and security. It uses RL algorithms to improve payment routing, dynamically alter pricing, and prioritize charging sessions depending on user preferences and network circumstances. EV owners benefit from more efficient and affordable charging, making EV adoption more desirable. The connectivity through the loT architecture allows safe, remote charging station monitoring and administration. The integration of RL and loT increases user experience and charging network stability. Predictive maintenance reduces downtime and costs via real-time data analytics. Our solution also optimizes charging schedules for cost savings and grid stability by adapting to dynamic power costs and grid conditions.