EVIOT-Futuristic Automation System for Electric Vehicle CS Charging Point Prediction and Booking System

The escalating levels of environmental pollution and the depletion of global fossil fuel reserves have accelerated the transition toward sustainable transportation alternatives. Electric Vehicles (EVs) are emerging as a promising solution to mitigate carbon emissions and reduce national oil import dependencies. However, the growing adoption of EVs presents new challenges, particularly in terms of establishing a scalable and efficient charging infrastructure. This paper presents the framework and architecture of a next-generation communication system designed for real-time EV charging slot prediction and online booking, based on the Internet of Things (IoT). A cloud-based platform is developed for intelligent Charging Station Management, capable of networking and handling multiple charging nodes. We propose a stochastic queuing model to simulate EV arrival patterns and service mechanisms at charging stations. Furthermore, we formulate an objective function that optimizes key performance metrics such as minimal queuing delay, optimal charging time, reduced travel distance, and low-cost energy utilization. The system's dynamic scheduling algorithm ensures efficient slot allocation, thereby minimizing wait times and preventing on-road EV breakdowns due to battery depletion. Real-time data acquisition and forecasting capabilities embedded within the cloud and IoT framework significantly enhance resource utilization and customer convenience. The proposed solution represents a step forward in achieving sustainable, cost-effective, and intelligent E-Mobility infrastructure suitable for smart city applications.