IoT-Enabled Smart Charging and Remote Monitoring Framework for Electric Vehicles

Abstract

Rapid Electric Vehicle (EV) adoption is increasing the demand for coordinated charging, grid-aware scheduling, battery protection, and continuous remote supervision. Conventional charging practices can create feeder peaks, increase energy cost, accelerate battery ageing, and provide limited visibility of charging-system anomalies. An Internet of Things enabled smart charging and monitoring framework is developed to coordinate bidirectional power exchange while satisfying user energy requirements and operational safety limits. The framework combines State-of-Charge (SOC) scheduling, tariff-aware optimization, peak-load control, battery degradation assessment, electrothermal modelling, equivalent-circuit voltage estimation, age-of-information tracking, and residual-based anomaly detection. Simulation is performed using a MathWorks numerical computing and dynamic-system environment for 20 EVs over 24 hours with 15-minute sampling. Coordinated charging raises initially distributed SOC levels of 25%–45% toward the required 80% departure level, while maintaining the allowable 20%–90% range. Smart scheduling shifts the dominant charging demand away from the uncontrolled peak near 9 h and limits the maximum grid demand to about 255 kW compared with approximately 275 kW. Battery temperature remains below about 26.6° C, and anomaly events are remotely identified when the normalized score exceeds the threshold. Applications include residential charging, fleet depots, smart grids, charging stations, demand response, battery-aware energy management, and secure operation.