Paper Title
DESIGN OF IOT BASEDEV CHARGING SYSTEM USING ESP32 AND CLOUD ANALYTICS SYSTEM

Abstract
The rapid adoption of electric vehicles (EVs) in residential environments has significantly increased household energy demand, introducing challenges related to electrical safety, load management, and energy cost optimization. Conventional EV charging systems operate without considering real-time household load conditions, often leading to circuit overloads, inefficient energy utilization, and higher electricity expenses during peak demand periods. This paper presents an intelligent IoT-enabled EV charging system designed to monitor real-time electrical parameters, forecast household load, and dynamically regulate EV charging to ensure safe and optimal energy utilization. The proposed system is developed using an ESP32-WROOM microcontroller integrated with a PZEM energy measurement module to accurately acquire voltage, current, power, and energy consumption data from residential loads. Two controlled bulb loads are used to emulate varying household demand conditions. Measured data is transmitted to a cloud-based MQTT broker and visualized through a Streamlit-based real-time dashboard, enabling continuous monitoring and user interaction. In addition to real-time monitoring, historical energy data is processed to forecast short-term load trends, allowing the system to intelligently schedule EV charging during low-load conditions and prevent overcurrent scenarios. Experimental results demonstrate reliable data acquisition, stable cloud communication, accurate load visualization, and effective charging control decisions. The proposed system offers a low-cost, scalable, and intelligent solution suitable for smart homes, energy-aware EV charging, and future smart grid applications. Keywords - Electric Vehicle Charging, Internet Of Things, ESP32, PZEM Energy Meter, Load Forecasting, MQTT, Streamlit Dashboard, Smart Energy Management.