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@article{203626,
        author = {Dr S Sri Gowri and K.G.VENKATA KRISHNA},
        title = {Real Time Energy Monitoring System with AI Driven Automation},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {11129-11135},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=203626},
        abstract = {This paper presents the design and implementation of an intelligent smart home IoT system that integrates embedded hardware, computer vision, and cloud-based alerting into a unified real-time monitoring and automation platform. The system is built around an ESP32 microcontroller, which functions as the central sensor hub communicating with a Python-based Flask web server through USB serial using a structured JSON protocol. The architecture is modular, reliable, and scalable, making it suitable for both residential and small-scale commercial applications. The hardware layer incorporates a DHT11 temperature and humidity sensor, MQ-2 gas sensor, flame sensor, dual ultrasonic sensors for distance measurement, a PIR motion sensor, and a voltage sensor. A key feature is the dual-mode human detection capability: sensor-based detection using PIR and ultrasonic sensors, and AI-powered detection using YOLOv8 for real-time person identification via a live webcam feed. The system also incorporates a Telegram-based instant alert mechanism for critical safety events including gas leakage, fire, and abnormal temperature. Simulation results confirm that the system achieves reliable real-time monitoring, accurate multi-sensor data fusion, and effective AI-driven automation for smart home environments.},
        keywords = {ESP32, IoT, YOLOv8, Smart Home Automation, Real-Time Monitoring, Flask, Telegram Alerts, Sensor Fusion, Energy Monitoring, Computer Vision.},
        month = {May},
        }