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@article{205239,
        author = {Arjun Ray and Kant Mondal and Rubal Hansda and Kuntal Ghosh and Sudip Samnta and Arpan Gope},
        title = {AI-BASED SMART ENERGY METER WITH LOADPREDICTION AND OPTIMIZATION},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {1},
        pages = {6121-6124},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=205239},
        abstract = {The increasing demand for electricity and the need for efficient energy management have led to the development of intelligent monitoring systems. Traditional energy meters only measure electricity consumption and do not provide real-time analysis or predictive capabilities. This research presents an AI-Based Smart Energy Meter with Load Prediction and Optimization that integrates Artificial Intelligence (AI), Internet of Things (IoT), and cloud computing technologies for smart energy management. The proposed system monitors electrical parameters such as voltage, current, power, and energy consumption using sensors connected to a microcontroller. The collected data is transmitted to a cloud platform through a Wi-Fi module for remote monitoring and analysis. AI and machine learning algorithms analyze historical energy usage patterns to predict future load demand and optimize energy consumption. The system helps reduce electricity wastage, improve energy efficiency, and lower electricity bills through intelligent load management. It also provides real-time monitoring, cloud-based accessibility, and predictive analytics for users. The proposed smart energy meter can be applied in residential homes, industries, commercial buildings, and smart grid systems. This research demonstrates that integrating AI and IoT technologies into smart metering systems improves energy monitoring, forecasting accuracy, and overall power management, contributing to sustainable and intelligent energy utilization.},
        keywords = {Artificial Intelligence (AI), Smart Energy Meter, Load Prediction, Breadboard, Jumper wires, Potentiometer, Resistors, Energy Optimization, Internet of Things (IoT), Machine Learning, Smart Grid, Energy Monitoring, Power Consumption Forecasting, Cloud Computing.},
        month = {June},
        }