Energy Consumption Prediction for Smart Homes

Author(s)	Prof. Saritha Kishore, Prof. Sowmya N S, Prof. Pankaja B, Prof. Chaithra V S, Prof. Chetana Jyothi
Country	India
Abstract	Energy consumption prediction is a critical aspect of smart home management, enabling efficient energy usage and cost reduction. This project focuses on developing a user-friendly web-based platform that predicts energy consumption patterns using time series analysis. The back-end, developed using Python, integrates models such as ARIMA and LSTM to provide accurate forecasts based on historical data. The designed ensures an intuitive responsive interface accessible on various devices.real- time updates smooth user interactions. The platform allows users to monitor energy usage, receive actionable insights, and optimize consumption effectively. Security measures, modular design, and performance optimization ensure reliability, scalability, and user satisfaction. By combining advanced predictive analytics with a simple, accessible interface, this project empowers users to manage energy consumption efficiently, promoting sustainability and reducing costs in smart homes.
Keywords	Python, ARIMA ,LSTM.
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 17, Issue 3, July-September 2026
Published On	2026-08-30

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