Smart home energy management: prediction and optimization

• Published in: 8th International Conference on Computing in Engineering and Technology (ICCET 2023) Vol. 2023; pp. 338 - 341
• Main Authors: Suman, B., Sambhav, S.
• Format: Conference Proceeding
• Language: English
• Published: The Institution of Engineering and Technology 2023
• DOI: 10.1049/icp.2023.1513

This study proposes a system for efficient energy management that takes the database of a smart home with multiple attributes as input, analyses the data in different elaborated forms, and predicts future energy consumption using multiple models like VAR, Prophet, and LightGBM regressor. The purpose of using different models for energy consumption forecasting is to compare them and determine which models are more accurate than others. The database used in this project is from a smart home containing various appliances with weather conditions and is available on Kaggle. The data obtained makes it possible to examine how electricity is used in a smart home and develop an effective system for analyzing power consumption. Energy consumption analysis and forecasting are crucial for lowering energy costs, encouraging sustainability, and maximizing performance. This article highlights the importance of energy consumption analysis and forecasting in promoting sustainability.