Application of Neural Networks to improve Energy Efficiency for household appliances

Abstract

This paper presents a method for predicting an appliance’s power consumption based on data collected by basic sensors. The collected data includes temperature, humidity, and current draw of the appliance over a specific period. A neural network is trained using this data to make power consumption predictions, which can be used to suggest the optimal appliance settings based on external factors observed during usage time. The proposed method can optimize energy consumption and reduce costs by providing personalized appliance settings based on real-time external conditions.