Advanced Home Automation Using Raspberry Pi and Machine Learning

The idea of sustainable energy, imposed people to think of a new alternative way to conserve energy. With the development of technology and internet, a new sensational advancement known as Internet of Things (IOT) was created. This paper mainly focuses on energy conservation through home automation for which sensors and a microprocessor is used. The appliances are sensed and controlled using Raspberry Pi for optimal use of electricity in the building. The unnecessary use of electricity due to carelessness of the customer is identified and controlled remotely using the mobile application. Machine learning algorithms are used for accurate load forecasting leading to effective home energy management.ML algorithms such as K Nearest Neibhour(KNN), Decision Tree Regres-sion (DTR), Support Vector Regression and Random Forest are implemented in TensorFlow for load forecasting.