IoT-Based Smart Home Implementation Using Cayenne Web Server and Android SDK

Abstract

Smart Home is a device in the vast IoT world right now. Smart homes are capable of controlling everything from lights to doors to the entire home that is part of the IoT network. The implementation of a smart home gives the user the ability to link  and control various parts of their home, yet for a smart home to be truly smart, the whole process of controlling the devices and various aspects of the home must be fully or partially automated. To this end, this paper proposes a smart home implementation that can control the environment of the home by assessing consumer behavior based on past data collected from various sensors. Analytics is done using machine learning, and the output from machine learning algorithms is given to the user in the app, and the user can choose whether to execute these instructions or can choose to simply ignore them. The app can also be used to control the components associated with a smart home. The application proposed in this paper describes the efficacy of data acquisition, the utility of algorithms, application interface and machine learning algorithms. This paper summarizes the challenges of learning and assessing smart homes and provides a better understanding of smart home systems.