ABSTRACT

50Billions of physical devices are presently connected to the Internet shaping the Internet of things (IoT). These devices are creating an enormous measure of information. The transmission and preparing this information is a testing task. Different IoT applications and future research bearings are likewise talked about. One of the unmistakable application fragments of IoT system is in the security sector. It is essential to provide solutions to counteract burglary and guarantee security to individuals at home. This chapter utilizing Raspberry Pi IoT foundation features the representation-driven advancement process for machine learning home security system. It comments on the employments of client end requests, for example, to safely transmit data through the layers of IoT engineering. It goes for giving a low-control, financially sensing, and ordinary IoT-based home security machine learning framework, which aids nearness recognition, Recognizable 98% proof, and verification of outsiders. The arrangement makes utilization of USB Webcam as a picture-catching unit and electric door hit as an actuator that gives application programming interface to assemble arrangements, which is perfect with Raspberry Pi IoT infrastructure.