IoT Based Intruder Detection System Integrated with Chatbot for Authentication

Internet of Things (IoT) enables connectivity and interoperability between users' devices, systems, services, networks, and especially control systems. Smart video surveillance is an IOT application as it uses the internet for a variety of functions. IOT-based Intruder Detection System (IDS) is the latest technology used in a wide range of places. It serves as a remote eye for the security force. In the existing technique, the AdaBoost algorithm needs a quality data set. And also, noisy data and outliershave to be avoided before adopting this algorithm. So, in this study, machine learning techniques such as the Haar-Cascade and local binary pattern histogram algorithms are used to overcome the above disadvantage to clearly detect the face. The camera module captures an image of a person as soon as the smart home switch is pressed, sends the still image to the Android device through the Telegram app, and alerts the owner about the person who is trying to enter through the door. The entire systems programming has been established in Python and Embedded C for a controller.