Home Security with IOT and ESP32 Cam - AI Thinker Module

Technology is advancing quickly and enhancing the quality of human life. In the context of human existence, security is crucial for safeguarding private belongings and the home. A home security system utilizing the Internet of Things (IoT) was devised as a solution to this issue. This approach is perceived as highly beneficial to the user in terms of monitoring and security. This system was developed using an ESP32 microcontroller and a few IOT components. A servo motor is used to lock or unlock the door when the password that was entered using the keypad does not match the password that was saved in the EEPROM. The GSM module is triggered and notifies the user with a "person detected" message when a motion sensor (PIR) detects motion based on body heat. In facial recognition applications, the Multi-Task Cascaded Convolutional Networks (MTMN) approach is widely used. Scale factor, stride, and face recognition criteria might be included in these setups. It allows us to enroll faces with face IDs via a web server by continuously capturing images and doing face detection/recognition without a WebSocket connection. In accordance with the client's orders, it will identify faces. The name of the recognized face will be used to start activities if it is successful. If enrollment is ongoing, the client-captured JPEG images are delivered following the collection of several samples. When an unknown face is recognized by comparison with the faces stored in flash memory, a buzzer will sound. The main objective of this research study is to provide a speedy and workable solution for the security issue while lowering false alerts and notifications.