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Pet recognition and monitoring system
- Author: Loghinescu Nicu Adrian
- Master: ACES
Overiew
Objective
The purpose of this project is to monitor specific behavior of your house pets. ESP32-CAM boards with cameras and motion detectors will be placed near areas of interest such as the pet feeder and will send a picture to a firebase server whenever the motion sensor is triggered. The server will use a ML model to recognize your specific pets and save specific data to a database, which can be used to track the pet's behavior.
Hardware
- AI Thinker ESP32-CAM - based on the ESP-32S module that integrates WIFI and Bluetooth
- OV2640 Camera - supports jpeg image output format
- PIR HC-SR501 Sensor - motion sensor based on the Passive Infrared technology
- FT232RL USB to Serial Converter - for programming the ESP32-CAM
Software and services
- Firebase
- Cloud functions - Used as a HTTP server
- Realtime database - For saving timestamps regarding pet detection
- Firebase Hosting - Simple Web interface for monitoring pet behavior and trying different ML models
- Google Teachable Machine - Classifier generator from Google that outputs Tensorflow models
- TensorflowJS - Tensorflow library for Javascript, will be used in the Cloud functions
- Arduino IDE alongside the required libraries for ESP32, HTTP client, WiFi, Firebase client and video camera
Architecture
Shortly, the architecture has classic client-server structure, where the esp32-cam is the http client and firebase the server. The other software and harware components are built on top of these two.
- Structure
