Design of Poultry Farm Monitoring and Disease Detection System using Internet of Things (IoT) and Image Processing

Abstract

In recent years, the use of technology in poultry farms has increased, and this appears in the increase in closed system farms. The main problem facing farmers is the diseases that affect chickens and the rapid spread of the disease among chickens. The project provides a suitable environment for poultry farms and increases chickens’ production. The proteus software has been used for the simulation of the circuits; which consist of a Digital Temperature and Humidity sensor -DHT11-, Light Dependent Resistor sensor -LDR-, fan, and lamp all connected to a Raspberry Pi. The DHT11 sensor senses both humidity and temperature and the LDR sensor sense the lighting level, all data from sensors are fed to the Raspberry Pi in order to control the fan and the lamp. The Node-Red software has been used for hardware implementation. Then image processing has been done using -the YOLO version 5 model- to train and detect the chicken then the feature of Swelling of the face and eyes. The farmer can supervise the status of the farm through his smart device that presents the lighting level, temperature, and humidity as well as the detection of Infectious Coryza. Also, it allows controlling ventilation as well as the lighting of the farm. Out of 10 times of operating the system 8 where a fine result on the Raspberry pi as well as operating on the node red dashboard, that for DHT11 sensor, but for LDR sensor the light level wasn't accurate due to the use of capacitor with it.