Implementation of the Threshold Method in an IoT-Based Monitoring System for Temperature, Humidity and Feed in Broiler Chicken Houses - Febryan Djastin Arya Raharja; Joni Maulindar; Arif Setiawan (Information Technology and Science (ITScience), 2026)
Broiler chickens require optimal house management to maintain productivity, particularly in terms of temperature, humidity, and feed availability. Monitoring that is still done manually can potentially cause delays in detecting changes in environmental conditions and feed stock, which can hinder the chickens’ growth. This study aims to implement a threshold method in an Internet of Things (IoT)-based monitoring system for temperature, humidity, and feed levels in broiler chicken houses. The study employed the ADDIE (Analysis, Design, Development, Implementation, Evaluation) development model, utilizing an ESP32 microcontroller, a DHT22 sensor to measure temperature and humidity, an HC-SR04 sensor to detect feed levels, a 4-channel relay module to control fans and incandescent lights, and a web dashboard connected to a Supabase database for real-time monitoring. The system applies threshold values adjusted to the broiler chickens’ growth phases so that the actuators can operate automatically to maintain optimal coop conditions. Test results show that the system is capable of monitoring temperature, humidity, and feed levels in real time, transmitting data to the web dashboard, and controlling lights and fans according to threshold values specifically, lights turn on when the temperature is below 31°C and fans turn on when the temperature is above 31°C. The implementation of this system improves the effectiveness of monitoring and controlling coop conditions and has the potential to support poultry farm productivity. The system applies threshold values adjusted to the growth phase of the broiler chickens so that the actuators can operate automatically to maintain optimal conditions in the coop. Test results show that the system is capable of monitoring temperature, humidity, and feed levels in real time, transmitting data to a web dashboard, and controlling lights and fans according to threshold values specifically, lights turn on when the temperature is below 31°C and fans turn on when the temperature is above 31°C. The implementation of this system improves the effectiveness of monitoring and controlling coop conditions and has the potential to support broiler farm productivity. Further development can be pursued by adding automatic notification features, improving sensor accuracy, and integrating an automatic feeding system.