Broodless egg hatching is often the choice of farmers when the mother does not incubate her eggs. However, to ensure hatching success, careful monitoring of temperature, humidity, and heat distribution in the incubator is essential. This thesis aims to develop an Internet of Things (IoT)-based automatic egg hatching control and monitoring system to improve the efficiency and success rate of broodless hatching. The system implements Sugeno fuzzy logic to regulate the incubator temperature dynamically and precisely, adjusting to the environmental variability that occurs during the hatching process. An ESP32 microcontroller is used as the control centre, which is integrated with temperature and humidity sensors (DHT11) as well as a Telegram application on mobile devices, enabling real-time monitoring and automatic notifications to users. The hatching test results of chicken eggs for 23 days showed a hatching success rate of 66.7% (4 out of 6 eggs), with controlled temperatures in the range of 36-39°C. Hatching failure in two eggs is indicated due to the position that is too close to the AC dimmer lamp, which causes uneven heat distribution. The implementation of Sugeno fuzzy in this system with an error of 0.01% proves the reliability of Sugeno fuzzy control method in maintaining temperature and humidity stability, which is very important in the egg hatching process. This system offers a practical and efficient solution for farmers in optimising the egg hatching process.
Supriyadi et al. (Tue,) studied this question.
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