Artificial Intelligence-Optimized Intelligent Egg Incubation for Energy-Aware Poultry Farming
Year: 2026
Type: article
Abstract: The rising demand for poultry products makes it necessary to implement artificial egg incubation systems, although backyard poultry and developing countries are hindered by manual incubation or expensive commercial incubation facilities. To overcome this, this paper introduces an artificial intelligence-optimized egg incubation system with energy awareness in poultry farming, offering a low-cost, intelligent, and optimal incubation solution. The proposed system is designed using an Arduino-embedded system with temperature and humidity sensors, heating, and fans, with a GSM notification system for real-time monitoring of incubation conditions. The proposed system differs from traditional incubation systems, which are based on threshold values, as this system uses a machine learning approach-based predictive control system, which predicts changes in environmental factors to control actuators proactively. Based on anticipated changes in temperatures and humidity, this approach avoids unnecessary activation of heating and fans, which cuts down on energy consumption with optimal incubation conditions. Experimental outcome shows better temperature regulation, improved incubation success, and significant energy savings over traditional ON/OFF control systems. The outcome validates that artificial intelligence is beneficial in developing intelligent, adaptive, and energy-conscious egg incubation systems for backyard poultry farming.
Institutions: Injibara University, ETH Zurich, Addis Ababa University
Language: English
Topic: Arduino and IoT Applications
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid:
OpenAlex ID: W7128819247