IncuVision: Android-Based Egg Incubator with Machine Learning Algorithm using OpenCV

Nel Panaligan; Jayvee Ube

doi:10.70922/8cwj4373

Authors

Nel Panaligan Davao del Sur State College Author https://orcid.org/0000-0001-6074-0148
Jayvee Ube Author

DOI:

https://doi.org/10.70922/8cwj4373

Abstract

The poultry industry is a key part of the Philippines' agricultural sector, with chicken eggs playing a vital role. Traditional methods of assessing egg fertility, such as manual candling, are time-consuming and prone to human error. Despite advancements, local poultry farms still rely on manual methods, lacking automated and real-time monitoring systems, resulting in unreliable evaluations. This study developed IncuVision, an Android-based egg incubator application that uses machine learning and OpenCV to enhance egg monitoring and fertility detection. The app provides real-time data on egg status, monitors embryo development stages, and generates data visualizations. The system was evaluated through feedback from IT faculty, an advisory committee, and egg farmers, focusing on functional suitability, performance efficiency, reliability, and usability. The system achieved a General Weighted Mean (GWM) of 4.30, highlighting its success in delivering an efficient, user-friendly, and reliable tool for egg incubation monitoring. These findings demonstrate the app’s potential to modernize hatchery operations through automated monitoring and real-time notifications. SDG 9 – Industry, Innovation and Infrastructure by introducing intelligent digital solutions that modernize agricultural practices, promote the use of innovative technologies, and strengthen infrastructure in the poultry sector through automation and real-time data systems. The integration of AI and mobile technology can help optimize incubation processes and foster more sustainable and technologically advanced poultry farming practices.

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