DEVELOPMENT OF MACHINE LEARNING ALGORITHM USING COMPUTER VISION FOR PREDICTIVE ANALYTICS IN A BATTERY CAGE POULTRY SYSTEM

Okolie U. C; Iloh J. P. I; Mbachu C. B.

Authors & affiliations

Okolie U. C

Electronics Development Institute (ELDI) Awka, Anambra State, Nigeria

Iloh J. P. I

Department of Electrical/Electronic Engineering, Chukwuemeka Odumegwu Ojukwu University, Uli Campus, Anambra State, Nigeria.

Mbachu C. B.

Department of Electrical/Electronic Engineering, Chukwuemeka Odumegwu Ojukwu University, Uli Campus, Anambra State, Nigeria.

Abstract

Summary

In order to protect animal welfare, increase production, and lower the frequency of disease outbreaks, the growing poultry industry particularly in battery cage systems requires advanced monitoring technologies. This study presents the development of a machine learning algorithm using computer vision for predictive analytics, early disease detection, and real-time behaviour assessment in battery cage poultry systems. Convolutional neural networks (CNNs) were used to scan high-resolution video streams in order to identify physical symptoms that may indicate health issues and identify aberrant behaviours. To improve the precision of decision-making, additional parameters were analyzed, such as feeding patterns, temperature, and movement metrics. While predictive algorithms foresee possible disease spread and productivity trends, the system uses supervised learning to categorize actions and identify anomalies. When compared to traditional methods, the computer vision method showed significant improvements in behavioral monitoring and early disease identification, offering a scalable, non-invasive option for smart poultry farming. Through automation and data-driven insights, this innovation promotes proactive poultry management methods, enhancing animal welfare, and supports sustainable poultry production.

Keywords

Index Terms

Convolutional neural network machine learning computer version battery cage poultry

Citation & details

How to cite this article

Authors: Okolie U. C, Iloh J. P. I, Mbachu C. B.

Volume/Issue: Volume 10, Issue 1

Pages: 18-28

Published: February 27, 2026

Affiliations: Electronics Development Institute (ELDI) Awka, Anambra State, Nigeria, Department of Electrical/Electronic Engineering, Chukwuemeka Odumegwu Ojukwu University, Uli Campus, Anambra State, Nigeria.

Okolie U. C, Iloh J. P. I, Mbachu C. B. (2026). DEVELOPMENT OF MACHINE LEARNING ALGORITHM USING COMPUTER VISION FOR PREDICTIVE ANALYTICS IN A BATTERY CAGE POULTRY SYSTEM. International Journal of Innovative Engineering, Technology & Science (IJIETS), Volume 10, Issue 1, 18-28.

Okolie U. C, Iloh J. P. I, Mbachu C. B.. "DEVELOPMENT OF MACHINE LEARNING ALGORITHM USING COMPUTER VISION FOR PREDICTIVE ANALYTICS IN A BATTERY CAGE POULTRY SYSTEM." International Journal of Innovative Engineering, Technology & Science (IJIETS), vol. Volume 10, Issue 1, 2026, pp. 18-28.

Okolie U. C, Iloh J. P. I, Mbachu C. B.. "DEVELOPMENT OF MACHINE LEARNING ALGORITHM USING COMPUTER VISION FOR PREDICTIVE ANALYTICS IN A BATTERY CAGE POULTRY SYSTEM." International Journal of Innovative Engineering, Technology & Science (IJIETS) Volume 10, Issue 1 (2026): 18-28.

@article{developmentofmachinelearningalgorithmusingcomputervisionforpredictiveanalyticsinabatterycagepoultrysystem2026, author = {Okolie U. C and Iloh J. P. I and Mbachu C. B.}, title = {DEVELOPMENT OF MACHINE LEARNING ALGORITHM USING COMPUTER VISION FOR PREDICTIVE ANALYTICS IN A BATTERY CAGE POULTRY SYSTEM}, journal = {International Journal of Innovative Engineering, Technology & Science (IJIETS)}, year = {2026}, volume = {Volume 10, Issue 1}, pages = {18-28} }

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