Review on poultry automation using IoT and machine learning
Lecturer, Department of Electronics and Communication Engineering, DACG Government Polytechnic, Chikkamagaluru, Karnataka, India.
Review Article
World Journal of Advanced Research and Reviews, 2020, 08(03), 466–474
Publication history:
Received on 21 October 2020; revised on 14 December 2020; accepted on 17 December 2020
Abstract:
The poultry industry is undergoing a transformative technological revolution through the strategic integration of Internet of Things (IoT) and Machine Learning (ML) technologies. This comprehensive review explores the current state of poultry automation, examining innovative approaches that leverage advanced sensor networks, data analytics, and intelligent algorithms to address critical challenges in agricultural productivity. By synthesizing emerging research, the paper demonstrates how IoT and ML technologies are revolutionizing poultry farming through enhanced environmental monitoring, predictive health management, and precision resource optimization. These technological interventions offer unprecedented insights into animal welfare, operational efficiency, and sustainable farming practices, enabling real-time tracking of physiological parameters, early disease detection, and intelligent decision-making frameworks. The review critically analyzes the potential of these technologies to transform traditional agricultural methods, highlighting their capacity to improve farm productivity, reduce manual labor, and implement more targeted and responsive management strategies. As global food security demands increasingly sophisticated agricultural solutions, the convergence of IoT and ML represents a pivotal advancement in creating more intelligent, efficient, and responsive poultry production systems.
Keywords:
Poultry Automation; Internet of Things (IoT); Machine Learning (ML); Smart Agriculture; Precision Farming; Animal Welfare; Agricultural Technology; Sensor Networks; Predictive Analytics; Sustainable Farming
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Copyright © 2020 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0