Precision Livestock Farming Systems in India: AI and ML in Livestock Farming

Abstract

Precision Livestock Farming (PLF) is transforming traditional livestock management in India by integrating advanced technologies such as sensors, IoT, artificial intelligence, and automated systems. This review explores the current status, challenges, and technological advancements in PLF systems across the Indian livestock sector. It synthesises peer-reviewed research articles, government reports, industry publications, and case studies published between 2015 and 2024. The literature search focused on databases including PubMed, Google Scholar, Science Direct, and Indian agricultural research databases. The methodology involved a systematic review of more than 50 relevant publications. The findings highlight the use of monitoring tools for animal health, behaviour, reproduction, and productivity, with a focus on systems like RFID tags, rumination detectors, and automated milking. Special emphasis is given to disease detection, heat stress management, early pregnancy diagnosis, and real-time behavioural analysis. Applications of PLF in grazing systems using GPS/GIS technologies and early warning systems in poultry farming are also discussed. Despite infrastructural and economic challenges, PLF holds immense promise for improving animal welfare, reducing resource use, and enhancing sustainability in Indian livestock farming. The review underscores the need for policy support, farmer awareness, and localised innovations to achieve scalable and effective PLF implementation in India.