Iot Based Livestock Precision Feeding System Using Machine Learning

Radosveta Sokullu, Baran Yusuf Tanriverdi,Rossitza Goleva

2022 8th International Conference on Energy Efficiency and Agricultural Engineering (EE&AE)(2022)

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摘要
The livestock sector is one of the most important sectors in modern farming, ensuring at least 33% of the protein consumed by a person with average dietary requirements. In traditional farming sheep, goats, cows and other livestock are generally bred by inserting average amounts of food supplies into predefined containers. Main goal is maximizing milk and/or meat gains. In recent years a new concept has emerged in the realm of smart farming - Precision Livestock Farming – which aims not only increasing production and efficiency in the livestock sector, but also reducing costs and ensuring adequate feeding amounts for each separate animal. This paper describes a system using two newly emerging technologies, namely IoT and machine learning. The proposed system records the biological clocks of animals according to their daily eating patterns and then based on the recorded data estimates the feeding amount and feeding times and ensures they are according supplied with food.
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关键词
Agriculture 4.0,smart farming,livestock feeding,Internet of Things (IoT),machine learning,LSTM
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