Iot Based Livestock Precision Feeding System Using Machine Learning

R. Sokullu, Baran Tanriverdi, R. Goleva
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引用次数: 1

Abstract

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.
使用机器学习的基于物联网的牲畜精确喂养系统
畜牧业是现代农业中最重要的部门之一,确保了平均膳食需求的人所消耗的蛋白质的至少33%。在传统农业中,绵羊、山羊、奶牛和其他牲畜的饲养方式通常是将平均数量的食物放入预定的容器中。主要目标是最大化牛奶和/或肉类收益。近年来,智能农业领域出现了一个新概念——精准畜牧业——其目标不仅是提高畜牧业的产量和效率,还包括降低成本和确保每只动物的充足饲料量。本文描述了一个使用两种新兴技术的系统,即物联网和机器学习。该系统根据动物的日常饮食模式,记录动物的生物钟,然后根据记录的数据估计喂食量和喂食时间,并确保它们得到适当的食物供应。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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