论文标题
基于人工智能的牛的数字双胞胎模型
AI Based Digital Twin Model for Cattle Caring
论文作者
论文摘要
在本文中，我们开发了由人工智能（AI）驱动的牛身份的创新数字双胞胎。这项工作建立在一个农场物联网系统上，该系统远程监视并追踪牛状态。使用从农场物联网系统中获取的传感器数据生成了基于深度学习（DL）的牛健康的数字双模型。可以实时监测牛的健康和生理周期，并且可以使用该模型预期牛的下一个生理周期的状态。这项工作的基础是验证数字双胞胎模型合法性所需的大量数据。就行为状态而言，发现用局部麻醉和美洛昔康治疗的牛表现出最小的疼痛反应。这项工作中开发的数字双胞胎模型可用于监测牛的健康
In this paper, we developed innovative digital twins of cattle status that are powered by artificial intelligence (AI). The work was built on a farm IoT system that remotely monitors and tracks the state of cattle. A digital twin model of cattle health based on Deep Learning (DL) was generated using the sensor data acquired from the farm IoT system. The health and physiological cycle of cattle can be monitored in real time, and the state of the next physiological cycle of cattle can be anticipated using this model. The basis of this work is the vast amount of data which is required to validate the legitimacy of the digital twins model. In terms of behavioural state, it was found that the cattle treated with a combination of topical anaesthetic and meloxicam exhibits the least pain reaction. The digital twins model developed in this work can be used to monitor the health of cattle
