基于AI的数字孪生养牛模型
AI Based Digital Twin Model for Cattle Caring
摘要：
在本文中，我们开发了由人工智能（AI）驱动的牛状态的创新数字孪生。这项工作建立在一个农场物联网系统上，该系统远程监控和跟踪牛的状态。使用从农场物联网系统获取的传感器数据，生成了基于深度学习（DL）的牛健康数字孪生模型。利用该模型可以对牛的健康状况和生理周期进行实时的监测，并可以预测牛下一个生理周期的状态。这项工作的基础是验证数字孪生模型合法性所需的大量数据。在行为状态方面，发现局部麻醉剂和美洛昔康联合给药的牛表现出最小的疼痛反应。这项工作中开发的数字孪生模型可用于监测牛的健康状况
英文摘要：
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
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
