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The agriculture industry recently started using IoT technology for keeping a check and maintaining the health of cattle. This paper presents the creation and deployment of an Internet of Things-based system that chains cow health metrics. The three sensors used by the system are an accelerometer, a pulse sensor, and an infrared contactless temperature sensor. All these are connected to an Espressif Dev Kit V1 board. The data will be sent from the sensors, which is then forwarded to ThingSpeak and stored in Azure Blob storage. There is a machined-learning model developed using the Random Forest approach and compare with different models that is used to analyze the data more profoundly. Using both history and current values, this algorithm can make possible predictions about the ill health in cows.

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Connected Livestock: Revolutionizing Cattle Health Monitoring with IoT and Machine Learning

  • 会议论文

  • 发表日期：

    2025年

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  • B. V. V. Rajesh,
  • C. S. Pavan Kumar,
  • T. Govind Rajesh

摘要

The agriculture industry recently started using IoT technology for keeping a check and maintaining the health of cattle. This paper presents the creation and deployment of an Internet of Things-based system that chains cow health metrics. The three sensors used by the system are an accelerometer, a pulse sensor, and an infrared contactless temperature sensor. All these are connected to an Espressif Dev Kit V1 board. The data will be sent from the sensors, which is then forwarded to ThingSpeak and stored in Azure Blob storage. There is a machined-learning model developed using the Random Forest approach and compare with different models that is used to analyze the data more profoundly. Using both history and current values, this algorithm can make possible predictions about the ill health in cows.