Abstract

In Indonesia, there is still no real-time system for monitoring the health of cattle. Instead, a microchip RFID ear tag is used, which is implanted in the cow, but there is still no connection to the Internet of Things to help cattle producers with monitoring. The existing monitoring still relies on human labour, which is undoubtedly inefficient, particularly if you have to keep track on the health of many cows on a big farm. Cattle's movement, heart rate, and body temperature may all be read via a collar gadget. By gathering information from temperature sensors, heart rate sensors, and an inertial measurement unit installed on a dairy cow's neck, information is sent via the internet. To provide normal, less normal, and abnormal health categorization outputs, the gathered data is saved and categorised using machine learning. Also, depending on the axis sensor, generate a graphic output.

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