Design and Implementation of The Smart Weighing Precision Livestock Monitoring Technology based on the Internet of Things (IoT)

Tri Kushartadi, Muh. Asnoer Laagu, Muhamad Asvial


The traditional approach to weight measurement, which measures each sheep individually, is time-consuming, and sometimes, human error triggers other issues, such as data validation, sheep classification, etc. Most farmers or breeders nowadays still manage their livestock traditionally, which is inefficient. We proposed that the Livestock Live Monitoring System is designed to collect measured data in real-time and display data in graphics; these models combine Bluetooth Low Energy as a wearable sensor to identify animals and Smart Weight Measurement to deliver weight and health data to the cloud system. This system aims to measure livestock and store the data in the server application so livestock monitoring can be done in real-time and remotely. The technology used in this system is ESP32, Load Cell, Bluetooth Low Energy, and Message Queue Telemetry Transport Protocol. Wearable devices act as an identification tag for livestock, and a smart weight scale is used to weigh the livestock and integrate it with the system. Two sheep are used as experiment objects, and their measured weight is compared to their weight when measured traditionally using a conventional scale. Based on the experiment, the weight data measured using the system has an accuracy of 99.82% for sheep number 1 and 99.17% for sheep number 2. This proposed system provides many benefits, including real-time livestock monitoring, cost efficiency, and an efficient feeding system for sheep using weight data.


Internet of Things; smart weight scale; Bluetooth low energy identification; weight data; sheep classification.

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