The following report was prepared and published by our sister platform SPEEDA—April 2024.

The dependence on human observation and judgement in traditional livestock care can result in imprecise estimations of animal health, estrus (the state of an animal being on heat) and feed requirements. This decreases farm productivity while increasing costs and lowering the quality of output such as meat, milk or eggs.

Smart livestock monitoring (SLM) has emerged as a solution, introducing a more precise data-driven approach to improve efficiency in livestock care. SLM brings in wearable, external sensor, video capturing, and environmental monitoring devices for real-time animal monitoring as well as robots for precise feeding and milking. SLM solutions capture, analyse, and interpret data on parameters such as livestock behaviour, health, estrus, and feeding in real time. This allows more precise decision-making, thereby improving productivity and cost savings.

SLM is an advancement of precision livestock farming (PLF) concepts such as targeted resource allocation via individual or group animal identification. The early use of PLF in livestock care includes pedometers for identifying estrus and robots for precise milking (automated milking systems: AMS) and precise feeding (automated feeding systems: AFS). PLF has now evolved into SLM, which focuses on continuous data capture to monitor individual livestock or groups in real time, while making predictive analyses on illness, estrus, and inadequate nutrition.

This report focuses on the use of wearables, external sensors, video capturing, and environmental monitoring devices in livestock care, while also touching on recent advancements in automated feeding.