Livestock management, or precision livestock farming, uses IoT-enabled collars or tags to track and monitor the health and location of livestock.
What is IoT-Enabled Livestock Management?
Livestock management, also known as livestock monitoring or precision livestock farming, uses IoT-enabled devices to track and monitor the health of livestock, most commonly cattle.
Traditional methods of livestock monitoring involve individually inspecting animals for signs of disease or injury. This method is both costly and highly unreliable. An Oklahoma University found lung lesions and scarring in 37 percent of cattle that had never been diagnosed as sick and, in a trial at the Meat Animal Research Center, 68 percent of steers tested showed signs of past respiratory infection.
Although the animals had recovered on their own, studies have shown that once livestock has been ill, they never catch up to the rest of the healthy herd in health or value.
How it Works
IoT-enabled livestock management solutions take the guesswork out of herd health. Using a wearable collar or tag, battery-powered sensors monitor the location, temperature, blood pressure and heart rate of animals and wirelessly send the data in near-real-time to farmers’ devices.
This allows farmers to check in on the health and location of each individual animal in their herd from anywhere as well as receive alerts if something falls outside of the normal range. Rather than physically check the vitals of each individual animal to see if an illness has spread, they know immediately which livestock is affected and which are not.
Besides tracking health, livestock monitoring solutions can use GPS tracking to gather and store historical data on preferred grazing spots or use temperature tracking to determine the peak of mating season.
Key Benefits of IoT-Enabled Livestock Management
- Monitor the health and vitality of livestock in real-time, enabling farmers to quickly treat animals and prevent the spread of illness or disease.
- Track grazing animals to prevent loss and to identify grazing patterns.
- Gather and analyze historical data to identify trends in cattle health or to track the spread of illness.
- Monitor readiness to mate or give birth, preventing the loss of new calves and optimizing breeding practices.