Livestock Monitoring
Livestock Monitoring
Case Study

Livestock Monitoring

Writer

Alex Turner

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FLEMAL @ Jean Luc Flemal

Wearable devices powered by GPS trackers, RFID, cameras, microphones, and temperature sensors used to monitor livestock and help farmers identify issues like diseases before they spread or escalate.
Wearable devices powered by GPS trackers, RFID, cameras, microphones, and temperature sensors used to monitor livestock and help farmers identify issues like diseases before they spread or escalate.

Livestock Monitoring & Livestock Wearables

Managing animal health and identifying issues before they escalate is a crucial aspect of modern livestock operations. Wearable technologies and infrared cameras could monitor vital signs such as temperature, as well as movement patterns, eating habits, and the stress levels of livestock. As society is acquiring more awareness and empathy regarding animal health, there could be backlash and ethical concerns about implantable and ingestible sensors. Therefore, a unique aspect of wearables is that they are a less invasive way to make farming "smarter," mainly when connected with other platforms such as decision support systems.

Cameras, microphones, and Nano Thermal Sensors can be used to provide real-time or near-real-time information and diagnose animal ailments. Sensors capture information from cameras, microphones, thermometers,and accelerometers such as images, audio, heat, or motion from individual animals or groups of animals. The data is stored in external drives or sent to a cloud-based processing node to be processed by Machine Vision and Deep Learning algorithms which, combined with behaviors mapped to the algorithm and individual identification for example from Optical Character Recognition, can then send near real-time alerts to farmers, warning of events like the onset of labor or specimens becoming sick with contagious diseases. This data could also help identify specific areas where efficiency can be improved, such as energy use, water waste, feed conversion, and intake.

Livestock monitoring devices also include GPS trackers, Ultra High Frequency (UHF) RFID Tags or injectable RFID ampoule tags. These RFID tags are normally implanted on the ear of the cattle and can be custom printed with information such as tag data, farm name, and logo. To retrieve data, GPS trackers use the Global System for Mobile Communications. This communication protocol allows researchers to collect information about an animal's movements without the need to recapture it. To be used, network coverage or cellular phone service must be available. Non-GSM collars use Ultra High-Frequency radio signals to transmit data from Ultra High Frequency (UHF) RFID Tags, however for data to be collected, the animal's location must be known within a few hundred yards. By contrast, GPS tracking collars rely on batteries, typically lasting a year. Longer-life batteries weigh more, adding cost and weight to the unit, which already can weigh up to a pound. Recent advances in the use of Nanosatellites and miniaturized transmitters or chips can also be used to track and monitor migrating wildlife and also livestock.

Use Cases

Cattle Monitoring

  • Ghanaian-based Anitrack uses location and movement sensors to create wearable devices, or smart collars, for cattle to monitor their health and activity. This is of particular benefit in Africa, where cattle theft and cattle deaths due to disease are common.

  • UK-based IceRobotics developed CowAlert which uses a combination of cloud platforms and IoT-connected monitoring sensors to continuously monitor each cow on an individual basis. The monitoring sensors, called "IceQubes," are fitted to the rear leg of each cow and use an accelerometer that measures orientation and acceleration across three axes, multiple times per second. Each animal’s movement is recorded constantly, and Deep Learning algorithms analyze the data collected, providing accurate alerts on fertility, lying time, lameness, and mobility.

Sheep Monitoring

  • Monitoring sheep when in flocks allows farmers to manage issues such as health, herd movement, and safety. Sheep worrying by dogs or other animals causes injuries and death and is also thought to causes issues with breeding. The UK-based Ewetrack is developing a series of geofenced, IoT-connected GPS ear tags for tracking and monitoring sheep. Using location data and motion sensing, the tag can trigger an alert when sheep get out of a virtually fenced zone. The devices can also alert farmers to lambing activity, especially when birthing outdoors so that they can ensure the survival of lambs after birth.

Pig Monitoring

  • Pig monitors include RGB-D or video cameras coupled with 3D Modeling that use depth sensors and Hyperspectral Sensor Imaging (HSI) to transmit a live feed of livestock that can be remotely viewed or processed to track growth as well as changes in behavior patterns such as tail-biting which may indicate abnormalities or ill health. Microphones and audio sensors can identify respiratory infections by picking up higher frequencies in the coughing of pigs. Monitoring systems can also include in-pen devices such as Ultra High-Frequency RFID tags on ear tags and at feeding and water stations to measure occurrence and duration of feeding and drinking; thermal camera and Infrared thermography (IRT) or infrared temperature sensors such as thermistors or bolometers to measure temperature non-invasively; pressure mats containing load cells to detect weight and gait; and accelerometers to track animal movement, behavior and therefore welfare.

Future Perspectives

In the coming years, medical diagnosis and treatment applications will lead to substantial growth due to the rising prevalence of new zoonotic diseases. As the emerging technologies involved in Livestock Monitoring evolve toward smaller, more comfortable wearables with decreased energy consumption, it is possible to imagine a model of hyper-personalized animal care. Even large-scale farm operations would be able to improve the connection between producers and their animals.

Besides, it could also stimulate a reliable production ecosystem in which consumers are empowered to make decisions based on acceptable farming practices. It could help promote those who achieve more sustainability in the food chain (See Sustainability Labels for more on this). Farmers, on the other hand, would be able to make better decisions based on consumer practices and wishes.

5 topics
Agricultural-based Economic Development
Agricultural Policy and Rural Development
Environment Policy, Economics, and Management
Food and Nutrition Security
Private Sector Development
6 SDGs
02 Zero Hunger
03 Good Health and Well-Being
08 Decent Work and Economic Growth
09 Industry, innovation and infrastructure
12 Responsible Consumption and Production
15 Life On Land

Related Content

2 organizations
1 technology domains
4 technology methods
  • Deep Learning
  • Machine Vision
  • Hyperspectral Imaging (HSI)
  • 3D Modeling
3 technology applications
1 stories
1 industries
  • Agriculture
5 topics
  • Agricultural-based Economic Development
  • Agricultural Policy and Rural Development
  • Environment Policy, Economics, and Management
  • Food and Nutrition Security
  • Private Sector Development
6 SDGs
  • 02 Zero Hunger
  • 03 Good Health and Well-Being
  • 08 Decent Work and Economic Growth
  • 09 Industry, innovation and infrastructure
  • 12 Responsible Consumption and Production
  • 15 Life On Land