Will Facial and Video Recognition Manage Tomorrow’s Cows?
Will Facial and Video Recognition Manage Tomorrow’s Cows?
Technology continues to revolutionize dairying as we know it, offering valuable tools to address labor shortages and improve overall herd management. Most dairy producers are familiar with robotic milkers and herd management systems that use radio-frequency identification (RFID) tags, collars or leg monitors to track individual animal data. These tools have become essential for streamlining workflows and monitoring herd health.
But the next evolution in dairy technology is here, and it’s looking your cows right in the face. Thanks to advances in computing power and artificial intelligence, facial recognition is emerging as a new method for animal identification (AI) and behavior monitoring. This innovation brings a new level of precision and objectivity to herd management while further eliminating the need for physical identifiers and reducing reliance on manual observation.
Facial Recognition in Practice
The technology used for facial recognition in dairy cattle is like that used in smartphones or for airport security. It works by mapping unique facial features of each cow to identify and track them across their life. With just a camera and software system, data can be collected, all without the need for physical tags or hardware devices that can be lost or damaged.
Several tech companies are now commercializing this style of system. CattleEye uses AI-powered video analytics to monitor cow locomotion and behavior. They mount cameras along cow lanes or milking parlors. They do this to capture footage that is then analyze the information to identify early signs of lameness or other health issues. This system offers remote monitoring capabilities and integrates with herd management software for actionable insights.
The up and coming myANIML combines facial recognition with behavior tracking and machine learning to alert producers to subtle health or welfare concerns before they escalate. By continuously monitoring individual cows, myANIML provides early detection of illnesses such as mastitis or lameness, allowing producers to intervene sooner and improve outcomes.
These systems not only support labor efficiency by reducing hands-on time, but they also help improve animal welfare, health outcomes and, ultimately, profitability.
Facial and Video Recognition Software
Each cow’s face is as unique as a human fingerprint, with identifiable features like hair whorls, nose shape, coat patterns, and even eye position. Facial and video recognition software is now tapping into these distinguishing traits to offer a contactless method of livestock identification.
Several innovators are advancing this space. For instance, 406 Bovine has developed a system that uses a short 3- to 5-second video clip captured via smartphone of an animal’s head. That footage is then uploaded into a private database. When an animal needs to be identified, a quick photo taken on a phone can be matched to that database, instantly pulling up the animal’s management history. This method offers an appealing alternative to traditional identification (ID) systems, which are prone to loss, tampering, or wear over time.
Joe Hoagland, founder of the American Black Hereford Association has designed an app, CattleTracs, that uses facial recognition to verify cattle identity. Initially developed to support disease traceability and age and source verification in the beef industry, the app is now gaining international traction. Hoagland’s team is currently collaborating with the European Commission to adapt CattleTracs for use in Brazil. They aim to help Brazilian beef producers prove their cattle are not raised on deforested land, a new requirement for export to the European Union. The app tags each cattle photo with GPS coordinates and a timestamp, providing digital proof of origin. These early efforts have shown encouraging accuracy rates, with facial ID correctly matching cattle 94% of the time in same-day comparisons.
Technical advances continue to refine how these systems work. Developers are testing multiple types of facial analytics algorithms. Some have a design to identify a specific animal from a database, others to confirm whether a photo matches a known ID. Both methods rely on biometric markers like facial geometry and texture analysis (comparing subtle pixel-level differences in coloration). These techniques are especially effective with cattle that have coat patterns or varied coloring. However, uniformly black cattle can present challenges due to low facial texture contrast, particularly as animals age or accumulate mud and debris in feedlot environments.
While there’s always work to be done, these technologies are advancing rapidly. As databases grow and algorithms improve, facial and video recognition could become a routine tool for disease traceability, marketing, regulatory compliance, and everyday herd management.
What Does the Future Hold?
Facial recognition technology is not intended to replace existing cattle management systems. Rather, it’s design is to enhance them. According to the developer behind 406 Bovine, the platform integrates seamlessly with many popular herd management software systems. Depending on the setup, a cow’s digital profile can link into preexisting databases such as breeding dates, health treatments, pen movements, and vaccination records.
These types of systems are currently reliant on smartphone hardware to capture facial data. This accessibility makes the technology portable and scalable, and continued improvements in smartphone camera performance will further unlock its full potential.
The promise of this innovation lies in its ability to digitize and automate what was once time consuming, manual work. This precision not only reduces errors, but also streamlines decisionmaking and supports early disease detection.
In the long term, this shift is expected to reduce the need for handling systems like chutes and manual scales, decrease stress on animals, and support more sustainable and data-driven operations.
The Challenges Ahead
Photo and video image identification still has a few hiccups. One challenge lies in the quality of images. Reliable identification demands clear, unobstructed photos in good lighting. Variables like poor weather, dust, camera wear and movement can compromise image clarity and reduce system accuracy. We may still be a few years away from smartphone technology that consistently meets these demands.
On the implementation side, producers must prepare to invest time and resources during the onboarding phase. Capturing each animal’s biometric data accurately requires careful planning, as does setting up and maintaining a reliable database. While the gains are substantial, the upfront costs (both in equipment and labor) may be a barrier to some operations.
Still, many of these obstacles being taken care of through software updates, improved user training, and hardware advancements. As the tech continues to evolve, solutions will become more affordable and user-friendly for operations of all sizes.
Facial recognition and video-based analytics are quickly emerging as powerful tools in modern cattle management. They offer producers the ability to identify and monitor animals more accurately, reduce labor demands, and make better-informed decisions for herd health and productivity. While the technology still faces practical limitations, the rate of advancement suggests these gaps will narrow quickly.
By integrating with existing herd software and leveraging devices farmers already use, facial recognition is poised to become an essential part of modern livestock production. As adoption grows and the technology matures, producers who invest early may gain a significant edge in both performance and traceability in a rapidly evolving marketplace.
By Jaclyn Krymowski
October 2025
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