In order to use HorseCare, the sensors must be attached on top of the foot or forefoot protection (as described in the instructions) or the mono-sensor clip must be attached to the harness and activated (the blue light should flash). Then start the mobile app and start training. The data from the sensors will automatically be sent directly to your personal system cabinet.

The only purpose of HorseCare at this stage of development is the early diagnosis of any organic abnormalities in the horse that could potentially lead to lameness or similar problems. HorseCare should be treated as an attentive and sensitive assistant who will not miss even the slightest change in your pet’s movements and will immediately let you know about it. Using HorseCare allows you to start preventative measures at an early stage of the onset of lameness and eliminate or significantly reduce the duration of the disease. 

The sensor kit you have purchased can be used on any horse. But please note that each sensor set sends data to a separate account linked directly to your horse. You can certainly move the sensor set between your pets, but in that case, since the basis of the system is BigData, we cannot provide an accurate indication of the location of possible problems. It will be like a family photo from which your portrait will have to be highlighted. We recommend a combination of – 1 set of sensors – one horse.

Since the system is based on state-of-the-art data processing methods (BigData, AI and ML (machine learning)), the system is generally very good at correcting errors that occur during its use. What can’t the complex take into account? If you have attached the sensors in such a way that they are not firmly attached to the leg during training and make additional chaotic movements during use.

This project option is available in the premium package. Here you get an in-depth analysis of the horse to be bought compared with the BigData which forms the basis of the system. We give a very precise assessment of the horse’s movement and prognosis of its prospects in the selected class. For more precise information and to take out a premium subscription please use our feedback form. By describing the enquiry. Our manager will contact you immediately.

The instructions are available for download at this link .

Horse weight and RFID: essential details for the system’s operation When renting a horse, owners don’t always have precise information about its weight or RFID chip number. However, these parameters are crucial. The horse’s weight is necessary for calculating energy expenditure, determining balance, and identifying the center of gravity. Without this information, the system cannot perform its functions accurately. As for identification, our cloud-based AI relies solely on the RFID chip. This unique identifier is the only reliable way to accurately recognize a specific horse. We’ve tested numerous alternatives, but this method is the only one that works consistently. It’s important to note that providing the RFID chip information is the user’s responsibility. Without this element, the system cannot be used.

Some owners working with multiple horses wonder if a single set of sensors can be used for different animals. Technically, this is possible. However, such an approach comes with significant limitations. The initial data entered for the base horse remains unchanged, which means about 30% of the system’s functionality will be unavailable. Why does this happen?
-Weight differences. The weight of a horse affects calculations, and using data from one horse for another will lead to errors.
-Unique signatures. Each horse has its own individual characteristics that the system recognizes. Attempting to transfer signatures from one horse to another disrupts accurate operation.
Therefore, our stance is clear: one set of sensors equals one horse. This is a fundamental rule to ensure the system’s precision and efficiency.

At first glance, it may seem convenient for sensors to automatically begin recording as soon as they are placed on the horse. However, this approach presents several significant issues. Accumulation of “noise” data From experience, we know that there can be a delay of 30 to 45 minutes between saddling the horse and the actual start of training on the field. If sensors actively record during this time, the volume of irrelevant data could equal or even exceed the volume of useful information. This not only slows down analysis but also interferes with accurate sports analytics. Distortion of training results In the user dashboard, key metrics such as:
-training duration,
-distance covered,
-energy expenditure,
-and other parameters are displayed. If these calculations include time spent walking to the field or warming up before training, the data becomes less accurate. This is critical, as these metrics are used to assess the horse’s fitness and progress.
For this reason, manually starting the training recording via the app remains the best solution. It ensures that only relevant data essential for analysis is captured.

At the heart of HorseCare is Big Data, which enables you to determine very precisely the typical movements of your horse at each gait and detect the smallest deviations from your horse’s typical movements. The data is provided by 3 high-tech sensors, which acquire information on 9 measuring planes 1700 times per second. The collected values are stored in your personal study and serve as the basis for monitoring and conclusions.

The HorseCare package can be of great help to professionals who breed and train performance horses, but this option is not available as standard. If you are interested, please use the feedback form.

HorseCare can be used for all types of training. The cloud-based system perfectly recognises the type of training as well as all your horse’s gaits. It keeps a very close eye on what is going on and provides you with important information at the right time. In general we recommend regular use during your standard training. This way the Artificial Intelligence gets to know your horse much better and becomes more and more precise with each training session.

The system is based on the principle of in-depth knowledge of your horse’s specific movement patterns. Throughout the entire period of use, the system collects a huge amount of information about your horse’s movement patterns and takes excellent care of older horses.

The system updates data every second as the cloud server receives data from thousands of sensors in use around the world. Since the main development mechanism of the system is the use of AI and ML, we can say that as the data is accumulated and learned, HorseCare gets smarter and smarter. You do not have to worry about updating the application. We have put the very principle of learning and development at the heart of the system. Rather, after a while, you should expect a phone call and the question “Good morning, how are you? Say hello to your horse and tell him his last training session was great!” And the caller calling you will be himself AI HorseCare… ))) (Joking)

To delete an account, you must submit a request to the support team on the “Request for deletion of HorseCare account” page

The idea of automatically turning off sensors once they are removed from the horse may seem convenient. However, as experience shows, it doesn’t solve all problems and creates additional complications.
1.Lack of reliable data on the start and end of training Determining the exact moment the training begins or ends without the rider’s involvement is nearly impossible. The training process is individual: it can range from intense work in the arena to a leisurely warm-up or cool-down. Automation based on signals from sensors cannot clearly distinguish between these states.
2.The rider’s role in controlling the recording Only the rider knows exactly when the training begins and ends. This is due to the unique nature of each session: one horse may require a warm-up before the main block, while another may need an extended cool-down. Relying solely on automation risks compromising the quality of the data.
For these reasons, manually starting and ending the training recording through the app remains the optimal solution. It allows the user to control critical stages of the process and avoid capturing irrelevant data.

Ideally, data from sensors should be transmitted to the server instantly and become available in the user dashboard. However, practice has shown that this approach does not always work in every situation.
1. Internet connection issues In the early stages of development, the system was configured to automatically upload data to the internet right after the training session. But once we encountered users in areas with no mobile internet (such as some remote stables), serious problems arose. Data tried to upload endlessly, causing additional issues: unnecessary battery drain, system overload, and, most importantly, data loss.
2.Data reliability Now, all data is first saved on the device, and its upload to the server is done manually when stable internet access is available. This approach ensures that no training session is lost due to connection issues.
As a result, manual control of data transfer has proven to be more effective and secure. This solution came with experience and makes the system more resilient to different operating conditions.