Given that the detection of lameness today is mainly carried out by visual subjective assessment of the animal, initially by the breeder himself and then by the veterinarian, the proposed system will be a reliable and affordable solution to the issue of early diagnosis of lameness.

It has been proven that the use of the 5-point grading scale does not provide particular reliability in the diagnosis of lameness, while other modern methods of diagnosing lameness are mainly based on the use of visual media where they try to diagnose animals with lameness using images and videos. The disadvantage of these methods lies in their difficulty to monitor the animal continuously in its natural habitat.

Therefore, the need to establish a new method of detecting lameness with continuous recording of the kinesiological characteristics of the animal in its natural space using new machine learning algorithms will provide a clear solution to the problem of timely diagnosis of lameness at an early stage.

In Greece, approximately 730,000 cattle are raised, of which 140,000 are dairy, 236,000 are meat and the rest are of mixed production. Of these, approximately 660,000 tons of milk and 40,000 tons of beef are produced (ELSTAT 2019). These figures make it imperative to deal with lameness at an early stage, since its increased rates of occurrence can cause a serious economic impact on livestock units. The cost per incident has been reported to be €216 (Netherlands) and $478 (US).

This cost includes the required medication, labor costs for podiatry, milk loss and the vet’s fee. All this can be avoided by implementing the proposed system of early diagnosis of lameness. The farmer will now have in his hands a reliable tool with the help of which he will be able to improve the efficiency of the herd by taking advantage of the full life cycle of his livestock by avoiding the premature slaughter of animals with lameness.

It will also increase the milk production capacity of the animals significantly through the rapid diagnosis of disease symptoms in the latent state, optimization of oestrus detection and reproductive management of the herd, as well as nutritional and health disorders of the animals. Finally, the operating costs of the unit will be reduced due to a reduction in the corresponding expenses for pharmaceutical treatments and veterinary services. All this will result in the upgrading of local products, the upgrading and expansion of the company’s operations and the strengthening of human resources at the local level.