A major disease of dairy cattle is called cow lameness (or hoof disease). Gait refers to the pattern of movement of the limbs of animals. Gaits are typically classified according to footfall patterns, and while the gait is at it should be the cow can move and feed freely. Where hoof disease occurs, the movement of the animal is adversely affected. One reason for the disease is the development of an ulcer, which can arise due to a bacterial infection. The disease can be life-threatening.
A solution to help fairy farmers to detect the disease has developed from images of cow gait. This is a device that consists of an image analyzer scanner and software. This took the form of machine learning, where a series of images helped a computer program ‘learn’ the signs and symptoms of the disease. The tool now has an accuracy of 99 percent.
The image analyzer and computer program have been developed by Professor Yago Yasushi from the Institute of Scientific and Industrial Research at Osaka University. The project was supported by together with Professor Nakada Ken from Rakuno Gakuen University. The aim was come up with something relatively simple to use, in the form of hand-held scanner that a dairy farmer could deploy rapidly and easily. The technology could, the researchers add, be the first step towards the ‘smart cowhouse’.
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Current methods for detecting lameness in cows are reliant upon visual cues and the experience of the framer. This includes looking at things like back arch. To make the visual process more accurate, researchers have devised an image analysis method that uses a waterproof and dustproof Microsoft Kinect. This is a camera-based sensor that can measure the distance to an object. Hundreds of cow images were used to enable the software to learn the various types of gait and to highlight which were a concern.
In a research note, Professor Yagi states: “Our achievements will mark the start of techniques for monitoring cows using artificial intelligence powered image analysis.”
For the next part of cow related research, Professor Yagi aims to develop an automatic milking machine and feeding robot.
