Technology applied to the field: what to do?

One of the problems we can detect is the health status of trees (whether they are dead, dry, or dying), caused by factors of a nutritional nature. In the example below, we obtain a database of multispectral images to feed the algorithm. Thus, using machine learning algorithms, we can predict the health status of a given plantation. In the example, we use a multispectral image as input for the algorithm, and as output, we get markings indicating the health status of the eucalyptus. The blue diamonds indicate that the tree is dying, and the red ones indicate that it is dead or dry. The squares are training samples for the algorithm to learn how to detect the problem in question. This is just one of several areas where we can improve the production process, minimize costs, and prevent waste. But for this to be possible, a large amount of data and skilled developers are needed to create machine learning algorithms applicable to the client's images. Want to know more about how Pix Force can help your company achieve better results using artificial intelligence? Get in touch here!