Image processing with cameras and AI enables applications that were previously unthinkable. In agriculture, for example, it supports the optimal application of fertilizers, the visual monitoring of products and growth phases, and the processing of harvested crops.
Digitized and automated processes are becoming increasingly important in modern agricultural enterprises. Machine vision methods play a key role here. Among other things, they can be used for a variety of precision farming applications.
The increased utilization of precision agriculture has resulted in more data breaches. Precision agriculture is a management system that relies on measuring and quantifying vast amounts of data to improve yields and decrease inputs.
Justin Gong, Co-founder and Vice President of XAG, kicked off the conference by carefully elaborating the Smart Agriculture POV Report 2020. This report for the first time clarifies the definitions regarding digital agriculture, precision agriculture and smart agriculture.
Artificial intelligence can be used, for example, to classify fruit varieties or to identify damaged parts, e.g. apples with marks or color deviations. To cover all possible variances with classical image processing would be very time-consuming and costly. With artificial intelligence, however, these challenges can be solved in no time at all. IDS NXT ocean is a user-friendly all-one-one system which requires neither special knowledge in deep learning nor camera programming. Only sample images and knowledge on how to evaluate them (e.g. "good apples" / "bad apples") are needed. This makes the start into AI-based image processing particularly easy. Camera hardware, software, infrastructure and support come from a single company. For beginners, IDS offer the IDS NXT ocean Creative Kit, which includes all components and workflows to create, train and run a neural net.