From the report «How Computer Vision Is Fast Becoming the Backbone of Next-Generation Agronomy», of Raviv Itzhaky , published in Precision agriculture.
Remote agronomy and to a large extent remote agriculture could become a reality. As autonomous machines and robots take on an increasing number of roles, the necessity for a large workforce may be no longer needed. A report from S&P Global forecasts that by 2025, perception systems and picking algorithms will enable aspects of autonomous harvesting in controlled environment agriculture (CEA).
The Computer vision is at the core of enabling autonomous machines, helping them to react to situations on the field or even detect obstacles. Technology even enables us to react to hyper-accurate location data from satellite imagery, which is able to bring centimeter-level detail.
The impact of this technology is huge. Visual sensors and computer vision will be crucial to help the entire industry meet the food demands of a growing global population. It won’t be a revolution but a progressive evolution as visual technologies become mainstream. For example, the report points to machine learning algorithms ingesting drone, plane, and satellite images of increased resolution and greater spectral range, further enabling remote agronomy.