When AI enables the efficient use of resources in forestry irrigation

Stora Enso (Sweden-Finland, 25,000 employees in 30 countries) is a global-leading provider of renewable solutions in packaging, biomaterials, and wooden constructions. Together with Arauco (Chile, 13,000 employees), they acquired Montes del Plata in a joint venture. Montes del Plata, owned by two of the world's largest forestry companies, produces pulp with the latest equipment and technological techniques. Its purpose is to become "a world leader in sustainable pulp production through responsibly managed forests".

We developed a Machine Learning module to make forestry irrigation more efficient.
The company had watering machines that were manually operated and could only irrigate one row of trees at the time. They needed to find a solution to reduce the mortality of new trees in the drier months, as well as use water more efficiently in irrigation.
The irrigation machine in operation.
Our team developed an artificial vision module that can be attached to the multiple arms of a newly-designed watering machine.

It detects plants in real-time and automatically activates the irrigation mechanism to water the trees.

This computer vision module enables the irrigation of several rows per pass: saving time, and costs and improving survival rate.
This module enables the reliable irrigation of several rows per pass:
saving time, costs, and improving survival rate.
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