Our cooperation with Aetina has been flawless and the technical support team is very helpful, competent and responsive.
— Toke Nielsen, Software and Computer Vision Developer - sScale lead
The Challenge: Outdated Systems and Modern AI Demands
Traditional manual timber stack measurement is a slow, manual, labor-intensive process, plagued by inaccuracy and safety risks for workers in harsh weather.
Dralle A/S, a leader in forestry digital technology, faced critical limitations with their legacy timber stack measurement system. Their initial system, an x86 platform with classic computer vision techniques (i.e., watershed algorithms and Hough transform), couldn’t keep pace with modern AI demands.
The limitations were clear: slow machine learning execution, insufficient processing power for accurate log end detection, and a bulky size unsuitable for their camera box. These constraints ultimately rendered advanced AI and machine learning unusable on the existing platform, pushing Dralle towards a crucial turning point: the need for a solution capable of harnessing advanced AI and machine learning capabilities.