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Lari Melander

Big Data Fusion in Forest Harvesters  

>> 2016-2019 

Doctoral Graduate

Research is focusing on developing a new industrial internet concept in forest harvesting domain for utilizing better the data available from various sources. The main idea is to aggregate collected Big Data, such as harvester’s CAN bus data and other multi-dimensional information used in wood procurement, using modern machine learning and data fusion methods.

Research includes also development of new sensor systems for estimating the key properties of the forest environment. Main interest is to create a system that would efficiently offer organized positioned data for optimizing wood procurement. 

Industry Partner

Jarmo Hämäläinen


Academic Supervisor

Risto Ritala


Kalle Einola


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