New publication: The importance of data quality assessment for machinery data in the field of agriculture
Apr 08 2022
Researchers from DEMETER, Morteza Abdipourchenarestansofla of John Deere and Christof Schroth of Fraunhofer IESE have a new publication titled ‘The importance of data quality assessment for machinery data in the field of agriculture”. The pilot study in DEMETER ‘In-Service Monitoring of Agricultural Machinery” is used to investigate data quality issues for machinery data. This use case develops a job cost • calculation system which aims to support the farmer by automating cost calculation associated to a given field operation. This technology, its reliability and accuracy, requires high-quality data that avoids misleading results. The system leverages telematics machinery data with the scope of fertilizer and chemical applicators in small grain. The chemical and fertilizer applications take place several times during the season.