Project DataSato Aims to Create Ecosystems for Data Warehouses in Farms
– GrainSense successfully part of the pilot demonstrations
Project DataSato (translates as “Data Harvest”) is a Finland based venture, part of the EIP-AGRI Network (European Innovation Partnership), that develops the business ability of agricultural primary production in accordance with the principles of sustainable development. The main goal of this project is to improve farmers' ability to use the data obtained from agricultural machinery in their own business. GrainSense takes part to the project by providing GS Flow Analyzers to be used as part of the demonstrations, at the same time gaining valuable insight from the field tests.
The project demonstrates how farm data from different IT systems is obtained from devices, machines and services to the data warehouse controlled by the farmer. The farmers' vision is that with the help of data and its efficient sharing, they would be able to form strong networks. With the help of networks, farmers would be able to strengthen their position in the data economy.
For the farmer, a data warehouse can bring significant added value to arable farming, especially in crop planning and optimization of production inputs. In this case, the environmental load caused by arable farming can also be reduced as a result of the utilization of data.
Proof of Concept with the GS Flow Analyzer
For the DataSato project, GrainSense has delivered two GS Flow Analyzers to combine harvesters for grain quality measurements for the 2023 and 2024 harvest seasons. In addition to the equipment deliveries, GrainSense has made the necessary changes to the software back-end systems, so that the integration into the ecosystem under development is technically easy.
One installation site is at the Tarvaala Bioeconomics campus and the other at KPEDU's Kannus site. In both test sites, data collection has been successfully completed for 2023.
Mr. Marko Paavola, part of the project team at KPEDU, the Central Ostrobothnia education associations, wrote his thesis titled “Data transmission of work machine data” about the demonstrations of the DataSato project from harvest season 2023.
“The cooperation with GrainSense has been extremely productive. Their team took part to installing and commissioning, and have been available remotely also in later trial runs. I believe the cooperation has been mutually fruitful, as we’ve had such a good technical back up for optimizing the devices, and at the same time GrainSense has been able to test their solutions in realistic environment and get ideas and feedback for further development”, Mr. Paavola explains.
Mr. Antti Leinonen, COO of GrainSense, finds this project valuable for GrainSense. The results of the Datasato project confirm the understanding that collecting quality data during harvesting using an analyzer solution integrated into combine harvesters is a welcome innovation compared to more traditional operating models.
“The experiences gained from this harvest season have been very valuable information for our product development to understand the possible development targets of the equipment, but above all to understand the added value the equipment brings to the customer. Collecting grain quality information during harvesting on a block-by-block basis and map-based visualization of the collected data are very new technologies. Our solutions are absolutely cutting edge globally in this development work. The introduction of real-time quality measurement as part of harvesting is expected to grow at an accelerating pace. GS Flow has already attracted a great deal of interest among the industry's biggest players”, Mr. Leinonen from GrainSense describes their findings from the project.
Towards next season and pilot farms
While building a new kind of an innovative ecosystem, technical challenges are bound to occur, and the Datasato project had its minor setbacks as well. In this case though, installing and commissioning the GrainSense Flow Analyzer was very successful. The project team was able to get the proof on concept done during the first harvest season, and now they are ready to take the project to dedicated farms next season.
“We reached our goals during the first harvest season. We measured the moisture and protein content from the yield and transferred the data in real-time to the cloud service, together with GPS location data. Also, the project coordinators have been very satisfied with how this part of the project has been successful”, Mr. Paavola states.
Furthermore, the project also promotes agriculture that utilizes greater resource- and climate-wise data and digitization. The utilization of machine data will probably play a significant role in the future in developing arable farming business in accordance with the principles of sustainable development. Optimizing production inputs can both improve business profitability and simultaneously enhance environmental protection.
“It's great that GrainSense was given the opportunity to participate in this project. Agricultural ecosystem development and a fair data economy require shared goals in the fields of responsibility and sustainability. The project has helped GrainSense to figure out its own positioning in this development”, Mr. Leinonen concludes.
For more information about these demonstrations, read Marko Paavola’s thesis “Data transmission of work machine data” (in Finnish only) http://urn.fi/URN:NBN:fi:amk-2023120133439