Good Practice - Project
Agricultural business development with intelligent data analytics
An EIP-AGRI Operational Group in Finland developed an intelligent data analysis service for farmers.
General information
RDP Priority
- P1. Knowledge transfer and innovation
RDP Focus Area
- 1B: Links with research & innovation
RDP Measure
- M16: Cooperation
Summary
Big Data technologies will play key roles in agriculture in the near future. Already on a daily basis, farmers use machinery and equipment that collect large amounts of data that cannot be used effectively without Big Data tools. An EIP-AGRI Operational Group developed an intelligent data analysis service through which farmers can make better business decisions based on information related to crop mapper data, soil samples, satellite imagery, etc.
Results
The project created the new analytical service for farmers which uses both open source and private data for over 150 users-farmers and 4 000 land plots.
Promoter
Tampere Technical University Foundation*
Funding
Total budget 395 000.00 (EUR)
EAFRD 165 900.00 (EUR)
National/Regional 229 100.00 (EUR)
Ressources
Agricultural business development with intelligent data analytics
(PDF – 2.97 Mo)
Context
Agricultural production continues to modernise and transform. Farmers are able to gather large amounts of data on their everyday work machinery and equipment such as tractors, harvesters, drones, but this information cannot be effectively processed without modern tools such as Big Data technologies. This project would help allow farmers to use inputs in the most efficient way and consequently increase farm profitability in an environmentally sustainable way.
Objectives
This EIP-AGRI Operational Group aimed to build an intelligent data analysis service through which farmers can make better business decisions based on information related to crop mapper data, soil samples, satellite imagery, etc.
Activities
The project included five different work packages, which were:
- The collection of farm data and establishing data connections.
- The acquisition of a data server and software.
- The development of a concept design and user interface for the data analysis service.
- A communications campaign to promote the service and support users.
- The production of educational material - including videos - for farmers.
The project also tested new technologies for gathering precise information about soil structure, such as soil scanners, multi- and hyperspectral cameras, and artificial intelligence for yield forecasting.
The project organised the first FinDrones conference in 2019, which has been held every year since. The project also contributed to the publication of: “New Developments and Environmental Applications of Drones. Proceedings of FinDrones 2020.”
Main results
The project resulted in the launch of a new analytics service www.Peltodata.fi for farmers. The service combines data collected from different sources and formats (e.g. satellite images) and thus enables farmers to access detailed information about their soil condition, nutrient levels, yield prediction, etc. This, in turn, allows them to optimise production, improve profitability and minimise the environmental impact of agriculture.
The Peltodata-service uses both open source and private data for over 150 user-farmers and 4 000 land plots.
Key lessons
Currently, there is a lot of data collected at farm level. However, this information is scattered and stored in different services or devices and only a small fraction is used in support of decision making. In the future, it will be important to pay more attention to data quality, transferability, and rights.
“Flying and utilising drones needs a lot of training, if we want to receive top quality data. This is a real training need of future farmers – many young farmers already know how to do it.”
Petri Linna, project manager