PILOT CLUSTER TWO Precision Farming
Pilot SUmmary
Agricultural Machinery, Precision Farming.
Description:
The cluster will also focus on arable crops but specifically on the usage of agricultural machinery and the establishment of precision farming. The pilots will concentrate on monitoring arable crops through sensors and their documentation, while decision support systems will be developed for live support of agricultural process in a secure and trusted way. The data will reuse existing platforms and services and link the results to the DEMETER platform.
Partners involved:
John Deere (DE), LESP (CZ), AVINET (NO), WODR (PL), PSNC (PL), m2Xpert (DE), Fraunhofer (DE), Napierała (PL), Frackowiak (PL).
Pilot projects run under pilot cluster two:
Pilot 2.1 - In-Service Condition Monitoring of Agricultural Machinery
In-Service Condition Monitoring of Agricultural Machinery
Using onboard sensors for in-service monitoring of engine data as well as data of the exhaust gas after treatment decreases the need for PEMS (Portable Emissions Measurement System).
Pilot 2.2 - Automated Documentation of Arable Crop Farming Processes
Automated Documentation of Arable Crop Farming Processes
Today, agricultural processes are often documented with a considerable time lag after they are carried out, leading to inaccuracies. In addition, the cost of a job depends on various factors.
Pilot 2.3 - Data Brokerage Service and Decision Support System for Farm Management
Data Brokerage Service and Decision Support System for Farm Management
Farming related data is produced by several suppliers, using different systems, data models and APIs. This data varies from machinery data, satellite data, meteorological data, land parcel information systems…
Pilot 2.4 - Benchmarking at Farm Level Decision Support System
Benchmarking at Farm Level Decision Support System
There are several different data sets for agriculture, but many of them are rarely used in practice. Farmers often have challenges with the practical use of data when making decisions on the farm, especially in management.
