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Challenge #7
MACHINERY
MONITORING
Analysis, processing and standardization
of data from agriculture machinery for
easier utilization by farmers
Description of Challenge
Agricultural machinery significantly influences the
economic profitability of crop management. How to
operate machinery on the field and achieve the best
result in farming business? Data collection from
running machine in time and location or Meteo sensor
on the field can be one of basic controlling for farmers.
From a technical point of view the monitoring system
involves tracking of the vehicles position using GPS
combined with acquisition of information from on-
board terminal or field sensors (CAN-BUS, ISOBUS)
and their online or offline transfer to GIS environment
in ISO XML format.
Verification process
Verification of the data collection will be done at medium-sized farm, where it will serve for an evaluation of
tractors work during operation such as soil tillage, fertilization, sowing and application of nutrients and
chemicals for crop protection.
Similar monitoring of Meteo data will be tested at the enterprise which is offering services for farmers for
assessing the quality of work for customers.
Verification, data controlling and visualization will be in first step, next step will analyze data with focus on:
• Evaluation of the economic efficiency of machinery operations within the fields - farm
• Precise records of crop management treatments
• Management of machinery operations – increasing the efficiency of planning of crop management
• Control of requirement for field operations:
• control of pass-to-pass errors and overlaps, coverage of maintained area and recommended work speed
• Control of applied input material in comparison to prescribed rates
• On line monitoring of weeds
• On line monitoring of weather
CHALLENGE GOALS
 Visuals Tracking the machinery fleet which allows localization of farm vehicles in real time.
This information provides an overview of current operations of machines and is crucial for the
planning of field work and an evaluation of machines usage in time.
 Evaluation of economic efficiency of the crop management treatments within the fields. A
prerequisite is the identification of fields and tractor equipment for the accurate estimation of
field job costs based on the fuel consumption and used and working time.
 Evaluation of machinery passes on the soil environment. This includes detailed analysis of
the tractor trajectories within the fields considering the site specific conditions. The aim is to
estimate the negative effect of machine tracks on the soil environment (especially soil
compaction) and compliance of agro-environmental limits (nitrates directive, GAEC, protection
of water resources, other protected area etc.)
 Open for future update local changes
Test data available:
 ISOxml file from tractor offline
 ISOxml file from tractor online
 Meteo data in ??????? format online
Other info on pavel.gnip@agcocorp.com
Thank you for your
participation.

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Agrihub INSPIRE Hackathon 2021: Challenge #7: Analysis, processing and standardisation of data from agriculture machinery for easier utilization by farmers

  • 2. MACHINERY MONITORING Analysis, processing and standardization of data from agriculture machinery for easier utilization by farmers
  • 3. Description of Challenge Agricultural machinery significantly influences the economic profitability of crop management. How to operate machinery on the field and achieve the best result in farming business? Data collection from running machine in time and location or Meteo sensor on the field can be one of basic controlling for farmers. From a technical point of view the monitoring system involves tracking of the vehicles position using GPS combined with acquisition of information from on- board terminal or field sensors (CAN-BUS, ISOBUS) and their online or offline transfer to GIS environment in ISO XML format.
  • 4. Verification process Verification of the data collection will be done at medium-sized farm, where it will serve for an evaluation of tractors work during operation such as soil tillage, fertilization, sowing and application of nutrients and chemicals for crop protection. Similar monitoring of Meteo data will be tested at the enterprise which is offering services for farmers for assessing the quality of work for customers. Verification, data controlling and visualization will be in first step, next step will analyze data with focus on: • Evaluation of the economic efficiency of machinery operations within the fields - farm • Precise records of crop management treatments • Management of machinery operations – increasing the efficiency of planning of crop management • Control of requirement for field operations: • control of pass-to-pass errors and overlaps, coverage of maintained area and recommended work speed • Control of applied input material in comparison to prescribed rates • On line monitoring of weeds • On line monitoring of weather
  • 5. CHALLENGE GOALS  Visuals Tracking the machinery fleet which allows localization of farm vehicles in real time. This information provides an overview of current operations of machines and is crucial for the planning of field work and an evaluation of machines usage in time.  Evaluation of economic efficiency of the crop management treatments within the fields. A prerequisite is the identification of fields and tractor equipment for the accurate estimation of field job costs based on the fuel consumption and used and working time.  Evaluation of machinery passes on the soil environment. This includes detailed analysis of the tractor trajectories within the fields considering the site specific conditions. The aim is to estimate the negative effect of machine tracks on the soil environment (especially soil compaction) and compliance of agro-environmental limits (nitrates directive, GAEC, protection of water resources, other protected area etc.)  Open for future update local changes
  • 6. Test data available:  ISOxml file from tractor offline  ISOxml file from tractor online  Meteo data in ??????? format online Other info on pavel.gnip@agcocorp.com
  • 7. Thank you for your participation.