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Automating the process of importing data into an FMIS using information from tractor’s CAN-Bus communication

Published online by Cambridge University Press:  01 June 2017

D. S. Paraforos ,
V. Vassiliadis ,
D. Kortenbruck ,
K. Stamkopoulos ,
V. Ziogas ,
A. A. Sapounas  and
H. W. Griepentrog
D. S. Paraforos*
Affiliation:
University of Hohenheim, Institute of Agricultural Engineering, Process Engineering in Plant Production (440d), Garbenstr. 9, 70599, Stuttgart, Germany
V. Vassiliadis
Affiliation:
Agrostis Agricultural Information Systems, Α. Tritsi 21, Pylaia, 57001, Thessaloniki, Greece
D. Kortenbruck
Affiliation:
University of Hohenheim, Institute of Agricultural Engineering, Process Engineering in Plant Production (440d), Garbenstr. 9, 70599, Stuttgart, Germany
K. Stamkopoulos
Affiliation:
Agrostis Agricultural Information Systems, Α. Tritsi 21, Pylaia, 57001, Thessaloniki, Greece
V. Ziogas
Affiliation:
Agrostis Agricultural Information Systems, Α. Tritsi 21, Pylaia, 57001, Thessaloniki, Greece
A. A. Sapounas
Affiliation:
Agrostis Agricultural Information Systems, Α. Tritsi 21, Pylaia, 57001, Thessaloniki, Greece
H. W. Griepentrog
Affiliation:
University of Hohenheim, Institute of Agricultural Engineering, Process Engineering in Plant Production (440d), Garbenstr. 9, 70599, Stuttgart, Germany
*
†E-mail: d.paraforos@uni-hohenheim.de
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Abstract

This paper is focusing on how to eliminate the required time for importing all the necessary data into a farm management information system (FMIS). This process was automated by using ISO 11783 and SAE J1939 communication information from the tractor’s CAN-Bus. Using a data logger and a machine to machine (M2M) gateway inside the tractor’s cabin, CAN-Bus data were recorded and transmitted to the cloud-based server of the FMIS. There, a script was responsible for parsing and aggregating the raw machine data into specific agricultural tasks and then importing them into the FMIS. The operator could choose the type of the performed task by a number of switches connected with the digital inputs of the data logger.

Keywords

Future internet, CAN-BusSAE J1939M2M communicationcloud-based computing
Type
Information and Decision Support Systems
Information
Advances in Animal Biosciences , Volume 8 , Special Issue 2: Papers presented at the 11th European Conference on Precision Agriculture (ECPA 2017), John McIntyre Centre, Edinburgh, UK, July 16–20 2017 , July 2017 , pp. 650 - 655
Copyright
© The Animal Consortium 2017 

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References

Ampatzidis, Y, Tan, L, Haley, R and Whiting, MD 2016. Cloud-based harvest management information system for hand-harvested specialty crops. Computers and Electronics in Agriculture 122, 161–167.Google Scholar
de Jong, J 1997. Calculation of the tractor and equipment operating cost based on the litres of fuel used for an operation on a per hectare basis. Tea Research Foundation (Central Africa) Quarterly Newsletter 127, 15–21.Google Scholar
Fountas, S, Carli, G, Sørensen, CG, Tsiropoulos, Z, Cavalaris, C, Vatsanidou, A et al. 2015. Farm management information systems: Current situation and future perspectives. Computers and Electronics in Agriculture 115, 40–50.Google Scholar
Fountas, S, Sorensen, CG, Tsiropoulos, Z, Cavalaris, C, Liakos, V and Gemtos, T 2015. Farm machinery management information system. Computers and Electronics in Agriculture 110, 131–138.Google Scholar
Anonymous 2015. ISO 11783-10 Tractors and machinery for agriculture and forestry - Serial control and communications data network - Part 10: Task controller and management information system data interchange. Geneva.Google Scholar
Nikkilä, R, Seilonen, I and Koskinen, K 2010. Software architecture for farm management information systems in precision agriculture. Computers and Electronics in Agriculture 70 (2), 328–336.Google Scholar
Oksanen, T, Piirainen, P and Seilonen, I 2015. Remote access of ISO 11783 process data by using OPC Unified Architecture technology. Computers and Electronics in Agriculture 117, 141–148.Google Scholar
Paraforos, DS, Griepentrog, HW and Vougioukas, SG 2016a. Methodology for designing accelerated structural durability tests on agricultural machinery. Biosystems Engineering 149, 24–37.Google Scholar
Paraforos, DS, Vassiliadis, V, Kortenbruck, D, Stamkopoulos, K, Ziogas, V, Sapounas, AA et al. 2016b. A farm management information system using future internet technologies. In Proceedings: 5th IFAC Conference on Sensing, Control and Automation for Agriculture, August 14–17, 2016, Seattle, USA, IFAC-PapersOnLine, 49, (16) 324–329.Google Scholar
Pereira, FCN and Warren, DHD 1980. Definite clause grammars for language analysis - A survey of the formalism and a comparison with augmented transition networks. Artificial Intelligence 13 (3), 231–278.Google Scholar
Sørensen, CG, Pesonen, L, Bochtis, DD, Vougioukas, SG and Suomi, P 2011. Functional requirements for a future farm management information system. Computers and Electronics in Agriculture 76 (2), 266–276.Google Scholar
Steinberger, G, Rothmund, M and Auernhammer, H 2009. Mobile farm equipment as a data source in an agricultural service architecture. Computers and Electronics in Agriculture 65 (2), 238–246.Google Scholar
Tsiropoulos, Z, Fountas, S, Gemtos, T, Gravalos, I and Paraforos, D 2013. Management information system for spatial analysis of tractor- implement draft forces. In Proceedings: 9th European Conference on Precision Agriculture, Precision agriculture’ 13, 349–356. Wageningen Academic Publishers, The Netherlands.Google Scholar