Methods and procedures for automatic collection and management of data acquired from on-the-go sensors with application to on-the-go soil sensors.

Date

2012-02-01T00:00:00Z

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Elsevier Science B.V., Amsterdam.

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Article

ISSN

0168-1699

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Free to read from

Citation

Sven Peets, Abdul Mounem Mouazen, Kim Blackburn, Boyan Kuang, Jens Wiebensohn, Methods and procedures for automatic collection and management of data acquired from on-the-go sensors with application to on-the-go soil sensors, Computers and Electronics in Agriculture, Volume 81, February 2012, Pages 104–112.

Abstract

Sensors for on-the-go collection of data on soil and crop have become essential for successful implementation of precision agriculture. This paper analyses the potentials and develops general procedures for onthe- go data acquisition of soil sensors. The methods and procedures used to manage data with respect to a farm management information system (FMIS) are described. The current data communication standard for tractors and machinery in agriculture is ISO 11783, which is rather well established and has gained market acceptance. However, there are a significant number of non-ISO 11783 compliant sensors in practice. Thus, two concepts are proposed. The first concept is on-the-go data collection based on ISO 11783, which mostly covers data on parameters related to tractor and machine performance, e.g. speed, draught, fuel consumption, etc. Process data from sensors with Control Area Network (CAN) interfaces is converted into ISO 11783 XML and then imported into relational database at FMIS using RelaXML tool. There is also the export function from database to task controller (TC) to provide task management, as described in ISO 11783:10. The second concept is on- the-go data collection with non-ISO 11783 sensors. This data is likely to be recorded in many formats, which require an import service. An import service is based on local or public sharing or semantic mapping outputting a common format for FMIS (e.g. AgroXML). Import is best performed as close to the generation of sensor data as possible to maximise the availability of metadata. A case study of sensor based variable rate fertilisation (VRF) has been undertaken focussing on German fertilisation rules.

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NOTICE: this is the author’s version of a work that was accepted for publication in Computers and Electronics in Agriculture. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computers and Electronics in Agriculture, VOL 81 (2012) DOI:10.1016/j.compag.2011.11.011

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