Spatio-Temporal Localization of Agricultural Machinery Operations

Keywords:
Precise farming, GPS, Linear fuzzy space, Classification.

Abstract:
The utilization of agricultural mechanization is crucial to its efficient exploitation that, in turn, significantly influences the entire agricultural economy as well as soil quality. Contemporary agricultural machines are GPS enabled, allowing localization and recording of their motion. In this paper we present an approach to spatio-temporal localization of agricultural mechanization operations based on a linear classifier in fuzzy linear space. We trained a classifier on data labeled using a fuzzy linear classifier in order to create a training set for a data mining predictor that may be helpful in automated management of records describing agricultural machinery’s dynamics. The training set was comprised of spatial coordinates of the machine recorded from a GPS device and then manually classified into two classes, denoting whether the machine is utilized for its primary purpose (productive operations like sowing, cultivating, spraying, etc.) or for non-productive operations such as moving the machine in transport from/to fields.

CITATION:

IEEE format

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D. Vidaković, V. Malbaša, Z. Konjović, E. Pap, �. Obradović, “Spatio-Temporal Localization of Agricultural Machinery Operations,” in Sinteza 2017 - International Scientific Conference on Information Technology and Data Related Research, Belgrade, Singidunum University, Serbia, 2017, pp. 479-485. doi:10.15308/Sinteza-2017-479-485

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Vidaković, D., Malbaša, V., Konjović, Z., Pap, E., Obradović, �. (2017). Spatio-Temporal Localization of Agricultural Machinery Operations. Paper presented at Sinteza 2017 - International Scientific Conference on Information Technology and Data Related Research. doi:10.15308/Sinteza-2017-479-485

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