Abstract
Aim of study: An approach to integrate knowledge into the IT-infrastructure of precision agriculture (PA) is presented. The creation of operation relevant information is analyzed and explored to be processed by standardized web services and thereby to integrate external knowledge into PA. The target is to make knowledge integrable into any software solution. Area of study: The data sampling took place at the Heidfeld Hof Research Station in Stuttgart, Germany. Material and methods: This study follows the information science’s idea to separate the process from data sampling into the final actuation through four steps: data, information, knowledge, and wisdom. The process from the data acquisition, over a professional data treatment to the actual application is analyzed by methods modelled in the Unified Modelling Language (UML) for two use-cases. It was further applied for a low altitude sensor in a PA operation; a data sampling by UAV represents the starting point. Main results: For the implemented solution, the Web Processing Service (WPS) of the Open Geospatial Consortium (OGC) is proposed. This approach reflects the idea of a function as a service (FaaS), in order to develop a demand-driven and extensible solution for irregularly used functionalities. PA benefits, as on-farm processes are season oriented and a FaaS reflects the farm’s variable demands over time by origin and extends the concept to offer external know-how for the integration into specific processes. Research highlights: The standardized implementation of knowledge into PA software products helps to generate additional benefits for PA.
Highlights
Nowadays agriculture is highly mechanized and incorporates various sophisticated systems, technologies and sensors
The present research works out the benefit of a decentral logic behind machinery and user interface of the farm management information system (FMIS)
By the modelled use-cases, we present the fitness of components and their benefit for the involved parties
Summary
Nowadays agriculture is highly mechanized and incorporates various sophisticated systems, technologies and sensors. Evangelidis et al (2014) described a framework for geospatial cloud computing as a multi-tier client-server architecture, using service interfaces of the OGC He further emphasized the benefit of the integration of computer systems into incompatible platforms by standardized interfaces. Lee & Kim (2018) realized an implementation of an OGC WPS for a geo-based image analysis in a cloud platform He used the Platform-as-a-Service (PaaS)-technology as a scalable backend. We explored the possibilities and capabilities of a standardized service, offering functionalities to PA-applications We built this service, which is located directly above raw data, and supports software of the end-user via specific processing. Our task is to get familiar with working methods and material, like the OGC WPS and UML modelling, to analyze the activities of two PA-use-cases by UML and proof the proposed concept by realizing one use-case in real field conditions
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