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A Sensor Web-Enabled Infrastructure for Precision Farming

Institute of Crop Science, University of Hohenheim, Fruwirthstr. 23, 70599 Stuttgart, Germany
Institute of Phytomedicine, University of Hohenheim, Otto-Sander-Str. 5, 70599 Stuttgart, Germany
Centre for Geodesy and Geoinformatics, University of Applied Sciences (HFT) Stuttgart, Schellingstr. 24, 70174 Stuttgart, Germany
Author to whom correspondence should be addressed.
Academic Editors: Georg Bareth, Fei Yuan and Wolfgang Kainz
ISPRS Int. J. Geo-Inf. 2015, 4(1), 385-399;
Received: 30 November 2014 / Accepted: 5 March 2015 / Published: 18 March 2015
PDF [3054 KB, uploaded 18 March 2015]


The use of sensor technologies is standard practice in the domain of precision farming. The variety of vendor-specific sensor systems, control units and processing software has led to increasing efforts in establishing interoperable sensor networks and standardized sensor data infrastructures. This study utilizes open source software and adapts the standards of the Open Geospatial Consortium to introduce a method for the realization of a sensor data infrastructure for precision farming applications. The infrastructure covers the control of sensor systems, the access to sensor data, the transmission of sensor data to web services and the standardized storage of sensor data in a sensor web-enabled server. It permits end users and computer systems to access the sensor data in a well-defined way and to build applications on top of the sensor web services. The infrastructure is scalable to large scenarios, where a multitude of sensor systems and sensor web services are involved. A real-world field trial was set-up to prove the applicability of the infrastructure. View Full-Text
Keywords: Sensor Web Enablement; Open Geospatial Consortium; precision farming; interoperable; open source; 52° N; sensor; UAS; web service Sensor Web Enablement; Open Geospatial Consortium; precision farming; interoperable; open source; 52° N; sensor; UAS; web service

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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MDPI and ACS Style

Geipel, J.; Jackenkroll, M.; Weis, M.; Claupein, W. A Sensor Web-Enabled Infrastructure for Precision Farming. ISPRS Int. J. Geo-Inf. 2015, 4, 385-399.

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