Smart water management platform: IoT-based precision irrigation for agriculture

Kamienski, Carlos, Soininen, Juha-Pekka, Taumberger, Markus, Dantas, Ramide, Toscano, Attilio, Salmon Cinotti, Tullio, Filev Maia, Rodrigo and Torre Neto, Andre 2019, Smart water management platform: IoT-based precision irrigation for agriculture, Sensors, vol. 19, no. 2, pp. 276-276, doi: 10.3390/s19020276.

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Title Smart water management platform: IoT-based precision irrigation for agriculture
Author(s) Kamienski, Carlos
Soininen, Juha-Pekka
Taumberger, Markus
Dantas, Ramide
Toscano, Attilio
Salmon Cinotti, Tullio
Filev Maia, Rodrigo
Torre Neto, Andre
Journal name Sensors
Volume number 19
Issue number 2
Start page 276
End page 276
Total pages 1
Publisher MDPI AG
Place of publication Basel, Switzerland
Publication date 2019-01-11
ISSN 1424-8220
Keyword(s) FIWARE
Internet of Things
IoT platform
linked data
precision irrigation
smart agriculture
smart water management
Summary The smart management of freshwater for precision irrigation in agriculture is essential for increasing crop yield and decreasing costs, while contributing to environmental sustainability. The intense use of technologies offers a means for providing the exact amount of water needed by plants. The Internet of Things (IoT) is the natural choice for smart water management applications, even though the integration of different technologies required for making it work seamlessly in practice is still not fully accomplished. The SWAMP project develops an IoT-based smart water management platform for precision irrigation in agriculture with a hands-on approach based on four pilots in Brazil and Europe. This paper presents the SWAMP architecture, platform, and system deployments that highlight the replicability of the platform, and, as scalability is a major concern for IoT applications, it includes a performance analysis of FIWARE components used in the Platform. Results show that it is able to provide adequate performance for the SWAMP pilots, but requires specially designed configurations and the re-engineering of some components to provide higher scalability using less computational resources.
Language eng
DOI 10.3390/s19020276
Indigenous content off
Field of Research 0301 Analytical Chemistry
0906 Electrical and Electronic Engineering
HERDC Research category C1.1 Refereed article in a scholarly journal
Copyright notice ©2019, The Authors
Persistent URL http://hdl.handle.net/10536/DRO/DU:30128577

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