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Irriman Platform: Enhancing Farming Sustainability through Cloud Computing Techniques for Irrigation Management.

Authors :
Forcén-Muñoz, Manuel
Pavón-Pulido, Nieves
López-Riquelme, Juan Antonio
Temnani-Rajjaf, Abdelmalek
Berríos, Pablo
Morais, Raul
Pérez-Pastor, Alejandro
Source :
Sensors (14248220); Jan2022, Vol. 22 Issue 1, p228-228, 1p
Publication Year :
2022

Abstract

Crop sustainability is essential for balancing economic development and environmental care, mainly in strong and very competitive regions in the agri-food sector, such as the Region of Murcia in Spain, considered to be the orchard of Europe, despite being a semi-arid area with an important scarcity of fresh water. In this region, farmers apply efficient techniques to minimize supplies and maximize quality and productivity; however, the effects of climate change and the degradation of significant natural environments, such as, the "Mar Menor", the most extent saltwater lagoon of Europe, threatened by resources overexploitation, lead to the search of even better irrigation management techniques to avoid certain effects which could damage the quaternary aquifer connected to such lagoon. This paper describes the Irriman Platform, a system based on Cloud Computing techniques, which includes low-cost wireless data loggers, capable of acquiring data from a wide range of agronomic sensors, and a novel software architecture for safely storing and processing such information, making crop monitoring and irrigation management easier. The proposed platform helps agronomists to optimize irrigation procedures through a usable web-based tool which allows them to elaborate irrigation plans and to evaluate their effectiveness over crops. The system has been deployed in a large number of representative crops, located along near 50,000 ha of the surface, during several phenological cycles. Results demonstrate that the system enables crop monitoring and irrigation optimization, and makes interaction between farmers and agronomists easier. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14248220
Volume :
22
Issue :
1
Database :
Complementary Index
Journal :
Sensors (14248220)
Publication Type :
Academic Journal
Accession number :
154615399
Full Text :
https://doi.org/10.3390/s22010228