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Mobile application based sustainable irrigation water usage decision support system: an intelligent sensor CLOUD approach

Citation

Li, C and Dutta, R and Kloppers, C and D'Este, C and Morshed, A and Almeida, A and Das, A and Aryal, J, Mobile application based sustainable irrigation water usage decision support system: an intelligent sensor CLOUD approach, IEEE SENSORS 2013 Proceedings, 3-6 November 2013, Baltimore, USA, pp. 1565-1568. ISBN 978-1-4673-4642-9 (2013) [Refereed Conference Paper]

Copyright Statement

Copyright 2013 IEEE

DOI: doi:10.1109/ICSENS.2013.6688523

Abstract

In this paper a novel data integration approach based on three environmental Sensors Model Networks (including the Bureau of Meteorology-SILO database, Australian Cosmic Ray Sensor Network database (CosmOz), and Australian Water Availability Project (AWAP) database) has been proposed to estimate ground water balance and average water availability. An unsupervised machine learning based clustering technique (Dynamic Linear Discriminant Analysis (D-LDA)) has been applied for extracting knowledge from the large integrated database. The Commonwealth Scientific and Industrial Research Organisation (CSIRO) Sensor CLOUD computing infrastructure has been used extensively to process big data integration and the machine learning based decision support system. An analytical outcome from the Sensor CLOUD is presented as dynamic web based knowledge recommendation service using JSON file format. An intelligent ANDROID based mobile application has been developed, capable of automatically communicating with the Sensor CLOUD to get the most recent daily irrigation, water requirement for a chosen location and display the status in a user friendly traffic light system. This recommendation could be used directly by the farmers to make the final decision whether to buy extra water for irrigation or not on a particular day.

Item Details

Item Type:Refereed Conference Paper
Keywords:irrigation, water usage, app, intelligent
Research Division:Engineering
Research Group:Geomatic Engineering
Research Field:Geomatic Engineering not elsewhere classified
Objective Division:Environment
Objective Group:Land and Water Management
Objective Field:Land and Water Management of environments not elsewhere classified
Author:Das, A (Dr Aruneema Das)
Author:Aryal, J (Dr Jagannath Aryal)
ID Code:88525
Year Published:2013
Deposited By:Geography and Environmental Studies
Deposited On:2014-02-05
Last Modified:2014-12-11
Downloads:0

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