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Mobile application based sustainable irrigation water usage decision support system: an intelligent sensor CLOUD approach
conference contribution
posted on 2023-05-23, 08:15 authored by Li, C, Dutta, R, Kloppers, C, D'Este, C, Morshed, A, Almeida, A, Das, A, Jagannath AryalIn 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.
History
Publication title
IEEE SENSORS 2013 ProceedingsEditors
R Trew, E BrownPagination
1565-1568ISBN
978-1-4673-4642-9Department/School
Tasmanian School of MedicinePublisher
Institute of Electrical and Electronics EngineersPlace of publication
USAEvent title
IEEE Sensors 2013Event Venue
Baltimore, USADate of Event (Start Date)
2013-11-03Date of Event (End Date)
2013-11-06Rights statement
Copyright 2013 IEEERepository Status
- Restricted