Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/13375
Title: Surviving the data deluge: geostatistical and signal processing methodologies for smart farm sensor networks
Contributor(s): Falzon, Gregory  (author)orcid ; Henry, David  (author); Taylor, Kerry (author); Lefort, Laurent (author); Gaire, Raj (author); Wark, Tim (author); Schneider, Derek  (author)orcid ; Trotter, Mark  (author); Murphy, Aron  (author); Lamb, David  (author)
Publication Date: 2013
Handle Link: https://hdl.handle.net/1959.11/13375
Abstract: There is a trend towards the deployment of more and more soil, plant, animal, asset, and machinery performance sensors on the farm. More sensors mean more data, especially if it is generated in live streams and it remains a significant challenge for it to be distilled to a manageable size and rendered in a useable form. Seemingly simple and intuitive 'front-ends' require specialised and complex algorithms and software working behind the scenes. The SMART FARM sensor network is an example of a future farm technology which can generate very large data sets. This network monitors meteorological and soil conditions over an area of approximately 500 acres. There are 100 nodes equipped with multiple sensors all transmitting data back to a central server at 5 minute intervals, 24 hours a day, 7 days a week. In this paper we will survey the range of statistical and computing tools being developed by the SMART FARM team to render this information rich data field into management-relevant information including visualisation, detection and understanding of trends, and generating critical state alarms.
Publication Type: Conference Publication
Conference Details: Digital Rural Futures Conference 2013: Inaugural Digital Rural Futures Conference, Armidale, Australia, 26th - 28th June, 2013
Source of Publication: Proceedings of the Digital Rural Futures Conference, p. 41-41
Publisher: University of New England
Place of Publication: Armidale, Australia
Fields of Research (FoR) 2008: 090609 Signal Processing
070104 Agricultural Spatial Analysis and Modelling
010401 Applied Statistics
Fields of Research (FoR) 2020: 400607 Signal processing
300206 Agricultural spatial analysis and modelling
490501 Applied statistics
Socio-Economic Objective (SEO) 2008: 830401 Browse Crops
961402 Farmland, Arable Cropland and Permanent Cropland Soils
830406 Sown Pastures (excl. Lucerne)
Socio-Economic Objective (SEO) 2020: 100501 Browse crops
180605 Soils
100505 Sown pastures (excl. lucerne)
HERDC Category Description: E3 Extract of Scholarly Conference Publication
Publisher/associated links: http://www.une.edu.au/smart/
Appears in Collections:Conference Publication
School of Science and Technology

Files in This Item:
3 files
File Description SizeFormat 
Show full item record

Page view(s)

1,778
checked on May 26, 2024
Google Media

Google ScholarTM

Check


Items in Research UNE are protected by copyright, with all rights reserved, unless otherwise indicated.