Development of an intelligent environmental knowledge system for sustainable agricultural decision support
journal contribution
posted on 2023-05-17, 20:45authored byDutta, R, Morshed, A, Jagannath Aryal, D'Este, C, Das, A
The purpose of this research was to develop a knowledge recommendation architecture based on unsupervised machine learning and unified resource description framework (RDF) for integrated environmental sensory data sources. In developing this architecture, which is very useful for agricultural decision support systems, we considered web based large-scale dynamic data mining, contextual knowledge extraction, and integrated knowledge representation methods. Five different environmental data sources were considered to develop and test the proposed knowledge recommendation framework called Intelligent Environmental Knowledgebase (i-EKbase); including Bureau of Meteorology SILO, Australian Water Availability Project, Australian Soil Resource Information System, Australian National Cosmic Ray Soil Moisture Monitoring Facility, and NASA’s Moderate Resolution Imaging Spectroradiometer. Unsupervised clustering techniques based on Principal Component Analysis (PCA), Fuzzy-CMeans (FCM) and Self-organizing map (SOM) were used to create a 2D colour knowledge map representing the dynamics of the i-EKbase to provide “prior knowledge” about the integrated knowledgebase. Prior availability of recommendations from the knowledge base could potentially optimize the accessibility and usability issues related to big data sets and minimize the overall application costs. RDF representation has made i-EKbase flexible enough to publish and integrate on the Linked Open Data cloud. This newly developed system was evaluated as an expert agricultural decision support for sustainable water resource management case study in Australia at Tasmania with promising results.
History
Publication title
Environmental Modelling and Software
Volume
52
Pagination
264-272
ISSN
1364-8152
Department/School
School of Geography, Planning and Spatial Sciences
Publisher
Elsevier Sci Ltd
Place of publication
The Boulevard, Langford Lane, Kidlington, Oxford, England, Oxon, Ox5 1Gb