Digital knowledge ecosystem for achieving sustainable agriculture production

a case study from Sri Lanka

Athula Ginige, Anusha I. Walisadeera, Tamara Ginige, Lasanthi De Silva, Pasquale Di Giovanni, Maneesh Mathai, Jeevani Goonetillake, Gihan Wikramanayake, Giuliana Vitiello, Monica Sebillo, Genoveffa Tortora, Deborah Richards, Ramesh Jain

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

14 Citations (Scopus)

Abstract

Crop production problems are common in Sri Lanka which severely effect rural farmers, agriculture sector and the country's economy as a whole. A deeper analysis revealed that the root cause was farmers and other stakeholders in the domain not receiving right information at the right time in the right format. Inspired by the rapid growth of mobile phone usage among farmers a mobile-based solution is sought to overcome this information gap. Farmers needed published information (quasi static) about crops, pests, diseases, land preparation, growing and harvesting methods and real-Time situational information (dynamic) such as current crop production and market prices. This situational information is also needed by agriculture department, agro-chemical companies, buyers and various government agencies to ensure food security through effective supply chain planning whilst minimising waste. We developed a notion of context specific actionable information which enables user to act with least amount of further processing. User centered agriculture ontology was developed to convert published quasi static information to actionable information. We adopted empowerment theory to create empowerment-oriented farming processes to motivate farmers to act on this information and aggregated the transaction data to generate situational information. This created a holistic information flow model for agriculture domain similar to energy flow in biological ecosystems. Consequently, the initial Mobile-based Information System evolved into a Digital Knowledge Ecosystem that can predict current production situation in near real enabling government agencies to dynamically adjust the incentives offered to farmers for growing different types of crops to achieve sustainable agriculture production through crop diversification.

Original languageEnglish
Title of host publicationDSAA 2016 : 3rd IEEE International Conference on Data Science and Advanced Analytics
Subtitle of host publicationproceedings
Place of PublicationPiscataway, N. J
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages602-611
Number of pages10
ISBN (Electronic)9781509052066
DOIs
Publication statusPublished - 22 Dec 2016
Event3rd IEEE International Conference on Data Science and Advanced Analytics, DSAA 2016 - Montreal, Canada
Duration: 17 Oct 201619 Oct 2016

Other

Other3rd IEEE International Conference on Data Science and Advanced Analytics, DSAA 2016
CountryCanada
CityMontreal
Period17/10/1619/10/16

Keywords

  • Digital Knowledge Ecosystem for Agriculture
  • Mobile-based Information System for Farmers
  • Sustainable Agriculture Production

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