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Integration of RESTful Services in Agro Advisory System

  • Mahesh TitiyaEmail author
  • Vipul Shah
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 955)

Abstract

There is a large amount of data related to agricultural practices being collected via different sources but it is not being u sed for maximum benefit for the farmers due to lack of mediums for the information to flow and other factors like language differences, lack of technology to access that information etc. Information Communication Technology (ICT) can helps to bridge that gap by creating systems that are easier to access and are able to answer the basic questions for the farmers which helps the farmers to increase the production of the crop. Such a system should make use of all the data sources available and provide processed information that makes sense to the user. We have developed ontology based Agro-Advisory System to fulfill these requirements. It is acknowledged based system. The knowledge base is maintained in the form of ontology. Ontology contains cotton crop knowledge. Ontology is integrated with RESTful web services to develop our system. Farmers can ask their queries related to cotton crop cultivation by Android mobile and get recommendations on their mobile which improves cotton crop productivity. The system is also able to send notification and alert to farmers if any adverse change in weather condition.

Keywords

RESTful services Ontology Semantic web Recommended system RESTful architecture 

References

  1. 1.
    Hendler, J., Berners-Lee, T., Lassila, O.: The Semantic Web. Scientific American, New York City (2001)Google Scholar
  2. 2.
    XML: Extensible markup language. http://www.w3.org/XML/
  3. 3.
    Rdf: Resource description framework. http://www.w3.org/RDF/
  4. 4.
    Stephan, G., Pascal, H., Andreas, A.: Knowledge Representation and Ontologies. In: Studer, R., Grimm, S., Abecker, A. (eds.) Semantic Web Services, pp. 51–105. Springer, Heidelberg (2007).  https://doi.org/10.1007/3-540-70894-4_3CrossRefGoogle Scholar
  5. 5.
    Owl: Web ontology language. http://www.w3.org/2001/sw/wiki/OWL
  6. 6.
    Noy, N.F., McGuinness, D.L.: Ontology development 101: a guide to creating your first ontology. Stanford Knowledge Systems Laboratory, 25 2001Google Scholar
  7. 7.
    Laliwala, Z., Sorathia, V., Chaudhary, S.: Semantic and rule based event-driven services-oriented agricultural recommendation system. In: 26th IEEE International Conference on Distributed Computing Systems Workshops (ICDCSW06), pp. 24–30, July 2006Google Scholar
  8. 8.
    Noy, N.F.: Tools for mapping and merging ontologies. In: Staab, S., Studer, R. (eds.) Handbook on Ontologies. International Handbooks on Information Systems, pp. 365–384. Springer, Heidelberg (2004).  https://doi.org/10.1007/978-3-540-24750-0_18CrossRefGoogle Scholar
  9. 9.
    Koutu, G.K., Shastry, P.P., Mishra, D.K., Mandloi, K.C.: Handbook of Cotton, 1st edn. Studium Press (India) Pvt. Ltd., Delhi (2012)Google Scholar
  10. 10.
    Bhalotia, G., Hulgeri, A., Nakhe, C., Chakrabarti, S., Sudarshan, S.: Keyword searching and browsing in databases using BANKS. In: Proceedings - International Conference on Data Engineering, pp. 431–440 (2002)Google Scholar
  11. 11.
    S. Exchange and R. Development, eSagu : An IT- based personalized agroadvisory system for augmenting livelihoods of farmers, December 2006Google Scholar
  12. 12.
    Ramamritham, K., Bahuman, A., Duttagupta, S.: aAqua: a database-backended multilingual, multimedia community forum. In: Proceedings of the 2006 ACM SIGMOD International Conference on Management of Data, Ser. SIGMOD 06, pp. 784–786 (2006)Google Scholar
  13. 13.
    Shinde, S., Piplani, D., Srinivasan, K., Singh, D., Sharma, R., Mohnaty, P.: mKRISHI: simplification of IVR based services for rural community. In: Proceedings of the India HCI 2014 Conference on Human Computer Interaction, Ser. IndiaHCI 14, pp. 154–159 (2014)Google Scholar
  14. 14.
    G.K. Centre: AGRISNET - Information Network for Farmers, no. 3, March 2011Google Scholar
  15. 15.
    Roy, M., Ghosh, C.K.: The benefits of the e-learning agricultural project Kissankerala to digital immigrants and digital natives. Turk. Online J. Distance Educ. 14(2), 150–164 (2013)Google Scholar
  16. 16.
    Agropedia: A free and open source java framework for building semantic web and linked data applications. http://agropedia.iitk.ac.in
  17. 17.
    M. sabesh cicr: approved package of practices for cotton. http://www.cicr.org.in/pop/gj.pdf
  18. 18.
    Mehta, S.C., Agrawal, R., Kumar, A.: Forewarning crop pests and diseases: IASRI methodologies, pp. 67–77, Iasri (2005)Google Scholar
  19. 19.
    Sparql protocol and query language for rdf. http://www.w3.org/TR/rdf-sparql-query
  20. 20.
    Le, S.: Semantic web holds promises for ocean observing needs, in Oceans (2008)Google Scholar
  21. 21.
    Horridge, M., Knublauch, H., Rector, A., Stevens, R., Wroe, C.: A practical guide to building OWL ontologies using the Protg-OWL Plugin and CO-ODE Tools, pp. 0–117, vol. 27. The University Of Manchester (2004)Google Scholar
  22. 22.
    Pappu, N., Sarkar, R., Prabhakar, T.V.: Agropedia: humanization of agricultural knowledge. IEEE Internet Comput. 14(5), 57–59 (2010)CrossRefGoogle Scholar
  23. 23.
    Bichindaritz, I.: Mmoire: a framework for semantic interoperability of casebased reasoning systems in biology and medicine. Artif. Intell. Med. 36(2), 177–192 (2006)CrossRefGoogle Scholar
  24. 24.
    Sini, M., Yadav, V., Prabhakar, T.V., Singh, J., Awasthi, V.: Knowledge models in agropedia indica (2008)Google Scholar
  25. 25.
    Rajasurya, S., Muralidharan, T., Devi, S., Swamynathan, S.: Semantic information retrieval using ontology in university domain. CoRR, vol.abs/1207.5745 (2012)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Government Engineering CollegeRajkotIndia
  2. 2.Dharmsinh Desai UniversityNadiadIndia

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