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The pandemic COVID-19 and associated challenges with implementation of artificial intelligence (AI) in Indian agriculture

Author

Listed:
  • Debesh Mishra

    (Gandhi Institute for Technology)

  • Biswajit Mohapatra

    (Odisha University of Technology and Research)

  • Abhaya Sanatan Satpathy

    (Sri Sri University)

  • Kamalakanta Muduli

    (Papua New Guinea University of Technology)

  • Binayak Mishra

    (Gandhi Engineering College)

  • Swagatika Mishra

    (VSSUT)

  • Upma Paliwal

    (Institute of Professional Education and Research)

Abstract

The ongoing pandemic coronavirus (COVID-19) outbreak has resulted a greater burden and loss to farmers in India in view of number of restrictions on movement as well as social interactions, during which scenario the “artificial intelligence (AI)” could act as a catalyst in accelerating their progress in agriculture. This paper provided an evaluation of application and benefits of AI in agriculture and the challenging parameters for implementing AI in Indian agricultural sectors against COVID-19 crisis period. A survey based data was collected from 523 farmers, and interpreted using Interpretive Structural Modelling (ISM) and MICMAC. The associated challenging parameters to implement AI were identified as “responsive time and accuracy levels; the absence of standardisation; a need for huge data; big data costs; method of implementation; versatility; insufficient awareness of context; and loss of employment;” respectively.

Suggested Citation

  • Debesh Mishra & Biswajit Mohapatra & Abhaya Sanatan Satpathy & Kamalakanta Muduli & Binayak Mishra & Swagatika Mishra & Upma Paliwal, 2024. "The pandemic COVID-19 and associated challenges with implementation of artificial intelligence (AI) in Indian agriculture," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 15(6), pages 2715-2729, June.
    • Handle: RePEc:spr:ijsaem:v:15:y:2024:i:6:d:10.1007_s13198-024-02293-z
    DOI: 10.1007/s13198-024-02293-z
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