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Type : Other Article

Constraint Analysis in Usage of Artificial Intelligence Application in Agricultural Production

Vikash , P.S. Shehrawat , Aditya and Babu Lal

Abstract

Artificial intelligence tools and techniques play an important role in enhancing agricultural production. Farmers need advance tools and techniques on every critical stage of crop cultivation. The present study was conducted at KVK of CCS-HAU located in different districts of Haryana. Further, a total of 150 respondents were interviewed personally at their respective places for the study. The present study revealed that constraints faced by agricultural professionals in using robots, costlier to implement considered most severe constraint and ranked first. In constraint in using weather forecast, availability of historical and real time data was considered most severe constraint and ranked first. In constraint related to policy, no supporting budget to buy equipment was considered most severe constraint and ranked first. In constraint related to accessibility of reliable information, accessibility problem in rural areas was considered most severe constraint and ranked first. In constraint related to cost, cost of using smart system was high was considered most severe constraint and ranked first. In constraint in ease of use and training, less knowledge of operating the equipment was considered most severe constraint and ranked first. In non-physical constraint in using Artificial Intelligence (AI) technique, inadequate information was considered most severe constraint and ranked first. In constraint in implementation of AI technique, untrained manpower was considered most severe constraint and ranked first. In constraint in using laser land leveller, high cost of the equipment cannot be maintained by small farmers was considered most severe constraint and ranked first. In socio-psychological constraints, low socio-economical condition was considered most severe constraint and ranked first.

Keyword: Artificial intelligence tools; Farmers; Constraints; Weighted mean score.

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