Abstract

Abstract In a Modern era, growth in population has led to increase the many related issues. One of the issue is agriculture related causes. Farmers worldwide have ambiguous and varied opinions, perspectives on integrating technology into agricultural activities. Some of them are enthusiastic and all focused towards accepting the technology, others are wary and bemused towards introducing modern technologies, while most of them are cautious while hard towards the usage of technologies to increase yields and boost returns. A model focused on AI & ML would identify farmers into tiny, medium and high groups based on their adaptability and tolerance to technology use. Sitting on top of that will be a recommendation sengine operated by Deep Learning Network that indicates a farmer's escalation from the lower to the higher tier viz. small to medium in length. The guidelines will be cost-effective and suggest optimum acceleration by negligible changes in teaching, organizational adjustments and capital creation through a new contract, sharing in a UBERized model. Herein, a pilot has already been completed on 500 + farmers in India to gather data, categorizing them manually into tiny, medium and big categories. The suggested plan would have tremendous socio-economic effects on the farmers' lives, coupled with significant environmental protection benefits. After the analysis of the data, a smart information system has been created which is specific for the demand of the famers. From this they can get various information’s and can fulfill their needs. This kind of support system will helpful for the growth of the famers. The farmers would be able to improve their agricultural practices through smart e-marketplace derived from crowds.

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