The aim of the current use case is to develop bunch of Artificial, machine and deep learning algorithms with highest smartness and can control a Robot for doing above tasks with accuracy of 95% or above.
Agricultural AI bots are harvesting crops at a higher volume and faster pace than human laborers, more accurately identifying and eliminating weeds, and reducing cost and risk. AI farmers present a permanent solution for the unpredictable and fluctuating agricultural workforce.
The crux of smart farming is using a blended workforce of digital help alongside traditional farmers and tools.
Traditionally, farms have needed many workers — mostly seasonal — to produce and harvest crops. However, fewer people are entering the farming profession due to the physical labor and high turnover rate of the job. Furthermore, most agricultural efforts use highly mobile migrant labor, which presents challenges for a stable and predictable workforce.
AI solves critical farm labor challenges by augmenting or removing work and reducing the need for large numbers of workers.
Low
AI- Neural Network, GIS Mapping
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