Unmanned Aerial Vehicle Direct Seeding Versus Ground Seeding Mechanization Services in Smallholder Farming Systems of North West IGP on Energy Use Efficiency and Quality of Rice Culture: A Review

Abstract

Various sectors use AI technologies to increase output and productivity. AI in agriculture also enables farmers to boost productivity while minimizing harmful environmental effects. AI is transforming the food-processing industry, where agricultural emissions have dropped by 20%. Mechanization is once again one of the top development policy targets for changing the smallholder agricultural system in the north west IGP. To support public investment or company development programs, however, previous and ongoing efforts frequently suffer from a lack of scientific data on end-user effective demand for various sorts of mechanical improvements. Rice production involves intricate agronomic procedures. Seeding, fertilizing, and pesticide application are labour- and time-intensive tasks that have low automation efficiency. Currently, a lot of research focuses on the single UAV operation on rice, but there aren't many applications that cover the entire process of sowing, fertilizing, and applying pesticides. Based on the intelligent operating platform, a mUAV was created to oversee the planting of rice. This aircraft accomplished three tasks on the same flight platform: seeding, fertilizer application, and pesticide application. Machine design was carried out using simulations of CFD. The cultivation patterns of mechanical rice direct seeder, mechanical rice transplanter, and mUAV seeding were compared to perform a comparative evaluation of the entire process. With improved rice automation, fewer labour inputs, and lower costs, it is intended that this evaluation will offer new machinery for rice farming patterns in various conditions.