Title: AI In Agriculture Using UAV to Detect Weeds


Karanpreet Verma

ASET, AMITY University, Noida, Uttar Pradesh (INDIA)


To keep track of agronomic and environmental variables, UAV’s have displayed a tremendous  capabilities by capturing pictures at High spatial resolution. Ground-control-points (GCPs) must have to obtain to make sure the precision of the mosaicking process. This study was put through into wheat field naturally overspread by grass leaves and big-leaved at large initial phenological level. UAV flying at altitudes of 30 to 100 m and using a large number of GCPs (15 to 60) , ultra-high spatial resolution ortho-images is able to give rise to ultra- high spatial resolution ortho-images can be generated with the geo-referencing precision necessary to map small weeds in the field of wheat at very initial phenological stage. 1 acre field was divided into 4 sub-fields equally, 15 GCP's of different colour configurations were placed in each 4 sub fields providing a precise percentage of weeds in each sub fields detected using UAV. The outcome of the weed detection would give out the exact usage of the pesticide as per the weed detected (%) in each 4-sub field rather than, spraying the pesticide on the whole entire field.