Implementation of Digital Image Processing for Rice Field Harvest Time and Area Size Estimation using Images Taken from Autonomous Aerial Harvest Surveillance - Wijayanto, Inung; Nurjannah, Wijayanto; Fathurrohim Nur, Nurjannah (International Journal of Engineering and Technology, 2019)
Problem faced by Indonesian farmers is the low price of the unhulled rice which happened when several region has the same harvest time. Indonesian Ministry of Agriculture encourage the farmers to do crop diversification to keep the crop price high. In order to support this policy, we provide estimation data so that local departement under the Ministry of Agriculture can give advice to farmers in their area to choose the right crops to plant. By using an Autonomous Aerial Harvest Surveillance (AAHS), we take images of rice fields to estimate the harvest time. The AAHS also provide global positioning system data while flying through its waypoint mission. These data are sent directly to the ground station (GS). By analyzing the RGB color space, and classification using backpropagation neural network, we have the average accuracy for harvest time estimation on real time flight testing is 82,73%, while the average accuracy for area size estimation is 73,92 %. Based on the feedback we received from local agriculture department, the accuration result is enough to help them forecasting the harvest result in their area.Â