Real Time Classification System of Black Soldier Fly Larva

Food waste presents a significant issue, contributing extensively to greenhouse gas emissions and climate change. When food waste decomposes in landfills, it generates methane, a greenhouse gas that is significantly derogation effective to the atmosphere than carbon dioxide. Additionally, the production, transportation, and disposal of food waste significantly contribute to global greenhouse gas emissions. This study explores an innovative approach to mitigate the environmental impact of food waste by using food scraps to create compost for animal feed, specifically utilizing the Black Soldier Fly Larva (BSFL). Accurate control of food quantity for various larval stages is essential, necessitating precise stage classification. This process is complex due to the larvae's similar and small color variations. In this paper, we introduce a mobile application designed to classify and detect the growth stages of BSFL, ranging from stage 1 to stage 4, which are high in protein and beneficial for animal feed, to stages 5 and 6, which are ideal for preparing pupae that can be used in skincare products. Our approach employs the YOLOv8 model for larval stage classification and detection, achieving an impressive mAP50-95 of 0.812, surpassing the performance of YOLOv7 (mAP50-95 of 0.781) and YOLOv5 (mAP50-95 of 0.789).