Ripeness Detection of Areca Nut Using AlexNet

Arecanut is a commercial crop widely cultivated in India, which ranks second in global arecanut production. Harvesting arecanuts at specific stages is crucial for optimal yield. Traditionally, two skilled workers are required: a professional tree climber to pluck the nuts and an examiner to check ripeness by peeling a few nuts with their teeth. This method is laborintensive, time-consuming, and potentially dangerous. In order to address these issues by using an AlexNet-based machine learning model to accurately predict nut ripeness, thus reducing losses. The system, comprising a webcam, Raspberry Pi, and cutter unit, captures images of arecanut bunches. Features like color, shape, size, and texture are analyzed to classify nuts as ripened, intermediate, or unripened. If the nuts are ripe, a buzzer alerts the user to cut the bunch using a remote-controlled cutter unit.