Deep Learning Based Robotic System for Sericulture

摘要

Cultivating silkworms to yield silk is a complex and old activity known as sericulture. Sericulture has an imperative role in building economies and developing trading routes, both historically and culturally. The business still thrives today by fusing old methods with cutting-edge technology to satisfy the demand for the priceless and opulent silk fabrics around the world. Currently, sericulture is developed using a traditional approach takes a great deal of effort and time. Mulberry leaves are grown and fed to silk worms. Many mulberry leaves and silkworms get numerous diseases and illnesses as outcome of these traditional practices. Because silkworms are susceptible to infection from tiny defects in mulberry bushes, farmers must take additional maintenance when growing the plants. One among the main issues is the increased variety of weeds in mulberry fields, which means that eradicating them from the fields needs huge labour. The suggested innovation signifies a revolutionary breakthrough in the sericulture area. The article presents a very creative, lightweight, and reasonably priced Agribot outfitted with a camera and computer system to identify pests and weeds on leaves. The potential of this system to transform mulberry leaf cutting and pest and weed identification is great since it leverages the capabilities of deep learning techniques.