Key points are not available for this paper at this time.
Silk production in Bangladesh’s rural economy, which is the practice of raising silkworms, has long been an essential part of the country’s rural economy and this has contributed a lot to the national economy as well as improved people’s lives. Traditional sericulture however faces problems such as pest infestations, inconsistent yields of mulberry leaves, wasteful use of resources and effects of climatic change despite the country having favorable climate that supports silk farming and availability of a skilled labor force. These challenges can be addressed through recent technological innovations including artificial intelligence technology and drone surveillance for instance. Drones fitted with cameras combined with GPS have ability to control fully grown mulberry farms whereas artificial intelligence system analyze data on optimal resource management in terms of pests’ control among others. The objective is to establish how drones and AI can affect Bangladeshi sericulture farming field primarily in Jessore and Rajshahi – two most important sericulture areas in the country. For two crop cycles namely July-October 2022 and March-June 2023, research used drones along with TensorFlow for AI integration where it recorded aspects such as leaf yield, pest loads, input application rates among others. Technologies integrations had resulted to increased mulberry leaf yield by approximately 18% from 2500Kg/ha to 2950Kg/ha.
Oli Ahmed (Tue,) studied this question.