Affiliation:
1. Global Academy of Technology, Bangalore, Karnataka, India
Abstract
The sericulture industry in India, plays a vital role in the economy, with silk production contributing significantly to the country's textile sector. However, the industry faces challenges due to the detrimental impact of diseases on silk production. To address this issue, this project proposes a comprehensive monitoring system that integrates sensors for temperature, humidity, and light levels, alongside machine learning algorithms for the early detection of common silkworm diseases such as pebrine, flacherie, etc. By ensuring optimal rearing conditions and proactively managing disease outbreaks, the model aims to minimize production losses and enhance silk yield. Given the importance of silk in India's textile industry, increasing yield is crucial for meeting domestic demand, promoting exports, and bolstering economic growth. Through the adoption of advanced technologies and proactive disease management strategies, this project seeks to strengthen the sericulture sector and secure a sustainable future for silk production in India
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