Development of an AI-Integrated Smart Sericulture System for Climate- resilient Silk Production in India

Dhanapriya M *

Birla Institute of Technology (BIT), Mesra, Ranchi, Jharkhand – 835215, India.

*Author to whom correspondence should be addressed.


Abstract

Sericulture is a key agro-based rural industry in India, contributing significantly towards employment generation and socioeconomic progress, particularly in backward and tribal regions. But problems such as outbreaks of pests and diseases, fluctuations in the market environment, weather unpredictability, and inefficient utilization of resources are threatening the industry increasingly. A framework for strategy in developing an AI-enabled smart sericulture system to enhance sustainability, productivity, and climate resilience of silk production is offered in this paper. Emerging technologies such as artificial intelligence (AI), machine learning (ML), deep learning (DL), the internet of things (IoT), and drone-based systems are all incorporated into the proposed model to monitor, predict, and optimize every stage of the sericulture process. Adaptive raising schedules decision-support technologies, disease and pest forecasting algorithms, image processing for cocoon quality assessment, and real-time environmental monitoring within rearing buildings are key aspects. Farmers are provided with direct access to localized knowledge and recommendations through the utilization of digital advisory tools and smartphone applications. Central Silk Board (CSB) pilot project case studies in Karnataka and Assam depict the beneficial benefits of insightful interventions on yield growth, disease management, and efficient post-harvesting. The policy recommendations heavily focus on the necessity of public-private collaborations, capacity- building programs, harmonization of AgriStack and Digital India, and economic support in terms of insurance policies and subsidies. By leveraging digital innovation, the smart sericulture model presents an innovative solution to transform India's silk industry, reduce climate stress exposure vulnerabilities, and support inclusive rural growth. The research concludes that India could emerge as a global leader in sustainable and intelligent silk production if the right balance of technology, governmental support, and mass participation is established.

Keywords: Sericulture, artificial intelligence (AI), machine learning (ML), drone-based systems, smart agriculture, climate resilience, digital advisory tools


How to Cite

M, Dhanapriya. 2025. “Development of an AI-Integrated Smart Sericulture System for Climate- Resilient Silk Production in India”. Asian Journal of Environment & Ecology 24 (6):141-58. https://doi.org/10.9734/ajee/2025/v24i6732.

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