Precision Sericulture and Smart Technologies: Integrating IoT, AI and Automation for Silk Sustainability

Abstract

Precision sericulture represents a transformative shift in the silk industry, integrating digital innovations such as the Internet of Things (IoT), artificial intelligence (AI), robotics, and automation to modernize traditional practices. This review highlights the foundational principles, enabling technologies, and advanced innovations that define this emerging paradigm. Key applications include sensor-based environmental control, AI-enabled disease diagnostics, drone-assisted crop management, and blockchain-supported traceability systems. By improving resource use efficiency, minimizing human error, and enhancing productivity, these tools promote sustainable and climate-resilient silk production. Advanced materials such as nanotech-enhanced silk fibers and digital twin models further expand the industry's potential into high-value sectors like smart textiles and medical fabrics. Despite these advances, widespread adoption is hindered by challenges such as high initial costs, digital illiteracy, data fragmentation, and connectivity limitations. To overcome these barriers, inclusive strategies involving public–private partnerships, open-source technology, and localized training are essential. This paper also identifies research gaps in edge AI, biosensors, carbon accounting, and interoperability. Overall, precision sericulture offers a promising path toward inclusive rural development, climate adaptation, and global competitiveness in silk production.