A Review of Silk Farming Automation Using Artificial Intelligence, Machine Learning, and Cloud-Based Solutions

A comprehensive literature review on the applications of Artificial Intelligence (AI) and machine learning (ML), integrated with cloud computing solutions in sericulture, has been presented in the paper. The silk industry has a small percentage of the global textile market (less than 0.2%), but its production base is spread over 60 countries in the world. In India alone, it provides employment to more than 9 million people and adds revenue to the country's economy. However, this industry faces a few challenges in its various production stages such as egg counting, disease detection, cocoon deformity detection, and optimum environment control which directly influence the quality and quantity of raw silk production. The conventional approach to address these challenges incurred huge labor costs. Hence, the introduction of automation in this industry is an urgent need, and the implementation of AI techniques can prove to be a game changer since AI has already revolutionized various sectors of agriculture and provided better solutions by assisting agriculturists in the improvement of production as well as management. The present study covers various important contributions where AI, ML, and cloud computing solutions were employed to encounter the challenges related to the silk industry.