Recent advancement of intelligent-systems in edible birds nest: A review from production to processing

Edible Bird Nest (EBN) constitutes a thriving industry in several Southeast Asian nations where its value chain encompasses several critical processes starting with nest harvesting to processing, and finally sales. However, a detailed review addressing EBN production from an intelligent system perspective is currently missing. Hence, this paper aims to document a comprehensive study of the various parts of the EBN value chain, where machine-intelligence has been incorporated into various solutions. We classified all the EBN processes into three primary segments: farming and production, quality control, and market analysis. In farming and production, two key areas emerge. First, there is process analysis which involves Failure Mode and Effect Analysis (FMEA) as well as profit, cost, and efficiency analysis, while swiftlet house monitoring pinpoints the optimal environment for swiftlets to flourish. On the other hand, works related to the second segment of quality control can be divided two primary approaches: image analysis which involves either auto-grading or automatic impurities inspection, and chemical analysis to ascertain the origin and authenticity of the EBN. The third and final domain of market analysis, covers both business strategy and customer behavior analysis. We have identified the integration of cutting-edge intelligent methods in each area while offering recommendations for future work. Our findings also unveiled intricate patterns, networks, relationships, and trends in the application of machine intelligence within the EBN value chain. These insights highlight many underexplored areas as well as several strategic aspects in this emerging industry.