International Journal Of Imaging

Abstract

AI-Based Monitoring of Swiftlet Nests: ClassifyingShapes for Enhancing Farming Practices

Author: Bandi Blessy, Puppala Tejashwi , Nandyala Rajesh , Mr. K Rajeshwar.

Abstract:

Swiftlet farming, a cornerstone of the edible bird nest industry, holds significant economic importance, particularly in Southeast Asia. The nests, crafted from the saliva of swiftlets, are highly valued for their nutritional and medicinal properties. Traditional methods of monitoring swiftlet nests are labor-intensive, prone to human error, and lack the precision needed for optimizing yield and quality. Despite advances in farming techniques, challenges such as inconsistent nest shapes, improper environmental conditions, and the inability to detect anomalies early have limited the industry's potential.AI-based monitoring systems offer a transformative approach to addressing these issues. By integrating machine learning and image processing techniques, the systems classify nest shapes, track growth stages, and identify abnormalities that indicate environmental or health concerns. The study introduces an AI-driven framework for swiftlet nest monitoring, aiming to overcome t