An Efficient Edge-Based System for Nucleated Oval-Shaped Red Blood Cell Counting

The integration of innovative technologies in animal healthcare has gained significance in recent years, aiming to enhance diagnostic capabilities across various species. In this work, we address a specific challenge within avian healthcare: the accurate counting of nucleated Red Blood Cells (RBCs). We propose a novel Cell Counter and Detector (CCD) algorithm, specifically designed for avian RBCs, which utilizes smartphones and optical microscopes for rapid and precise cell counting. Leveraging Multi-access Edge Computing (MEC) technology, the system ensures efficient data processing, privacy preservation, and ease of use through a user-friendly web interface. The results demonstrate that our method achieves an accuracy of 0.98, significantly outperforming existing approaches. Moreover, our system enables professionals to use the tools they already have without requiring expensive instruments. Our system leverages MEC to enable real-time processing and privacy-preserving data management, setting a new benchmark for avian blood diagnostics in terms of cost-effectiveness and accuracy. Beyond its immediate implications for avian healthcare, this research underscores the broader potential of technology in improving diagnostics for diverse animal species.