His groundbreaking work focuses on the transformation of the egg industry through the integration of advanced technologies. By utilizing non-destructive optical sensing, IoT, AI, big data, and cloud computing, he aims to develop smart systems for egg production, quality inspection, and grading. His research highlights the potential of these innovations to enhance automation, biosecurity, and animal welfare. A significant part of his work involves applying various CNN and transfer learning models for nondestructive chicken egg fertility detection, demonstrating their high accuracy and potential for industry-wide implementation
1. Ahmed, M. W., Hossainy, S. J., Khaliduzzaman, A., Emmert, J. L., & Kamruzzaman, M. (2023). Non-destructive optical sensing technologies for advancing the egg industry toward industry 4.0: A review. Comprehensive Reviews in Food Science and Food Safety, 22, 4378–4403. Link to DOI