EGGS EMBRYO EARLY DETECTION

For this project, I was assigned to develop a proof of concept (POC) mechanism and prototype a system to detect the presence or absence of embryos in eggs during the first few days after they are laid, emphasizing speed and accuracy.
My approach involved establishing a clear solving strategy, which focused on understanding and controlling the interfaces between multiple disciplines. I started by identifying the core challenges in biophysics, photography, image processing, and machine learning, then outlined how each field could contribute to the overall solution. By collaborating with multidisciplinary teams from lighting, optics, photography, image processing, and machine learning, I ensured each discipline worked harmoniously. This integrated approach led to a seamless system where the final prototype achieved a 100% success rate in detecting embryos with unprecedented speed and precision.