In collaboration with: Fish Research Center – Suez Canal university

Team Members:

NameGitHubLinkedInCVE-mailUniversity E-mail
Hussam EldinClick HereClick HereClick
Omar AnasClick HereClick HereClick
Youssef MohamedClick HereClick HereClick
Ali AhmedClick HereClick HereClick


Dr. Ayman EzzatClick
Dr. Ayman NabilClick
Eng. Noha

Project Description:

Fish Farms have become important in the modern life as they have a huge contribution to the economy and ensures a reliable supply and wide distribution of fish globally. Fish farming is a tedious process that requires a lot of labor work. Lack of monitoring leads to fish loss so, monitoring fish farms automatically would lower the risks of fish loss. Our project aims to automatically detect and alert fish farmers on any anomalies in the fish ponds like detection of fish abnormal behaviors and toxic ammonia levels in water which lower the risks of fish loss in fish farms and increase fish production.




Final Thesis:


  • MSR-YOLO: Method to Enhance Fish Detection and Tracking in Fish Farms. 
    • ANT 2020 (The 11th International Conference on Ambient Systems, Networks and Technologies).
    • Published
    • Publication URL: Click Here
  • Detecting Abnormal Fish Behavior Using Motion Trajectories. 
    • MobiSPC 2020 (The 17th International Conference on Mobile Systems and Pervasive Computing).
    • Published
  • Classification and Analysis of Fish Behavior Using Extracted Motion Features . 
    • IJCSysE (International Journal of Computational Systems Engineering).
  • YOLO Fish Detection with Euclidean Tracking in Fish Farms . 
    • JAIHC (Journal of Ambient Intelligence and Humanized Computing).