The idea of the project was the usage of artificial intelligence on vehicles being self-driven and able to correctly identify traffic obstacles in real-time so that they are helpful in preventing accidents. These vehicles have sensors such as cameras that are commonly used to help autonomous cars track and monitor their surroundings. However, in low visibility conditions such as snow, rain, or fog, these sensors have difficulty reading or detecting signs, pedestrians, or other vehicles, especially in Africa and the Middle East, fogs and sandstorms pose severe limitations for cameras and sensors as these situations reduce visibility and affect driver safety. Therefore, in this project, the graduates used modern deep-learning algorithms to improve the image under these conditions. The project ended up successfully detecting more objects in the enhanced image than in the low-visibility image.

This project was under the supervision of Prof. Dr. Ahmed Diaa from the Faculty of Engineering, Electronics and Communications Department and Dr. Ibrahim Sabah from Valeo Company.

This victory comes as a culmination of the efforts of the Faculty of Engineering to link students to the labor market through constructive cooperation with major companies. The cooperation protocol signed with Valeo helped the students in many fields including providing training for students, introducing joint curricula to serve the labor market, as well as supervising their graduation projects.