Portfolio

Project Overview

FERapp (Facial Expression Recognition Application) was an innovative, enriching-with-technology collaborative graduation project undertaken by four enthusiastic students. My major contribution was in the back-end development using Python and Flask, making the system robust and efficient. The project showed that we could work as an integrated team and deliver quality, for which we received an outstanding grade from the Graduation Projects Committee: A+. This recognition reflects the technical excellence of the project and its potential for real-world applications.

The project aims to develop a facial recognition and analysis system to measure customer satisfaction in various environments, including retail stores, restaurants, service centers, and during Hajj and Umrah. The system will analyze facial expressions captured through video or images to determine customers’ emotional states. In specific scenarios, such as (neutral, happy, sad, angry…), the system will alert the monitoring center if negative emotions are detected, allowing organizers to respond appropriately. By providing stakeholders with accurate and real-time insights into customers’ emotions, the proposed system aims to enable them to make informed decisions, improve service delivery, and enhance the overall customer experience.