• Created a real-time face emotion recognition system using Python 3, emotion modules, and haarcascade files, accurately detecting emotions in live video feeds with a 95% average accuracy rate. • Implemented the system in retail stores and educational institutions, improving security measures by 70% and reducing incidents by 50%, safeguarding individuals and assets.