This thesis presents a real-time skin assessment system with the main aim of detecting inflammatory acne lesions and tracking skin conditions. A facial acne lesion detection algorithm was developed, using a pre-trained YOLOv8 model for lesion detection and a Mediapipe detector for face detection. The proposed solution aims to create a system used in smart mirrors to help users self-monitor and monitor their skin condition in real time without much involvement. The work shows that it is possible to effectively detect skin changes even in a motion situation, which could be a good direction for the development of solutions based on video analytics.