Lida Song, Canada

DistraXcel represents an innovative AI-powered system designed to enhance productivity by using computer vision and machine learning to mitigate distractions from digital applications and websites [1]. The internet, a "giant hypodermic" filled with distracting "psychoactive drugs," significantly impedes focus, especially for individuals with neurodevelopmental disorders, such as ADHD and autism [2]. DistraXcel addresses this problem by identifying and blocking distracting digital content, leveraging Python and Tkinter for the front-end, Firebase for back-end operations, and Roboflow for building an object detection and classification model. However, challenges such as auto-login hassles, AI's specificity to certain screens leading to false negatives, and cross-platform GUI inconsistencies were encountered [3]. Through methodical experiments, the AI demonstrated strong identification capabilities but also revealed an overfitting issue. A user perception survey highlighted an improvement in perceived productivity post-use, indicating DistraXcel's effectiveness while suggesting room for addressing broader distraction factors. DistraXcel advances beyond current methodologies by offering a more positive feedback mechanism, extensive customization, and prioritizing privacy [4]. It evolves as a user-centric tool aimed at fostering a focused and productive digital environment, providing considerable aid to students and workers alike, especially those with neurodevelopmental disorders. DistraXcel marks a significant step forward in addressing the pervasive issue of digital distractions.

Focus Assistance, Computer Vision, Machine Learning, Python