International Journal of Science, Engineering and TechnologyAuthors: K. Dhakshina, Jaya Nandhini S, Karthika B., Mr.P.T Prithivirajan
Abstract: Human memory is under increasing strain due to constant digital interaction, pervasive multitasking, and informa-tion overload. While conventional note-taking and productivity tools exist, they often necessitate significant active effort and structured input, which limits their practicality for everyday users and individuals facing attention-related challenges, such as Attention-Deficit/Hyperactivity Disorder (ADHD). This paper introduces LifeMemory, an AI-assisted personal memory sys-tem engineered to passively capture, intelligently organize, and contextually retrieve user memories through natural language interaction. The system facilitates the storage of thoughts, tasks, conversations, and decisions with minimal friction, enabling their recall precisely when needed. By leveraging advanced large lan-guage models and semantic memory structuring, LifeMemory functions as a cognitive extension rather than a conventional static note-taking application. The core design principles pri-oritize accessibility, emotional awareness, and cognitive load reduction. A functional web-based prototype was developed and rigorously evaluated for usability and recall effectiveness. Prelim-inary results demonstrate significant improvements in memory retrieval speed and a noticeable reduction in mental effort for both neurotypical users and those experiencing attention difficulties, highlighting its potential as a robust cognitive support tool.
DOI: http://doi.org/10.5281/zenodo.18052885
