Vision AI Driven Multimodal Assistive System with Memory Recall For Visually Impaired

DOI

10.2991/978-94-6239-723-1_23How to use a DOI?

Keywords

Assistive Vision AI; Multimodal Emotion Recognition; AI-based Memory Recall; Cognitive Assistive Technology

Abstract

According to global health research more than 2.2 bilion people worldwide are affected by visually impairement or blindness, highlighting the growing need for intelligent assistive technology. Visually impaired individuals often struggle with perceiving their surroundings, recognizing people, and recalling experiences. Conventional aids like canes and voice devices lack context awareness and real-time support. This project introduces a Vision AI-based assistive system that leverages object detection, face recognition, emotion analysis, and memory recall. Using advanced AI, computer vision, and NLP technologies, the system provides real-time environment sensing, emotion interpretation, and interaction logging. A voice-based interface ensures easy communication and hands-free operation. By offering accurate recognition and memory support, the system enhances independence, safety, and social engagement, demonstrating the transformative potential of AI for visually impaired users.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Prachi Kawtikwar
AU  - Harsha Bhute
PY  - 2026
DA  - 2026/07/14
TI  - Vision AI Driven Multimodal Assistive System with Memory Recall For Visually Impaired
BT  - Proceedings of the International Conference on Responsible, Risk-aware, and Regulated AI (RRRAI 2026)
PB  - Atlantis Press
SP  - 247
EP  - 259
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6239-723-1_23
DO  - 10.2991/978-94-6239-723-1_23
ID  - Kawtikwar2026
ER  -