Design of an Agentic-AI-Based Accessible Library Service for Persons with Disabilities
Issued Date
2025-01-01
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Scopus ID
2-s2.0-105040644825
Journal Title
6th Technology Innovation Management and Engineering Science International Conference Times Icon 2025 Proceedings
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SCOPUS
Bibliographic Citation
6th Technology Innovation Management and Engineering Science International Conference Times Icon 2025 Proceedings (2025)
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Tonnondaeng P., Maneechay P., Warinsiriruk E., Wang Y.T. Design of an Agentic-AI-Based Accessible Library Service for Persons with Disabilities. 6th Technology Innovation Management and Engineering Science International Conference Times Icon 2025 Proceedings (2025). doi:10.1109/TIMES-iCON67125.2025.11488108 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/117165
Title
Design of an Agentic-AI-Based Accessible Library Service for Persons with Disabilities
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Abstract
To address persistent barriers in information access for persons with visual impairments, this paper proposes a conceptual design of an Agentic-AI-enabled accessible library service model that supports more independent use of library resources. The system integrates two core components: an AI Agent that answers general library inquiries and book-location queries via natural-language voice interaction, and an Optical Character Recognition (OCR) based reading module that converts printed text into digital text and delivers it as synthesized speech. Orchestrated through automated workflow, these components form an autonomous, staff-independent service workflow that reduces reliance on human assistance. System performance was evaluated in two experimental modules: Module 1 assessed the AI Agent's ability to respond to typical librarian-user queries, and Module 2 evaluated the accuracy of searching for and identifying shelf locations of specific books, while the OCR module was tested on Thai text, English text, and mathematical expressions. The results showed 0 % residual error in reconstructing Thai and English descriptive text, whereas mathematical content remained challenging. Overall, the findings support the technical feasibility of the proposed model as a foundation for more inclusive, AIsupported library services for visually impaired users.