@inproceedings{das-etal-2025-drishti,
    title = "{DRISHTI}: Drug Recognition and Integrated System for Helping the visually Impaired with Tag-based Identification",
    author = "Das, Sajeeb  and
      Paul, Srijit  and
      Muhury, Ucchas  and
      Islam, Akib Jayed  and
      Barua, Dhruba Jyoti  and
      Salehin, Sultanus  and
      Datta, Prasun",
    editor = "Das, Sudhansu Bala  and
      Mishra, Pruthwik  and
      Singh, Alok  and
      Muhammad, Shamsuddeen Hassan  and
      Ekbal, Asif  and
      Das, Uday Kumar",
    booktitle = "Proceedings of the Workshop on Beyond English: Natural Language Processing for all Languages in an Era of Large Language Models",
    month = sep,
    year = "2025",
    address = "Varna, Bulgaria",
    publisher = "INCOMA Ltd., Shoumen, BULGARIA",
    url = "https://preview.aclanthology.org/corrections-2026-01/2025.globalnlp-1.17/",
    pages = "149--158",
    abstract = "DRISHTI is a novel RFID-vision integrated assistive medication-verification system that combines RFID contactless scanning, quantized AI-based vision processing, and adaptive audio feedback to provide comprehensive medication-safety assurance. The architecture integrates an MFRC522 RFID reader for rapid drug-container identification, a Raspberry Pi{--}mounted camera running a quantized Gemma3-4B vision model for prescription-document analysis, and a hierarchical validation engine employing confidence-weighted scoring across five critical safety dimensions. Operating entirely offline, the system processes compressed medication data through multi-criteria classification while preserving user privacy and eliminating cloud dependencies. In evaluations across 149 test scenarios, DRISHTI achieved 86.57{\%} overall accuracy and 100{\%} detection of safety-critical cases, including expired medications, dosage mismatches, and drug interactions. The system delivers sub-millisecond response times with real-time, urgency-differentiated audio feedback, offering a practical solution for enhancing independence and reducing healthcare risks for visually impaired individuals."
}