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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Issue: March 2026
Volume 11 | Issue 3
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 118
Article Submitted : 21574
Article Published : 8528
Total Authors : 22430
Total Reviewer : 805
Total Countries : 159
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Published Paper Details
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| Paper Title: | AI-Powered Blind Assistance System |
| Authors Name: | Manish Yadav , Sowmya M , Aarabhi M V , Anvitha H A , Mohan Kumar K J |
| Download E-Certificate: | Download |
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IJRTI_207202
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| Published Paper Id: | IJRTI2511016 |
| Published In: | Volume 10 Issue 11, November-2025 |
| DOI: | |
| Abstract: | Abstract: The AI-Powered Blind Assistance System is a real-time, intelligent tool that helps people with vision impairments navigate their environment more freely and safely. The system combines the power of Artificial Intelligence, Computer Vision, and IoT to detect and recognize objects while also identifying nearby obstacles. It uses a webcam to continuously capture the visual environment, and a lightweight TensorFlow Lite model deployed on a Raspberry Pi processes this data to perform real-time object detection and classification. In addition to visual analysis, the system incorporates an ultrasonic sensor to measure the distance to nearby objects and obstacles. Based on the proximity data, it provides haptic feedback (vibrations) to alert the user about immediate physical hazards. Simultaneously, audio feedback is delivered via earphones to communicate the names of detected objects, allowing the user to make informed decisions about their movement. This dual-feedback mechanism enhances spatial awareness and improves safety in both indoor and outdoor environments. Unlike traditional white canes or passive aids, this system actively analyses the surroundings using AI, offering a smarter and more intuitive experience. Through improved perception of their surroundings, the project seeks to empower visually challenged people and promote safer, more self-assured, and more independent mobility. |
| Keywords: | Keywords: AI, Blind Assistance, Computer Vision, IoT, Raspberry Pi, Object Detection, Assistive Technology |
| Cite Article: | " AI-Powered Blind Assistance System", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 11, page no.a116-a121, November-2025, Available :http://www.ijrti.org/papers/IJRTI2511016.pdf |
| Downloads: | 000237 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2511016
Registration ID:207202
Published In: Volume 10 Issue 11, November-2025
DOI (Digital Object Identifier):
Page No: a116-a121 Country: Mysuru, Karnataka, India Research Area: Electronics & Communication Engg. Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2511016 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2511016 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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