Design and development of a Wearable Assistive device for Individuals with Vision Loss / (Record no. 614788)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02297nam a22001577a 4500 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 610 |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Mashal, Abdul Hameed |
| 245 ## - TITLE STATEMENT | |
| Title | Design and development of a Wearable Assistive device for Individuals with Vision Loss / |
| Statement of responsibility, etc. | Abdul Hameed Mashal |
| 264 ## - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Place of production, publication, distribution, manufacture | Islamabad : |
| Name of producer, publisher, distributor, manufacturer | SMME- NUST; |
| Date of production, publication, distribution, manufacture, or copyright notice | 2025. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 75p. |
| Other physical details | Soft Copy |
| Dimensions | 30cm |
| 500 ## - GENERAL NOTE | |
| General note | This thesis presents the design and implementation of an intelligent, multi-functional visual<br/>aid on a low-cost embedded platform to help visually impaired people become more aware<br/>of their surroundings and more independent. A lot of the time, traditional assistance devices<br/>are too expensive, don't do enough, or take up too much computing power. To overcome<br/>these constraints, this study creates a portable system utilizing a Raspberry Pi 5 and a<br/>conventional camera module, proficient in executing four essential functions in real-time:<br/>object detection, facial recognition, monocular depth-based obstacle avoidance, and<br/>currency identification.<br/>The core innovation of this work is a computationally efficient, two-stage processing<br/>pipeline. The lightweight primary object detector YOLOv8 initially looks at the scene to<br/>give it some general context. Based on this first analysis, the system smartly sends out<br/>specialised secondary models only when they are needed. For example, it might turn on a<br/>facial recognition module when it sees a "person" or a MiDaS-based depth estimate model<br/>when a huge, nearby object could be an obstacle. This context-aware method cuts down on<br/>the amount of processing power needed by a lot, making it possible for edge hardware to<br/>work in real time.<br/>The system gives the user clear audio announcements through a text-to-speech engine that<br/>are easy to understand and act on. The final implementation shows that a modular,<br/>intelligently layered AI architecture can provide a flexible, high-performance, and lowcost assistive solution that effectively connects complex computer vision capabilities with<br/>practical, real-world use for people who are blind or have low vision. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | MS Biomedical Engineering (BME) |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Supervisor : Dr. Muhammad Nabeel Anwar |
| 856 ## - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | <a href="http://10.250.8.41:8080/xmlui/handle/123456789/54816">http://10.250.8.41:8080/xmlui/handle/123456789/54816</a> |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | |
| Koha item type | Thesis |
| Withdrawn status | Permanent Location | Current Location | Shelving location | Date acquired | Full call number | Barcode | Koha item type |
|---|---|---|---|---|---|---|---|
| School of Mechanical & Manufacturing Engineering (SMME) | School of Mechanical & Manufacturing Engineering (SMME) | E-Books | 09/23/2025 | 610 | SMME-TH-1163 | Thesis |