Name
Abstract | ||
|---|---|---|
Visually impaired persons (VIPs) comprise a significant portion of the population and they are present in all corners of the world. In recent times, the technology proved its presence in every domain of life and innovative devices are assisting humans in all fields especially, artificial intelligence has dominated and outperformed the rest of the trades. VIPs need assistance in performing daily life tasks like object/obstacle detection and recognition, navigation, and mobility, particularly in indoor and outdoor environments. Moreover, the protection and safety of these people are of prime concern. Several devices and applications have been developed for the assistance of VIPs. Firstly, these devices take input from the surrounding environment through different sensors e.g. infrared radiation, ultrasonic, imagery sensor, etc. In the second stage, state of the art machine learning techniques process these signals and extract useful information. Finally, feedback is provided to the user through auditory and/or vibratory means. It is observed that most of the existing devices are constrained in their abilities. The paper presents a comprehensive comparative analysis of the state-of-the-art assistive devices for VIPs. These techniques are categorized based on their functionality and working principles. The main attributes, challenges, and limitations of these techniques have also been highlighted. Moreover, a score-based quantitative analysis of these devices is performed to highlight their feature enrichment capability for each category. It may help to select an appropriate device for a particular scenario. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/ACCESS.2022.3146728 | IEEE ACCESS |
Keywords | DocType | Volume |
Sensors, Assistive devices, Performance evaluation, Navigation, Vibrations, Real-time systems, Cameras, Assistive devices, wearable, IR sensor, ultrasonic sensor, laser scanner, visually impaired people, detection, recognition, navigation | Journal | 10 |
ISSN | Citations | PageRank |
2169-3536 | 0 | 0.34 |
References | Authors | |
0 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sadia Zafar | 1 | 0 | 0.68 |
| Muhammad Asif | 2 | 148 | 44.17 |
| Maaz Bin Ahmad | 3 | 0 | 0.34 |
| Taher M. Ghazal | 4 | 3 | 3.11 |
| Tauqeer Faiz | 5 | 0 | 0.34 |
| Munir Ahmad | 6 | 3 | 2.42 |
| Muhammad Adnan Khan | 7 | 9 | 8.71 |