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An Enhanced Transportation System for People of Determination
Uma Perumal1, Fathe Jeribi1, Mohammed Hameed Alhameed1
1College of Engineering and Computer Science, Jazan University, Jazan 45142, Saudi Arabia.
Sensors (Basel, Switzerland)
|October 16, 2024
Summary
This study introduces a novel guidance system to help visually impaired persons (VIPs) identify their correct bus. The system uses advanced AI models to accurately detect buses and their destinations, improving public transport accessibility.
Area of Science:
- Computer Science
- Artificial Intelligence
- Human-Computer Interaction
Background:
- Visually impaired persons (VIPs) face significant challenges in navigating public transportation, particularly in identifying correct buses and bus bays.
- Existing literature lacks analysis of bus bay identification for VIPs, highlighting a critical gap in accessible transit solutions.
Purpose of the Study:
- To develop and evaluate an AI-powered guidance system that assists visually impaired persons (VIPs) in identifying their designated bus and bus bay.
- To enhance the independence and accessibility of public transportation for visually impaired individuals.
Main Methods:
- Speech data processing and text conversion for destination input.
- Utilizing Arctan Gradient-activated Recurrent Neural Network (ArcGRNN) with GPS for bay detection.
- Employing Experienced Perturbed Bacteria Foraging Triangular Optimization Algorithm (EPBFTOA) for optimal bay selection.
- Bus identification via You Only Look Once (YOLO) models and text extraction using Sub-pixel Shuffling Convoluted Encoder-ArcGRNN Decoder (SSCEAD).
- Decision-making based on Multi-characteristic Non-linear S-Curve-Fuzzy Rule (MNC-FR) for accurate bus stop notification.
Main Results:
- The proposed system successfully identified the optimal bus bay and facilitated bus destination recognition.
- Achieved efficient processing times for bay selection (247,891 ms) and fuzzification (34,197 ms).
- Demonstrated superior performance compared to existing methods in guiding visually impaired passengers.
Conclusions:
- The developed guidance system significantly improves bus identification and accessibility for visually impaired persons.
- The integration of multiple AI models provides a robust and effective solution for public transport navigation challenges faced by VIPs.
- This research contributes to creating more inclusive and accessible transportation systems through technological innovation.
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