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Artificial Intelligence and Digitalization for Sustainable Development. 10th EAI International Conference, ICAST 2022, Bahir Dar, Ethiopia, November 4-6, 2022, Proceedings

Research Article

Assistive Smart Cane Technology for Visually Impaired Peoples: A Review

Cite
BibTeX Plain Text
  • @INPROCEEDINGS{10.1007/978-3-031-28725-1_12,
        author={Getnet Ayele Kebede and Yosef Kassa Shiferaw},
        title={Assistive Smart Cane Technology for Visually Impaired Peoples: A Review},
        proceedings={Artificial Intelligence and Digitalization for Sustainable Development. 10th EAI International Conference, ICAST 2022, Bahir Dar, Ethiopia, November 4-6, 2022, Proceedings},
        proceedings_a={ICAST},
        year={2023},
        month={3},
        keywords={Smart cane Cane ergonomics Deep learning Location tracking Feed-back system Visually impaired},
        doi={10.1007/978-3-031-28725-1_12}
    }
    
  • Getnet Ayele Kebede
    Yosef Kassa Shiferaw
    Year: 2023
    Assistive Smart Cane Technology for Visually Impaired Peoples: A Review
    ICAST
    Springer
    DOI: 10.1007/978-3-031-28725-1_12
Getnet Ayele Kebede1,*, Yosef Kassa Shiferaw1
  • 1: Faculty of Mechanical and Industrial Engineering, Department of Automotive and Electro Mechanical Engineering, Bahir Dar University
*Contact email: beget13@gmail.com

Abstract

Smart cane technology is an assistive technology that allows visually impaired people to walk more freely and independently. This study reviewed various researchers’ works on cane development methodologies. This review’s goal is to determine the full cane configuration of hardware parts, software architecture, and cane structure. We discussed object detection methods, object identification methods, flame detection methods, water detection methods, and location tracking methods. Recently, many researchers have focused on the key development of a smart cane using a computer vision system with Python and Yolo V5 deep learning algorithms to identify objects or obstacles in cane users’ paths. The hardware part is used to connect sensors to the Raspberry Pi module, which is mostly used as a controller. The ergonomics of cane structure are cane tip and handle shape, which is the key future of cane design. Finally, this study concludes that the most effective methods and materials for making and improving smart cane are described.

Keywords
Smart cane Cane ergonomics Deep learning Location tracking Feed-back system Visually impaired
Published
2023-03-19
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-031-28725-1_12
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