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Image Recognition-Based Architecture to Enhance Inclusive Mobility of Visually Impaired People in Smart and Urban Environments

Author

Listed:
  • Sara Paiva

    (ADiT-LAB, Instituto Politécnico de Viana do Castelo, 4900-367 Viana do Castelo, Portugal)

  • António Amaral

    (Departmento de Engenharia Mecânica, ISEP Politécnico do Porto, 4249-015 Porto, Portugal
    INESC TEC—Institute for Systems and Computer Engineering, Technology and Science, 4200-465 Porto, Portugal)

  • Joana Gonçalves

    (ADiT-LAB, Instituto Politécnico de Viana do Castelo, 4900-367 Viana do Castelo, Portugal)

  • Rui Lima

    (ADiT-LAB, Instituto Politécnico de Viana do Castelo, 4900-367 Viana do Castelo, Portugal)

  • Luis Barreto

    (ADiT-LAB, Instituto Politécnico de Viana do Castelo, 4900-367 Viana do Castelo, Portugal)

Abstract

The demographic growth that we have witnessed in recent years, which is expected to increase in the years to come, raises emerging challenges worldwide regarding urban mobility, both in transport and pedestrian movement. The sustainable development of cities is also intrinsically linked to urban planning and mobility strategies. The tasks of navigation and orientation in cities are something that we resort to today with great frequency, especially in unknown cities and places. Current navigation solutions refer to the precision aspect as a big challenge, especially between buildings in city centers. In this paper, we focus on the segment of visually impaired people and how they can obtain information about where they are when, for some reason, they have lost their orientation. Of course, the challenges are different and much more challenging in this situation and with this population segment. GPS, a technique widely used for navigation in outdoor environments, does not have the precision we need or the most beneficial type of content because the information that a visually impaired person needs when lost is not the name of the street or the coordinates but a reference point. Therefore, this paper includes the proposal of a conceptual architecture for outdoor positioning of visually impaired people using the Landmark Positioning approach.

Suggested Citation

  • Sara Paiva & António Amaral & Joana Gonçalves & Rui Lima & Luis Barreto, 2022. "Image Recognition-Based Architecture to Enhance Inclusive Mobility of Visually Impaired People in Smart and Urban Environments," Sustainability, MDPI, vol. 14(18), pages 1-19, September.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:18:p:11567-:d:915889
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    References listed on IDEAS

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    1. Mark Muller & Seri Park & Ross Lee & Brett Fusco & Gonçalo Homem de Almeida Correia, 2021. "Review of Whole System Simulation Methodologies for Assessing Mobility as a Service (MaaS) as an Enabler for Sustainable Urban Mobility," Sustainability, MDPI, vol. 13(10), pages 1-15, May.
    2. Abbasi, Sorath & Ko, Joonho & Min, Jaehong, 2021. "Measuring destination-based segregation through mobility patterns: Application of transport card data," Journal of Transport Geography, Elsevier, vol. 92(C).
    3. Groth, Sören, 2019. "Multimodal divide: Reproduction of transport poverty in smart mobility trends," Transportation Research Part A: Policy and Practice, Elsevier, vol. 125(C), pages 56-71.
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