On-site and remote crowdsourcing of accessibility data for people with mobility impairments : a case study in Zurich’s District 1

Witzel, Lina; Chhong, Sophy; Hutter, Hans-Peter; Darvishy, Alireza

doi:10.54941/ahfe1002949

Publication type:	Conference paper
Type of review:	Editorial review
Title:	On-site and remote crowdsourcing of accessibility data for people with mobility impairments : a case study in Zurich’s District 1
Authors:	Witzel, Lina Chhong, Sophy Hutter, Hans-Peter Darvishy, Alireza
et. al:	No
DOI:	10.54941/ahfe1002949
Proceedings:	Human Interaction and Emerging Technologies (IHIET-AI 2023): Artificial Intelligence and Future Applications
Editors of the parent work:	Ahram, Tared Taiar, Redha
Volume(Issue):	70
Page(s):	242
Pages to:	253
Conference details:	9th International Conference on Human Interaction & Emerging Technologies: Artificial Intelligence & Future Applications (IHIET-AI), Lausanne, Switzerland, 13-15 April 2023
Issue Date:	2023
Publisher / Ed. Institution:	AHFE International
ISBN:	978-1-958651-46-9
ISSN:	2771-0718
Language:	English
Subjects:	Accessibility; Barrier; Crowdsourcing; Data collection; Empirical study; Mobility impairment; On-site; Performance; Remote; Routing
Subject (DDC):	005: Computer programming, programs and data
Abstract:	Collecting accurate accessibility data systematically for pathways is a time-consuming task that typically requires expert knowledge. However, it is a prerequisite to enable reliable and trustworthy accessible routing. The development of Capture & Go, a mobile application to report barriers for people with mobility impairments, facilitates the on-site collection of crowdsourced accessibility data. Several other mapping tools contain accessibility data, although they have not been developed explicitly for this purpose. In contrast to Capture & Go, they allow data collection to be performed remotely. Using quantitative and qualitative approaches, we analyzed several such applications and examined their efficiency in capturing barriers in a case study of District 1 in Zurich. The remotely collected data was compared to the data of the barriers captured on-site using Capture & Go. Overall, the remote tools were less efficient than Capture & Go in terms of effort, coverage, and accuracy of the barriers, as well as usability.
URI:	https://digitalcollection.zhaw.ch/handle/11475/27606
Fulltext version:	Published version
License (according to publishing contract):	Licence according to publishing contract
Departement:	School of Engineering
Organisational Unit:	Institute of Computer Science (InIT)
Appears in collections:	Publikationen School of Engineering

Files in This Item:

There are no files associated with this item.

Show full item record

Witzel, L., Chhong, S., Hutter, H.-P., & Darvishy, A. (2023). On-site and remote crowdsourcing of accessibility data for people with mobility impairments : a case study in Zurich’s District 1 [Conference paper]. In T. Ahram & R. Taiar (Eds.), Human Interaction and Emerging Technologies (IHIET-AI 2023): Artificial Intelligence and Future Applications (Vol. 70, pp. 242–253). AHFE International. https://doi.org/10.54941/ahfe1002949

Witzel, L. et al. (2023) ‘On-site and remote crowdsourcing of accessibility data for people with mobility impairments : a case study in Zurich’s District 1’, in T. Ahram and R. Taiar (eds) Human Interaction and Emerging Technologies (IHIET-AI 2023): Artificial Intelligence and Future Applications. AHFE International, pp. 242–253. Available at: https://doi.org/10.54941/ahfe1002949.

L. Witzel, S. Chhong, H.-P. Hutter, and A. Darvishy, “On-site and remote crowdsourcing of accessibility data for people with mobility impairments : a case study in Zurich’s District 1,” in Human Interaction and Emerging Technologies (IHIET-AI 2023): Artificial Intelligence and Future Applications, 2023, vol. 70, pp. 242–253. doi: 10.54941/ahfe1002949.

WITZEL, Lina, Sophy CHHONG, Hans-Peter HUTTER und Alireza DARVISHY, 2023. On-site and remote crowdsourcing of accessibility data for people with mobility impairments : a case study in Zurich’s District 1. In: Tared AHRAM und Redha TAIAR (Hrsg.), Human Interaction and Emerging Technologies (IHIET-AI 2023): Artificial Intelligence and Future Applications. Conference paper. AHFE International. 2023. S. 242–253. ISBN 978-1-958651-46-9

Witzel, Lina, Sophy Chhong, Hans-Peter Hutter, and Alireza Darvishy. 2023. “On-Site and Remote Crowdsourcing of Accessibility Data for People with Mobility Impairments : A Case Study in Zurich’s District 1.” Conference paper. In Human Interaction and Emerging Technologies (IHIET-AI 2023): Artificial Intelligence and Future Applications, edited by Tared Ahram and Redha Taiar, 70:242–53. AHFE International. https://doi.org/10.54941/ahfe1002949.

Witzel, Lina, et al. “On-Site and Remote Crowdsourcing of Accessibility Data for People with Mobility Impairments : A Case Study in Zurich’s District 1.” Human Interaction and Emerging Technologies (IHIET-AI 2023): Artificial Intelligence and Future Applications, edited by Tared Ahram and Redha Taiar, vol. 70, AHFE International, 2023, pp. 242–53, https://doi.org/10.54941/ahfe1002949.