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Mapping Accessible Paths in the City Using Collective Intelligence

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dc.contributor.author Marques, Valmir
dc.contributor.author Graeml, Alexandre
dc.date.accessioned 2019-01-03T00:00:18Z
dc.date.available 2019-01-03T00:00:18Z
dc.date.issued 2019-01-08
dc.identifier.isbn 978-0-9981331-2-6
dc.identifier.uri http://hdl.handle.net/10125/59647
dc.description.abstract New information and communication technologies (ICTs) have an increasingly stronger role in people's lives, especially after the commoditization of smartphones. They affect many aspects of everyday life, including urban mobility. Some applications, including Waze, benefit from the collective intelligence (CI) of the crowds to gather the information they need to provide users with good advice on the routes to follow. But they are mainly focused on roads and streets, giving little information on the quality of sidewalks, which are essential to pedestrians, people on wheelchairs and blind people. With the intention to improve the mobility of citizens with special needs, we developed the prototype of an application that allows users themselves to update accessibility maps, tagging obstacles and also indicating the existence of resources that contribute to improve the mobility of people with special needs in urban spaces. Tests in a controlled environment helped to debug the application’s functionalities, before members of the intended target group of users were finally exposed to it. Results are promising, as users were able to include relevant data by themselves and seem motivated to keep doing so, due a sense of utility, social facilitation or simply due to altruism, as anticipated by the CI literature. One unexpected outcome was that impaired users are more excited about the potential the application has to give visibility to the challenges they face than with the actual improvement it can bring to their mobility.
dc.format.extent 10 pages
dc.language.iso eng
dc.relation.ispartof Proceedings of the 52nd Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Collective Intelligence and Crowds
dc.subject Digital and Social Media
dc.subject accessible maps, accessible routes, collective intelligence, crowdsensing, disabled people
dc.title Mapping Accessible Paths in the City Using Collective Intelligence
dc.type Conference Paper
dc.type.dcmi Text
dc.identifier.doi 10.24251/HICSS.2019.253
Appears in Collections: Collective Intelligence and Crowds


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