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Navcog3 in the wild: Large-scale Blind Indoor Navigation Assistant with Semantic Features

Title
Navcog3 in the wild: Large-scale Blind Indoor Navigation Assistant with Semantic Features
Authors
Sato D.Oh U.Guerreiro J.Ahmetovic D.Naito K.Takagi H.Kitani K.M.Asakawa C.
Ewha Authors
오유란
Issue Date
2019
Journal Title
ACM Transactions on Accessible Computing
ISSN
1936-7228JCR Link
Citation
ACM Transactions on Accessible Computing vol. 12, no. 3
Keywords
Indoor navigationPoints of interestUser evaluationVisual impairmentsVoice interaction
Publisher
Association for Computing Machinery
Indexed
SCOPUS scopus
Document Type
Article
Abstract
NavCog3 is a smartphone turn-by-turn navigation assistant system we developed specifically designed to enable independent navigation for people with visual impairments. Using off-the-shelf Bluetooth beacons installed in the surrounding environment and a commodity smartphone carried by the user, NavCog3 achieves unparalleled localization accuracy in real-world large-scale scenarios. By leveraging its accurate localization capabilities, NavCog3 guides the user through the environment and signals the presence of semantic features and points of interest in the vicinity (e.g., doorways, shops). To assess the capability of NavCog3 to promote independent mobility of individuals with visual impairments, we deployed and evaluated the system in two challenging real-world scenarios. The first scenario demonstrated the scalability of the system, which was permanently installed in a five-story shopping mall spanning three buildings and a public underground area. During the study, 10 participants traversed three fixed routes, and 43 participants traversed free-choice routes across the environment. The second scenario validated the system's usability in the wild in a hotel complex temporarily equipped with NavCog3 during a conference for individuals with visual impairments. In the hotel, almost 14.2h of system usage data were collected from 37 unique users who performed 280 travels across the environment, for a total of 30,200m traversed. © 2019 Association for Computing Machinery.
DOI
10.1145/3340319
Appears in Collections:
엘텍공과대학 > 컴퓨터공학과 > Journal papers
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