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The goal of the proposed project is to transform a large transportation hub into a smart and accessible hub (SAT-Hub), with minimal infrastructure change. The societal need is significant, especially impactful for people in great need, such as those who are blind and visually impaired (BVI) or with Autism Spectrum Disorder (ASD), as well as those unfamiliar with metropolitan areas. With our inter-disciplinary background in urban systems, sensing, AI and data analytics, accessibility, and paratransit and assistive services, our solution is a hu-man-centric system approach that integrates facility modeling, mobile navigation, and user interface designs. We leverage several transportation facili-ties in the heart of New York City and throughout the State of New Jersey as testbeds for ensuring the relevance of the research and a smooth transition to real world applications.
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Building Smart and Accessible Transportation Hubs with Internet of Things, Big Data Analytics, and Affective Computing
Large transportation hubs are difficult to navigate, especially for people with special needs such as those with visual impairment, Autism spectrum disorder (ASD), or simply those with navigation challenges. The primary objective of this research is to design and develop a novel cyber-physical infrastructure that can effectively and efficiently transform existing transportation hubs into smart facilities capable of providing better location-aware services. We investigated the integration of a number of Internet of Things (IoT) elements, including video analytics, Bluetooth beacons, mobile computing, and facility semantic models, to provide reliable indoor navigation services to people with special needs, yet requiring minimum infrastructure changes. Our pilot tests with people with special needs at a multi-floor building in New York City has demonstrated the effectiveness of our proposed framework.
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- PAR ID:
- 10065142
- Date Published:
- Journal Name:
- International Conference on Sustainable Infrastructure 2017
- Page Range / eLocation ID:
- 126 to 138
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Conference Paper:
- https://doi.org/10.1061/9780784481219.012
