This GCTC Team aims to systematically investigate a novel cyber-physical infrastructure framework that can effectively and efficiently transform existing transportation hubs into smart facilities. The Smart Hub is capable of providing better location-awareness services (e.g. finding terminals, improving travel experience, obtaining security alters) to the traveling public, especially for the underserved populations including those with visual impairment, Autism Spectrum Disorder (ASD), or simply navigation challenges.

Major Requirements:

• Develop and assemble project team
• Create scope and requirements and a project plan
• Design system architecture with both stationary and mobile nodes
• Develop mobile applications for mobile graph localization
• Register the mobile graph with the 3D model; design and roll out pilot
• Gain stakeholder support esp. PANYNJ and buy-in from the community
• Run pilot for two months

Key Performance Indicators (KPIs):

• Average time to find a terminal reduced by ~50%
• Increase of number of users with special needs ~25%
• User experience satisfaction increased by ~60%

Measurement Methods:

• Measure navigation time in minutes over 3-6 month period, compared to baseline.
• Measure number of people downloading and using the apps
• Questionnaires to measure user experience in terms of navigation, waiting times, and safety concerns

Replicability, Scalability, and Sustainability:

• Standardized processes are not unique to city or region and can be replicated and scaled up in multiple cities/communities. The solution is planned and designed to be replicated in 2 transportation hubs in the New York City area.
• The system will have its own business model to create sustainable revenue stream.

Projects Impact:

• Improve efficiency of big transportation hubs
• Improve quality of life for persons with visual impairments and/or ASDs, among others
• Improve travel safety and user experience in crowded environments


Phase I Pilot/Demonstration June 2016:
A demonstration system in small scale in a campus building for providing users travel guidance. Videos and visual demos to show the 3D modeling, crowd detection, and preliminary user localization.

Phase II Deployment June 2017:
A demonstration system in a major transportation hub in New York City for providing users travel guidance. Videos and visual demos to show the 3D modeling, crowd detection, and user localization and navigation assistance.

Team Information: Zhigang Zhu, Jie Gong, Team Lead: Zhigang Zhu ([email protected]), CUNY City College, Jie Gong ([email protected]), Rutgers University.

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