Customer-centric and Real-time Parking Recommendation

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Presentation transcript:

Customer-centric and Real-time Parking Recommendation By Mei Mei

What is Customer-centric and Real-time Parking Recommendation?

Motivation

Hypothesis

Real-time parking recommendation Location tracking pattern

Hypothesis support Customer location pattern analysis: Mosaic theory Machine learning Real-time street parking recommendation: object detectors Video analysis Algorythm

How? Hardware Software Camera Installation Intel Edison Mobile phone sensor AWS for cloud storage NYC Camera feed fetching + Image Processing Cloud based computing for behavioral analysis Machine Learning algorithm App development How?

Procedure Install Camera on CS Lounge: Install camera and guarantee data quality Install GPS tracking sensor on cars: collect user location data via mobile phone on car. Cloud upload: Upload data onto AWS Pattern Recognition: Garage Recognition Get NYC Data feed: Get data from website Recommendation Algorithm: Parking recommendation based on garage data

Initial experiment

Street

Functional Flowchart

The experiment