Parking Sensing and Information System: Sensors, Deployment, and Evaluation
Xiao Chen, Zhen (Sean) Qian, Ram Rajagopal, Todd Stiers, Christopher, Flores, Robert Kavaler, and Floyd Williams III

TL;DR
This paper presents a scalable smart parking system utilizing wireless sensors and cloud services to provide real-time occupancy and cruising time information, demonstrated through deployment and evaluation at Stanford University.
Contribution
It introduces an integrated hardware and analytical framework for cost-effective, real-time parking information dissemination using wireless sensor networks and cloud computing.
Findings
System successfully deployed at Stanford with high scalability.
Provides accurate occupancy and cruising time estimates.
Extensive evaluation confirms system effectiveness.
Abstract
This paper describes a smart parking sensing and information system that disseminates the parking availability information for public users in a cost-effective and efficient manner. The hardware framework of the system is built on advanced wireless sensor networks and cloud service over the Internet, and the system is highly scalable. The parking information provided to the users is set in the form of occupancy rates and expected cruising time. Both are obtained from our analytical algorithm processing both historical and real-time data, and are thereafter visualized in a color theme. The entire parking system is deployed and extensively evaluated at Stanford University Parking Structure-1.
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