Crowdsensing using Geofencing for Smart Parking
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Abstract
Finding a parking spot for a car is a practical problem faced by millions of drivers daily. Most of the times it involves anxiety and uncertainty, also considering a threat to environment, it wastes limited resources which includes time, road space, and fuel. Also drivers roam around in search of free parking spaces. These problems could be minimized if drivers had advance information of vacant parking spots. This information can be gathered with dedicated sensor systems keeping track of the reservation status of parking areas. New devices such as mobile phones come with a variable number of sensors and thus can interact with many things in environment. Recently mobile operating systems have started to incorporate means to offer contextual information derived from measurements of multiple sensors, i.e. by interacting with open sources it can get information about the surrounding. The idea is to investigate how these interacting capabilities could be used to derive information about available parking places in addition to parking sensor of the infrastructure or by smart parking using geofencing by which the model aims to reduce the traffic in the surrounding.
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