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BluePark : tracking parking and un-parking events in indoor parking lot

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dc.contributor.author Soubam, Sonia
dc.contributor.author Naik, Vinayak
dc.contributor.author Banerjee, Dipyaman
dc.contributor.author Chakraborty, Dipanjan
dc.date.accessioned 2015-10-26T03:37:01Z
dc.date.available 2015-10-26T03:37:01Z
dc.date.issued 2015-10-26T03:37:01Z
dc.identifier.uri https://repository.iiitd.edu.in/jspui/handle/123456789/335
dc.description.abstract Finding a parking spot in a busy indoor parking lot is a daunting task. Retracing a parked vehicle can be equally frustrating. We present BluePark, a collaborative sensing mechanism using smartphone sensors to solve these problems in real-time, without any input from user. We propose a novel technique of combining accelerometer and WiFi data to detect and localize parking and un-parking events in indoor parking lot. We validate our approach at the basement parking of a popular shopping mall. The proposed method out-performs Google Activity Recognition API by 20% in detecting drive state in indoor parking lot. Our experiments show 100% precision and recall for parking and un-parking detection events at low accelerometer sampling rate of 15Hz, irrespective of phone’s position. It has a low detection latency of 20 seconds with probability of 0.9 and good location accuracy of 10 meters. en_US
dc.language.iso en_US en_US
dc.relation.ispartofseries IIITD-TR-2015-009
dc.subject BluePark en_US
dc.subject Parking en_US
dc.title BluePark : tracking parking and un-parking events in indoor parking lot en_US
dc.type Technical Report en_US

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