JIPS (한국정보처리학회)
Current Result Document :
| 한글제목(Korean Title) |
Saturation Prediction for Crowdsensing Based Smart Parking System |
| 영문제목(English Title) |
Saturation Prediction for Crowdsensing Based Smart Parking System |
| 저자(Author) |
Mihui Kim
Junhyeok Yun
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| 원문수록처(Citation) |
VOL 15 NO. 06 PP. 1335 ~ 1349 (2019. 12) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
Crowdsensing technologies can improve the efficiency of smart parking system in comparison with present sensor based smart parking system because oflow install price and no restriction caused by sensor installation. A lot of sensing data is necessary to predict parking lot saturation in real-time. However in real world, it is hard to reach the required number of sensing data. In this paper, we model a saturation predication combining a time-based prediction model and a sensing data-based prediction model. The time-based model predicts saturation in aspects of parking lot location and time. The sensing data-based model predicts the degree of saturation of the parking lot with high accuracy based on the degree of saturation predicted from the first model, the saturation information in the sensing data, and the number of parking spaces in the sensing data. We perform prediction model learning with real sensing data gathered from a specific parking lot. We also evaluate the performance of the predictive model and show its efficiency and feasibility.
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| 키워드(Keyword) |
Crowdsensing
Regression Model
Saturation Prediction
Smart Parking System
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| 파일첨부 |
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