Dynamic Street-Parking Optimisation

Nuria Pazos, Michael Müller, M. Favre-Bulle, Kilian Brandt-Dit-Grieurin, Oliver Hüsser, M. Aeberli, N. Ouerhani
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引用次数: 11

Abstract

An instrument to improve the quality of life in large cities, helping to reduce the car traffic, is presented in this paper. It will result in a mobile guidance software that will help the drivers looking for a parking place to find it efficiently. SmartPark relies on available parking information systems, as well as on new sensors or even on social data inputs. A fixed magnetic on-street sensor and a video processing smart camera have been developed and prototypes of both devices were tested. Their data is available through a cloud-based Internet of Things infrastructure and continuously updated every few seconds. Databases will be built over time enabling data mining methods to infer parking availability models over time which will be used, eventually, by the algorithms feeding the mobile application.
动态街道停车优化
本文提出了一种改善大城市生活质量,减少汽车交通的工具。这将产生一个移动引导软件,帮助寻找停车位的司机有效地找到它。SmartPark依赖于现有的停车信息系统,以及新的传感器,甚至是社会数据输入。一种固定的磁性街道传感器和一种视频处理智能摄像头已经开发出来,并对这两种设备的原型进行了测试。他们的数据通过基于云的物联网基础设施提供,每隔几秒钟就会不断更新。随着时间的推移,数据库将被建立起来,使数据挖掘方法能够推断出一段时间内的停车位可用性模型,这些模型最终将被提供给移动应用程序的算法所使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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