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An algorithm for monitoring the traffic on a less traveled road using multi-modal sensor suite

机译:一种使用多模式传感器套件监视人迹罕至的道路上的交通的算法

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We conducted an experiment to correlate the information gathered by a suite of hard sensors with the information on social networks such as Twitter, Facebook, etc. The experiment consisting of monitoring traffic on a well-traveled road and on a road inside a facility. The sensors suite selected mainly consists of sensors that require low power for operation and last a longtime. The output of each sensor is analyzed to classify the targets as ground vehicles, humans, and airborne targets. The algorithm is also used to count the number of targets belonging to each type so the sensor can store the information for anomaly detection. In this paper, we describe the classifier algorithms used for acoustic, seismic, and passive infrared (PIR) sensor data.
机译:我们进行了一项实验,以将一组硬传感器收集的信息与诸如Twitter,Facebook等社交网络上的信息相关联。该实验包括监视行进道路和设施内部道路上的交通。所选的传感器套件主要由需要低功率运行且使用寿命长的传感器组成。分析每个传感器的输出,以将目标分类为地面车辆,人和空中目标。该算法还用于计算属于每种类型的目标的数量,因此传感器可以存储信息以进行异常检测。在本文中,我们描述了用于声学,地震和被动红外(PIR)传感器数据的分类器算法。

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