In this paper, a framework is developed for the purpose of detecting small hidden objects through weigh-inmotion data for security purposes. The 3 statistical principle is used to separate the outlier events and noises with normal traffic flow and the collected wheel loads are further used to identify the possible locations and weights of hidden objects. Correspondingly, an in-lab experiment has been conducted to validate the algorithm and excellent results have been reached. The system can be implemented at any security port and help to increase the security screening efficiencies at these locations.
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