Dynamic people flow early warning method based on mobile network signaling data

Abstract

The invention provides a dynamic people flow early warning method based on mobile network signaling data. The method includes the steps of: (1) separating a people flow early warning target region and people flow early warning observation regions; (2) counting and obtaining the people flow transition probability of each observation region distributed along with the travel time; (3) simultaneously counting a people flow leaving ratio in each period at the target region; and (4) predicting the total customer number from each observation region into the target region at the statistics time according to the real-time people flow in the observation regions and the people flow transition probability distributed along with the travel time, and predicting the customer number left from the target region before the statistics time according to the real-time people flow in the target region and the people flow leaving probability in the period at the region, thereby predicting the people flow size at the statistics time, and judging early warning grades. According to the invention, the current mobile network information is fully used, the target region and the observation regions are introduced, the statistics of the people flow at the target region is realized according to the people flow conditions of the target region and the observation regions, and the people flow early warning at the target region is finished according to a designate standard of the early warning grades.

Description

technical field [0001] The invention relates to the fields of urban computing and public safety, in particular to a dynamic human flow early warning method based on mobile network signaling data. Background technique [0002] With the continuous improvement of people's living standards in our country, the phenomenon of "blowout" of crowds often occurs in hot spots such as comprehensive business districts and famous tourist attractions in large cities, especially during holidays. However, the gathering of a large number of people often increases the possibility of stampede accidents in the area. Therefore, we need to strengthen the monitoring and management of the flow of people in urban hotspots, so as to reduce the probability of stampede accidents and ensure the safety of urban residents in hotspots. Personal safety. [0003] At present, the research on human flow monitoring in hotspot areas and densely populated areas has attracted extensive attention of researchers at h...

AI Technical Summary

Problems solved by technology

[0004] Traditional passenger flow statistics mainly rely on manual work, and are carried out by visual inspection in areas with a high concentration of people. The number of passengers, and what level of evacuation and emergency plans are in place

[0005] The method of counting people based on video recognition is more intelligent than manual counting. It is more suitable for subway stations, airports and some large exhibition halls. The invention patent "a method for monitoring and early warning of crowd density for large public places" uses video The recognition technology uses the comparison of the pixel values ​​of the video image to judge the size of the crowd density in the area. However, due to the deployment of a large number of cameras and servers, the deployment period is long and the hardware cost is high. Monitoring capabilities, unable to accurately understand the flow of people in the target area and surrounding areas

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