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A crowd early warning method based on MAC codes and face identification

A face recognition and people flow technology, applied in the field of people flow early warning based on MAC code and face recognition, can solve problems such as accidents, crowded people, bursting, etc., and achieve the effect of avoiding accidents

Active Publication Date: 2016-11-16
SHENZHEN MIRACLE WISDOM NETWORK CO LTD
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  • Claims
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AI Technical Summary

Problems solved by technology

[0002] With the rapid increase of the population in our country, there are more and more sudden accidents due to crowding, especially during holidays, people go out to travel more, and there will be crowded and bursting phenomenon in some tourist attractions. Failure to do a good job of guiding and shunting, accidents are prone to occur

Method used

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  • A crowd early warning method based on MAC codes and face identification

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Embodiment Construction

[0036] refer to figure 1 As shown, a kind of people flow warning method based on MAC code and face recognition of the present embodiment, it specifically comprises the following steps:

[0037] In the first step, the camera collects the faces of key people within the specified range through video surveillance, and sends out an alarm;

[0038] In the second step, the probe detects the hardware-related information of the client mobile phone (field strength, time, latitude and longitude (space) dimensions);

[0039] In the third step, the camera uploads the alarm information to the cloud;

[0040] In the fourth step, the probe uploads the hardware information of the detected ethical client to the cloud;

[0041] In the fifth step, the cloud constructs machine learning based on the alarm information of the camera and the ethical information collected by the probes in the dimensions of time, distance, and historical retention, and matches and collates face and hardware informatio...

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PUM

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Abstract

The invention discloses a crowd early warning method based on MAC codes and face identification. The method comprises the following steps: 1) collecting faces of key crowds appearing in a designated area and carrying out an alarm; 2) detecting client-side mobile phone hardware information; uploading the warning information to a cloud end; 4) uploading the detected client-side mobile phone hardware information to the cloud end; 5) associating the human faces and the hardware information and carrying out matching and correction; 6) the cloud end pushing the result to a visualization platform and a big data integration platform; 7) the visualization platform and the big data integration platform displaying the whole system in a manner of carrying out refreshing per minute according to real-time views; and 8) reporting crowd-related early warning and alarming information to a platform administrator, and automatically pushing the information to an outdoor big screen and client-side mobile phones in a monitoring area to achieve an early warning effect.

Description

technical field [0001] The invention relates to a human flow early warning method, more specifically, it relates to a human flow early warning method based on MAC codes and face recognition. Background technique [0002] With the rapid increase of the population in our country, there are more and more sudden accidents due to crowding, especially during holidays, people go out to travel more, and there will be crowded and bursting phenomenon in some tourist attractions. If you can't do a good job of dredging and shunting, accidents are prone to occur. Contents of the invention [0003] Aiming at the deficiencies in the prior art, the purpose of the present invention is to provide a method for early warning of human flow based on MAC code and face recognition. [0004] In order to achieve the above object, the present invention provides the following technical solutions: a method for early warning of people flow based on MAC code and face recognition, which specifically inc...

Claims

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Application Information

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IPC IPC(8): G08B21/02
CPCG08B21/02
Inventor 傅东生
Owner SHENZHEN MIRACLE WISDOM NETWORK CO LTD
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