CN108540757B - Monitoring system and monitoring method - Google Patents
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- CN108540757B CN108540757B CN201710115191.XA CN201710115191A CN108540757B CN 108540757 B CN108540757 B CN 108540757B CN 201710115191 A CN201710115191 A CN 201710115191A CN 108540757 B CN108540757 B CN 108540757B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
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- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
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- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
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Abstract
The invention discloses a monitoring system and a monitoring method, and relates to the technical field of multimedia. The monitoring system comprises: wireless network equipment, audio acquisition equipment and associated equipment; wherein the wireless network device is configured to: collecting a Media Access Control (MAC) address of a terminal connected to wireless network equipment in a monitoring area; the audio acquisition device is to: collecting audio information of a monitoring area; the association device is for: judging whether an abnormal event occurs in the monitoring area or not according to the audio information; associating the MAC address with the audio information; calling an MAC address associated with audio information when an abnormal event occurs in a monitoring area; and determining the participators of the abnormal event through the associated MAC address. The method and the system can accurately and efficiently realize the monitoring of the abnormal event, thereby determining the abnormal event participators.
Description
Technical Field
The present invention relates to the field of multimedia technologies, and in particular, to a monitoring method and a monitoring system.
Background
The traditional monitoring mode mainly comprises video monitoring. After the video monitoring equipment is deployed, law enforcement personnel can identify the suspect by searching the monitoring image.
However, abnormal events such as a crowd gathering, a stepping event, an emergency event, etc. may occur in the vicinity of the monitoring device. The traditional monitoring mode cannot accurately and efficiently realize the monitoring of the abnormal events. First, in a conventional monitoring mode, when a law enforcement officer calls a video monitor to identify a suspect, if the suspect leaves a monitoring picture, images of a plurality of monitoring areas and a long period of time need to be screened manually to capture the picture of the suspect again. Due to the limitation of the view angle and the picture of the monitoring video, all the personnel related to the case cannot be obtained. Due to the limitation of the deployment place, the visual angle and the visual distance of the camera, the monitoring blind area is large, the cost is greatly increased by the omni-directional seamless deployment of the camera in a certain space, and the popularization and the application are difficult. Secondly, the traditional monitoring method depends on manual identification, so that the identification efficiency is greatly reduced, a large amount of manual participation brings many subjective factors, and the identification accuracy is reduced. Thirdly, due to the influence of weather, the definition of monitoring data is also influenced, which brings difficulty to the identification of all suspects and may cause missing.
How to accurately and efficiently monitor the abnormal event so as to determine the abnormal event participators is an urgent technical problem to be solved.
Disclosure of Invention
The invention aims to solve the technical problems that: how to accurately and efficiently realize the monitoring of the abnormal event so as to determine the abnormal event participators.
According to an aspect of an embodiment of the present invention, there is provided a monitoring system, including: wireless network equipment, audio acquisition equipment and associated equipment; wherein the wireless network device is configured to: collecting a Media Access Control (MAC) address of a terminal connected to wireless network equipment in a monitoring area; the audio acquisition device is to: collecting audio information of a monitoring area; the association device is for: judging whether an abnormal event occurs in the monitoring area according to the audio information, and associating the MAC address with the audio information; and calling the MAC address associated with the audio information when the abnormal event occurs in the monitoring area, and determining the participators of the abnormal event according to the associated MAC address.
In some embodiments, the associating means is for associating the MAC address and the audio information acquired at the same time.
In some embodiments, the system further comprises a video capture device for capturing video images of the vicinity of the monitored area; the association device is further configured to: judging whether an abnormal event occurs in the monitoring area according to the audio information, and associating the video image with the audio information; and calling a video image associated with the audio information when the abnormal event occurs in the monitored area, and determining the image information of the participators of the abnormal event through the associated video image.
In some embodiments, the association device is used to associate video images and audio information captured at the same time.
In some embodiments, the association device is to: judging whether the volume of the audio is greater than a preset volume value or not; and if the volume value is greater than the preset volume value, determining that an abnormal event occurs in the monitoring area.
In some embodiments, the association device is to: acquiring sample frequency characteristics of sample audio information corresponding to the abnormal event; comparing the frequency characteristics of the audio information to the sample frequency characteristics; and if the frequency characteristics of the audio information are similar to the sample frequency characteristics, determining that an abnormal event occurs in the monitored area. .
According to another aspect of the embodiments of the present invention, there is provided a monitoring method, including: collecting a Media Access Control (MAC) address of a terminal connected to wireless network equipment in a monitoring area; collecting audio information of a monitoring area; judging whether an abnormal event occurs in the monitoring area according to the audio information, and associating the MAC address with the audio information; and calling the MAC address associated with the audio information when the abnormal event occurs in the monitoring area, and determining the participators of the abnormal event according to the associated MAC address.
In some embodiments, the same time-collected MAC address and audio information are associated.
In some embodiments, the method further comprises: collecting video images near a monitoring area; judging whether an abnormal event occurs in the monitoring area according to the audio information, and associating the video image with the audio information; and calling a video image associated with the audio information when the abnormal event occurs in the monitored area, and determining the image information of the participators of the abnormal event through the associated video image.
In some embodiments, the same time captured video image is associated with audio information.
In some embodiments, determining whether an abnormal event occurs in the monitored area according to the audio information includes: judging whether the volume of the audio is greater than a preset volume value or not; and if the volume value is greater than the preset volume value, determining that an abnormal event occurs in the monitoring area.
In some embodiments, determining whether an abnormal event occurs in the monitored area according to the audio information includes: acquiring sample frequency characteristics of sample audio information corresponding to the abnormal event; comparing the frequency characteristics of the audio information to the sample frequency characteristics; and if the frequency characteristics of the audio information are similar to the sample frequency characteristics, determining that an abnormal event occurs in the monitored area. .
The method and the system can accurately and efficiently realize the monitoring of the abnormal event, thereby determining the abnormal event participators.
Other features of the present invention and advantages thereof will become apparent from the following detailed description of exemplary embodiments thereof, which proceeds with reference to the accompanying drawings.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 shows a schematic structural diagram of an embodiment of the monitoring system of the present invention.
Fig. 2 shows a schematic structural diagram of another embodiment of the monitoring system of the present invention.
Fig. 3 shows a schematic diagram of the sound intensity distribution of a personal distress audio sample.
FIG. 4 shows a schematic of the sound intensity distribution of a normal street audio sample.
Fig. 5 shows a sound intensity distribution diagram of an applause audio sample.
Fig. 6 shows audio information detected at a monitoring site.
Fig. 7 shows a schematic flow chart of an embodiment of the monitoring method of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
A monitoring system according to an embodiment of the invention is described below with reference to fig. 1.
Fig. 1 shows a schematic structural diagram of an embodiment of the monitoring system of the present invention. As shown in fig. 1, the monitoring system 10 in the present embodiment includes: a wireless network device 102, an audio capture device 104, and an association device 106. The wireless network device 102 can collect the MAC address of the terminal connected to the wireless network device in the monitoring area; the audio capture device 104 is capable of capturing audio information for the monitored area. The association device 106 is configured to: judging whether an abnormal event occurs in the monitoring area according to the audio information, and associating the MAC address with the audio information; and calling the MAC address associated with the audio information when the abnormal event occurs in the monitoring area, and determining the participators of the abnormal event according to the associated MAC address.
The work flow of the monitoring system 10 in this embodiment is as follows:
the wireless network device 102 collects MAC addresses of terminals connected to the monitoring area wireless network device.
For example, several WIFI devices are deployed in a monitored area. After the terminal is connected to the WIFI equipment, the WIFI equipment can acquire the MAC address of the terminal. The wireless network device 102 sends each collected MAC address and the collection time thereof to the association device 106 in real time.
And (II) the audio acquisition equipment 104 acquires audio information of the monitored area.
For example, audio capture devices are deployed in a monitored area. The audio acquisition device can acquire audio information of the monitoring area in real time and send the acquired volume information and the acquisition time thereof to the association device 106 in real time.
And (III) the association equipment 106 judges whether an abnormal event occurs in the monitored area according to the audio information and associates the MAC address with the audio information.
(a) The MAC address is associated with the audio information.
In associating the MAC address with the audio information, the associating device 106 needs to associate the MAC address and the audio information collected at the same time. Thus, the association device 106 first synchronizes the system time of the audio capture device 104 with the wireless network device 102 and then performs an on-track storage of the received MAC address and audio information. When the audio files are stored in a track-bound mode, the MAC addresses and the audio information can be stored in the audio files or the index files of the audio files.
(b) And judging whether an abnormal event occurs in the monitoring area according to the audio information.
There are various bases for determining whether an abnormal event occurs in the monitoring area. One implementation is to determine whether the volume of the audio is greater than a preset volume value. And if the volume value is greater than the preset volume value, determining that an abnormal event occurs in the monitoring area.
For example, based on multi-site field simulation testing, it is known that: the sound intensity in quiet places is below 30 decibels, the sound intensity of people in normal conversations is 30-55 decibels, the sound intensity in streets and public places is 55-75 decibels, the sound intensity in noisy and hot crowd is about 80-90 decibels, and the sound intensity is generally above 90 decibels for screaming, cheering, asking for help and the like. Fig. 3 shows a sound intensity distribution diagram of a personal distress audio sample, fig. 4 shows a sound intensity distribution diagram of a normal street audio sample, fig. 5 shows a sound intensity distribution diagram of a cheering audio sample, and fig. 6 shows audio information detected at a monitoring site. According to the sound intensity distribution situations shown in fig. 3, 4 and 5, the audio information in fig. 6 can be analyzed, so that the situations of cheering and whooping in the monitored area can be obtained.
Another implementation is to obtain a sample frequency feature of the sample audio information corresponding to the abnormal event, and then compare the frequency feature of the audio information with the sample frequency feature. And if the frequency characteristics of the audio information are similar to the sample frequency characteristics, determining that an abnormal event occurs in the monitored area. .
For example, a frequency domain analysis algorithm is used for carrying out certain feature analysis on the collected audio, whether the features obtained through analysis are matched with the preset audio features of the gathering party is judged, or the features obtained through analysis are input into a trained model, the features obtained through analysis are matched with the preset audio features of the gathering party, or if the result output by the model is gathering, the gathering party is indicated. When the audio features of the gathering parties are preset, audio of a plurality of gathering parties collected historically can be used as samples, and the audio features of the gathering parties are preset according to the samples. When the model is trained, the audio collected historically by a plurality of gathering parties can be used as a training sample for training.
The order of the steps (a) and (b) may be adjusted according to actual needs. For example, the MAC address may be associated with audio information, and then whether an abnormal event occurs in the monitored area may be determined according to the audio information. And judging whether an abnormal event occurs in the monitoring area or not according to the audio information, and if the abnormal event occurs in the monitoring area, associating the MAC address with the audio information. That is, the occurrence of an abnormal event in the monitored area is taken as a trigger condition for associating the MAC address with the audio information.
And (IV) calling the MAC address associated with the audio information when the abnormal event occurs in the monitoring area, and determining the participators of the abnormal event according to the associated MAC address.
For example, for a situation that a party gathering may occur in a certain video image, corresponding volume information may be called, if the volume is greater than a preset threshold, it is indicated that an abnormal event such as a gathering may occur, at this time, a corresponding MAC address may be called, and the mobile phone number of a party gathering participant is determined through the terminal MAC address of the party gathering participant, so as to determine the identity of the party gathering participant.
In the embodiment, whether an abnormal event occurs is judged by using the monitoring audio, the MAC address of the electronic equipment carried by the suspect in the monitoring is determined by using the incidence relation between the monitoring audio and the MAC address detection data, and then the contact is positioned by searching and positioning the MAC address and the like, so that the monitoring of the abnormal event can be accurately and efficiently realized, and the personnel participating in the abnormal event are determined. Furthermore, the above embodiment has the following advantages: firstly, the limitation of the traditional monitoring mode on the visual angle and the picture of the monitoring video is overcome, and all people related to the case can be obtained. Secondly, the monitoring cost is reduced, and the popularization and the application are convenient. And thirdly, the monitoring process is more automatic, the artificial identification is avoided, the identification efficiency is greatly improved, the influence caused by subjective factors in the artificial identification is avoided, and the identification accuracy is improved. Fourthly, the influence caused by weather reasons is reduced, and the condition of omission caused by low definition of the monitoring picture caused by the weather reasons is reduced.
A monitoring system according to another embodiment of the present invention is described below with reference to fig. 2.
Fig. 2 shows a schematic structural diagram of another embodiment of the monitoring system of the present invention. As shown in fig. 2, on the basis of the embodiment shown in fig. 1, the monitoring system 20 in this embodiment further includes a video capture device 208, and the video capture device 208 can capture video images near the monitored area. The association device 106 is further configured to: judging whether an abnormal event occurs in the monitoring area according to the audio information, and associating the video image with the audio information; and calling a video image associated with the audio information when the abnormal event occurs in the monitored area, and determining the image information of the participators of the abnormal event through the associated video image.
In this embodiment, the audio capture device 104 may be an audio collector integrated in the video capture device 208. After the video capture device 208 captures the video images near the monitored area, the association device 106 may track and store the MAC address captured by the wireless network device 102, the video images monitored by the video capture device 208, and the audio information captured by the audio capture device 104. Specifically, during the track-merging storage, for a frame of video image monitored by the video acquisition device 208, the MAC address acquired by the wireless network device 102 and the audio information acquired by the audio acquisition device 104 may be stored in the index file of the video image in a track-merging manner according to the principle that the acquisition time, and the monitoring time are the same or similar. The MAC address and audio information may also be stored in an audio file or other file corresponding to the video image. And as long as the acquisition time of the MAC address and the acquisition time of the audio information are the same as the monitoring time of the video image, the three are stored in a rail combination way.
After the occurrence of an abnormal event such as a gathering party and the like is determined through the audio information, the image information of the personnel participating in the abnormal event can be determined through the video image which is recorded in a track-combining manner with the audio information. For example, wearing dressing of the abnormal event participants, the number of the abnormal event participants, the source and destination of the abnormal event participants, and the like, so as to facilitate case recovery and investigation and evidence collection.
For example, in a practical application scenario, the sound intensity data may be modeled in combination with the video image, the MAC address. The application model may include: firstly, identifying the number of people on site through video images, and judging whether the site is a mass activity or a personal help-seeking event through sound intensity; secondly, identifying the number of people on site in the area which cannot be covered by the video sector by combining Mac data, and identifying whether the site is mass or personal activity by sound intensity; and thirdly, judging the activity with which characteristics the scene belongs to according to the sound intensity change rule. In a data management platform, sound intensity sample data of multiple scenes (such as a crowd alarm, a concert, a parade, a personal distress call and the like) are set in advance, a Bayesian Discriminant model (Bayesian Discriminant) or a data mining model such as an Artificial Neural Network (Artificial Neural Network) and a Support Vector Machine (Support Vector Machine) is established, the situation of the scene occurrence is analyzed and judged in real time, and an early warning signal is sent out when an abnormal situation is found.
The monitoring method of one embodiment of the present invention is described below with reference to fig. 7.
Fig. 7 shows a schematic flow chart of an embodiment of the monitoring method of the present invention. As shown in fig. 7, the monitoring method in this embodiment includes:
step S702, collecting the MAC address of the terminal connected to the wireless network equipment in the monitoring area.
For example, several WIFI devices are deployed in a monitored area. After the terminal is connected to the WIFI equipment, the WIFI equipment can acquire the MAC address of the terminal. And the wireless network equipment sends each acquired MAC address and the acquisition time thereof to the associated equipment in real time.
Step S704, collecting audio information of the monitored area.
For example, audio capture devices are deployed in a monitored area. The audio acquisition equipment can acquire the audio information of the monitoring area in real time and send the acquired volume information and the acquisition time thereof to the associated equipment in real time.
Step S706, judging whether an abnormal event occurs in the monitoring area according to the audio information, and associating the MAC address with the audio information.
(a) The MAC address is associated with the audio information.
In associating a MAC address with audio information, it is necessary to associate the MAC address and the audio information collected at the same time. Therefore, the system time of the audio acquisition device and the system time of the wireless network device are synchronized, and then the received MAC address and the audio information are subjected to rail combination storage. When the audio files are stored in a track-bound mode, the MAC addresses and the audio information can be stored in the audio files or the index files of the audio files.
(b) And judging whether an abnormal event occurs in the monitoring area according to the audio information.
There are various bases for determining whether an abnormal event occurs in the monitoring area. One implementation is to determine whether the volume of the audio is greater than a preset volume value. And if the volume value is greater than the preset volume value, determining that an abnormal event occurs in the monitoring area.
For example, based on multi-site field simulation testing, it is known that: the sound intensity in quiet places is below 30 decibels, the sound intensity of people in normal conversations is 30-55 decibels, the sound intensity in streets and public places is 55-75 decibels, the sound intensity in noisy and hot crowd is about 80-90 decibels, and the sound intensity is generally above 90 decibels for screaming, cheering, asking for help and the like. According to the sound intensity distribution situations shown in fig. 3, 4 and 5, the audio information in fig. 6 can be analyzed, so that the situations of cheering and whooping in the monitored area can be obtained.
Another implementation is to obtain a sample frequency feature of the sample audio information corresponding to the abnormal event, and then compare the frequency feature of the audio information with the sample frequency feature. And if the frequency characteristics of the audio information are similar to the sample frequency characteristics, determining that an abnormal event occurs in the monitored area. .
For example, a frequency domain analysis algorithm is used for carrying out certain feature analysis on the collected audio, whether the features obtained through analysis are matched with the preset audio features of the gathering party is judged, or the features obtained through analysis are input into a trained model, the features obtained through analysis are matched with the preset audio features of the gathering party, or if the result output by the model is gathering, the gathering party is indicated. When the audio features of the gathering parties are preset, audio of a plurality of gathering parties collected historically can be used as samples, and the audio features of the gathering parties are preset according to the samples. When the model is trained, the audio collected historically by a plurality of gathering parties can be used as a training sample for training.
The order of the steps (a) and (b) may be adjusted according to actual needs. For example, the MAC address may be associated with audio information, and then whether an abnormal event occurs in the monitored area may be determined according to the audio information. And judging whether an abnormal event occurs in the monitoring area or not according to the audio information, and if the abnormal event occurs in the monitoring area, associating the MAC address with the audio information. That is, the occurrence of an abnormal event in the monitored area is taken as a trigger condition for associating the MAC address with the audio information.
Step 708, calling the MAC address associated with the audio information when the abnormal event occurs in the monitoring area, and determining the participant of the abnormal event according to the associated MAC address.
For example, for a situation that a party gathering may occur in a certain video image, corresponding volume information may be called, if the volume is greater than a preset threshold, it is indicated that an abnormal event such as a gathering may occur, at this time, a corresponding MAC address may be called, and the mobile phone number of a party gathering participant is determined through the terminal MAC address of the party gathering participant, so as to determine the identity of the party gathering participant.
In the embodiment, whether an abnormal event occurs is judged by using the monitoring audio, the MAC address of the electronic equipment carried by the suspect in the monitoring is determined by using the incidence relation between the monitoring audio and the MAC address detection data, and then the contact is positioned by searching and positioning the MAC address and the like, so that the monitoring of the abnormal event can be accurately and efficiently realized, and the personnel participating in the abnormal event are determined. Furthermore, the above embodiment has the following advantages: firstly, the limitation of the traditional monitoring mode on the visual angle and the picture of the monitoring video is overcome, and all people related to the case can be obtained. Secondly, the monitoring cost is reduced, and the popularization and the application are convenient. And thirdly, the monitoring process is more automatic, the artificial identification is avoided, the identification efficiency is greatly improved, the influence caused by subjective factors in the artificial identification is avoided, and the identification accuracy is improved. Fourthly, the influence caused by weather reasons is reduced, and the condition of omission caused by low definition of the monitoring picture caused by the weather reasons is reduced.
In one embodiment, the same time-collected MAC address and audio information are associated.
In one embodiment, the method further comprises:
step S705, a video image near the monitored area is acquired.
For example, video capture devices are deployed in a monitored area. The video acquisition equipment can acquire the audio information of the monitoring area in real time and send the acquired video image and the acquisition time thereof to the associated equipment in real time.
And step S707, judging whether an abnormal event occurs in the monitored area according to the audio information, and associating the video image with the audio information.
After the video images near the monitoring area are collected, the collected MAC addresses, the collected video images and the collected audio information can be stored in an integrated track mode.
Step S709, a video image associated with the audio information when the abnormal event occurs in the monitoring area is retrieved, and image information of a participant of the abnormal event is determined according to the associated video image.
After the occurrence of an abnormal event such as a gathering party and the like is determined through the audio information, the image information of the personnel participating in the abnormal event can be determined through the video image which is recorded in a track-combining manner with the audio information. For example, wearing dressing of the abnormal event participants, the number of the abnormal event participants, the source and destination of the abnormal event participants, and the like, so as to facilitate case recovery and investigation and evidence collection.
In one embodiment, the same time captured video image is associated with audio information.
During specific rail combination storage, aiming at a monitored frame of video image, the collected MAC address and the collected audio information can be stored in an index file of the video image in a rail combination mode according to the principle that the collection time, the collection time and the monitoring time are the same or similar. The MAC address and audio information may also be stored in an audio file or other file corresponding to the video image. And as long as the acquisition time of the MAC address and the acquisition time of the audio information are the same as the monitoring time of the video image, the three are stored in a rail combination way.
In one embodiment, the determining whether an abnormal event occurs in the monitored area according to the audio information includes: judging whether the volume of the audio is greater than a preset volume value or not; and if the volume value is greater than the preset volume value, determining that an abnormal event occurs in the monitoring area.
In one embodiment, the determining whether an abnormal event occurs in the monitored area according to the audio information includes: acquiring sample frequency characteristics of sample audio information corresponding to the abnormal event; comparing the frequency characteristics of the audio information to the sample frequency characteristics; and if the frequency characteristics of the audio information are similar to the sample frequency characteristics, determining that an abnormal event occurs in the monitored area. .
For example, in a practical application scenario, the sound intensity data may be modeled in combination with the video image, the MAC address. The application model may include: firstly, identifying the number of people on site through video images, and judging whether the site is a mass activity or a personal help-seeking event through sound intensity; secondly, identifying the number of people on site in the area which cannot be covered by the video sector by combining Mac data, and identifying whether the site is mass or personal activity by sound intensity; and thirdly, judging the activity with which characteristics the scene belongs to according to the sound intensity change rule. In a data management platform, sound intensity sample data of multiple scenes (such as a crowd alarm, a concert, a parade, a personal distress call and the like) are set in advance, a Bayesian Discriminant model (Bayesian Discriminant) or a data mining model such as an Artificial Neural Network (Artificial Neural Network) and a Support Vector Machine (Support Vector Machine) is established, the situation of the scene occurrence is analyzed and judged in real time, and an early warning signal is sent out when an abnormal situation is found.
It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program instructing relevant hardware, where the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (6)
1. A monitoring system, comprising: wireless network equipment, audio acquisition equipment and associated equipment; wherein the content of the first and second substances,
the wireless network device is to: collecting a Media Access Control (MAC) address of a terminal connected to wireless network equipment in a monitoring area;
the audio acquisition device is configured to: collecting audio information of a monitoring area;
the association device is configured to: judging whether an abnormal event occurs in the monitoring area or not according to the audio information, acquiring sample frequency characteristics of sample audio information corresponding to the abnormal event, comparing the frequency characteristics of the audio information with the sample frequency characteristics, if the frequency characteristics of the audio information are matched with the sample frequency characteristics, determining that the abnormal event occurs in the monitoring area, and associating the MAC address acquired at the same time with the audio information; and calling the MAC address associated with the audio information when the abnormal event occurs in the monitoring area, and determining the participators of the abnormal event according to the associated MAC address.
2. The system of claim 1, further comprising a video capture device for capturing video images of the vicinity of the monitored area;
the association device is further configured to:
judging whether an abnormal event occurs in the monitoring area according to the audio information, and associating the video image acquired at the same time with the audio information;
and calling a video image associated with the audio information when the abnormal event occurs in the monitoring area, and determining the image information of the participators of the abnormal event through the associated video image.
3. The system of claim 1, wherein the association device is to:
judging whether the volume of the audio is larger than a preset volume value or not;
and if the volume value is larger than the preset volume value, determining that an abnormal event occurs in the monitoring area.
4. A method of monitoring, comprising:
collecting a Media Access Control (MAC) address of a terminal connected to wireless network equipment in a monitoring area;
collecting audio information of a monitoring area;
judging whether an abnormal event occurs in the monitoring area or not according to the audio information, acquiring sample frequency characteristics of sample audio information corresponding to the abnormal event, comparing the frequency characteristics of the audio information with the sample frequency characteristics, if the frequency characteristics of the audio information are matched with the sample frequency characteristics, determining that the abnormal event occurs in the monitoring area, and associating the MAC address acquired at the same time with the audio information;
and calling the MAC address associated with the audio information when the abnormal event occurs in the monitoring area, and determining the participators of the abnormal event according to the associated MAC address.
5. The method of claim 4, wherein the method further comprises:
collecting video images near a monitoring area;
judging whether an abnormal event occurs in the monitoring area according to the audio information, and associating the video image acquired at the same time with the audio information;
and calling a video image associated with the audio information when the abnormal event occurs in the monitoring area, and determining the image information of the participators of the abnormal event through the associated video image.
6. The method of claim 4, wherein said determining whether an abnormal event occurs in the monitored area based on the audio information comprises:
judging whether the volume of the audio is larger than a preset volume value or not;
and if the volume value is larger than the preset volume value, determining that an abnormal event occurs in the monitoring area.
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| CN111091073A (en) * | 2019-11-29 | 2020-05-01 | 清华大学 | Abnormal event monitoring equipment and method combining video and audio |
| CN111556282A (en) * | 2020-03-16 | 2020-08-18 | 浙江大华技术股份有限公司 | System, method, computer equipment and storage medium for remote audio and video acquisition |
| CN111866454A (en) * | 2020-07-02 | 2020-10-30 | 广州博冠智能科技有限公司 | Sound and image linkage detection early warning method and device |
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