CN113206935A - Campus dual-prevention security prevention and control cloud platform and method - Google Patents
Campus dual-prevention security prevention and control cloud platform and method Download PDFInfo
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- CN113206935A CN113206935A CN202110392715.6A CN202110392715A CN113206935A CN 113206935 A CN113206935 A CN 113206935A CN 202110392715 A CN202110392715 A CN 202110392715A CN 113206935 A CN113206935 A CN 113206935A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
- H04N7/181—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a plurality of remote sources
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/02—Protocols based on web technology, e.g. hypertext transfer protocol [HTTP]
- H04L67/025—Protocols based on web technology, e.g. hypertext transfer protocol [HTTP] for remote control or remote monitoring of applications
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
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- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
- H04L67/125—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks involving control of end-device applications over a network
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- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/55—Push-based network services
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
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Abstract
The invention provides a campus dual-prevention security prevention and control cloud platform and a campus dual-prevention security prevention and control cloud method. This safety prevention and control cloud platform includes: the system comprises a cloud server, a local computing core cluster and a plurality of monitoring systems arranged in a campus; the campus is composed of a plurality of first areas, and each first area is composed of a plurality of second areas; each monitoring system comprises an edge node arranged in a first area and a plurality of acquisition devices respectively arranged in second areas, wherein each acquisition device comprises a dual-optical camera and an RFID reader; the acquisition equipment in each second area is in communication connection with the corresponding edge node in the first area; each edge node in the monitoring systems is in communication connection with a local computing core cluster through a campus internal network, and the local computing core cluster is in communication connection with the cloud server.
Description
Technical Field
The invention relates to the technical field of security and protection monitoring, in particular to a campus dual-prevention security and control cloud platform and a campus dual-prevention security and control cloud method.
Background
In recent years, the safety of the campus is more and more emphasized by people, in recent years, due to extension, the density of students is increased, the guarantee pressure of the campus safety is more and more large, the traditional security monitoring mainly excavates towards video stream data, and the campus garden environment is monitored manually or automatically to make situation judgment. However, the campus monitoring still has the following problems: (1) the method mainly comprises local centralized monitoring, weak support for mobile access, inconvenience for access during duty and insufficient intelligence of notification ways; (2) the existing monitoring equipment mainly uses visible light images, and the obtained information has limitation; (3) the method is mainly realized through optics in the aspect of judging the identity of a person, and has certain limitation; (4) collected data is not fully utilized, and deep analysis and mining of the data are lacked.
Disclosure of Invention
Aiming at the problem that the traditional security monitoring supports weak mobile access, the invention provides a campus dual-prevention security control cloud platform and a campus dual-prevention security control cloud method.
In one aspect, the invention provides a campus dual-prevention security prevention and control cloud platform, which comprises: the system comprises a cloud server, a local computing core cluster and a plurality of monitoring systems arranged in a campus; the campus is composed of a plurality of first areas, and each first area is composed of a plurality of second areas;
each monitoring system comprises an edge node arranged in a first area and a plurality of acquisition devices respectively arranged in second areas, wherein each acquisition device comprises a dual-optical camera and an RFID reader; the acquisition equipment in each second area is in communication connection with the corresponding edge node in the first area;
each edge node in the monitoring systems is in communication connection with a local computing core cluster through a campus internal network, and the local computing core cluster is in communication connection with the cloud server.
Further, the local compute core cluster includes: the data acquisition service module, the data storage service module and the data analysis module are sequentially connected;
the data collection service module is used for receiving data uploaded by each edge node;
the data storage service module comprises a video storage service unit and a video related record storage service unit;
the data analysis module is used for analyzing according to the data stored in the data storage service module and providing an API (application programming interface) and a cloud service, access and remote control interface;
and the cloud server performs data interaction with the local computing core cluster through the cloud service, access and remote control interface.
On the other hand, the invention also provides a security prevention and control method based on the campus dual-prevention security prevention and control cloud platform, which comprises the following steps:
the method comprises the steps that acquisition equipment acquires infrared imaging data, visible light data and RFID label data of personnel and/or vehicles and sends the acquired data to an edge node;
the edge node performs data processing on the data sent by the acquisition equipment and uploads a data processing result to the local computing core cluster; the data processing result comprises: mixing the marked composite video stream image, the regional security evaluation indexes of the second regions, the regional security evaluation indexes of the first regions and the overall regional security evaluation index of the campus;
the local computing core cluster stores and analyzes data processing results uploaded by each edge node, and uploads stored related data to the cloud server according to user settings;
the local computing core cluster and/or the cloud server receives an access control request of a user and provides related access control services for the user.
Further, the edge node performs data processing on the data sent by the acquisition device, and specifically includes:
the edge node forms the infrared thermal imaging video stream and the visible light video stream of each second area into RGBT double-light composite video stream through a video superposition algorithm;
aiming at each double-light composite image of the RGBT double-light composite video stream, the edge node performs composite processing on the double-light composite image and corresponding RFID label data to obtain an original image, a composite image video stream, the region safety index of each second region, image annotation data and other processing results;
for each composite image in the composite image video stream, the edge node associates the corresponding image annotation data in a layer overlapping manner to form a composite video stream image with mixed annotation;
and the edge node collects the area safety indexes of the second areas according to the area safety indexes of the second areas and a set collection model to obtain the area safety indexes of the first areas, and further collects the area safety indexes of the first areas to obtain the total area safety index of the campus.
Further, before the edge node performs data processing on the data sent by the acquisition equipment, the edge node also performs preliminary preprocessing on the data sent by the acquisition equipment; the preliminary pretreatment comprises the following steps: image transformation, content extraction, compression, format conversion, simple model processing and mode judgment.
Further, the local computing core cluster and/or the cloud server receives an access control request of a user, and provides a relevant access control service to the user, specifically including:
the method comprises the steps that a local computing core cluster and/or a cloud server receive a situation display request of a user and provide a situation display interface for the user; the interface displayed by the situation comprises: regional risk index information, patrol suggestion information, map information, and composite video walls.
Further, the method further comprises:
if the edge node identifies a risk source or a potential risk source after data processing is carried out on data sent by the acquisition equipment, submitting risk to a local computing core cluster node;
the local computing core cluster node sends an alarm after receiving the risk submitted by the edge node; pushing an alarm to the cloud server according to the user setting;
and after receiving the alarm pushed by the local computing core cluster node, the cloud server sends the alarm to related personnel and/or systems in a set alarm communication mode.
The invention has the beneficial effects that:
(1) in the aspect of video imaging, the amount of video information is improved through the infrared thermal imaging and visible light imaging mixed image, and the data is conveniently analyzed and evaluated by performing targeted processing on personnel and vehicles;
(2) in the aspect of personnel and vehicle identification, the related targets and states are accurately grasped in a mode of combining video and RFID, and a basis is provided for analysis and processing;
(3) through the cloud platform technology, remote access support is provided, the on-duty personnel and the remote monitoring personnel can conveniently access, and meanwhile, the intelligence of message notification is realized through a message communication push system and an early warning rule.
(4) According to the sensor and the cloud platform data, the data are analyzed and mined, and further the security situation is mastered.
Drawings
Fig. 1 is a schematic diagram of data acquired by an acquisition device according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a monitoring system according to an embodiment of the present invention;
fig. 3 is a schematic partial structural view of a campus dual-prevention security control cloud platform according to an embodiment of the present invention;
fig. 4 is a schematic diagram illustrating a cloud server providing remote user access according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a local compute core cluster according to an embodiment of the present invention;
fig. 6 is a schematic flow chart illustrating a campus dual prevention and security control method according to an embodiment of the present invention;
fig. 7 is a schematic flow chart of data processing performed by an edge node according to an embodiment of the present invention;
FIG. 8 is a schematic diagram of image annotation data provided in accordance with an embodiment of the present invention;
FIG. 9 is a fusion diagram of regional safety indices provided by an embodiment of the present invention;
FIG. 10 is a schematic illustration of a situational display provided by an embodiment of the present invention;
fig. 11 is a schematic diagram of a security alarm provided in the embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly described below with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. 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.
With reference to fig. 1 to 5, an embodiment of the present invention provides a campus dual-prevention security control cloud platform, including: the system comprises a cloud server, a local computing core cluster and a plurality of monitoring systems arranged in a campus; the campus is composed of a plurality of first areas, and each first area is composed of a plurality of second areas; each monitoring system comprises an edge node arranged in a first area and a plurality of acquisition devices respectively arranged in second areas, wherein each acquisition device comprises a dual-optical camera and an RFID reader; the acquisition equipment in each second area is in communication connection with the corresponding edge node in the first area; each edge node in the monitoring systems is in communication connection with a local computing core cluster through a campus internal network, and the local computing core cluster is in communication connection with the cloud server.
Specifically, the local computation core cluster is used for processing, storing the data computed and acquired by the edge node, and analyzing and processing the data; and transmitting the key data to the cloud server, receiving the control of the cloud server, providing corresponding service for the cloud server, and receiving local access and control.
The cloud server is used for receiving remote access of the user and sending push to the user; and also to provide additional computational support locally. The cloud server can manage a plurality of monitoring networks for centralized management, and can also map the account of the local computing core cluster to the cloud server to form a digital twin, so that corresponding information can still be acquired when the user is separated from the local environment.
The acquisition equipment and the edge nodes are interconnected through a network interface, on one hand, the cloud server can access each edge node in real time through the local computing core cluster; on the other hand, the edge node can provide data and processing results for the cloud server through the network.
One or more local computing core clusters are connected to the cloud server and exchange related data with the cloud server, and external equipment is connected to the cloud server through the Internet and the like to enjoy services provided by the cloud server, so that access to the local computing core clusters is achieved.
According to the campus dual-prevention safety prevention and control cloud platform provided by the embodiment of the invention, the dual-optical camera and the RFID reader-writer are used for carrying out combined collection, collected targets are people and vehicles, and collected data comprise infrared thermal imaging data, visible light data and RFID label data. It will be appreciated that the campus has previously issued RFID tags for personnel and vehicles as object identification tags. And (4) acquiring through a gridding mode, namely each group of acquisition equipment is only responsible for a certain grid area, and the acquisition equipment corresponds to the area. And the double-optical camera and the RFID reader-writer send the acquired data to the corresponding edge node for corresponding processing.
The acquisition equipment of a plurality of areas is subjected to primary processing by a certain edge node, and mainly performs certain conversion, content extraction, compression, format conversion, simple model processing, mode judgment and the like on RFID data, infrared thermal imaging data and visible light data. Wherein: the transformation refers to image basic transformation, including image basic transformation such as amplification, reduction, filtration, color mapping, inversion and the like; the content extraction refers to image content extraction operations such as background elimination, target enhancement, cutout and the like; compression refers to an operation of reducing the storage volume of an image; format conversion refers to an operation of converting from one image identification format to another image identification format; simple model processing refers to operations such as noise reduction, image quality improvement, edge enhancement, face recognition and the like by using image processing mathematics and a machine learning model; the mode judgment refers to the operation of using a mode algorithm to specifically enhance or weaken a specific mode; it is understood that the image processing such as transformation, content extraction, compression, format conversion, simple model processing, mode judgment, etc. can be performed by the corresponding existing plug-in.
It should be noted that, the user can organize the relationship between the region and the edge node by himself or herself as needed, and flexibly organize the structure of the system according to the actual scene and need.
On the basis of the foregoing embodiment, as shown in fig. 5, the structure of the local computing core cluster provided in the embodiment of the present invention includes a data collection service module, a data storage service module, and a data analysis module, which are connected in sequence; the data collection service module is used for receiving data uploaded by each edge node; the data storage service module comprises a video storage service unit and a video related record storage service unit; the data analysis module is used for analyzing according to the data stored in the data storage service module and providing an API (application programming interface) and a cloud service, access and remote control interface; and the cloud server performs data interaction with the local computing core cluster through the cloud service, access and remote control interface.
Specifically, the user uses the relevant services provided by the system through a user interaction interface, and the user interaction interface is realized through interfaces such as an API (application programming interface), a cloud platform and the like.
As shown in fig. 6 to 10, an embodiment of the present invention further provides a security prevention and control method for a campus dual-prevention security prevention and control cloud platform, including the following steps:
s101: the method comprises the steps that acquisition equipment acquires infrared imaging data, visible light data and RFID label data of personnel and/or vehicles and sends the acquired data to an edge node;
s102: the edge node performs data processing on the data sent by the acquisition equipment and uploads a data processing result to the local computing core cluster; the data processing result comprises: mixing the marked composite video stream image, the regional security evaluation indexes of the second regions, the regional security evaluation indexes of the first regions and the overall regional security evaluation index of the campus;
as an implementation manner, the edge node performs data processing on the data sent by the acquisition device, as shown in fig. 7 to 9, specifically including:
the edge node forms the infrared thermal imaging video stream and the visible light video stream of each second area into RGBT double-light composite video stream through a video superposition algorithm;
specifically, the step focuses on stream merging, which means single frame merging or merging of front and back frames based on some feature (such as time domain, frequency domain, optical flow, thermal feature, optical feature) correlation. The video superposition algorithm refers to an algorithm for forming an image with both infrared thermal imaging and visible light image information by mixing image signals of the infrared thermal imaging and the visible light image in a specific mode based on common characteristics of the infrared thermal imaging and the visible light image. It can be understood that the corresponding video overlay plug-in can be selected for overlay according to the needs of the user.
Aiming at each double-light composite image of the RGBT double-light composite video stream, the edge node performs composite processing on the double-light composite image and corresponding RFID label data to obtain an original image, a composite image video stream, the region safety index of each second region, image annotation data and other processing results;
specifically, this step focuses on single frame processing. The composite processing refers to a processing flow which utilizes related source data, calls a processing plug-in purchased by a user according to user setting (such as a video processing flow chart), processes related data in parallel or in series, and finally outputs a corresponding form result according to the user setting, wherein the processing flow can be nested recursively.
In practical application, the existing machine learning model related to the scene, which can be obtained by scene-oriented design according to the feature information contained in the image, can be adopted to evaluate the data to obtain the regional safety index. The facing scenario may include: number of people, density of people, behavior pattern of people, fall detection, detection of heat anomalies, and the like. The correlation degrees calculated by each model facing different scenes are weighted, averaged and the like to obtain a series of regional safety indexes such as risk index, crowd safety index, trampling index and the like, so that a manager can quickly find problems.
For each composite image in the composite image video stream, the edge node associates the corresponding image annotation data in a layer overlapping manner to form a composite video stream image with mixed annotation;
and the edge node collects the area safety indexes of the second areas according to the area safety indexes of the second areas and a set collection model to obtain the area safety indexes of the first areas, and further collects the area safety indexes of the first areas to obtain the total area safety index of the campus.
S103: the local computing core cluster stores and analyzes data processing results uploaded by each edge node, and uploads stored related data to the cloud server according to user settings;
s104: the local computing core cluster and/or the cloud server receives an access control request of a user and provides related access control services for the user.
As an implementable embodiment, the local computing core cluster and/or the cloud server receives an access control request of a user, and provides a relevant access control service to the user, specifically including:
the method comprises the steps that a local computing core cluster and/or a cloud server receive a situation display request of a user and provide a situation display interface for the user; as shown in fig. 10, the interface displayed by the situation includes: regional risk index information, patrol suggestion information, map information, and composite video walls.
Specifically, the regional risk index information is used for discovering risks in time; the inspection suggestion information is used for facilitating the inspection of the inspection personnel; the map information is used for displaying the campus panorama in a map mode; the composite video wall is used for directly checking the actual conditions of all areas of the campus and the results after video processing.
On the basis of the above embodiment, as an implementable manner, before the edge node performs data processing on the data sent by the acquisition device, the edge node further performs preliminary preprocessing on the data sent by the acquisition device. The preliminary pretreatment comprises the following steps: image transformation, content extraction, compression, format conversion, simple model processing and mode judgment.
On the basis of the foregoing embodiments, as shown in fig. 11, the security prevention and control method provided in the embodiments of the present invention further includes:
if the edge node identifies a risk source or a potential risk source after data processing is carried out on data sent by the acquisition equipment, submitting risk to a local computing core cluster node;
the local computing core cluster node sends an alarm after receiving the risk submitted by the edge node; pushing an alarm to the cloud server according to the user setting;
specifically, the user setting refers to a setting related to a push alert, such as a notification manner, a notification frequency, a notification content, a notifiable time, and the like.
And after receiving the alarm pushed by the local computing core cluster node, the cloud server sends the alarm to related personnel and/or systems in a set alarm communication mode.
According to the campus dual-prevention safety prevention and control cloud platform and the campus dual-prevention safety prevention and control cloud method, the positions and the densities of the personnel are sensed through the dual-optical video and RFID tag technology, the platform is used for safety accident prevention and analysis, a sensing scheme is provided for campus safety accident prevention, and the platform and the method have certain reference significance for campus safety prevention and control.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (7)
1. Dual prevention safety of campus prevents accuse cloud platform, its characterized in that includes: the system comprises a cloud server, a local computing core cluster and a plurality of monitoring systems arranged in a campus; the campus is composed of a plurality of first areas, and each first area is composed of a plurality of second areas;
each monitoring system comprises an edge node arranged in a first area and a plurality of acquisition devices respectively arranged in second areas, wherein each acquisition device comprises a dual-optical camera and an RFID reader; the acquisition equipment in each second area is in communication connection with the corresponding edge node in the first area;
each edge node in the monitoring systems is in communication connection with a local computing core cluster through a campus internal network, and the local computing core cluster is in communication connection with the cloud server.
2. The campus double prevention, security, control cloud platform of claim 1, wherein the local compute core cluster comprises: the data acquisition service module, the data storage service module and the data analysis module are sequentially connected;
the data collection service module is used for receiving data uploaded by each edge node;
the data storage service module comprises a video storage service unit and a video related record storage service unit;
the data analysis module is used for analyzing according to the data stored in the data storage service module and providing an API (application programming interface) and a cloud service, access and remote control interface;
and the cloud server performs data interaction with the local computing core cluster through the cloud service, access and remote control interface.
3. The campus dual-prevention security control cloud platform security control method based on claim 1 or 2, comprising:
the method comprises the steps that acquisition equipment acquires infrared imaging data, visible light data and RFID label data of personnel and/or vehicles and sends the acquired data to an edge node;
the edge node performs data processing on the data sent by the acquisition equipment and uploads a data processing result to the local computing core cluster; the data processing result comprises: mixing the marked composite video stream image, the regional security evaluation indexes of the second regions, the regional security evaluation indexes of the first regions and the overall regional security evaluation index of the campus;
the local computing core cluster stores and analyzes data processing results uploaded by each edge node, and uploads stored related data to the cloud server according to user settings;
the local computing core cluster and/or the cloud server receives an access control request of a user and provides related access control services for the user.
4. The security prevention and control method according to claim 3, wherein the edge node performs data processing on the data sent by the acquisition device, and specifically comprises:
the edge node forms the infrared thermal imaging video stream and the visible light video stream of each second area into RGBT double-light composite video stream through a video superposition algorithm;
aiming at each double-light composite image of the RGBT double-light composite video stream, the edge node performs composite processing on the double-light composite image and corresponding RFID label data to obtain an original image, a composite image video stream, the region safety index of each second region, image annotation data and other processing results;
for each composite image in the composite image video stream, the edge node associates the corresponding image annotation data in a layer overlapping manner to form a composite video stream image with mixed annotation;
and the edge node collects the area safety indexes of the second areas according to the area safety indexes of the second areas and a set collection model to obtain the area safety indexes of the first areas, and further collects the area safety indexes of the first areas to obtain the total area safety index of the campus.
5. The safety prevention and control method according to claim 3 or 4, wherein before the edge node performs data processing on the data sent by the acquisition device, the method further comprises performing preliminary preprocessing on the data sent by the acquisition device; the preliminary pretreatment comprises the following steps: image transformation, content extraction, compression, format conversion, simple model processing and mode judgment.
6. The security prevention and control method according to claim 3, wherein the local computing core cluster and/or the cloud server receives an access control request from a user, and provides a relevant access control service to the user, and specifically includes:
the method comprises the steps that a local computing core cluster and/or a cloud server receive a situation display request of a user and provide a situation display interface for the user; the interface displayed by the situation comprises: regional risk index information, patrol suggestion information, map information, and composite video walls.
7. The security prevention and control method of claim 3, further comprising:
if the edge node identifies a risk source or a potential risk source after data processing is carried out on data sent by the acquisition equipment, submitting risk to a local computing core cluster node;
the local computing core cluster node sends an alarm after receiving the risk submitted by the edge node; pushing an alarm to the cloud server according to the user setting;
and after receiving the alarm pushed by the local computing core cluster node, the cloud server sends the alarm to related personnel and/or systems in a set alarm communication mode.
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| CN113938508A (en) * | 2021-09-13 | 2022-01-14 | 杭州大杰智能传动科技有限公司 | Low-delay communication method and system for remote control of intelligent tower crane |
| CN113938508B (en) * | 2021-09-13 | 2023-06-02 | 杭州大杰智能传动科技有限公司 | Low-delay communication method and system for intelligent tower crane remote control |
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