CN111210150A - Intelligent park system based on edge calculation - Google Patents
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Abstract
The invention relates to the technical field of smart cities, in particular to a smart park system based on edge computing, which comprises a central server and a park server, wherein the park server is used for sending a data request; the central server is used for receiving the data request and acquiring the instantaneity requirement and bandwidth pressure of the data request. If the bandwidth pressure acquired by the central server is greater than a first threshold value and the instantaneity requirement of the data request is low, the central server arranges the data request into a waiting sequence; and after the central server acquires that the bandwidth pressure of the park server corresponding to the target is smaller than a second threshold value, the central server sends the data request to the corresponding park server according to the park server information of the target in the data request. The invention ensures the processing time delay of the data request with high instantaneity requirement through the instantaneity requirement of the data request and the judgment of the bandwidth pressure, and can reduce the network bandwidth pressure between the central server and the park server in the peak period.
Description
Technical Field
The invention relates to the technical field of smart cities, in particular to a smart park system based on edge computing.
Background
The large-scale manufacturing group company is required for business development, and mostly adopts the operation mode of building a plurality of factories. The information system is generally arranged in a group headquarters, the information construction work is planned and raised by the group headquarters in a unified way, and each factory area accesses the group information system through a special line or the Internet. With the advance of the business construction of the intelligent park of the enterprise, the business scenes accessed by each park are more and more, and higher requirements are provided for the real-time computing and processing capacity, the storage capacity and the private network bandwidth of the information system of the headquarters of the group.
In this regard, document CN109544052A discloses an intelligent community management system based on an edge computing server of the internet of things, which includes: perception layer, network layer, operation layer, platform layer and application layer, the perception layer is including a plurality of wisdom hardware, and the perception layer passes through the network layer and uploads the data of wisdom hardware to the operation layer, and the intraformational edge calculation server of operation is handled data, the platform layer is wisdom community cloud platform, and the operation layer is connected through multicast technique and platform layer establishment, the application layer is wisdom community cloud platform's mutual entry, the application layer includes a plurality of application module, realizes different interactive control. The invention solves the problems of low intellectualization degree and low safety factor of the conventional community management system.
However, in the existing intelligent community management system, under the condition of huge data volume processing, due to the large bandwidth pressure, the problems that the factory service processing time delay is difficult to reduce and the network bandwidth pressure is difficult to reduce can occur.
Disclosure of Invention
The invention solves the technical problems that the existing intelligent community management system is difficult to reduce factory service processing time delay and network bandwidth pressure, and provides an intelligent park system based on edge computing.
The basic scheme provided by the invention is as follows: an intelligent park system based on edge computing comprises a central server and a park server, wherein the park server is used for sending a data request; the central server is used for receiving the data request and acquiring the instantaneity requirement of the data request, the data request comprises the information of the target park server, and the central server is also used for acquiring the bandwidth pressure of the target park server. If the bandwidth pressure acquired by the central server is greater than a first threshold value and the instantaneity requirement of the data request is low, the central server arranges the data request into a waiting sequence; and after the central server acquires that the bandwidth pressure of the park server corresponding to the target is smaller than a second threshold value, the central server sends the data request to the corresponding park server according to the park server information of the target in the data request.
The working principle of the invention is as follows: after receiving the data request, the central server obtains the timeliness requirement of the data request and the information of the target park server in the data request, and then the central server obtains the bandwidth pressure information between the central server and the park server. If the central server judges that the instantaneity requirement of the data request is low and the bandwidth pressure between the central server and the target park server is also larger (larger than a first threshold), the central server arranges the data request into a waiting sequence and does not process the data request firstly. Between the park servers and the central server, the information interaction in the working period is very much, which results in that the bandwidth pressure between the central server and each park server is relatively large (the main reason is that the data volume generated in the working period of one park is very large due to the construction of an intelligent factory). But during periods of non-operation, bandwidth pressure dips may occur. Therefore, in the present invention, the central server processes the data request in the waiting sequence after acquiring the bandwidth pressure (less than the second threshold) with the target campus server. The method and the system have the advantages that the information with low instantaneity requirement can not occupy the channel resources of the information with high instantaneity requirement at the peak moment, and the bandwidth pressure between the central server and the park server is reduced in a peak staggering interaction mode.
According to the intelligent park system based on edge computing, disclosed by the invention, through the instantaneity requirement on the data request and the judgment on the bandwidth pressure, the processing time delay of the data request with high instantaneity requirement is ensured, namely, the time delay of the data request with high instantaneity requirement (more factory service information) is reduced, and the network bandwidth pressure between the central server and the park server in a peak period can be reduced.
Further, the data request comprises a visitor request, the visitor request comprising visitor identity information or vehicle information. Meanwhile, the personal identity information or the vehicle information of the visitor is reported, so that the visitor can be confirmed to be reserved to the maximum extent; thereby reducing the error rate of the reported information.
Further, the system also comprises a camera module which is used for collecting the information of the visitor or the vehicle. The camera module is used for collecting information of the visitor or the vehicle only by photographing or recording a video, so that the method is quick, convenient and fast, high in accuracy and short in information collection waiting time of the visitor.
The system further comprises a protocol adaptation module used for receiving the visitor or vehicle information collected by the camera module; and analyzing the access equipment and the access protocol of the target park, and opening a gateway to allow the visitor to pass. In a computer network, many protocols may be involved, and different protocols may operate at different network levels. The parsing of the different access devices and access protocols facilitates accurate and efficient subsequent processing of the visitor's personal or vehicle information.
The system further comprises an edge processing module used for analyzing and processing the access data and reporting the analysis and processing result. The access data is analyzed and processed, such as video data structured analysis, and the video content is organized into text information or visual graphic information which can be understood by computers and people by adopting processing means such as space-time segmentation, feature extraction, object recognition, deep learning and the like. Therefore, the huge number of videos collected by the group service access processing module can be refined, and the videos are changed into high-density data which are easier to search, occupy smaller memory and can be deeply mined, so that the searching and troubleshooting efficiency is greatly improved.
Further, the edge processing module is also used for storing the processed data into a corresponding structured data warehouse. Therefore, corresponding retrieval engines such as a face photo and feature library, a vehicle image and feature library can be established, so that various information collected by the group service access processing module is deeply mined, and the data analysis and prediction functions are fully improved.
And the edge processing module is used for processing the face recognition or the vehicle recognition by adopting an algorithm and returning the recognition result to the edge processing module. The reported image is identified and corrected by using the algorithm, and the key fields are extracted, so that manual input can be reduced, and the working efficiency is improved. Whether the personnel operate for the real living body; the method can effectively discriminate the fraudulent behavior and guarantee the benefit of the user.
Further, algorithms adopted by the algorithm module comprise an OCR algorithm, a face recognition algorithm and a living body detection algorithm. Optical Character Recognition (OCR) refers to a process of analyzing and recognizing an image file of text data to obtain text and layout information. By using the OCR technology, the images reported by the group service access processing module are identified and corrected, key fields are extracted, manual input can be reduced, and the working efficiency is improved. The face recognition is a biological recognition technology for carrying out identity recognition based on face feature information of people, and the technology can acquire a face image of a visitor in an unconscious state and also can carry out sorting, judgment and recognition on a plurality of faces; simple operation and intuitive result. The living body detection is a method for determining the real physiological characteristics of an object, and the human face key point positioning and human face tracking technology is used for verifying whether a visitor operates as a real living body per se; the method can effectively discriminate the fraudulent behavior and guarantee the benefit of the user.
Further, the system also comprises an offline data synchronization module which is used for synchronizing the original data received by the edge processing module to the central server in an offline manner according to the configuration strategy. This is beneficial to reduce the impact on normal service period bandwidth traffic and reduce processing pressure.
Further, the camera module adopts a cloud camera. The cloud camera is based on a cloud computing platform, a cloud monitoring platform and a cloud storage platform, and can provide a wireless network camera with high-definition image quality monitoring. The system can be operated independently without connecting a computer, and workers can monitor the instant dynamic images of visitors and vehicles at any place through a browser, so that the convenience and the practicability of the workers are improved.
Drawings
FIG. 1 is a block diagram of a first embodiment of an intelligent park system based on edge computing.
Fig. 2 is a block diagram of the system structure of a second embodiment and a third embodiment of the intelligent park system based on edge computing according to the present invention.
Detailed Description
The following is further detailed by the specific embodiments:
example one
An embodiment of an intelligent campus system based on edge computing according to the present invention is shown in fig. 1, and includes a campus server and a central server. After receiving the data request, the central server obtains the timeliness requirement of the data request and the information of the target park server in the data request, and then the central server obtains the bandwidth pressure information between the central server and the park server. If the central server judges that the instantaneity requirement of the data request is low and the bandwidth pressure between the central server and the target park server is also larger (larger than a first threshold), the central server arranges the data request into a waiting sequence and does not process the data request firstly. Between the park servers and the central server, the information interaction in the working period is very much, which results in that the bandwidth pressure between the central server and each park server is relatively large (the main reason is that the data volume generated in the working period of one park is very large due to the construction of an intelligent factory). But during periods of non-operation, bandwidth pressure dips may occur. After acquiring the bandwidth pressure (smaller than a second threshold value) with the target campus server, the central server processes the data request in the waiting sequence. The method and the system have the advantages that the information with low instantaneity requirement can not occupy the channel resources of the information with high instantaneity requirement at the peak moment, and the bandwidth pressure between the central server and the park server is reduced in a peak staggering interaction mode.
Example two
The difference from the first embodiment is that the system further includes a camera module, a protocol adaptation module, an edge processing module, an algorithm module, and an offline data synchronization module, as shown in fig. 2.
The park server adopts a Dall (DELL) R730/R7402U rack server, and visitors can register and reserve in a visitor access system of the park server and upload and register visitor identity card information or vehicle information and the like. When a visitor arrives at a gate of a park for reserved access, the cloud camera automatically shoots images and video information of the visitor vehicle and the visitor, and uploads the images and the video information to the protocol adaptation module (namely when the visitor does not make a reservation, the visitor can be recorded in a park server, and reservation information which does not pass through a central server is called as recorded information), and the cloud camera adopts a DS-2DC4120 intelligent ball machine produced by Haokwev.
The protocol adaptation module adopts a Royu star continent 4E1 protocol converter, analyzes different access equipment and access protocols after receiving visitor or vehicle information collected by the cloud camera, and submits the analyzed result to the edge processing module.
The edge processing module adopts a falcon video cloud structured server developed by Haikangwei to receive data submitted by the protocol adaptation module, firstly carries out logical scheduling processing on the access service of the park, and then carries out video data structured analysis processing on the access data. The method comprises the steps of carrying out structured extraction on important information in video content, and organizing the video content into text information or visual graphic information which can be understood by a computer and people by adopting processing means such as space-time segmentation, feature extraction, object recognition, deep learning and the like. Therefore, the huge number of videos collected by the group service access processing module can be refined and changed into high-density data which is easier to search, occupies smaller memory and can be deeply mined, and therefore the searching and troubleshooting efficiency is greatly improved. And when the bandwidth pressure between the edge processing module and the central server is small, the edge processing module uploads the recording information to the central server for recording.
The algorithm module adopts an Intel W-3175X processor and is loaded with AIocr face recognition software developed by Baidu corporation. And performing face recognition or vehicle recognition by adopting an OCR algorithm, and returning a recognition result to the edge processing module. If the reserved vehicle and the reserved visitor are identified, the edge processing module returns the identification result to the protocol adaptation module; if the visitor is not reserved, the edge processing module gives an alarm prompt. And after the protocol adaptation module receives the identification result, the protocol adaptation module matches the protocol to open the gateway to allow the visitor to pass.
The offline data synchronization module adopts an Intel i9-9980XE core 18 thread processor, and when the raw data received by the edge processing module is received, the raw data is uploaded to the central server offline according to the business requirement.
The central server adopts a Lenovo SR860 type server, acquires the timeliness requirement of the data request and the information of the target park server in the data request after receiving the data request, and then acquires the bandwidth pressure information between the central server and the park server. If the central server judges that the instantaneity requirement of the data request is low and the bandwidth pressure between the central server and the target park server is also larger (larger than a first threshold), the central server arranges the data request into a waiting sequence and does not process the data request firstly. Between the park servers and the central server, the information interaction in the working period is very much, which results in that the bandwidth pressure between the central server and each park server is relatively large (the main reason is that the data volume generated in the working period of one park is very large due to the construction of an intelligent factory). But during periods of non-operation, bandwidth pressure dips may occur. Thus, the central server processes the data request in the wait sequence after acquiring the bandwidth pressure (less than the second threshold) with the target campus server. The method and the system have the advantages that the information with low instantaneity requirement can not occupy the channel resources of the information with high instantaneity requirement at the peak moment, and the bandwidth pressure between the central server and the park server is reduced in a peak staggering interaction mode.
EXAMPLE III
Compared with the two embodiments, the difference is that after the edge processing module analyzes and processes the access data, the processed data is stored in the corresponding structured data warehouse, and the corresponding search engine, such as a face photo and feature library, a vehicle image and a feature library, is established, so that the deep mining of various information collected by the group service access processing module is realized, and the functions of analyzing and predicting the data are fully improved. The Intel W-3175X processor adopted by the algorithm module is also provided with Luxand Face SDK software and ArcFace3.0 software. The Luxand Face SD is Face recognition software, adopts a biological recognition technology for carrying out identity recognition based on Face feature information of people, can acquire Face images of visitors in an unconscious state, and can also carry out sorting, judgment and recognition on a plurality of faces; simple operation and intuitive result. ArcFace3.0 is a piece of living body detection software, and is used for verifying whether a visitor operates as a real person or not by determining the real physiological characteristics of an object and using a face key point positioning and face tracking technology; the method can effectively discriminate the fraudulent behavior and guarantee the benefit of the user.
Example four
The difference from the third embodiment is only that: the device also comprises a pressure sensor arranged on the ground of the gate of the garden; a rear camera is also arranged above the gate of the garden. The pressure sensor adopts a 10 t-grade weighing sensor (mainly aiming at visiting private vehicles and small-sized load-carrying vehicles, the weight is usually 1-9t) produced by Suzhou Tai Heng weighing equipment Limited company and is used for collecting the total weight of the visiting vehicles when entering and exiting a gate of a park; the rear camera adopts a VRT-Q11-11 type wireless camera and is used for shooting the specific conditions in the interior and the tail box of the visiting vehicle under the condition that constraint conditions are met. The park server is also configured to receive an interview event registered by the visitor at the time of the appointment and a predicted change in vehicle weight (m 1).
When a visiting vehicle enters and exits from a park doorway, the cloud cameras can acquire vehicle information, the pressure sensors can acquire total weight m2 and total weight m3 when the visiting vehicle enters and exits respectively, and the total weight data are sent to a park server. When the park server receives the total weight data (m2 and m3) of the visiting vehicle during entering and exiting collected by the pressure sensor, comparing the total weight data with the total weight data, and if the total weight of the visiting vehicle during entering and exiting is not in and exiting, normally releasing the visiting vehicle; if the total weight of the access is m4, and m4 is m1, the access is reasonable, and the vehicle can normally pass; if m4 is not equal to m1, a signal is sent to a rear camera which is installed at a position behind the barrier and can shoot the interior, the trunk and the like of the visiting vehicle, the shot video is sent to a park server, and then the barrier is opened for passing. Before the barrier gate is opened to pass, a signal can be sent to enable a worker to observe whether an abnormal condition exists or not. Therefore, the rear camera does not need to be started all the time, on one hand, energy is saved, and data redundancy is reduced; and on the other hand, the visitor can normally pass through the system, and related film and television evidence is left.
For example, when the visiting vehicle is a taxi and the visitor is a taxi, the total weight of the taxi entering and exiting the gate of the park is definitely different. If m1 is m4, the rear camera does not need to shoot the taxi interior and the taxi tail box, but if m1 is not equal to m4 and the difference value exceeds the threshold value, the rear camera is started to shoot, and the shot video is sent to a zone server, so that a worker can conveniently observe whether an abnormal condition exists. As another example, when the visiting vehicle is a truck or lorry, it goes to the park for loading or unloading. The total weight detected by the sensors at the entrance to and exit from the gate of the campus is different, and the difference in total weight is not consistent with the weight of the loaded or unloaded cargo (i.e., m4 is not equal to m 1). The camera can shoot this freight train or truck to take the garden server with the video transmission of shooing, whether the staff of being convenient for observes abnormal conditions such as steal fortune material.
The foregoing is merely an example of the present invention, and common general knowledge in the field of known specific structures and characteristics is not described herein in any greater extent than that known in the art at the filing date or prior to the priority date of the application, so that those skilled in the art can now appreciate that all of the above-described techniques in this field and have the ability to apply routine experimentation before this date can be combined with one or more of the present teachings to complete and implement the present invention, and that certain typical known structures or known methods do not pose any impediments to the implementation of the present invention by those skilled in the art. It should be noted that, for those skilled in the art, without departing from the structure of the present invention, several changes and modifications can be made, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the practicability of the patent. The scope of the claims of the present application shall be determined by the contents of the claims, and the description of the embodiments and the like in the specification shall be used to explain the contents of the claims.
Claims (10)
1. The utility model provides an wisdom garden system based on edge calculation, includes central server and garden server, its characterized in that: the park server is used for sending a data request; the central server is used for receiving the data request and acquiring the instantaneity requirement of the data request, the data request comprises the information of the target park server, and the central server is also used for acquiring the bandwidth pressure of the target park server;
if the bandwidth pressure acquired by the central server is greater than a first threshold value and the instantaneity requirement of the data request is low, the central server arranges the data request into a waiting sequence; and after the central server acquires that the bandwidth pressure of the park server corresponding to the target is smaller than a second threshold value, the central server sends the data request to the corresponding park server according to the park server information of the target in the data request.
2. The intelligent campus system based on edge computing of claim 1 wherein: the data request comprises a visitor request including visitor identity information or vehicle information.
3. The intelligent campus system based on edge computing of claim 2 wherein: the system also comprises a camera module used for collecting the information of the visitor or the vehicle.
4. The intelligent park system based on edge computing of claim 3, wherein: the protocol adaptation module is used for receiving the visitor or vehicle information acquired by the camera module; and analyzing the access equipment and the access protocol of the target park, and opening a gateway to allow the visitor to pass.
5. The intelligent campus system based on edge computing of claim 4 wherein: the device also comprises an edge processing module which is used for analyzing and processing the access data and reporting the analysis and processing result.
6. The intelligent campus system based on edge computing of claim 5 wherein: the edge processing module is also used for storing the processed data into a corresponding structured data warehouse.
7. The intelligent campus system based on edge computing of claim 6 wherein: the system also comprises an algorithm module which is used for carrying out face recognition or vehicle recognition by adopting an algorithm and returning a recognition result to the edge processing module.
8. The intelligent campus system based on edge computing of claim 7 wherein: algorithms adopted by the algorithm module comprise an OCR algorithm, a face recognition algorithm and a living body detection algorithm.
9. The intelligent edge-computing-based campus system of claim 8 wherein: the system also comprises an offline data synchronization module which is used for synchronizing the original data received by the edge processing module to the central server in an offline manner according to the configuration strategy.
10. The intelligent park system based on edge computing of claim 3, wherein: the camera module adopts a cloud camera.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| WO2022120872A1 (en) * | 2020-12-11 | 2022-06-16 | 南京大衍数字科技有限公司 | Edge computing-based smart community security monitoring system |
| CN115278315A (en) * | 2022-09-27 | 2022-11-01 | 南京鼎尔特科技有限公司 | Visual safety management intelligent operation and maintenance platform |
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| CN109639586A (en) * | 2018-12-05 | 2019-04-16 | 量子云未来（北京）信息科技有限公司 | A kind of data transmission method, apparatus and system |
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| CN109639586A (en) * | 2018-12-05 | 2019-04-16 | 量子云未来（北京）信息科技有限公司 | A kind of data transmission method, apparatus and system |
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