CN113727068A

CN113727068A - Explosion-proof type edge image computing equipment

Info

Publication number: CN113727068A
Application number: CN202110990805.5A
Authority: CN
Inventors: 刘云川; 郑光胜; 黄进凯; 蒋俊之; 叶明�; 杨正川
Original assignee: Beijing Baolong Hongrui Technology Co ltd
Current assignee: Beijing Baolong Hongrui Technology Co ltd
Priority date: 2021-08-26
Filing date: 2021-08-26
Publication date: 2021-11-30

Abstract

The invention provides explosion-proof edge image computing equipment, and relates to the technical field of artificial intelligence. The invention accelerates the rapid popularization, the copying and the iteration of projects, realizes the functions of the automatic deployment, the automatic expansion and contraction of the container cluster, the maintenance and the like, and enlarges the processing efficiency of the edge image computing equipment.

Description

Explosion-proof type edge image computing equipment

Technical Field

The invention belongs to the technical field of artificial intelligence, particularly relates to the field of edge image calculation, and relates to an explosion-proof edge image calculation device.

Background

Edge computing means that an open platform integrating network, computing, storage and application core capabilities is adopted on one side close to an object or a data source to provide nearest-end services nearby. The application program is initiated at the edge side, so that a faster network service response is generated, and the basic requirements of the industry in the aspects of real-time business, application intelligence, safety, privacy protection and the like are met. The edge computation is between the physical entity and the industrial connection, or on top of the physical entity. And the cloud computing still can access the historical data of the edge computing.

Edge calculation is not a fresh word. AKAMAI, a provider of content delivery networks CDN and cloud services, works with IBM for "edge computing" as early as 2003. Being one of the largest distributed computing services in the world, it was burdened with 15-30% of the world's network traffic at that time. The purpose and solution of "Edge computing" is proposed in one of its internal research projects, and Edge-based services are provided on its WebSphere by AKAMAI with IBM.

For the internet of things, the edge computing technology makes a breakthrough, which means that many controls are realized through local equipment without being handed to a cloud, and the processing process is completed in a local edge computing layer. This will undoubtedly promote the processing efficiency greatly, alleviate the load in the cloud. The need is addressed at the edge end by providing faster response for the user due to closer proximity to the user.

Edge computing devices are simply devices that process data in a large number of devices or software in the field. However, edge computing devices are not ordinary local computers or mobile devices that perform limited computing tasks on the edge, but rather edge platforms with cloud computing or storage functionality, only in the cloud or high-speed data center. Wherever your edge network is, at remote sites, at branch offices or at headquarters data centers, AI/ML analytics, mobile computing, edge computing devices will bring the cloud's intelligence closer to edge processing tasks, and even storage.

Edge computing devices are critical to optimizing IoT and IIoT devices and other applications by bringing computing power closer to the data source. Such edge computing hardware is an edge technology intended to reduce the telecommunication requirements between the server and the client. Ultimately reducing latency and improving security, reliability and bandwidth.

The device in the prior art has a large limitation on access, and cannot support the expansion of the device to the maximum extent, so that the existing device is very complicated and difficult to apply.

Disclosure of Invention

The invention aims to provide an explosion-proof edge image computing device, which can solve the problems that the edge image computing device in the prior art is difficult to realize automatic deployment of container clusters, has less automatic expansion and contraction capacity and cannot be maintained, and the processing efficiency of the edge image computing device is improved.

The embodiment of the invention is realized by the following steps:

the embodiment of the application provides an explosion-proof edge image computing device, which comprises a deployment container, a load balancer, a cache system, a distributed file system, a workflow engine, a scene intelligent analysis module and a third-party docking system, wherein the deployment container, the load balancer, the cache system, the distributed file system and the workflow engine are in signal connection, and the edge image computing device acquires streaming media data of the third-party docking system through a network cable or a data cable.

The third party docking system includes: USB camera, HDMI camera, network camera, AI cloud platform and cloud platform camera, USB camera and HDMI camera adopt the data line to be connected with explosion-proof type edge image computing equipment, and network camera, AI cloud platform and cloud platform camera adopt the net twine to be connected with explosion-proof type edge image computing equipment.

In some embodiments of the present invention, the deployment container is: automated container deployment in the manner of Docker + K8S.

In some embodiments of the present invention, the load balancer is: the Nginx with high load and high stability and the LVS with strong load resistance and stable work provide load balancing service together.

In some embodiments of the present invention, the cache system includes: redis and Memcache combined cache module.

In some embodiments of the present invention, the distributed file system is: and the FastDFS is combined to build the distributed file system.

In some embodiments of the invention, the workflow engine is: activiti is used as a workflow engine.

In some embodiments of the present invention, the third party docking system is: the third party provides a Web Service interface with related functions for the external connection of the system, so that other systems can call the video monitoring module provided by the system.

In some embodiments of the present invention, the operating voltage of the edge image computing device is 9-35V.

In some embodiments of the present invention, the content analyzed by the scene intelligent analysis module includes: the identification is dressed to personnel's labour protection, the identification is worn to the gauze mask, the identification is worn to the goggles, the useless identification is worn to the solid danger, monitor the equipment displacement, monitor leaving behind the object, to the detection of invasion of foreign language, the monitoring of butt joint cell-phone, to the smoking monitoring, to personnel's action identification, to the statistics of figures, to hoist and mount operation monitoring, to the operation monitoring of kindling, to the monitoring is worn to the aerial work safety belt, to the naked light cigarette naked light identification, to face identification, to the instrument identification, to tool setting brake switch identification, to vehicle license plate identification and to fatigue identification.

Compared with the prior art, the embodiment of the invention has at least the following advantages or beneficial effects:

in the invention, the third-party docking system supports various communication modes such as Restful API, socket, RPC, ros/rossbridge and the like, can exchange data with any system, further improves the application range of the equipment, and the deployment container, the load balancer, the cache system, the distributed file system and the workflow engine are all integrated on a main board in the equipment, thereby avoiding the delay generated when relevant modules process or exchange information to the maximum extent, further improving the overall calculation efficiency of the equipment, and the edge image calculation equipment acquires the streaming media data of the third-party docking system through a network cable or a data cable, and further improving the application range of the equipment. Due to the fact that the container is automatically deployed in a Docker + K8S mode, rapid popularization, copying and iteration of projects are accelerated, functions of automatic deployment, automatic expansion and contraction of container clusters, maintenance and the like are achieved, and processing efficiency of edge image computing equipment is improved. Because the Nginx with high load capacity and high stability and the LVS with strong load resistance and strong work stability are adopted to provide load balancing service, the Nginx has high load capacity and high stability, can bear high load pressure and is stable, the dependence on network stability is very small, and the performance is good under a high-flow environment; the LVS has strong load resistance and stable working performance, only distributes, does not generate extra flow, and has lower consumption on resources of a memory and a cpu. The invention reduces the access to the database in the application, improves the access speed of the application and reduces the load of the database because of adopting the cache module combining Redis and Memcache. Because a cache module combining Redis and Memcache is adopted, more complex data structures List, Set or Sorted Set are supported, and the data backup method has a persistence function and a data backup function. The high-speed searching capability of the data in the memory is provided, and the high-performance access to the data is ensured. Due to the adoption of the distributed file system constructed by the FastDFS combination, the files are distributed and managed, the files can be freely stored, synchronized, accessed, uploaded and downloaded, the problem of large-capacity storage is solved, the system has the mechanisms of redundant backup, load balancing, linear capacity expansion and the like, and the reliability of the system is improved while the high performance is ensured. Because Activiti is used as a workflow engine, business process modeling and marking specifications of BPMN2.0 are realized, and process scheduling can be performed through API (application programming interface), so that business can be performed according to a set process, and the business process can be updated on line, so that the system can be quickly adapted to business change development, and the system can be better maintained and expanded. The invention provides a Web Service interface with related functions for other systems to call the video monitoring module provided by the system, thereby facilitating the integration of video monitoring into an internal system by a client and realizing uniform management. The third-party docking system comprises the USB camera, the HDMI camera, the network camera, the AI cloud platform and the cloud platform camera, and the USB camera, the HDMI camera, the network camera, the AI cloud platform and the cloud platform camera are connected through a network, so that the application range of the invention is expanded.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.

FIG. 1 is a schematic diagram of an application scenario of an edge image computing device according to the present invention;

fig. 2 is a schematic structural diagram of an edge image computing apparatus according to the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations.

Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. 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 application.

It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.

In the description of the present application, it should be noted that the terms "upper", "lower", "inner", "outer", and the like indicate orientations or positional relationships based on orientations or positional relationships shown in the drawings or orientations or positional relationships conventionally found in use of products of the application, and are used only for convenience in describing the present application and for simplification of description, but do not indicate or imply that the referred devices or elements must have a specific orientation, be constructed in a specific orientation, and be operated, and thus should not be construed as limiting the present application.

In the description of the present application, it is also to be noted that, unless otherwise explicitly specified or limited, the terms "disposed" and "connected" are to be interpreted broadly, e.g., as being either fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in the present application can be understood in a specific case by those of ordinary skill in the art.

Some embodiments of the present application will be described in detail below with reference to the accompanying drawings. The embodiments described below and the individual features of the embodiments can be combined with one another without conflict.

Examples

Referring to fig. 1-2, the embodiment provides an explosion-proof edge image computing device, which includes a deployment container, a load balancer, a cache system, a distributed file system, a workflow engine, a scene intelligent analysis module, and a third party docking system. The third-party docking system supports various communication modes such as Restful API, socket, RPC, ros/rossbridge and the like, can exchange data with any system, further improves the application range of the equipment, and the deployment container, the load balancer, the cache system, the distributed file system and the workflow engine are all integrated on a mainboard inside the equipment, so that delay generated when relevant modules perform information processing or exchange information is avoided to the greatest extent, the overall calculation efficiency of the equipment is further improved, the edge image calculation equipment acquires streaming media data of the third-party docking system through a network cable or a data cable, and the application range of the equipment is further improved.

Further, in some embodiments of the present invention, the third party docking system includes: USB camera, HDMI camera, network camera, AI cloud platform and cloud platform camera, USB camera and HDMI camera adopt the data line to be connected with explosion-proof type edge image computing equipment, and network camera, AI cloud platform and cloud platform camera adopt the net twine to be connected with explosion-proof type edge image computing equipment, and the application range of edge image computing equipment has further been promoted to such relevant module of deployment and connection.

Further, in some embodiments of the present invention, the deployment container is: due to the fact that the container is automatically deployed in the Docker + K8S mode, rapid popularization, copying and iteration of projects are accelerated, functions of automatic deployment, automatic expansion and contraction, maintenance and the like of container clusters are achieved, and processing efficiency of edge image computing equipment is improved.

Further, in some embodiments of the present invention, the load balancer is: the Nginx with high load capacity and high stability and the LVS with high load resistance and strong work stability are adopted to provide the load balancing service together, so that the Nginx has high load capacity and high stability, can bear high load pressure and is stable, the dependence on network stability is very small, and the performance is good under a high-flow environment; the LVS has strong load resistance and stable working performance, only distributes, does not generate extra flow, and has lower consumption on resources of a memory and a cpu.

Further, in some embodiments of the present invention, the cache system includes: the combined cache module of Redis and Memcache adopts the combined cache module of Redis and Memcache, so that the invention reduces the access to the database in the application, improves the access speed of the application and reduces the load of the database.

Further, in some embodiments of the present invention, the distributed file system is: the distributed file system constructed by combining the FastDFS adopts a cache module combining the Redis and the Memcache, supports more complex data structures List, Set or signed Set, and has a persistence function and a data backup function. The high-speed searching capability of the data in the memory is provided, and the high-performance access to the data is ensured.

Further, in some embodiments of the present invention, the workflow engine is: the method adopts Activiti as a workflow engine, realizes business process modeling and labeling specification of BPMN2.0 by adopting Activiti as the workflow engine, can perform process scheduling through API, enables business to be performed according to set processes, can update business processes on line, enables the system to be quickly adapted to business change development, and ensures better maintenance and expansion of the system.

Further, in some embodiments of the present invention, the third party docking system is: the Web Service interface providing the related functions for the external connection of the third party is used by other systems to call the video monitoring module provided by the system, and the Web Service interface providing the related functions is used by other systems to call the video monitoring module provided by the system, so that the video monitoring is integrated into the internal system by a client conveniently, and the unified management is realized.

Further, in some embodiments of the present invention, the operating voltage of the edge image computing device is 9 to 35V, and since most of application scenes of the edge image computing device are in an area without stable power supply, and secondly, specifications of the power interface are many, in order to extend the application range of the edge device, a 9 to 35V power supply is provided for the edge device in the present application, so as to prepare for accessing the edge image computing device, and improve the operating range of the edge image computing device while ensuring the stable operation of the edge image computing device.

Further, in some embodiments of the present invention, the content analyzed by the scene intelligence analysis module includes: the identification is dressed to personnel's labour protection, the identification is worn to the gauze mask, the identification is worn to the goggles, the useless identification is worn to the solid danger, monitor the equipment displacement, monitor leaving behind the object, to the detection of invasion of foreign language, the monitoring of butt joint cell-phone, to the smoking monitoring, to personnel's action identification, to the statistics of figures, to hoist and mount operation monitoring, to the operation monitoring of kindling, to the monitoring is worn to the aerial work safety belt, to the naked light cigarette naked light identification, to face identification, to the instrument identification, to tool setting brake switch identification, to vehicle license plate identification and to fatigue identification.

In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The apparatus embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

In addition, functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.

The working principle is as follows:

and starting the explosion-proof edge image computing equipment, driving the cache system, the distributed file system and the content deployment container by the workflow engine at the same time, sending various data read by the cache system and the distributed file system from the third-party access system to the scene intelligent analysis module for analysis, marking corresponding labels on the analyzed data respectively, classifying the data of the corresponding labels through the content deployment container after the analysis is finished, and writing the classified data into the distributed file system again. When the cache system works, the load balancer monitors the working state of the cache system, distributes cache reading distribution in the cache system and keeps the cache system in a safe and healthy working state. The deployment container can also carry out the automatic deployment of the container cluster in the working process, and the interior of the container can be automatically expanded and maintained according to the requirement.

The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.

It will be evident to those skilled in the art that the present application is not limited to the details of the foregoing illustrative embodiments, and that the present application may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.

Claims

1. The explosion-proof edge image computing equipment is characterized by comprising a deployment container, a load balancer, a cache system, a distributed file system, a workflow engine, a scene intelligent analysis module and a third-party docking system, wherein the deployment container, the load balancer, the cache system, the distributed file system and the workflow engine are in signal connection, and the edge image computing equipment acquires streaming media data of the third-party docking system through a network cable or a data cable.

2. An explosion-proof edge image computing apparatus according to claim 1, wherein: the third party docking system includes: USB camera, HDMI camera, network camera, AI cloud platform and cloud platform camera, USB camera and HDMI camera adopt the data line to be connected with explosion-proof type edge image computing equipment, network camera, AI cloud platform and cloud platform camera adopt the net twine to be connected with explosion-proof type edge image computing equipment.

3. An explosion-proof edge image computing apparatus according to claim 1, wherein: the deployment vessel is: automated container deployment in the manner of Docker + K8S.

4. An explosion-proof edge image computing apparatus according to claim 1, wherein: the load balancer is as follows: the Nginx with high load and high stability and the LVS with strong load resistance and stable work provide load balancing service together.

5. An explosion-proof edge image computing apparatus according to claim 1, wherein: the cache system is as follows: redis and Memcache combined cache module.

6. An explosion-proof edge image computing apparatus according to claim 1, wherein: the distributed file system is as follows: and the FastDFS is combined to build the distributed file system.

7. An explosion-proof edge image computing apparatus according to claim 1, wherein: the workflow engine is as follows: activiti is used as a workflow engine.

8. An explosion-proof edge image computing apparatus according to claim 1, wherein: the third-party docking system comprises: the third party docking system provides a Web Service interface with related functions for other systems to call the video monitoring module provided by the system.

9. An explosion-proof edge image computing apparatus according to claim 1, wherein: the working voltage of the edge image computing equipment is 9-35V.

10. An explosion-proof edge image computing apparatus according to claim 1, wherein: the content analyzed by the scene intelligent analysis module comprises: the identification is dressed to personnel's labour protection, the identification is worn to the gauze mask, the identification is worn to the goggles, the useless identification is worn to the solid danger, monitor the equipment displacement, monitor leaving behind the object, to the detection of invasion of foreign language, the monitoring of butt joint cell-phone, to the smoking monitoring, to personnel's action identification, to the statistics of figures, to hoist and mount operation monitoring, to the operation monitoring of kindling, to the monitoring is worn to the aerial work safety belt, to the naked light cigarette naked light identification, to face identification, to the instrument identification, to tool setting brake switch identification, to vehicle license plate identification and to fatigue identification.