CN110827164A - Intelligent aquaculture management system and method based on edge cloud - Google Patents
Intelligent aquaculture management system and method based on edge cloud Download PDFInfo
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- CN110827164A CN110827164A CN201911113370.5A CN201911113370A CN110827164A CN 110827164 A CN110827164 A CN 110827164A CN 201911113370 A CN201911113370 A CN 201911113370A CN 110827164 A CN110827164 A CN 110827164A
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Abstract
The invention relates to a smart aquaculture management system and method based on edge cloud, wherein the system comprises: the global center is used for uniformly managing the plurality of edge cloud centers, is also used for uniformly arranging the application on a container platform or a traditional platform, pushes the edge cloud platform application to automatically pull up through an application arrangement template, and is also used for automatically pushing an artificial intelligence computing model; the edge cloud center is used for managing the farm in the area and collecting data, preprocessing and pre-judging the data, transmitting the structured data back to the global center, and returning the calculation result of the simple service to the upper application of the user. The invention has the beneficial effects that: a. the system can be flexibly deployed around a farm, the high deployment requirement of the traditional intelligent culture system is reduced, and the defects of slow data transmission and complex calculation are improved; b. the system can process various types of data such as video data and text data at the same time, and performs full-ring data collection, thereby facilitating management and monitoring.
Description
Technical Field
The invention belongs to the field of edge computing, and particularly relates to an intelligent aquaculture management system and method based on edge cloud.
Background
The intelligent farming system of the aquaculture industry faces many challenges. For example, how to complete the informatization of multiple breeding links on the premise of reducing the labor; how to store and analyze the received data. The traditional intelligent culture system is high in data acquisition difficulty, marginalized in calculation and analysis, high in manual support cost and incapable of achieving real intelligent culture.
Disclosure of Invention
In order to solve the technical problems, the invention provides an intelligent aquaculture management system and method based on edge cloud.
The technical scheme for solving the technical problems is as follows: an edge cloud based smart aquaculture management system comprising:
the global center is used for uniformly managing the plurality of edge cloud centers, is also used for uniformly arranging the application on a container platform or a traditional platform, pushes the edge cloud platform application to automatically pull up through an application arrangement template, and is also used for automatically pushing an artificial intelligence computing model;
the edge cloud center is used for managing the farm in the area and collecting data, preprocessing and pre-judging the data, transmitting the structured data back to the global center, and returning the calculation result of the simple service to the upper application of the user.
In order to achieve the above object, the present invention further provides a smart aquaculture management method based on edge cloud, comprising:
the global center uniformly manages a plurality of edge cloud centers, is responsible for uniformly arranging the application on a container platform or a traditional platform, pushes the edge cloud platform application to automatically pull up through an application arrangement template, and is responsible for automatically pushing an artificial intelligence computing model;
the edge cloud center manages and collects data of the farm in the area, preprocesses and pre-judges the data, transmits the structured data back to the global center, and returns the calculation result of the simple service to the upper application of the user.
The invention has the beneficial effects that:
a. the system can be flexibly deployed around a farm, the high deployment requirement of the traditional intelligent culture system is reduced, and the defects of slow data transmission and complex calculation are improved;
b. the system can process various types of data such as video data and text data at the same time, and performs full-ring data collection, thereby facilitating management and monitoring.
Drawings
FIG. 1 is a system architecture diagram of an intelligent aquaculture management system based on edge clouds according to an embodiment of the present invention;
FIG. 2 is a diagram of a hardware connection structure of an intelligent aquaculture platform according to an embodiment of the present invention;
FIG. 3 is a diagram of components of a local compute node in an intelligent aquaculture system according to an embodiment of the present invention.
Detailed Description
The principles and features of this invention are described below in conjunction with the following drawings, which are set forth by way of illustration only and are not intended to limit the scope of the invention.
Fig. 1 is a system architecture diagram of an intelligent aquaculture management system based on edge cloud according to an embodiment of the present invention, as shown in fig. 1, the system hierarchy design includes a global center and an edge cloud center. The global center uniformly manages a plurality of edge cloud centers. Meanwhile, the global center is also responsible for the uniform arrangement of the application on the container platform or the traditional platform; an application arrangement template is pushed to push the edge cloud platform application to automatically pull up; and automatically pushing an artificial intelligence calculation model.
The edge cloud management center is responsible for farm management and data collection in the area, preprocesses and judges data, transmits structured data back to the global center, and returns the calculation result of the simple service to the upper application of the user.
Fig. 2 is a hardware connection structure diagram of an intelligent aquaculture platform according to an embodiment of the present invention, and as shown in fig. 2, the platform architecture design includes an internet of things infrastructure, a local computing node, a remote cloud platform, an application orchestration, an OSS/BSS, and an upper application.
The Internet of things infrastructure comprises Internet of things equipment such as automatic environment monitoring, automatic equipment electrification control and high-definition video camera shooting.
The local computing node is responsible for storage, analysis and computation of local multimedia data. For example, after the water quality monitoring data is generated, the local edge computing node performs preprocessing and only sends the structured information to the remote cloud platform.
The remote cloud platform comprises a control node, a computing node, a storage node and a virtual network element interface and is responsible for data record storage, intelligent analysis and statistics and remote personnel management and monitoring.
The OSS/BSS is an operation support system and a business support system, and comprises modules of customer relationship management, a data acquisition system, billing and accounting, comprehensive settlement and marketing support.
The cloud platform application orchestration supports application orchestration of container platforms and legacy platforms. The application editing template of the remote cloud platform is applicable to various platforms, automatic pushing and unmanned manual intervention configuration. The method has the advantages of self-arrangement, self-push and self-adaptive configuration, and achieves real automation.
The upper application mainly comprises user functions such as personnel management monitoring, WeChat small programs, artificial intelligence application and the like; a deep learning and machine learning model component is added in the upper-layer application to analyze data and predict results, the deep learning and machine learning application is a high-grade application and can predict and analyze various types of data, a big data calculation template can be automatically pushed to each sub-platform, and the sub-platforms automatically adjust configuration to meet the calculation results of the calculation template.
FIG. 3 is a diagram of components of a local compute node in an intelligent aquaculture system according to an embodiment of the present invention. Compare with traditional wisdom breed platform, increased local calculation node.
The local computing node comprises an edge gateway and business components thereof, and is composed of local storage, analysis, function computation, a rule engine and the like. The edge gateway enhances the computing power of the local computing node, and some simple business logic directly processes and returns information to the user equipment at the edge node.
The remote cloud platform remotely manages the local computing nodes by calling the StarlingX API. The system is mainly responsible for equipment management, component management and node management of local computing nodes, automatic pushing application arrangement and self-adaptive deployment without manual monitoring and deployment. The local computing node also exchanges structured data with the cloud platform by calling the StarlingX API to meet the user business logic.
Meanwhile, the remote cloud platform also calls remote operation management and equipment management through a StarlingX API, and monitors whether the operation of personnel is standard or not. The remote cloud platform comprises business components such as storage, big data, middleware, artificial intelligence and the like besides the edge computing management component. And the remote cloud platform undertakes a big data computing model training task. The task components comprise cloud model training, edge data analysis, data cloud storage and cloud device control. Through machine learning and deep learning, the optimal solution of the calculation model is predicted and simulated, and the trained calculation template can be automatically pushed to each edge platform in the future to automatically adjust and deploy equipment.
The edge cloud center and the remote cloud platform are integrated in an open API mode, and calling between the local computing node and the remote cloud platform is facilitated. Whether manual operation can be standardized or not can be remotely monitored and managed, all data are collected from the putting condition of shrimp fries, the using condition of feed to the capturing condition of mature shrimps and the like, and all links are realized, and the data can be circulated.
Compared with the prior art, the invention has the following characteristics:
i. compared with the traditional intelligent culture system, the intelligent culture system has the advantages that due to the addition of the edge computing technology, the shrimps, objects and people in the shrimp farm can be brought into the information management with a lower labor cost; and the isolation among subsystems is broken, and a physical foundation and an information infrastructure are connected. The operation is simple, and the management of a specially-assigned person is not needed;
ii, the novel intelligent aquaculture system greatly improves the calculation feedback speed, utilizes the characteristic that the edge gateway has calculation capacity, preprocesses data and transmits the data to a remote end for analysis, so that managers can immediately obtain the analysis and feedback of the data and can make adjustment in time; the edge gateway has a plurality of interfaces, so that the data of various media, such as pictures, videos and structured data, can be received conveniently, and the storage and calculation of multimedia data are realized;
the novel intelligent aquaculture system can plan and assemble adapters in a unified mode according to requirements, data interaction between the sensors and the information system is broken through, and all sensing hardware is managed in a unified mode.
The reader should understand that in the description of this specification, reference to the description of the terms "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the modules and units in the above described system embodiment may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of a unit is merely a logical division, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed.
Units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment of the present invention.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit 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 invention essentially or partially contributes to the prior art, or all or part of the technical solution can 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 invention. 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.
While the invention has been described with reference to specific embodiments, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. An intelligent aquaculture management system based on edge cloud, comprising:
the global center is used for uniformly managing the plurality of edge cloud centers, is also used for uniformly arranging the application on a container platform or a traditional platform, pushes the edge cloud platform application to automatically pull up through an application arrangement template, and is also used for automatically pushing an artificial intelligence computing model;
the edge cloud center is used for managing the farm in the area and collecting data, preprocessing and pre-judging the data, transmitting the structured data back to the global center, and returning the calculation result of the simple service to the upper application of the user.
2. The intelligent aquaculture management system based on edge cloud as claimed in claim 1, wherein said global center comprises:
the remote cloud platform comprises a control node, a computing node, a storage node and a virtual network element interface and is responsible for data record storage, intelligent analysis and statistics and remote personnel management and monitoring;
the OSS/BSS operation support system and the business support system comprise a customer relationship management module, a data acquisition system module, a charging and accounting module, a comprehensive settlement module and a marketing support module;
the application arrangement module is used for supporting the application arrangement of a container platform and a traditional platform;
and the upper-layer application comprises a personnel management monitoring module, a WeChat small program module and an artificial intelligence application module.
3. The intelligent aquaculture management system based on edge cloud as claimed in claim 1 wherein said edge cloud center comprises local computing nodes;
the local compute node includes an edge gateway, a local storage component, a streaming analysis component, a function computation component, and a rules engine component.
4. The intelligent aquaculture management system based on edge cloud of claim 3 wherein the remote cloud platform is specifically responsible for the local computing node device management, component management, node management, remote operations management, undertaking big data computing model training tasks, automatic push application orchestration and adaptive deployment.
5. The intelligent aquaculture management system based on edge cloud as claimed in claim 3 or 4, wherein the remote cloud platform and the local computing node interact by calling StarlingX API interface.
6. An intelligent aquaculture management method based on edge cloud is characterized by comprising the following steps:
the global center uniformly manages a plurality of edge cloud centers, is responsible for uniformly arranging the application on a container platform or a traditional platform, pushes the edge cloud platform application to automatically pull up through an application arrangement template, and is responsible for automatically pushing an artificial intelligence computing model;
the edge cloud center manages and collects data of the farm in the area, preprocesses and pre-judges the data, transmits the structured data back to the global center, and returns the calculation result of the simple service to the upper application of the user.
7. The intelligent aquaculture management method based on edge cloud as claimed in claim 6, wherein the global center comprises:
the remote cloud platform comprises a control node, a computing node, a storage node and a virtual network element interface and is responsible for data record storage, intelligent analysis and statistics and remote personnel management and monitoring;
the OSS/BSS operation support system and the business support system comprise a customer relationship management module, a data acquisition system module, a charging and accounting module, a comprehensive settlement module and a marketing support module;
the application arrangement module supports the application arrangement of a container platform and a traditional platform;
and the upper-layer application comprises a personnel management monitoring module, a WeChat small program module and an artificial intelligence application module.
8. The intelligent aquaculture management method based on edge cloud as claimed in claim 6 wherein said edge cloud center comprises local computing nodes;
the local compute node includes an edge gateway, a local storage component, a streaming analysis component, a function computation component, and a rules engine component.
9. The intelligent aquaculture management method based on edge cloud of claim 8 wherein the remote cloud platform is specifically responsible for the local computing node device management, component management, node management, remote operation management, undertaking big data computing model training tasks, automatic push application orchestration and adaptive deployment.
10. The intelligent aquaculture management method based on edge cloud as claimed in claim 8 or 9, wherein the remote cloud platform and the local computing node interact by calling StarlingX API interface.
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