CN116069299A - API-based Internet of things big data front end management method and system - Google Patents
API-based Internet of things big data front end management method and system Download PDFInfo
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- CN116069299A CN116069299A CN202310208958.9A CN202310208958A CN116069299A CN 116069299 A CN116069299 A CN 116069299A CN 202310208958 A CN202310208958 A CN 202310208958A CN 116069299 A CN116069299 A CN 116069299A
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- G16Y—INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE INTERNET OF THINGS [IoT]
- G16Y40/00—IoT characterised by the purpose of the information processing
- G16Y40/10—Detection; Monitoring
Abstract
The invention provides a method and a system for managing big data front end of Internet of things based on an API (application program interface), wherein the system comprises the following steps: the system comprises an input unit, a data acquisition unit, a data analysis unit and a data interface unit; the input unit is used for inputting basic information and FSU equipment information of the existing equipment of the target place and binding the relation between the acquisition equipment and the FSU equipment; the data acquisition unit is used for receiving real-time monitoring data acquired by the FSU equipment; the data analysis unit is used for carrying out classification management and analysis according to the acquired monitoring data to obtain classification statistical data and data analysis results; the data interface unit is used for providing an access interface for a user to access the required data through the access interface. The method and the system are beneficial to improving convenience and high efficiency of platform management of the Internet of things.
Description
Technical Field
The invention relates to the technical field of application of the Internet of things, in particular to an API-based method and system for managing big data front ends of the Internet of things.
Background
There are more and more internet of things platforms in society, which are focused on the industry, and the platforms are complex and popular. But each industry needs to build an application platform of the internet of things, which accords with the characteristics of the industry, an enterprise manager cannot quickly respond to the application change of the platform, and a large amount of development time is used for communication among the enterprise manager, professional technicians and programmers. Therefore, an enterprise needs a development tool capable of rapidly realizing the application of the internet of things by users to meet the requirements of the generation of the application platform of the internet of things in different industries and scenes.
Disclosure of Invention
Aiming at the problems, the invention aims to provide an API-based method and system for managing big data front ends of the Internet of things.
The aim of the invention is realized by adopting the following technical scheme:
in a first aspect, the present invention provides an API-based driving internet of things big data front end management system, comprising: the system comprises an input unit, a data acquisition unit, a data analysis unit and a data interface unit;
the input unit is used for inputting basic information and FSU equipment information of the existing equipment of the target place and binding the relation between the acquisition equipment and the FSU equipment;
the data acquisition unit is used for receiving real-time monitoring data acquired by the FSU equipment;
the data analysis unit is used for carrying out classification management and analysis according to the acquired monitoring data to obtain classification statistical data and data analysis results;
the data interface unit is used for providing an access interface for a user to access the required data through the access interface.
In one embodiment, the system further comprises a large screen display unit;
the large screen display unit is used for displaying the large screen according to the real-time monitoring data, the classified statistical data and the data analysis result of the system.
In one embodiment, the system further comprises a device creation unit;
the device creation unit is used for creating a category of the device.
In one embodiment, the target site includes an oil depot, an oil station.
In one embodiment, the input unit comprises a device input unit, a station library input unit and an expert input unit;
the equipment input unit is used for inputting basic information and FSU equipment information of all equipment of the oil station, wherein the basic information of the equipment comprises a station library to which the equipment belongs;
the station library input unit is used for inputting relevant information of the station library, including configuring the corresponding relation between the gas station equipment and the FSU equipment;
the expert input unit is used for inputting maintenance expert information corresponding to the equipment.
In one embodiment, the system further comprises a video monitoring unit;
the video monitoring unit is used for configuring a camera arranged in the oil station, receiving video monitoring data acquired by the camera and displaying the video monitoring data.
In one embodiment, the system further comprises a management unit, wherein the management unit comprises a metadata management unit and a model management unit;
the metadata management unit is used for collecting metadata of the source data and the target database and uniformly managing the metadata of the database table;
the model management unit is used for managing the data statistical model and the data analysis model used in the data analysis unit.
In a second aspect, the present invention provides a method for managing big data front end of internet of things based on API driver, including:
s1, creating by the equipment: creating a class of devices;
s2, equipment input: inputting basic information, FSU equipment information and equipment binding FSU data of the existing equipment of an oil depot and an oil station;
s3, data acquisition: performing classification management and analysis according to the acquired monitoring data to obtain classification statistical data and data analysis results;
s4, data analysis: performing classification management and analysis according to the acquired monitoring data to obtain classification statistical data and data analysis results;
s5, data interface: providing an access interface for a user to access the required data through the access interface;
s6, large screen display: and carrying out large-screen display according to the real-time monitoring data, the classified statistical data and the data analysis result of the system.
In one embodiment, the method further comprises: s7, video monitoring: and configuring a camera arranged in the oil station, receiving video monitoring data acquired by the camera, and displaying the video monitoring data.
In one embodiment, the method further comprises:
s8, metadata management: collecting metadata of source data and a target database, and uniformly managing the metadata of a database table;
s9, model management: and managing a data statistical model and a data analysis model for data analysis.
The beneficial effects of the invention are as follows: according to the system and the method for managing the big data front end of the Internet of things based on the API driver, through managing the accessed original data, information such as the table structure, the fields, the indexes, the main external keys and the like in the service system can be conveniently and rapidly inquired and managed, and online multi-person collaborative data modeling analysis is realized. The platform manages model development by establishing project management, and can realize the effect of API interface/capacity multiplexing, thereby being beneficial to improving the convenience and the high efficiency of the platform management of the Internet of things.
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The invention will be further described with reference to the accompanying drawings, in which embodiments do not constitute any limitation of the invention, and other drawings can be obtained by one of ordinary skill in the art without inventive effort from the following drawings.
Fig. 1 is a frame structure diagram of an internet of things big data front end management system based on an API driver according to an exemplary embodiment of the present invention;
fig. 2 is a flowchart illustrating a method for managing big data front ends of internet of things based on an API driver according to an exemplary embodiment of the present invention.
Detailed Description
The invention is further described in connection with the following application scenario.
Referring to fig. 1, an API-based system for managing big data of internet of things includes: the system comprises an input unit, a data acquisition unit, a data analysis unit and a data interface unit;
the input unit is used for inputting basic information and FSU equipment information of the existing equipment of the oil depot and the oil station, and binding the relation between the acquisition equipment and the FSU equipment;
the data acquisition unit is used for receiving real-time monitoring data acquired by the FSU equipment; the monitoring data comprise equipment state monitoring data, equipment signal monitoring data and equipment fault reporting data;
the data analysis unit is used for carrying out classification management and analysis according to the acquired monitoring data to obtain classification statistical data and data analysis results; the data analysis result comprises real-time fault information, real-time alarm information and the like;
the data interface unit is used for providing an access interface for a user to access the required data through the access interface.
In a scene, provincial summary information in the authority range can be checked through a data analysis unit, wherein the provincial summary information comprises equipment statistics, maintenance work order statistics, station library area distribution statistics, equipment production classification statistics, equipment maintenance amount statistics, equipment quantity statistics, maintenance level statistics and the like.
In one embodiment, the system further comprises a large screen display unit;
the large screen display unit is used for displaying a large screen according to real-time monitoring data, classified statistical data and data analysis results of the system; the method comprises the steps of displaying the data of the destination site of the city, displaying the real-time fault information, real-time alarm information and work order processing information.
In a scene, the large screen display unit is used for a large screen display, and can intuitively see the key summary analysis information of the whole province, including equipment statistics, alarm statistics, accumulated faults, fault distribution, real-time monitoring, whole province monitoring, ground city monitoring and the like.
In one embodiment, the system further comprises a device creation unit;
the device creation unit is used for creating a category of the device.
In a scene, the equipment comprises a generator, an oiling machine, a fire extinguisher oil-water separation tank, an oil tank, a leakage detector, a video monitoring system and the like. The equipment comprises production equipment, technical protection equipment, production auxiliary equipment, environmental protection equipment, office equipment and the like; the apparatus is an apparatus belonging to an oil station/oil station. By setting FSU codes, equipment binds FSU numbers to be collected.
In one embodiment, the target site includes an oil depot, an oil station.
In one embodiment, the input unit comprises a device input unit, a station library input unit and an expert input unit;
the equipment input unit is used for inputting basic information and FSU equipment information of all equipment of the oil station, wherein the basic information of the equipment comprises a station library to which the equipment belongs;
the station library input unit is used for inputting relevant information of the station library, including configuring the corresponding relation between the gas station equipment and the FSU equipment;
the expert input unit is used for inputting maintenance expert information corresponding to the equipment.
In one scenario, the device entry is to manage all devices of the gas station, wherein one device can only hang one station library, and can pick up other station libraries as required.
The station library entry is related information of the management station library, and comprises configuration equipment and corresponding FUS acquisition codes.
The expert library input is the expert corresponding to the management equipment, and the expert corresponding to each oil station is selected when the oil station is maintained.
In one embodiment, the system further comprises a video monitoring unit;
the video monitoring unit is used for configuring a camera arranged in the oil station, receiving video monitoring data acquired by the camera and displaying the video monitoring data.
In one embodiment, the system further comprises a management unit, wherein the management unit comprises a metadata management unit and a model management unit;
the metadata management unit is used for collecting metadata of the source data and the target database and uniformly managing the metadata of the database table;
the model management unit is used for managing the data statistical model and the data analysis model used in the data analysis unit.
The invention designs the big data front-end management system of the Internet of things based on the API drive, completes the omnibearing management of the business models of a plurality of business systems of enterprises and metadata thereof, realizes the unified model standardization of the metadata of the enterprises, and standardizes the development of the management data model; the multi-user collaborative version management is realized, and the problem of repeated construction of the model is avoided; the multiplexing effect of the same type of equipment is realized, the configured attributes comprise basic attributes, equipment configuration, alarm configuration, stream calculation data points, picture configuration, geographic information configuration, network inspection, custom attributes, event configuration and the like, and the modeled realization enhances the uniformity, convenience and high efficiency of management.
The low-code internet of things analysis platform can conveniently and rapidly inquire and manage information such as table structures, fields, indexes, main external keys and the like in a service system by managing the accessed original data, and realizes online multi-person cooperation data modeling. The platform manages model development by establishing project management, and can realize the effect of API interface/capacity multiplexing.
Based on the management system provided above, referring to the embodiment of fig. 2, the invention provides a management method of big data front end of internet of things based on API driver, comprising:
s1, creating by the equipment: creating a class of devices; the equipment comprises a generator, an oiling machine, a fire extinguisher oil-water separation tank, an oil tank, a leak detector, a video monitoring system and the like; the types of equipment include production equipment, technical protection equipment, production auxiliary equipment, environmental protection equipment, office equipment and the like
S2, equipment input: inputting basic information, FSU equipment information and equipment binding FSU data of the existing equipment of the oil depot/oil station;
s3, data acquisition: receiving real-time monitoring data collected by FSU equipment; the monitoring data comprise equipment state monitoring data, equipment signal monitoring data and equipment fault reporting data;
s4, data analysis: performing classification management and analysis according to the acquired monitoring data to obtain classification statistical data and data analysis results;
s5, data interface: providing an access interface for a user to access the required data through the access interface;
s6, large screen display: and carrying out large-screen display according to the real-time monitoring data, the classified statistical data and the data analysis result of the system.
In one embodiment, in step S3, after receiving the real-time monitoring data collected by the FSU device, the collected data is stored in the library table. Based on the bottom collection equipment of the Internet of things, the power consumption is analyzed to promote enterprise energy consumption management, and energy conservation and emission reduction are realized.
In a scenario, in step S4, the "data analysis" can only view (acquire) the provincial summary information in the authority range and perform statistics and analysis, including equipment statistics, maintenance work order statistics, station library area distribution statistics, equipment production classification statistics, equipment maintenance amount statistics, equipment quantity statistics, maintenance level statistics, and the like.
In a scene, in step S5, real-time data of the device is obtained through a KEY of the device; the data in the library table can be accessed by configuring the api, and the api access can be accessed only after the token is generated by using the key of the corresponding user.
In a scene, in step S6, the "large screen display" is used for a large screen display, so that the important summary analysis information of the whole province can be intuitively seen, including equipment statistics, alarm statistics, accumulated faults, fault distribution, real-time monitoring, whole province monitoring, ground city monitoring and the like. Wherein the system displays the oil station/oil depot geographic location based on the GIS map. The system monitoring profile is displayed through the large screen, so that the running state of the system is clear at a glance, and the visual level of the system is improved.
In one embodiment, the method further comprises: s7, video monitoring: and configuring a camera arranged in the oil station, receiving video monitoring data acquired by the camera, and displaying the video monitoring data.
In one embodiment, the method further comprises:
s8, metadata management: collecting metadata of source data and a target database, and uniformly managing the metadata of a database table;
s9, model management: and managing a data statistical model and a data analysis model for data analysis.
It should be noted that, in each embodiment of the present invention, each functional unit/module may be integrated in one processing unit/module, or each unit/module may exist alone physically, or two or more units/modules may be integrated in one unit/module. The integrated units/modules described above may be implemented either in hardware or in software functional units/modules.
From the description of the embodiments above, it will be apparent to those skilled in the art that the embodiments described herein may be implemented in hardware, software, firmware, middleware, code, or any suitable combination thereof. For a hardware implementation, the processor may be implemented in one or more of the following units: an Application Specific Integrated Circuit (ASIC), a Digital Signal Processor (DSP), a Digital Signal Processing Device (DSPD), a Programmable Logic Device (PLD), a Field Programmable Gate Array (FPGA), a processor, a controller, a microcontroller, a microprocessor, other electronic units designed to perform the functions described herein, or a combination thereof. For a software implementation, some or all of the flow of an embodiment may be accomplished by a computer program to instruct the associated hardware. When implemented, the above-described programs may be stored in or transmitted as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a computer. The computer readable media can include, but is not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
Finally, it should be noted that the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the scope of the present invention, and although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention.
Claims (10)
1. The utility model provides a big data front end management system of thing networking based on API drive which characterized in that includes: the system comprises an input unit, a data acquisition unit, a data analysis unit and a data interface unit;
the input unit is used for inputting basic information and FSU equipment information of the existing equipment of the target place and binding the relation between the acquisition equipment and the FSU equipment;
the data acquisition unit is used for receiving real-time monitoring data acquired by the FSU equipment;
the data analysis unit is used for carrying out classification management and analysis according to the acquired monitoring data to obtain classification statistical data and data analysis results;
the data interface unit is used for providing an access interface for a user to access the required data through the access interface.
2. The big data front end management system based on the API driver internet of things of claim 1, further comprising a big screen display unit;
the large screen display unit is used for displaying the large screen according to the real-time monitoring data, the classified statistical data and the data analysis result of the system.
3. The API-based drive internet of things big data front end management system of claim 1, further comprising a device creation unit;
the device creation unit is used for creating a category of the device.
4. The internet of things big data front end management system based on the API driver of claim 1, wherein said target site comprises an oil depot, an oil station.
5. The internet of things big data front end management system based on the API driver according to claim 4, wherein the input unit comprises an equipment input unit, a station library input unit and an expert input unit;
the equipment input unit is used for inputting basic information and FSU equipment information of all equipment of the oil station, wherein the basic information of the equipment comprises a station library to which the equipment belongs;
the station library input unit is used for inputting relevant information of the station library, including configuring the corresponding relation between the gas station equipment and the FSU equipment;
the expert input unit is used for inputting maintenance expert information corresponding to the equipment.
6. The API-based drive internet of things big data front end management system according to claim 4, further comprising a video monitoring unit;
the video monitoring unit is used for configuring a camera arranged in the oil station, receiving video monitoring data acquired by the camera and displaying the video monitoring data.
7. The API-based internet of things big data front end management system of claim 1, further comprising a management unit, wherein the management unit comprises a metadata management unit and a model management unit;
the metadata management unit is used for collecting metadata of the source data and the target database and uniformly managing the metadata of the database table;
the model management unit is used for managing the data statistical model and the data analysis model used in the data analysis unit.
8. The method for managing the big data front end of the Internet of things based on the API is characterized by comprising the following steps of:
s1, creating by the equipment: creating a class of devices;
s2, equipment input: inputting basic information, FSU equipment information and equipment binding FSU data of the existing equipment of an oil depot and an oil station;
s3, data acquisition: receiving real-time monitoring data collected by FSU equipment;
s4, data analysis: performing classification management and analysis according to the acquired monitoring data to obtain classification statistical data and data analysis results;
s5, data interface: providing an access interface for a user to access the required data through the access interface;
s6, large screen display: and carrying out large-screen display according to the real-time monitoring data, the classified statistical data and the data analysis result of the system.
9. The API-based internet of things big data front end management method of claim 8, further comprising: s7, video monitoring: and configuring a camera arranged in the oil station, receiving video monitoring data acquired by the camera, and displaying the video monitoring data.
10. The API-based internet of things big data front end management method of claim 8, further comprising:
s8, metadata management: collecting metadata of source data and a target database, and uniformly managing the metadata of a database table;
s9, model management: and managing a data statistical model and a data analysis model for data analysis.
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Application publication date: 20230505 |