CN112235326B - Internet of things equipment data analysis method and device and electronic equipment - Google Patents
Internet of things equipment data analysis method and device and electronic equipment Download PDFInfo
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- CN112235326B CN112235326B CN202011468561.6A CN202011468561A CN112235326B CN 112235326 B CN112235326 B CN 112235326B CN 202011468561 A CN202011468561 A CN 202011468561A CN 112235326 B CN112235326 B CN 112235326B
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Abstract
The invention provides an analysis method and device for equipment data of the Internet of things and electronic equipment, and relates to the technical field of the Internet of things, and the method comprises the following steps: acquiring device data of Internet of things equipment accessed to a cloud; wherein the device data includes: industry attribute and equipment attribute to be analyzed; determining a corresponding cloud equipment object model for the Internet of things equipment based on the industry attribute; the Internet of things devices with the same industry attribute correspond to the same cloud device model; and analyzing the equipment data by utilizing a rule matching template library of the cloud equipment object model to obtain the equipment attribute of the Internet of things equipment. In the method, the Internet of things devices with the same industry attribute correspond to the same cloud device object model, and the rule matching template library of the cloud device object model realizes one-to-many analysis of the Internet of things device data by the cloud device object model, so that the repetitive work of research and development personnel is reduced, and the work efficiency is effectively improved.
Description
Technical Field
The invention relates to the technical field of Internet of things, in particular to a method and a device for analyzing equipment data of the Internet of things and electronic equipment.
Background
At present, along with the rapid development of industry 4.0, in order to better serve enterprises in enterprise manufacturing, capacity and quality are improved, and more accurate intellectualization is realized, entity equipment in the space of the internet of things is generally digitalized, a data model of the entity equipment is constructed at the cloud end, an equipment model is obtained, the equipment model is a data model for transmitting equipment data by a sensor, but the equipment attributes produced by each manufacturing enterprise are not uniform, one set of data model is redeveloped to butt joint the equipment data transmitted by the sensor when the cloud end is accessed into the internet of things equipment every time, so that research and development repeatability work is large, and the working efficiency is low.
Disclosure of Invention
The invention aims to provide an analysis method and device for equipment data of the Internet of things and electronic equipment, so that repeated work of research personnel is reduced, and the work efficiency is effectively improved.
In a first aspect, the present invention provides an analysis method for internet of things device data, including: acquiring device data of Internet of things equipment accessed to a cloud; wherein the device data comprises: industry attribute and equipment attribute to be analyzed; determining a corresponding cloud equipment model for the Internet of things equipment based on the industry attribute; the Internet of things devices with the same industry attribute correspond to the same cloud device model; and analyzing the equipment data by utilizing a rule matching template library of the cloud equipment object model to obtain the equipment attribute of the Internet of things equipment.
In an optional implementation manner, obtaining device data of the internet of things device accessing to the cloud includes: acquiring a data transmission protocol of the Internet of things equipment; and analyzing the data packet sent by the Internet of things equipment based on the data transmission protocol to obtain the equipment data of the Internet of things equipment.
In an alternative embodiment, the method further comprises: judging whether the parameter value of the target equipment attribute is in a preset value range or not; the target equipment attribute is any one of the equipment attributes of the equipment of the Internet of things; if the parameter value of the target equipment attribute is not in the preset value range, judging whether the equipment attribute identification of the Internet of things equipment is completely matched with the data identification in the rule matching template library; if the data are not matched completely, the equipment data are discarded and abnormal data reception is fed back; and if the matching is complete, determining that the Internet of things equipment is in an abnormal state.
In an alternative embodiment, the method further comprises: obtaining an individualized calculation model; wherein the personalized calculation model is a model for performing preset operations on parameter values of the device attributes; and calculating the parameter values of the equipment attributes by using the personalized calculation model to obtain a personalized statistical result.
In an alternative embodiment, the method further comprises: recording the calling times of each cloud equipment object model; and determining the distribution of the Internet of things equipment accessed to the cloud based on the calling times.
In an alternative embodiment, the method further comprises: acquiring a device attribute template of the Internet of things device accessed to the cloud; wherein, the device attribute template comprises: the corresponding relation between the equipment attribute and the equipment attribute identification; establishing a mapping relation between each equipment attribute identification and a data identification in a cloud equipment model based on the equipment attribute template; the cloud equipment model is an equipment model which is stored in advance by a cloud and has the same industrial attribute as the Internet of things equipment; and storing the mapping relation into a rule matching template library of the cloud equipment object model.
In a second aspect, the present invention provides an analysis apparatus for data of an internet of things device, including: the first acquisition module is used for acquiring the equipment data of the Internet of things equipment accessed to the cloud; wherein the device data comprises: industry attribute and equipment attribute to be analyzed; the first determining module is used for determining a corresponding cloud equipment model for the Internet of things equipment based on the industry attribute; the Internet of things devices with the same industry attribute correspond to the same cloud device model; and the analysis module is used for analyzing the equipment data by utilizing a rule matching template library of the cloud equipment object model to obtain the equipment attribute of the Internet of things equipment.
In an optional implementation manner, obtaining device data of the internet of things device accessing to the cloud includes: the obtaining unit is used for obtaining a data transmission protocol of the Internet of things equipment; and the analysis unit is used for analyzing the data packet sent by the Internet of things equipment based on the data transmission protocol to obtain the equipment data of the Internet of things equipment.
In a third aspect, the present invention provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program operable on the processor, and the processor executes the computer program to implement the steps of the method according to any of the foregoing embodiments.
In a fourth aspect, the invention provides a computer readable medium having non-volatile program code executable by a processor, the program code causing the processor to perform the method of any of the preceding embodiments.
The invention provides an analysis method of Internet of things equipment data, which comprises the following steps: acquiring device data of Internet of things equipment accessed to a cloud; wherein the device data includes: industry attribute and equipment attribute to be analyzed; determining a corresponding cloud equipment object model for the Internet of things equipment based on the industry attribute; the Internet of things devices with the same industry attribute correspond to the same cloud device model; and analyzing the equipment data by utilizing a rule matching template library of the cloud equipment object model to obtain the equipment attribute of the Internet of things equipment.
In the prior art, before the cloud analyzes the data of the internet of things, a set of corresponding equipment object model needs to be developed for each piece of internet of things equipment, so that the research and development repeatability is high, and the work efficiency is low. According to the method for analyzing the Internet of things equipment data, after the equipment data of the Internet of things equipment accessing to the cloud are obtained, the corresponding cloud equipment object model is determined for the Internet of things equipment according to the industry attribute of the Internet of things equipment, and then the equipment data are analyzed by utilizing the rule matching template library of the cloud equipment object model, so that the equipment attribute of the Internet of things equipment is obtained. In the method, the Internet of things devices with the same industry attribute correspond to the same cloud device object model, and the rule matching template library of the cloud device object model realizes one-to-many analysis of the Internet of things device data by the cloud device object model, so that the repetitive work of research and development personnel is reduced, and the work efficiency is effectively improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of an analysis method for internet of things device data according to an embodiment of the present invention;
fig. 2 is a flowchart of an optional method for analyzing data of an internet of things device according to an embodiment of the present invention;
fig. 3 is a logic diagram illustrating a cloud device object model invoked through an API interface according to an embodiment of the present invention;
fig. 4 is a functional block diagram of an apparatus for analyzing data of an internet of things device according to an embodiment of the present invention;
fig. 5 is a schematic diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Some embodiments of the invention are described in detail below with reference to the accompanying drawings. The embodiments described below and the features of the embodiments can be combined with each other without conflict.
Along with the rapid development of thing networking, generally with the entity thing networking device digitalize in the thing networking space in the enterprise's manufacturing production, and then make thing networking device management more accurate more intelligent, in order to realize this purpose, the research and development personnel need construct rather than corresponding equipment thing model for the entity equipment in the high in the clouds, and equipment thing model is a data model of sensor transmission equipment data, and for example, the equipment attribute of X lathe has: ws represents the water temperature value, wy represents the pressure value, that is, for the X machine tool, the equipment attribute mark corresponding to the (equipment attribute) water temperature value is ws; the device attribute identifier corresponding to the (device attribute) pressure value is wy, after the sensor on the X machine tool detects the device attribute, for example, ws =50, wy =80, the data is packed and uploaded to the cloud, and after the cloud receives the device data, in order to accurately analyze the device attribute, a set of data model needs to be developed for the X machine tool in advance to dock the device data transmitted by the sensor. However, because the attributes of the devices produced by each manufacturing enterprise are not uniform, a set of data model needs to be redeveloped to connect the device data transmitted by the sensor every time the cloud accesses one piece of internet of things device, so that the research and development repeatability is large, and the working efficiency is low. In view of the above, embodiments of the present invention provide a method for analyzing data of an internet of things device, so as to alleviate the technical problems mentioned above.
Example one
Fig. 1 is a flowchart of an analysis method for internet of things device data according to an embodiment of the present invention, and as shown in fig. 1, the method specifically includes the following steps:
step S102, obtaining device data of the Internet of things device accessed to the cloud.
Specifically, before analyzing the internet of things device data, the device data of the internet of things device accessing the cloud end is firstly acquired, wherein the device data includes: industry attribute and equipment attribute to be analyzed; the industry attribute can be understood as industry information of the internet of things device, for example, if the internet of things device is an excavator, the cloud can determine that the received device data is excavator data according to the device data sent by the internet of things device. The cloud-accessed device data is data represented by device attribute marks designed by a device manufacturer and corresponding device attributes, and the device attributes cannot be accurately analyzed under the condition that the meaning of each mark is uncertain.
For example, the equipment attributes of an excavator manufactured by company a are: jws for water temperature values, jwy for pressure values; the equipment attributes of the excavator produced by company B are as follows: wwa represents the water temperature value; wwy represents pressure values; jws, jwy, wwa and wwy all represent device attribute identifications, the device data received by the cloud are only jws =30, jwy =100, wwa =60 and wwy =80, and when the device data transmitted by the sensor is docked, the cloud cannot resolve the device attributes if the meaning of the device identifications is not clear.
The above-mentioned equipment data is generally that after each sensor on the internet of things equipment detects corresponding equipment attribute, the rethread is preset the transmission path and is unified to be sent to the high in the clouds, and the high in the clouds can be understood as the server that carries out data processing to the equipment data of internet of things equipment.
And S104, determining a corresponding cloud equipment model for the Internet of things equipment based on the industry attribute.
In the embodiment of the invention, the cloud end embeds system model libraries of some industries according to the accumulated information of the Internet of things industry, namely, embeds equipment models of a plurality of industries, wherein the Internet of things equipment with the same industry attribute corresponds to the same cloud end equipment model; and a unique ID may be set for each cloud device model. Therefore, after receiving the device data of the internet of things device, the cloud determines a cloud device object model required to be used for data analysis by using the industry attribute of the cloud.
For example, when excavator devices manufactured by all manufacturers are connected to the cloud, the same equipment model is used for analyzing data, only one data identifier is provided for each equipment attribute in the equipment model, for example, in a cloud equipment model corresponding to the excavator industry, AAA (data identifier) represents a water temperature value (equipment attribute), although jws represents the water temperature value in the equipment attribute of the excavator manufactured by company a and wwa represents the water temperature value in the equipment attribute of the excavator manufactured by company B, after the cloud is connected to the cloud, the cloud does not need to respectively develop equipment models for company a and company B, but enables AAA and jws to form a mapping relationship, AAA and wwa form a mapping relationship, so that a new equipment model does not need to be developed for each excavator device, but the same equipment model is shared by relying on the one-to-many mapping relationships, thereby reducing the workload of research and development, the working efficiency is improved.
And S106, analyzing the equipment data by utilizing a rule matching template library of the cloud equipment object model to obtain the equipment attribute of the Internet of things equipment.
In the embodiment of the invention, when the cloud equipment model analyzes the equipment data, a rule matching template library of the equipment model is specifically used for matching the equipment data, wherein the rule matching template library stores mapping relations of each data identifier of the cloud equipment model and equipment attribute identifiers of a plurality of pieces of internet-of-things equipment in the industry to which the cloud equipment model belongs, such as the mapping relations of AAA and jws and the mapping relations of AAA and wwa. Therefore, when the received device data includes jws =30, the cloud can obtain the water temperature value of the currently-accessed excavator as 30 according to the mapping relationship. The method is applied to the rule mapping engine of the equipment model, and the rule mapping engine has the advantages of high data processing speed and stability.
In the prior art, before the cloud analyzes the data of the internet of things, a set of corresponding equipment object model needs to be developed for each piece of internet of things equipment, so that the research and development repeatability is high, and the work efficiency is low. According to the method for analyzing the Internet of things equipment data, after the equipment data of the Internet of things equipment accessing to the cloud are obtained, the corresponding cloud equipment object model is determined for the Internet of things equipment according to the industry attribute of the Internet of things equipment, and then the equipment data are analyzed by utilizing the rule matching template library of the cloud equipment object model, so that the equipment attribute of the Internet of things equipment is obtained. In the method, the Internet of things devices with the same industry attribute correspond to the same cloud device object model, and the rule matching template library of the cloud device object model realizes one-to-many analysis of the Internet of things device data by the cloud device object model, so that the repetitive work of research and development personnel is reduced, and the work efficiency is effectively improved.
The method for analyzing the data of the internet of things device provided by the embodiment of the invention is described above, and the optional implementation of some steps and other functions developed on the basis of the method of the invention are introduced one by one.
In an optional implementation manner, in step S102, the device data of the internet of things device accessing the cloud is obtained, which specifically includes the following contents:
acquiring a data transmission protocol of the Internet of things equipment; and analyzing the data packet sent by the equipment of the Internet of things based on a data transmission protocol to obtain the equipment data of the equipment of the Internet of things.
Specifically, the cloud in the embodiment of the present invention is compatible with multiple communication protocols of the internet of things, for example, CoAP (Constrained Application Protocol), MQTT (Message Queuing Telemetry Transport), JMS (Java Message Service), and the like, each piece of internet of things equipment uses a data transmission Protocol supported by the internet of things equipment to package device data and then sends the device data to the cloud, so that in order to accurately acquire the device data of the internet of things equipment, the cloud first needs to acquire which transmission Protocol is specifically used by the internet of things equipment, and then accurately analyzes the received data package by using the data transmission Protocol, so as to acquire the device data of the internet of things equipment.
After the cloud analyzes the device data sent by the internet of things device by using the device object model, some operation state information of the internet of things device, such as a temperature value, a pressure value, a working time, an operation time and the like, can be obtained, and in an optional embodiment, as shown in fig. 2, the method further includes the following steps:
and step S107, judging whether the parameter value of the target equipment attribute is in a preset value range.
After the numerical parameter information sent by the sensor is analyzed by the cloud, the numerical parameter information can be dynamically checked to check the accuracy of the parameter values of all the equipment attributes, and specifically, whether the parameter values of the target equipment attributes are within a preset value range is judged, wherein the target equipment attributes are any one of the equipment attributes of the internet of things equipment; each numerical device attribute should be set to a corresponding value range, which needs to be set according to the actual needs of the user, for example, if it is known that the water temperature range of some internet of things device should be 60 ℃ to 100 ℃ during normal operation, the preset value range corresponding to the device attribute of the water temperature value can be set to 60 ℃ to 100 ℃.
If the parameter value of the target device attribute is not within the preset value range, executing step S108; and if the parameter value of the target equipment attribute is in the preset value range, recording and storing the parameter value of the target equipment attribute.
And S108, judging whether the equipment attribute identification of the Internet of things equipment is completely matched with the data identification in the rule matching template library.
If not, go to step S109; if the match is complete, go to step S110.
Step S109, discard the device data and feed back a data reception abnormality.
And step S110, determining that the Internet of things equipment is in an abnormal state.
Specifically, if it is determined that the parameter value of the target device attribute exceeds the corresponding preset value range, it is further determined whether the device attribute identifier of the internet of things device is completely matched with the data identifier in the rule matching template library, and if the data is analyzed under the condition of incomplete matching, it is determined that the analyzed data cannot correctly reflect the operation information of the internet of things device, so that the device data is selected to be discarded, and abnormal data reception is fed back; if the parameter value of the target equipment attribute exceeds the corresponding preset value range and the equipment attribute identification of the Internet of things equipment is confirmed to be completely matched with the data identification in the rule matching template library, the data analysis is correct, and the Internet of things equipment is in an abnormal state. If a display connected with the cloud is arranged, the analyzed data can be displayed, and a data verification result is displayed.
When checking the accessed device data, a time window mode can be selected to extract a piece of device data, and then the extracted piece of device data is checked, for example, a piece of device data is randomly extracted from a plurality of pieces of device data received every 5 minutes and checked; or a plurality of pieces of equipment data can be collected in batches, then the plurality of pieces of equipment data are compared, the attributes of each piece of equipment data are compared, and the similarities and differences are found out, wherein the basic principle is as follows: m samples (M < N) are extracted from N samples with equal probability, and the samples are simulated by an array and extracted with equal probability directly. The method comprises the following steps: randomly taking a number between 0, N-1 (assuming the first sample is labeled 0) each time, comparing the number with the previous number, and if the number is the same as the last number taken, continuing the random drawing until a number different from all the previous numbers is taken; if not, the random number is added into the result set, and random extraction is continued until the number in the result set is M.
In an alternative embodiment, the method of the present invention further comprises the steps of:
step S21, obtaining a personalized calculation model; the personalized calculation model is a model for executing preset operation on parameter values of equipment attributes.
And step S22, calculating the parameter values of the equipment attributes by using the personalized calculation model to obtain personalized statistical results.
In the embodiment of the invention, after the rule mapping engine analyzes the device attribute of the internet of things device, a user can select some personalized model libraries built in the cloud according to actual requirements, a plurality of personalized calculation models are stored in the personalized model libraries, the personalized calculation models are models capable of executing preset operation on the parameter values of the device attribute, if the user selects one or more personalized calculation models when analyzing the device data of the internet of things device by using the device model at the cloud, one or more personalized statistical results can be obtained while outputting the data analysis result, and further the operation state of the internet of things device is deeply analyzed. For example, the device attributes of the operating duration and the operating duration are preset in the device model, the device attribute of the device on-time rate is defined in the personalized calculation model, and the device on-time rate = the operating duration/the operating duration, so that after the cloud device model analyzes the device data, the specific parameter value of the device on-time rate can be further obtained by using the personalized calculation model. The personalized model library provides a plurality of selectable calculation models for a user, and the user can train the application and the use range of the model library after selecting and using.
In an alternative embodiment, the method of the present invention further comprises the steps of:
step S31, recording the calling times of each cloud equipment object model;
and step S32, determining the distribution of the Internet of things equipment accessed to the cloud based on the calling times.
In the embodiment of the invention, after the rule mapping engine is used for calling the cloud equipment model to analyze the equipment data, the called times of each cloud equipment model can be recorded, and the distribution of the Internet of things equipment accessed to the cloud is further determined according to the called times.
In the above, a detailed description is given of how to use the cloud equipment model to analyze the equipment data transmitted by the internet of things equipment, and a description is given below of a process of constructing the cloud equipment model for data analysis.
In an alternative embodiment, the method of the present invention further comprises the steps of:
step S41, acquiring a device attribute template of the Internet of things device accessed to the cloud; wherein, the device attribute template comprises: and the corresponding relation between the equipment attribute and the equipment attribute identification.
Firstly, to analyze device data of the internet of things device, the rule mapping engine first acquires a device attribute template of the internet of things device accessing the cloud, where the device attribute template includes a correspondence between a device attribute and a device attribute identifier, for example, jws described above represents a water temperature value, where jws is the device attribute identifier, the water temperature value is the device attribute, and the two have a unique correspondence. The device attribute template user can perform custom configuration on the web page, or can directly upload a standard template (such as an excel-format document) of the device attribute, and complete the configuration of the device attribute template through batch import, or select from preset attribute templates provided by the web page, wherein the preset attribute templates can be sorted according to the calling times of all cloud device models.
Step S42, establishing a mapping relation between each equipment attribute identification and the data identification in the cloud equipment object model based on the equipment attribute template; the cloud equipment model is an equipment model which is stored in advance by the cloud and has the same industry attribute as the Internet of things equipment.
In the embodiment of the invention, the internet of things devices with the same industry attribute use the same device model in a unified manner at the cloud, so after the device attribute template of the internet of things device is obtained, the corresponding cloud device model is determined according to the industry attribute, and then the mapping relationship between each device attribute identifier of the internet of things device and the data identifier in the cloud device model is established, for example, in the cloud device model corresponding to the excavator industry, AAA (data identifier) represents a water temperature value (device attribute), and jws represents a water temperature value in the device attribute of the excavator produced by company a configured by a user, at this time, the mapping relationship between AAA and jws needs to be established, and so on, and the mapping relationship between all the data identifiers in the cloud device model is completed.
And step S43, storing the mapping relation into a rule matching template library of the cloud equipment object model.
And finally, storing the mapping relation into a rule matching template library of the cloud equipment object model, and when the rule mapping engine calls the cloud equipment object model, performing data analysis by using the mapping relation in the rule matching template library corresponding to the equipment object model.
The establishment of the cloud equipment model can realize streaming data processing, calculation, summarization and historical data presentation based on the cloud equipment model, and the client can call the equipment model in a manner of adopting an Http request API interface (RPC modification of a TCP protocol can be carried out, so that the access performance and the access speed are improved). For processing based on the device data dimension, fig. 3 is a logic diagram for calling the cloud device object model through the API interface according to the embodiment of the present invention.
In the method for analyzing the internet of things equipment data, the multiple internet of things equipment with the same industry attribute correspond to the same equipment model at the cloud end, namely, one equipment model can deal with multiple kinds of equipment, the technical problem that the bottom layer attributes of the equipment are inconsistent and cannot be unified is not concerned, the equipment model is standardized, the equipment data of the internet of things equipment can be analyzed by establishing the mapping relation between the equipment attribute identification of the internet of things equipment and the data identification of the equipment model, the technical problem that the operation flow of analyzing the internet of things equipment data in the internet of things industry is complex at present is solved, the repetitive work of research and development personnel is reduced, and the work efficiency is effectively improved. The device model can be subjected to secondary evolution and derived to obtain multiple models; the user can also customize common addition, subtraction, multiplication and division (selecting an individualized calculation model) to calculate the desired service data, and aiming at the condition that the equipment attributes are too much and the user cannot identify, the method can be used for quickly and simply filtering out the required equipment attributes, and the filtered data is simpler, easier to understand and more humanized.
Example two
The embodiment of the invention also provides an analysis device for the data of the internet of things equipment, which is mainly used for executing the analysis method for the data of the internet of things equipment provided by the first embodiment of the invention.
Fig. 4 is a functional block diagram of an analysis apparatus for internet of things device data according to an embodiment of the present invention, and as shown in fig. 4, the apparatus mainly includes: a first obtaining module 10, a first determining module 20, and a parsing module 30, wherein:
the first obtaining module 10 is configured to obtain device data of an internet of things device accessing a cloud; wherein the device data includes: industry attributes and device attributes to be parsed.
The first determining module 20 is configured to determine a corresponding cloud device model for the internet of things device based on the industry attribute; the Internet of things equipment with the same industry attribute corresponds to the same cloud equipment model.
The analysis module 30 is configured to analyze the device data by using the rule matching template library of the cloud device model to obtain a device attribute of the internet of things device.
In the prior art, before the cloud analyzes the data of the internet of things, a set of corresponding equipment object model needs to be developed for each piece of internet of things equipment, so that the research and development repeatability is high, and the work efficiency is low. According to the device for analyzing the internet of things equipment data, after the equipment data of the internet of things equipment accessing the cloud are obtained, the corresponding cloud equipment object model is determined for the internet of things equipment according to the industry attribute of the internet of things equipment, and then the equipment data are analyzed by utilizing the rule matching template library of the cloud equipment object model, so that the equipment attribute of the internet of things equipment is obtained. In the embodiment of the invention, the internet of things devices with the same industry attribute correspond to the same cloud device object model, and the rule matching template library of the cloud device object model realizes one-to-many analysis of the internet of things device data by the cloud device object model, so that the repetitive work of research and development personnel is reduced, and the work efficiency is effectively improved.
Optionally, the first obtaining module 10 includes:
and the acquisition unit is used for acquiring a data transmission protocol of the Internet of things equipment.
And the analysis unit is used for analyzing the data packet sent by the Internet of things equipment based on the data transmission protocol to obtain the equipment data of the Internet of things equipment.
Optionally, the apparatus further comprises:
the first judgment module is used for judging whether the parameter value of the target equipment attribute is in a preset value range or not; the target equipment attribute is any one of the equipment attributes of the equipment of the Internet of things.
And the second judgment module is used for judging whether the equipment attribute identifier of the Internet of things equipment is completely matched with the data identifier in the rule matching template library or not if the parameter value of the target equipment attribute is not in the preset value range.
And the second determining module discards the equipment data and feeds back data receiving abnormity if the equipment data are not completely matched.
And the third determining module is used for determining that the Internet of things equipment is in an abnormal state if the Internet of things equipment is completely matched with the Internet of things equipment.
Optionally, the apparatus further comprises:
the second acquisition module is used for acquiring the personalized calculation model; the personalized calculation model is a model for executing preset operation on parameter values of equipment attributes.
And the operation module is used for operating the parameter values of the equipment attributes by utilizing the personalized calculation model to obtain a personalized statistical result.
Optionally, the apparatus further comprises:
and the recording module is used for recording the calling times of each cloud equipment object model.
And the fourth determining module is used for determining the distribution of the Internet of things equipment accessed to the cloud based on the calling times.
Optionally, the apparatus further comprises:
the third acquisition module is used for acquiring a device attribute template of the Internet of things device accessed to the cloud; wherein, the device attribute template comprises: and the corresponding relation between the equipment attribute and the equipment attribute identification.
The establishing module is used for establishing a mapping relation between each equipment attribute identification and the data identification in the cloud equipment object model based on the equipment attribute template; the cloud equipment model is an equipment model which is stored in advance by the cloud and has the same industry attribute as the Internet of things equipment.
And the storage module is used for storing the mapping relation into a rule matching template library of the cloud equipment object model.
EXAMPLE III
Referring to fig. 5, an embodiment of the present invention provides an electronic device, including: a processor 60, a memory 61, a bus 62 and a communication interface 63, wherein the processor 60, the communication interface 63 and the memory 61 are connected through the bus 62; the processor 60 is arranged to execute executable modules, such as computer programs, stored in the memory 61.
The memory 61 may include a high-speed Random Access Memory (RAM) and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory. The communication connection between the network element of the system and at least one other network element is realized through at least one communication interface 63 (which may be wired or wireless), and the internet, a wide area network, a local network, a metropolitan area network, and the like can be used.
The bus 62 may be an ISA bus, PCI bus, EISA bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 5, but this does not indicate only one bus or one type of bus.
The memory 61 is used for storing a program, the processor 60 executes the program after receiving an execution instruction, and the method executed by the apparatus defined by the flow process disclosed in any of the foregoing embodiments of the present invention may be applied to the processor 60, or implemented by the processor 60.
The processor 60 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 60. The Processor 60 may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the device can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components. The various methods, steps and logic blocks disclosed in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory 61, and the processor 60 reads the information in the memory 61 and, in combination with its hardware, performs the steps of the above method.
The method and the device for analyzing the data of the internet of things equipment and the computer program product of the electronic equipment provided by the embodiments of the present invention include a computer-readable storage medium storing a nonvolatile program code executable by a processor, where instructions included in the program code may be used to execute the method described in the foregoing method embodiments, and specific implementation may refer to the method embodiments, and will not be described herein again.
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 functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer-readable storage medium executable by a processor. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes 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.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. An analysis method for Internet of things equipment data is characterized by comprising the following steps:
acquiring device data of Internet of things equipment accessed to a cloud; wherein the device data comprises: industry attribute and equipment attribute to be analyzed; the industry attribute represents industry information of the Internet of things equipment;
determining a corresponding cloud equipment model for the Internet of things equipment based on the industry attribute; the Internet of things devices with the same industry attribute correspond to the same cloud device model;
analyzing the equipment data by utilizing a rule matching template library of the cloud equipment object model to obtain the equipment attribute of the Internet of things equipment; the rule matching template library stores mapping relations between each data identifier of the cloud equipment model and equipment attribute identifiers of a plurality of pieces of internet-of-things equipment in the industry to which the cloud equipment model belongs; the cloud equipment model only has one data identifier for each equipment attribute, and the data identifier and the equipment attribute identifiers with the same equipment attribute of the similar equipment produced by different companies have mapping relations.
2. The method of claim 1, wherein obtaining device data of the internet of things device accessing the cloud comprises:
acquiring a data transmission protocol of the Internet of things equipment;
and analyzing the data packet sent by the Internet of things equipment based on the data transmission protocol to obtain the equipment data of the Internet of things equipment.
3. The method of claim 1, further comprising:
judging whether the parameter value of the target equipment attribute is in a preset value range or not; the target equipment attribute is any one of the equipment attributes of the equipment of the Internet of things;
if the parameter value of the target equipment attribute is not in the preset value range, judging whether the equipment attribute identification of the Internet of things equipment is completely matched with the data identification in the rule matching template library;
if the data are not matched completely, the equipment data are discarded and abnormal data reception is fed back;
and if the matching is complete, determining that the Internet of things equipment is in an abnormal state.
4. The method of claim 1, further comprising:
obtaining an individualized calculation model; wherein the personalized calculation model is a model for performing preset operations on parameter values of the device attributes;
and calculating the parameter values of the equipment attributes by using the personalized calculation model to obtain a personalized statistical result.
5. The method of claim 1, further comprising:
recording the calling times of each cloud equipment object model;
and determining the distribution of the Internet of things equipment accessed to the cloud based on the calling times.
6. The method of claim 1, further comprising:
acquiring a device attribute template of the Internet of things device accessed to the cloud; wherein, the device attribute template comprises: the corresponding relation between the equipment attribute and the equipment attribute identification;
establishing a mapping relation between each equipment attribute identification and a data identification in a cloud equipment model based on the equipment attribute template; the cloud equipment model is an equipment model which is stored in advance by a cloud and has the same industrial attribute as the Internet of things equipment;
and storing the mapping relation into a rule matching template library of the cloud equipment object model.
7. The utility model provides an analytical equipment of thing networking device data which characterized in that includes:
the first acquisition module is used for acquiring the equipment data of the Internet of things equipment accessed to the cloud; wherein the device data comprises: industry attribute and equipment attribute to be analyzed; the industry attribute represents industry information of the Internet of things equipment;
the first determining module is used for determining a corresponding cloud equipment model for the Internet of things equipment based on the industry attribute; the Internet of things devices with the same industry attribute correspond to the same cloud device model;
the analysis module is used for analyzing the equipment data by utilizing a rule matching template library of the cloud equipment object model to obtain the equipment attribute of the Internet of things equipment; the rule matching template library stores mapping relations between each data identifier of the cloud equipment model and equipment attribute identifiers of a plurality of pieces of internet-of-things equipment in the industry to which the cloud equipment model belongs; the cloud equipment model only has one data identifier for each equipment attribute, and the data identifier and the equipment attribute identifiers with the same equipment attribute of the similar equipment produced by different companies have mapping relations.
8. The apparatus of claim 7, wherein obtaining device data of the internet of things device accessing the cloud comprises:
the obtaining unit is used for obtaining a data transmission protocol of the Internet of things equipment;
and the analysis unit is used for analyzing the data packet sent by the Internet of things equipment based on the data transmission protocol to obtain the equipment data of the Internet of things equipment.
9. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method of any of claims 1 to 6 when executing the computer program.
10. A computer-readable medium having non-volatile program code executable by a processor, the program code causing the processor to perform the method of any of claims 1 to 6.
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