CN118093699A - Digital twinning-based regional intelligent management method and device and electronic equipment - Google Patents
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Abstract
Digital twinning-based regional intelligent management method and device and electronic equipment, and relate to the field of digital twinning. In the method, a plurality of first sensing data acquired by a plurality of sensing facilities are acquired, wherein one sensing facility correspondingly acquires one or more first sensing data; processing the plurality of first perception data based on a preset business rule to obtain second perception data; carrying out standardization processing on a plurality of second perception data by adopting a standardized data interface and mapping the standardization processing to a standard data model so that the standard data model can conveniently transmit the plurality of second perception data to a first visual interface according to a preset standard format; and displaying the plurality of second perception data to a user through the first visual interface. By implementing the technical scheme provided by the application, the problem that the whole planning overall scheme is not embodied in the traditional method when the data are displayed, and the comprehensive regional intelligent management cannot be realized is solved.
Description
Technical Field
The application relates to the technical field of digital twinning, in particular to a regional intelligent management method and device based on digital twinning and electronic equipment.
Background
Regional intelligence refers to that various sensing facilities and data acquisition equipment are deployed in a designated region through a modern information technology and an Internet of things technology, so that comprehensive monitoring, control and optimization of operation of the designated region are realized. The regional intelligent construction is a complex and huge task project, and relates to the fields of multiple businesses such as infrastructure, perception data, technical platforms, data monitoring and the like.
The digital twin is applied to the field of regional management, simulation, monitoring and analysis of the region can be realized, the digital twin platform can integrate sensing facility data, monitor various variables in a designated region in real time, and automatically trigger an alarm or an early warning notification once an abnormal condition is detected. However, in the process of integrating the sensing facility data, multiple data types and data sources are involved, and there may be an association relationship between the data, in the related art, a single data processing and displaying are performed for different sensing facilities in the regional intelligent management method, the method may ignore the diversity and association of the data, and the overall planning and planning scheme is not reflected when the data is displayed, so that the comprehensive regional intelligent management cannot be realized.
Therefore, there is a need for a digital twin-based regional intelligent management method, device and electronic equipment that can solve the above problems.
Disclosure of Invention
The application provides a digital twin-based regional intelligent management method, a digital twin-based regional intelligent management device and electronic equipment, and solves the problem that the traditional method does not embody an overall planning and planning scheme when data are displayed and cannot realize comprehensive regional intelligent management.
In a first aspect of the present application, there is provided a digital twin-based regional intelligent management method, the method being applied to a digital twin platform, the method comprising: acquiring a plurality of first sensing data acquired by a plurality of sensing facilities, wherein one sensing facility correspondingly acquires one first sensing data; processing a plurality of first perception data based on preset business rules to obtain second perception data, wherein the preset business rules comprise data screening rules, data aggregation rules, data association analysis rules and abnormality detection rules; the method comprises the steps of carrying out standardization processing on a plurality of second perception data by adopting a standardized data interface and mapping the standardization processing to a standard data model so that the standard data model can conveniently transmit the plurality of second perception data to a first visual interface according to a preset standard format, wherein the standardization processing comprises format standardization, transmission protocol standardization, data field standardization and data transmission frequency standardization; and displaying the plurality of second perception data to a user through the first visual interface.
By adopting the technical scheme, the centralized management and processing of various data sources in the area are realized by integrating various first perception data acquired by a plurality of perception facilities and applying the preset business rules for processing, and the consistency of the data is improved. The preset business rules, including data screening, aggregation, association analysis and anomaly detection rules, are adopted to enable the data processing process to be automatic and standardized, reduce the requirement of human intervention, and improve the efficiency and consistency of data processing. And the second perception data is mapped to the standard data model through the standardized data interface and is transmitted according to a preset standard format, so that the consistency and interoperability of the data are ensured, and the complexity of data integration is reduced. And simultaneously, a plurality of second perception data are presented to a user in an intuitive and interactive mode through a first visual interface, so that the user can better understand and analyze various data of the area, and management and decision making are supported.
Optionally, the acquiring multiple first sensing data acquired by multiple sensing facilities specifically includes: creating a plurality of first perception data into a plurality of real-time data streams by adopting a streaming data processing technology, wherein one type of first perception data corresponds to one real-time data stream; and acquiring a plurality of real-time data streams through the data access layer so that the plurality of real-time data streams are input according to the time sequence.
By adopting the technical scheme, the streaming data processing technology is adopted to create a plurality of first perception data into a plurality of real-time data streams, so that the real-time processing of the data acquired by the perception facilities is facilitated, the data can be continuously transmitted in a streaming mode, and the real-time performance of the data processing is improved. The data access layer is used for acquiring a plurality of real-time data streams and integrating the data streams together according to a time sequence, so that the data acquired by different sensing facilities can be cooperatively analyzed according to a time axis, and the time correlation of the data can be comprehensively considered. Since the data processing is real-time, the manager can monitor and respond to the data more quickly.
Optionally, in the processing the first sensing data based on the preset service rule to obtain the second sensing data, processing the plurality of first sensing data based on the data aggregation rule to obtain the second sensing data specifically includes: judging the aggregation dimension of a plurality of first perception data, wherein the aggregation dimension comprises a time dimension, a region dimension and a category dimension; and aggregating the plurality of first perception data according to the aggregation dimension and the aggregation rule to obtain a plurality of second perception data, wherein the aggregation rule comprises aggregation in the same time period, aggregation in the same region and aggregation in the same category, and one type of second perception data corresponds to one or more types of first perception data.
By adopting the technical scheme, a plurality of different first perception data are integrated together according to the time dimension, the area dimension and the category dimension, so that the complexity of the data is simplified, the quantity of the original data which needs to be processed by a manager is reduced, the aggregated second perception data comprise more information about a specific time period, area dimension or category, the manager can comprehensively know the time and area direction, and more targeted decision making and strategy are facilitated.
Optionally, in the processing the first sensing data based on the preset service rule to obtain the second sensing data, processing the plurality of first sensing data based on the anomaly detection rule to obtain the second sensing data specifically includes: performing abnormality judgment on the second perception data by adopting a business rule engine, wherein a preset business rule is stored in the business rule engine; judging whether the second perception data is matched with a plurality of abnormal conditions defined in the abnormal detection rule, wherein the plurality of abnormal conditions comprise a threshold abnormal condition, a trend abnormal condition and a statistical abnormal condition; and if the second sensing data is matched with the first abnormal condition, executing the operation corresponding to the first abnormal condition, and displaying the operation in the first visual interface, wherein the operation comprises the generation of an alarm and the display of a notice, and the first abnormal condition is any one of a plurality of abnormal conditions.
By adopting the technical scheme, the business rule engine is adopted to detect the abnormality in real time, and timely identify and respond to the abnormality in the data acquired by the sensing facility, thereby being beneficial to early finding problems and taking appropriate measures to prevent or reduce potential risks. When the second sensory data matches an anomaly condition defined in the anomaly detection rule, the digital twinning platform may take the generation of an alarm, trigger a notification, or take other predetermined action in the display interface.
Optionally, in the processing the first sensing data based on the preset service rule to obtain the second sensing data, processing the plurality of first sensing data based on the data screening rule to obtain the second sensing data specifically includes: judging whether the first perception data meets a screening condition, wherein the screening condition is data repetition or data deletion; and if the first perception data meets the screening condition, filtering the first perception data to obtain second perception data.
By adopting the technical scheme, the data which do not meet the quality standard are identified and filtered, the quality and the accuracy of the second perception data are guaranteed, and the reliability of the data is improved.
Optionally, the displaying the plurality of second sensing data to the user through the first visual interface specifically includes: acquiring a target data type of any one of a plurality of second sensing data, wherein the target data type is any one of numerical value data, state data, position data, time data and count data; searching a display mode corresponding to the target data type in a preset database, wherein the preset database comprises a corresponding relation between the data type of the second perception data and the display mode, and the display mode comprises a graph, a line graph and a histogram; and according to the display mode corresponding to the target data type, displaying the first visual interface on the second perception data corresponding to the target data type.
By adopting the technical scheme, the target data type is acquired, the corresponding display mode is selected according to the corresponding relation in the preset database, and for different types of data, different display modes such as a graph, a line graph or a column graph are adopted, so that a manager is helped to better understand the trend, distribution and association of the data. Data visualization helps administrators quickly extract useful information from large amounts of data. Meanwhile, different display modes can highlight the data characteristics in different aspects, and help the manager to make decisions.
Optionally, after the first visual interface is displayed on the second perception data corresponding to the target data type according to the display mode corresponding to the target data type, the method further includes: responding to the modification operation of the user on the first visual interface, wherein the modification operation comprises modification of the data display mode; modifying the first visual interface based on a modification instruction corresponding to the modification operation to obtain a second visual interface; and displaying the second visual interface to a user.
By adopting the technical scheme, the user is allowed to customize the display mode, the size and the color of the visual interface according to personal preference and requirements, so that the requirements of the user are met. The user can adjust the interface according to different working scenes and requirements so as to meet the requirements of specific tasks.
In a second aspect of the present application, there is provided a digital twinning-based regional intelligent management apparatus, the apparatus being a digital twinning platform comprising: the device comprises an acquisition module, a processing module and a display module;
The acquisition module is used for acquiring a plurality of types of first perception data acquired by a plurality of perception facilities, wherein one perception facility correspondingly acquires one type of first perception data;
the processing module is used for processing the plurality of first perception data based on preset business rules to obtain second perception data, wherein the preset business rules comprise data cleaning rules, data screening rules, data aggregation rules, data association analysis rules and abnormality detection rules;
The processing module is also used for carrying out standardization processing on the plurality of second perception data by adopting the standardized data interface and mapping the standardization processing to the standard data model so that the standard data model can conveniently transmit the plurality of second perception data to the first visual interface according to a preset standard format, and the standardization processing comprises format standardization, transmission protocol standardization, data field standardization and data transmission frequency standardization;
And the display module is used for displaying various second perception data to a user in a first visual interface mode.
Optionally, the acquiring module acquires a plurality of types of first sensing data acquired by a plurality of sensing facilities, specifically including: the acquisition module adopts a streaming data processing technology to create a plurality of first perception data into a plurality of real-time data streams, wherein one type of first perception data corresponds to one real-time data stream; the acquisition module acquires a plurality of real-time data streams through the data access layer so that the plurality of real-time data streams are input according to the time sequence.
Optionally, the processing module processes the first sensing data based on a preset service rule to obtain second sensing data, and processes the plurality of first sensing data based on a data aggregation rule to obtain second sensing data, which specifically includes: the processing module judges the aggregation dimension of various first perception data, wherein the aggregation dimension comprises a time dimension, a region dimension and a category dimension; the processing module aggregates the plurality of first perception data according to the aggregation dimension and the aggregation rule to obtain a plurality of second perception data, wherein the aggregation rule comprises aggregation in the same time period, aggregation in the same region and aggregation in the same category, and one type of second perception data corresponds to one or more types of first perception data.
Optionally, the processing module processes the first sensing data based on a preset service rule to obtain second sensing data, processes the plurality of first sensing data based on an anomaly detection rule to obtain second sensing data, and specifically includes: the processing module adopts a business rule engine to judge the abnormality of the second perception data, and the business rule engine stores preset business rules; the processing module judges whether the second perception data is matched with a plurality of abnormal conditions defined in the abnormal detection rule, wherein the plurality of abnormal conditions comprise a threshold abnormal condition, a trend abnormal condition and a statistical abnormal condition; if the second sensing data is matched with the first abnormal condition, the processing module executes the operation corresponding to the first abnormal condition and displays the operation in the first visual interface, wherein the operation comprises the generation of an alarm and the display of a notice, and the first abnormal condition is any one of a plurality of abnormal conditions.
Optionally, the processing module processes the first sensing data based on a preset service rule to obtain second sensing data, processes the plurality of first sensing data based on a data screening rule to obtain second sensing data, and specifically includes: the processing module judges whether the first perception data meets a screening condition, wherein the screening condition is data repetition or data deletion; and if the first perception data meets the screening condition, the processing module deletes the first perception data to obtain second perception data.
Optionally, the displaying module displays the plurality of second sensing data to the user through the first visual interface, specifically including: the acquisition module acquires a target data type of any one of a plurality of second sensing data, wherein the target data type is any one of numerical data, state data, position data, time data and count data; the processing module searches a display mode corresponding to the target data type in a preset database, wherein the preset database comprises a corresponding relation between the data type of the second perception data and the display mode, and the display mode comprises a graph, a line graph and a histogram; and the display module displays the first visual interface on the second perception data corresponding to the target data type according to the display mode corresponding to the target data type.
Optionally, after the display module performs the display of the first visual interface on the second perception data corresponding to the target data type according to the display mode corresponding to the target data type, the method further includes: the processing module responds to the modification operation of the user on the first visual interface, wherein the modification operation comprises modification of a data display mode; the processing module modifies the first visual interface based on the modification instruction corresponding to the modification operation to obtain a second visual interface; and the display module displays the second visual interface to a user.
In a third aspect the application provides an electronic device comprising a processor, a memory, a user interface and a network interface, the memory for storing instructions, the user interface and the network interface for communicating with other devices, the processor for executing instructions stored in the memory to cause the electronic device to perform a method of any of the above.
In a fourth aspect of the application there is provided a computer readable storage medium, in which computer instructions are stored. When the instructions are executed, the method steps shown above are performed.
In summary, one or more technical solutions provided in the embodiments of the present application at least have the following technical effects or advantages:
1. The centralized management and processing of various data sources in the area are realized by integrating various first perception data acquired by a plurality of perception facilities and applying the preset business rules for processing, so that the consistency of the data is improved. The preset business rules, including data screening, aggregation, association analysis and anomaly detection rules, are adopted to enable the data processing process to be automatic and standardized, reduce the requirement of human intervention, and improve the efficiency and consistency of data processing. And the second perception data is mapped to the standard data model through the standardized data interface and is transmitted according to a preset standard format, so that the consistency and interoperability of the data are ensured, and the complexity of data integration is reduced. Simultaneously, a plurality of second perception data are presented to a user in an intuitive and interactive mode through a first visual interface, so that the user can better understand and analyze various data of the area, and management and decision making are supported;
2. By adopting a streaming data processing technology, a plurality of first perception data are created into a plurality of real-time data streams, so that the instant processing of the data acquired by the perception facilities is facilitated, the data can be continuously transmitted in a streaming form, and the real-time performance of the data processing is improved. The data access layer is used for acquiring a plurality of real-time data streams and integrating the data streams together according to a time sequence, so that the data acquired by different sensing facilities can be cooperatively analyzed according to a time axis, and the time correlation of the data can be comprehensively considered. Since the data processing is real-time, the manager can monitor and respond to the data more quickly;
3. The display mode, the size and the color of the visual interface are allowed to be customized by a user according to personal preference and requirements, so that the requirements of the user are met. The user can adjust the interface according to different working scenes and requirements so as to meet the requirements of specific tasks.
Drawings
Fig. 1 is a flow chart of a digital twin-based regional intelligent management method according to an embodiment of the present application.
Fig. 2 is a schematic structural diagram of an area intelligent management device based on digital twinning according to an embodiment of the present application.
Fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Reference numerals illustrate: 201. an acquisition module; 202. a processing module; 203. a display module; 300. an electronic device; 301. a processor; 302. a communication bus; 303. a user interface; 304. a network interface; 305. a memory.
Detailed Description
In order that those skilled in the art will better understand the technical solutions in the present specification, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments.
In describing embodiments of the present application, words such as "for example" or "for example" are used to mean serving as examples, illustrations, or descriptions. Any embodiment or design described herein as "such as" or "for example" in embodiments of the application should not be construed as preferred or advantageous over other embodiments or designs. Rather, the use of words such as "or" for example "is intended to present related concepts in a concrete fashion.
In the description of embodiments of the application, the term "plurality" means two or more. For example, a plurality of systems means two or more systems, and a plurality of screen terminals means two or more screen terminals. Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating an indicated technical feature. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless expressly specified otherwise.
In the process of carrying out regional intelligent management by adopting a digital twin technology, various data types and data sources are involved, and the data may have association relations. However, in the related method, the data collected by different sensing facilities are subjected to single data processing and presentation, which may ignore the diversity and relevance of the data. The method cannot fully display the management condition of the area, so that the comprehensive area management cannot be realized. In order to solve the above problems, the present application provides a digital twin-based regional intelligent management method, a device and an electronic apparatus, and referring to fig. 1, fig. 1 is a flow chart of a disclosed digital twin-based regional intelligent management method according to an embodiment of the present application. The method is applied to a digital twin platform and comprises the following steps of S101 to S104:
Step S101: and acquiring a plurality of types of first sensing data acquired by a plurality of sensing facilities, wherein one sensing facility correspondingly acquires one type of first sensing data.
In the above steps, various sensing facilities are deployed in the preset area, and the sensing facilities may include sensors, monitoring cameras, device monitoring apparatuses, energy management devices, and the like. Each sensing facility is responsible for collecting one or more sensing data such as temperature, humidity, pressure, equipment operating status, energy consumption, etc. After the sensing facility collects the sensing data, the sensing facility transmits the data to the data twinning platform.
In a digital twin platform, a streaming data processing technology is adopted to create a plurality of first perception data into a plurality of real-time data streams, wherein one first perception data corresponds to one real-time data stream; and acquiring a plurality of real-time data streams through the data access layer so that the plurality of real-time data streams are input according to the time sequence.
Specifically, for each first perceived data, a corresponding data stream is first created using a streaming data processing technique (APACHE KAFKA), each data stream being responsible for capturing a particular data type from a particular perceived facility. For example, the data of the temperature sensor will be distributed to one temperature data stream. And acquiring the sensing data from the sensing facility in real time by adopting an HTTP communication protocol, and integrating various data into a central data stream processing platform after the sensing data is acquired so as to facilitate subsequent processing. And at the same time, the acquisition time of each data stream is marked for subsequent time series analysis and presentation.
Step S102: and processing the plurality of first perception data based on preset business rules to obtain second perception data, wherein the preset business rules comprise data cleaning rules, data screening rules, data aggregation rules, data association analysis rules and abnormality detection rules.
In the above step, processing the plurality of first sensing data based on the data filtering rule to obtain second sensing data specifically includes: judging whether the first perception data meets a screening condition, wherein the screening condition is that data repetition or data deletion exists; and if the first perception data meets the screening condition, deleting the first perception data to obtain second perception data.
Specifically, the data filtering rule includes removing duplicate values, processing missing values, and outlier processing. Checking whether repeated records exist in the data based on the data cleaning rule, deleting the repeated records so as to avoid the repeated introduction of the data into analysis, checking the missing value in the data, and deleting the missing value. And identifying and processing an abnormal value, wherein the abnormal value is an input error condition in the data record.
Processing the plurality of first perception data based on the data aggregation rule to obtain second perception data specifically comprises the following steps: judging the aggregation dimension of a plurality of first perception data, wherein the aggregation dimension comprises a time dimension, a region dimension and a category dimension; and aggregating the plurality of first perception data according to the aggregation dimension and the aggregation rule to obtain a plurality of second perception data, wherein the aggregation rule comprises aggregation in the same time period, aggregation in the same region and aggregation in the same category, and one type of second perception data corresponds to one or more types of first perception data.
Specifically, the dimensions for aggregation are first determined, including a time dimension, a region dimension, and a category dimension. For the time dimension, the aggregation can be performed in time periods of minutes, hours or days, and for each time period, different aggregation modes can be used for aggregation, wherein the aggregation modes comprise averaging, summation, maximum value and minimum value. The selection of the aggregation mode can be selected according to actual requirements, the application is not limited to the selection, and each time period after aggregation generates an aggregated data point. For the regional dimension, the first sensing data in the same region can be aggregated, and for different regions, different aggregation modes can be selected according to actual requirements. For category dimensions, first perceived data belonging to the same data category may be aggregated. After the above-described aggregation rule-based processing is completed, a plurality of second perception data can be obtained. The second sensory data may be used for subsequent analysis, visualization operations, and for generating alarms and notifications to better understand data trends and relationships within the area.
For example, assuming that there are multiple temperature sensors in an industrial park, the temperature value may be recorded every one minute. In the time-dimension polymerization, the temperature values within one hour are averaged to calculate an average temperature per hour. This can be used to learn about average temperature trends per hour on the campus. Assuming that the campus monitors power consumption using multiple electricity meters, a total aggregate may be employed to calculate the total power consumption per hour, thereby helping to understand the total power usage per hour. In the process of regional dimension aggregation, the campus is divided into different regions, each region is internally provided with a humidity sensor, and average aggregation can be adopted to calculate average humidity in each region, so that the humidity levels of different regions can be compared. Assuming that the waste bins in each zone are equipped with sensors to monitor waste fill, a total aggregate can be used to calculate the total waste production in each zone to help understand the waste production in the different zones. For class dimension aggregation, assuming multiple meteorological sensors within a campus, each sensor collecting different types of meteorological data, such as temperature, humidity, and wind speed, average aggregation may be employed for each meteorological data. For example, the average temperature, average humidity and average wind speed for different meteorological data may be calculated. This helps to understand the campus condition under different meteorological conditions. Assuming different types of energy, such as electricity and natural gas, are used on the campus, a sum aggregate may be employed for each energy type to calculate the total consumption of each type of energy. This helps to understand the use of various energy sources.
The data association analysis rules are used to help identify correlations or relationships between data, and the Apriori algorithm (a priori algorithm) is used to discover association rules between data based on the nature of frequent item sets. A first perceived dataset in the overall central data stream processing platform is first scanned to identify a frequent item set, which is a combination of items that frequently occur in the dataset. And generating a series of candidate item sets simultaneously, detecting whether the candidate item sets occur frequently, and calculating the support degree of each candidate item set, namely the occurrence frequency in data. Designating a preset support threshold, filtering out a term set with support lower than the preset support threshold by using an Apriori algorithm, and reserving frequent term sets. Finally, association rules are generated, which indicate the relationships between the items.
For example, in a regional intelligent management system for an industrial park, the Apriori algorithm may be used to mine association rules between perceived utility data. For example, assuming that the data set includes sensory facility data within a campus, where the items may be different types of devices or sensors, by running these algorithms it is possible to find out which devices or sensors' data are often present at the same time, which helps the manager to better understand the relevance between the devices, possibly helping resource allocation and maintenance decisions. For the perception data with higher correlation, the correlation display can be performed in the subsequent display process. The sensing facilities in the campus are assumed to include temperature sensors, humidity sensors, light sensors, and people flow sensors. These sensors collect data at different locations and at different times. Based on the data correlation analysis rules, it may be found that the temperature sensor data and the humidity sensor data have a strong correlation, such as a high temperature (high temperature sensor data) is often accompanied by a low humidity (low humidity sensor data). At this time, in the process of display, the data of the temperature sensor and the data of the humidity sensor can be displayed together.
In one possible implementation manner, the processing of the plurality of first perception data based on the anomaly detection rule to obtain the second perception data specifically includes: performing abnormality judgment on the second perception data by adopting a business rule engine, wherein a preset business rule is stored in the business rule engine; judging whether the second perception data is matched with a plurality of abnormal conditions defined in the abnormal detection rule, wherein the plurality of abnormal conditions comprise a threshold abnormal condition, a trend abnormal condition and a statistical abnormal condition; and if the second sensing data is matched with the first abnormal condition, executing the operation corresponding to the first abnormal condition, and displaying the operation in the first visual interface, wherein the operation comprises the generation of an alarm and the display of a notice, and the first abnormal condition is any one of a plurality of abnormal conditions.
Specifically, a business rule engine is firstly established, wherein a preset business rule is stored in the business rule engine, the preset business rule comprises an abnormality detection rule, the abnormality detection rule comprises a threshold abnormality condition, a trend abnormality condition and a statistical abnormality condition, the threshold abnormality condition is based on a predefined threshold, the abnormality is triggered when the data exceeds or falls below the threshold, and the trend abnormality condition is the trend of the monitored value. For example, a certain parameter that increases or decreases several times in succession indicates a trend anomaly, and a statistical anomaly condition is to detect anomalies using a statistical method, for example, by checking whether the data deviates from a normal distribution by means of a mean and a standard deviation. And the business rule engine matches the abnormal judgment conditions based on the preset business rules, and if the second perception data matches the abnormal conditions, the corresponding operation is executed, including generating an alarm or a notification, and simultaneously presenting the abnormal condition to the user through the first visual interface.
Step S103: and carrying out standardization processing on the plurality of second perception data by adopting a standardized data interface and mapping the standardized data to a standard data model so that the standard data model can conveniently transmit the plurality of second perception data to the first visual interface according to a preset standard format, wherein the standardization processing comprises format standardization, transmission protocol standardization, data field standardization and data transmission frequency standardization.
In the step, the plurality of second perception data are subjected to standardized processing so as to be convenient to be transmitted to the first visual interface, so that the consistency of the data is ensured. Format normalization refers to the fact that different sensing devices may represent data in different data formats during the acquisition process. Data format standardization refers to converting such data into a unified format to ensure that such data has a consistent structure and representation, for example, the data format may be unified into JSON format for transmission. Transport protocol standardization refers to the possibility that different data sources may exchange data using different communication protocols and transport means. The goal of the transmission protocol standardization is to ensure that different data sources use the same communication protocol and standardized transmission mechanism so as to realize reliable transmission of data, thereby being beneficial to eliminating the problem of mismatching of the communication protocol and ensuring correct transmission of the data. Data field normalization refers to the possibility that different sensors may use different fields and data structures. Data field normalization ensures that these fields are mapped into a generic, standard data model to ensure that data from different data sources can be properly transferred. At the same time, different data sources may generate data updates at different frequencies. Data transmission frequency normalization involves normalizing the time interval of data updates to ensure that data is updated at a consistent rate on the first visualization interface. Through the normalization process described above, the various second sensory data are converted to a common standard, such that the various sensory data may be presented in a consistent manner in the first visual interface without being affected by the variability of the data sources.
Step S104: and displaying the plurality of second perception data to a user through the first visual interface.
In the step, the target data type of any one of the plurality of second sensing data is acquired, wherein the target data type is any one of numerical value data, state data, position data, time data and count data; searching a display mode corresponding to the target data type in a preset database, wherein the preset database comprises a corresponding relation between the data type of the second perception data and the display mode, and the display mode comprises a graph, a line graph and a histogram; and according to the display mode corresponding to the target data type, displaying the first visual interface on the second perception data corresponding to the target data type.
Specifically, firstly, the data types are matched through rule conditions and data attributes, and the specific target data types to be displayed are determined, wherein the target data types comprise numerical data, state data, position data, time data or count data and the like. And selecting a proper display mode according to the mapping rule of the target data type from a preset database. After the display mode is determined, performing visualization processing on the second perception data corresponding to the target data type, and selecting the display modes such as a curve chart, a line chart, a histogram, a scatter chart, a heat chart and a state icon by selecting proper visualization tools. The extracted second sensory data is bound to the selected visualization tool to present the data in the visualization, mapping the data to the axes of the icon, the data points, and other visualization elements.
For example, the numerical data may be displayed in a graph, which generally relates to a trend of change, the graph may be used to display the change of temperature with time, and the graph may be used to clearly display the change of temperature with time, so as to help the manager know the trend of temperature rise or fall, and possible abnormal situation. The status data can be displayed in the form of status icons, which are generally discrete, and through which the on and off states of the device can be more intuitively displayed. For the counting data, a histogram mode can be adopted, for example, the energy consumption conditions of different buildings can be displayed in a histogram mode, so that the high-consumption areas are identified, and the performance of different areas can be better compared.
In a possible implementation manner, after the first visual interface is displayed on the second perception data corresponding to the target data type according to the display manner corresponding to the target data type, the method further includes: responding to the modification operation of the user on the first visual interface, wherein the modification operation comprises modification of the data display mode; modifying the first visual interface based on a modification instruction corresponding to the modification operation to obtain a second visual interface; and displaying the second visual interface to a user.
Specifically, the user can also customize the display interface, and the user can select different display modes, such as a graph, a bar graph and the like, through options or drop-down menus on the interface. At the same time, the user can also adjust the size of the first visual interface by adjusting the border and scaling of the interface, and at the same time, the user can also modify the colors of icons, data points or text to better distinguish different data or highlight important information. When it is detected that the user has performed a modification operation, corresponding modification instructions, such as redrawing a chart, changing a chart type, rearranging data points, etc., need to be generated. And finally, displaying the modified second visual interface to the user.
Referring to fig. 2, the present application further provides a digital twin-based regional intelligent management device, which includes: the device is a digital twin platform, which comprises: an acquisition module 201, a processing module 202 and a display module 203;
An acquisition module 201, configured to acquire a plurality of types of first sensing data acquired by a plurality of sensing facilities, where one sensing facility acquires a corresponding type of first sensing data;
The processing module 202 is configured to process the plurality of first sensing data based on a preset service rule to obtain second sensing data, where the preset service rule includes a data cleaning rule, a data screening rule, a data aggregation rule, a data association analysis rule, and an anomaly detection rule;
The processing module 202 is further configured to perform standardization processing on the plurality of second sensing data by using a standardized data interface and map the standardized processing to a standard data model, so that the standard data model transmits the plurality of second sensing data to the first visual interface according to a preset standard format, and the standardization processing includes format standardization, transmission protocol standardization, data field standardization and data transmission frequency standardization;
and the display module 203 is configured to display the plurality of second sensing data to the user through the first visual interface.
In one possible implementation, the acquiring module 201 acquires a plurality of first sensing data acquired by a plurality of sensing facilities, specifically including: the acquisition module 201 adopts a streaming data processing technology to create a plurality of first perception data into a plurality of real-time data streams, wherein one first perception data corresponds to one real-time data stream; the acquisition module 201 acquires a plurality of real-time data streams through the data access layer, so that the plurality of real-time data streams are input according to a time sequence.
In a possible implementation manner, in the processing module 202 processes the first sensing data based on the preset business rule to obtain the second sensing data, processes the plurality of first sensing data based on the data aggregation rule to obtain the second sensing data, specifically includes: the processing module 202 determines an aggregate dimension of the plurality of first perception data, the aggregate dimension including a time dimension, a region dimension, and a category dimension; the processing module 202 aggregates the plurality of first sensing data according to the aggregation dimension and the aggregation rule to obtain a plurality of second sensing data, wherein the aggregation rule comprises aggregation in the same time period, aggregation in the same region and aggregation in the same category, and one type of second sensing data corresponds to one or more types of first sensing data.
In a possible implementation manner, in the processing module 202 processes the first sensing data based on the preset business rule to obtain the second sensing data, processes the plurality of first sensing data based on the anomaly detection rule to obtain the second sensing data, specifically includes: the processing module 202 performs abnormality judgment on the second perceived data by adopting a business rule engine, wherein a preset business rule is stored in the business rule engine; the processing module 202 determines whether the second perceived data matches a plurality of abnormal conditions defined in the abnormal detection rule, the plurality of abnormal conditions including a threshold abnormal condition, a trend abnormal condition, and a statistical abnormal condition; if the second perceived data matches the first abnormal condition, the processing module 202 executes an operation corresponding to the first abnormal condition, and displays the operation in the first visual interface, where the operation includes generating an alarm and displaying a notification, and the first abnormal condition is any one of the plurality of abnormal conditions.
In a possible implementation manner, in the processing module 202 processes the first sensing data based on the preset business rule to obtain the second sensing data, processes the plurality of first sensing data based on the data filtering rule to obtain the second sensing data, specifically includes: the processing module 202 judges whether the first perceived data satisfies a screening condition, wherein the screening condition is data repetition or data deletion; if the first sensing data meets the filtering condition, the processing module 202 deletes the first sensing data to obtain the second sensing data.
In one possible implementation, the presenting module 203 presents the plurality of second perception data to the user through the first visual interface, specifically includes: the acquisition module 201 acquires a target data type of any one of a plurality of second sensing data, the target data type being any one of numerical value data, state data, position data, time data, and count data; the processing module 202 searches a display mode corresponding to the target data type in a preset database, wherein the preset database comprises a corresponding relation between the data type of the second perception data and the display mode, and the display mode comprises a graph, a line graph and a histogram; the display module 203 displays the first visual interface on the second perception data corresponding to the target data type according to the display mode corresponding to the target data type.
In a possible implementation manner, after the display module 203 performs the display of the first visual interface on the second perceived data corresponding to the target data type according to the display manner corresponding to the target data type, the method further includes: the processing module 202 responds to the modification operation of the user on the first visual interface, wherein the modification operation comprises modification of the data display mode; the processing module 202 modifies the first visual interface based on the modification instruction corresponding to the modification operation to obtain a second visual interface; the display module 203 displays the second visual interface to the user.
It should be noted that: in the device provided in the above embodiment, when implementing the functions thereof, only the division of the above functional modules is used as an example, in practical application, the above functional allocation may be implemented by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules, so as to implement all or part of the functions described above. In addition, the embodiments of the apparatus and the method provided in the foregoing embodiments belong to the same concept, and specific implementation processes of the embodiments of the method are detailed in the method embodiments, which are not repeated herein.
The application also discloses electronic equipment. Referring to fig. 3, fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure. The electronic device 300 may include: at least one processor 301, at least one network interface 304, a user interface 303, a memory 305, at least one communication bus 302.
Wherein the communication bus 302 is used to enable connected communication between these components.
The user interface 303 may include a Display screen (Display), a Camera (Camera), and the optional user interface 303 may further include a standard wired interface, and a wireless interface.
The network interface 304 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface), among others.
Wherein the processor 301 may include one or more processing cores. The processor 301 utilizes various interfaces and lines to connect various portions of the overall server, perform various functions of the server and process data by executing or executing instructions, programs, code sets, or instruction sets stored in the memory 305, and invoking data stored in the memory 305. Alternatively, the processor 301 may be implemented in at least one hardware form of digital signal Processing (DIGITAL SIGNAL Processing, DSP), field-Programmable gate array (Field-Programmable GATE ARRAY, FPGA), programmable logic array (Programmable Logic Array, PLA). The processor 301 may integrate one or a combination of several of a central processing unit (Central Processing Unit, CPU), an image processor (Graphics Processing Unit, GPU), and a modem, etc. The CPU mainly processes an operating system, a user interface, an application program and the like; the GPU is used for rendering and drawing the content required to be displayed by the display screen; the modem is used to handle wireless communications. It will be appreciated that the modem may not be integrated into the processor 301 and may be implemented by a single chip.
The Memory 305 may include a random access Memory (Random Access Memory, RAM) or a Read-Only Memory (Read-Only Memory). Optionally, the memory 305 includes a non-transitory computer readable medium (non-transitory computer-readable storage medium). Memory 305 may be used to store instructions, programs, code, sets of codes, or sets of instructions. The memory 305 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing the above-described respective method embodiments, etc.; the storage data area may store data or the like involved in the above respective method embodiments. Memory 305 may also optionally be at least one storage device located remotely from the aforementioned processor 301. Referring to fig. 3, an operating system, a network communication module, a user interface module, and an application program of the digital twin-based regional intelligent management method may be included in the memory 305 as one type of computer storage medium.
In the electronic device 300 shown in fig. 3, the user interface 303 is mainly used for providing an input interface for a user, and acquiring data input by the user; and the processor 301 may be configured to invoke an application program in the memory 305 that stores digital twin based regional intelligence management methods that, when executed by the one or more processors 301, cause the electronic device 300 to perform the methods as described in one or more of the embodiments above. It should be noted that, for simplicity of description, the foregoing method embodiments are all described as a series of acts, but it should be understood by those skilled in the art that the present application is not limited by the order of acts described, as some steps may be performed in other orders or concurrently in accordance with the present application. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all of the preferred embodiments, and that the acts and modules referred to are not necessarily required for the present application.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and for parts of one embodiment that are not described in detail, reference may be made to related descriptions of other embodiments.
In the several embodiments provided by the present application, it should be understood that the disclosed apparatus may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, such as a division of units, merely a division of logic functions, and there may be additional divisions in actual implementation, such as multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some service interface, device or unit indirect coupling or communication connection, electrical or otherwise.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable memory. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in whole or in part in the form of a software product stored in a memory, comprising several instructions for causing a computer device (which may be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method of the various embodiments of the present application. And the aforementioned memory includes: various media capable of storing program codes, such as a U disk, a mobile hard disk, a magnetic disk or an optical disk.
The foregoing is merely exemplary embodiments of the present disclosure and is not intended to limit the scope of the present disclosure. That is, equivalent changes and modifications are contemplated by the teachings of this disclosure, which fall within the scope of the present disclosure. Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure.
This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains.
Claims (10)
1. The regional intelligent management method based on digital twinning is characterized by being applied to a digital twinning platform, and comprises the following steps:
acquiring a plurality of first sensing data acquired by a plurality of sensing facilities, wherein one sensing facility correspondingly acquires one or more first sensing data;
processing the plurality of first perception data based on preset business rules to obtain second perception data, wherein the preset business rules comprise data screening rules, data aggregation rules, data association analysis rules and abnormality detection rules;
Carrying out standardization processing on the plurality of second perception data by adopting a standardized data interface and mapping the standardized processing to a standard data model so that the standard data model can transmit the plurality of second perception data to a first visual interface according to a preset standard format, wherein the standardization processing comprises format standardization, transmission protocol standardization, data field standardization and data transmission frequency standardization;
and displaying a plurality of second perception data to a user through a first visual interface.
2. The method according to claim 1, wherein the acquiring the plurality of first sensing data acquired by the plurality of sensing devices specifically comprises:
Creating a plurality of first perception data into a plurality of real-time data streams by adopting a streaming data processing technology, wherein one of the first perception data corresponds to one real-time data stream;
And acquiring a plurality of real-time data streams through a data access layer so that the plurality of real-time data streams are input according to a time sequence.
3. The method of claim 1, wherein in the processing the first sensing data based on the preset business rule to obtain second sensing data, processing a plurality of first sensing data based on the data aggregation rule to obtain second sensing data, specifically includes:
judging the aggregation dimension of a plurality of first perception data, wherein the aggregation dimension comprises a time dimension, a region dimension and a category dimension;
And aggregating the plurality of first perception data according to the aggregation dimension and the aggregation rule to obtain a plurality of second perception data, wherein the aggregation rule comprises aggregation in the same time period, aggregation in the same region and aggregation in the same category, and one type of second perception data corresponds to one or more types of first perception data.
4. The method of claim 1, wherein in the processing the first sensing data based on the preset business rule to obtain second sensing data, processing a plurality of first sensing data based on the anomaly detection rule to obtain second sensing data, specifically includes:
Performing abnormality judgment on the second perceived data by adopting a business rule engine, wherein the business rule engine stores the preset business rule;
Judging whether the second perception data is matched with a plurality of abnormal conditions defined in the abnormal detection rule, wherein the plurality of abnormal conditions comprise a threshold abnormal condition, a trend abnormal condition and a statistical abnormal condition;
and if the second perception data is matched with a first abnormal condition, executing an operation corresponding to the first abnormal condition, and displaying the operation in the first visual interface, wherein the operation comprises the steps of generating an alarm and displaying a notice, and the first abnormal condition is any one of a plurality of abnormal conditions.
5. The method of claim 1, wherein in the processing the first sensing data based on the preset business rule to obtain second sensing data, processing a plurality of first sensing data based on the data filtering rule to obtain second sensing data, specifically includes:
judging whether the first perception data meets a screening condition or not, wherein the screening condition is that data repetition or data deletion exists;
And if the first perception data meets the screening condition, deleting the first perception data to obtain second perception data.
6. The method according to claim 1, wherein the presenting the plurality of second perception data to the user through the first visual interface comprises:
Obtaining a target data type of any one of the plurality of second sensing data, wherein the target data type is any one of numerical value data, state data, position data, time data and count data;
Searching a display mode corresponding to the target data type in a preset database, wherein the preset database comprises a corresponding relation between the data type of the second perception data and the display mode, and the display mode comprises a graph, a line graph and a histogram;
And displaying the first visual interface on the second perception data corresponding to the target data type according to the display mode corresponding to the target data type.
7. The method of claim 6, wherein after the displaying the first visual interface on the second perceived data corresponding to the target data type according to the display manner corresponding to the target data type, the method further comprises:
Responding to the modification operation of the user on the first visual interface, wherein the modification operation comprises modification of a data display mode;
Modifying the first visual interface based on a modification instruction corresponding to the modification operation to obtain a second visual interface;
and displaying the second visual interface to the user.
8. Regional wisdom management device based on digital twin, its characterized in that, the device is digital twin platform, digital twin platform includes: an acquisition module (201), a processing module (202) and a display module (203);
The acquisition module (201) is configured to acquire a plurality of types of first sensing data acquired by a plurality of sensing facilities, where one sensing facility acquires one type of first sensing data correspondingly;
The processing module (202) is configured to process the plurality of first sensing data based on a preset service rule to obtain second sensing data, where the preset service rule includes a data cleaning rule, a data screening rule, a data aggregation rule, a data association analysis rule and an anomaly detection rule;
the processing module (202) is further configured to perform standardization processing on the plurality of second sensing data by using a standardized data interface and map the standardized processing to a standard data model, so that the standard data model transmits the plurality of second sensing data to the first visual interface according to a preset standard format, and the standardization processing includes format standardization, transmission protocol standardization, data field standardization and data transmission frequency standardization;
the display module (203) is used for displaying a plurality of second perception data to a user through a first visual interface.
9. An electronic device comprising a processor (301), a memory (305), a user interface (303) and a network interface (304), the memory (305) being adapted to store instructions, the user interface (303) and the network interface (304) being adapted to communicate to other devices, the processor (301) being adapted to execute the instructions stored in the memory (305) to cause the electronic device (300) to perform the method according to any of claims 1-7.
10. A computer readable storage medium storing instructions which, when executed, perform the method steps of any of claims 1-7.
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