Smart Park Digital Twin Platform System

Abstract

The present invention relates to the technical field of smart parks. Specifically, it relates to a digital twin platform system for a smart park, which includes a park Internet of Things system, a data center system, and a cloud application system; the data center system includes a device gateway, the device gateway is connected to a first message middleware, and the first message middleware is connected to a data center; the cloud application system includes a second message middleware, the second message middleware is connected to an RDBMS; the RDBMS is connected to an application server, the application server is connected to a digital twin application module and a background management module; the application server is connected to the data center, and the second message middleware is connected to the first message middleware. The present invention can support planning and construction, assist park operation, and drive industrial development.

Description

Technical Field

[0001] The present invention relates to the technical field of smart parks, and specifically, to a digital twin platform system for smart parks. Background Art

[0002] A smart park generally refers to a standard building or building complex planned and constructed by the government (in cooperation between private enterprises and the government), with complete water supply, power supply, gas supply, communication, roads, warehousing and other supporting facilities, reasonable layout, and capable of meeting the production and scientific experiment needs of a certain specific industry.

[0003] Digital twin makes full use of data such as physical models, sensor updates, and operation history, integrates the simulation processes of multiple disciplines, multiple physical quantities, multiple scales, and multiple probabilities, and completes the mapping in the virtual space, so as to reflect the full life cycle process of the corresponding physical equipment. Digital twin is a concept beyond reality and can be regarded as a digital mapping system of one or more important and interdependent equipment systems. Digital twin is a generally applicable theoretical and technical system that can be applied in many fields. Currently, it is widely used in product design, product manufacturing, medical analysis, engineering construction and other fields. Currently, it is most deeply applied in the field of engineering construction in China, and the field of intelligent manufacturing has the highest attention and the hottest research.

[0004] Currently, the intelligent application systems of parks are mainly reflected in the following aspects:

[0005] 1. In terms of park safety supervision, the main functions are reflected in monitoring, early warning, hidden danger investigation, comprehensive emergency linkage, etc.

[0006] 2. In terms of park environmental protection supervision, such as the monitoring of organized and unorganized emissions in the park, energy monitoring, air pollution, water pollution monitoring, etc.

[0007] 3. In terms of park security management, such as the closed management of the park, the monitoring and alarm management inside and around the park, the management of dangerous chemical vehicles in the park, the management of dangerous chemical parking lots and logistics in the park, etc.

[0008] 4. In terms of park energy management, the monitoring of energy consumption of enterprises in the park is carried out, such as the remote collection and analysis of data such as water, electricity, gas, and steam of enterprises through the Internet of Things, which plays a decision-making support role in the energy dispatching of the park and responding to the government's energy conservation and consumption reduction targets.

[0009] However, in reality, smart parks are mixed, with low intelligence, requiring human-machine collaboration, which instead increases the labor intensity. Summary of the Invention

[0010] The content of the present invention is to provide a digital twin platform system for smart parks, which can overcome certain or some defects of the prior art.

[0011] A digital twin platform system for an intelligent park according to the present invention includes a park Internet of Things system, a data center system, and a cloud application system;

[0012] The data center system includes a device gateway, the device gateway is connected to a first message middleware, and the first message middleware is connected to a data center;

[0013] The cloud application system includes a second message middleware, the second message middleware is connected to an RDBMS; the RDBMS is connected to an application server, the application server is connected to a digital twin application module and a background management module; the application server is connected to the data center, and the second message middleware is connected to the first message middleware;

[0014] The digital twin application module can use BIM+GIS to construct a building information model for the buildings in the park, and visually display the data feedback by all sensors installed in the park and the historical operation data.

[0015] In one embodiment, the digital twin application module includes a product investment promotion module, an operation service module, a commercial consumption module, an intelligent Internet of Things module, an online platform operation situation module, a park activity operation module, a procurement operation module, a park energy consumption module, and an intelligent parking module.

[0016] In one embodiment, the commercial consumption module includes a monitoring device, a data acquisition and preprocessing sub-unit, a data processing and modeling unit, and a data sub-transmission module;

[0017] The monitoring device collects the personnel flow in the commercial area of the park;

[0018] The data acquisition and preprocessing sub-unit obtains the data of each store in the park, classifies and summarizes the stores, and displays each store in the corresponding building information model;

[0019] The data processing and modeling unit obtains the data of the monitoring device, divides the commercial area according to the number of personnel flow, and marks different types of commercial areas with different colors in the building information model, reads the data of the data acquisition and preprocessing value unit, and establishes a commercial consumption model data acquisition unit according to the daily turnover status and customer consumption list of each store's history;

[0020] The data sub-transmission module transmits the data of the data processing and modeling unit to the data processing center, and the data processing center processes the data and outputs an investment promotion operation report to the product investment promotion module and the operation service module.

[0021] In one embodiment, the park Internet of Things system includes multiple projects, and the projects are connected to corresponding edge servers.

[0022] In one embodiment, the project includes Internet of Things devices, a sub-control system, and sensors.

[0023] In one embodiment, a data center is connected to multiple data processing service modules.

[0024] In one embodiment, a second message middleware is connected to a Redis cache module.

[0025] In one embodiment, the data processing service modules include a stream processing module, a third message middleware, a data storage module, and a batch processing module.

[0026] In one embodiment, the stream processing module includes a data cleaning module, a data parsing module, an alarm judgment module, and a status judgment module that are connected in sequence.

[0027] In one embodiment, the data storage module includes an HDFS raw database, a Cassandra NoSQL database, an RDBMS business database, and a Redis real-time database.

[0028] In one embodiment, the batch processing module includes a Spark data analysis module, a Spark ML machine learning module, and a data mining module.

[0029] The present invention can support planning and construction, assist in park operation, and drive industrial development. Through the cooperation among the park Internet of Things system, the data center system, and the cloud application system, the convenience of the park is greatly enhanced, and the work efficiency of park employees is also improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 It is a structural block diagram of a digital twin platform system for a smart park in Embodiment 1;

[0031] Figure 2 It is a structural block diagram of the data processing service module in Embodiment 1. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0032] To further understand the content of the present invention, the present invention will be described in detail in combination with the drawings and embodiments. It should be understood that the embodiments are only for explaining the present invention and not for limiting it.

[0033] Embodiment 1

[0034] As Figure 1 and Figure 2 shown, this embodiment provides a digital twin platform system for a smart park, which includes a park Internet of Things system, a data center system, and a cloud application system.

[0035] The campus IoT system includes multiple projects, which are connected to corresponding edge servers. The projects include IoT devices, sub-control systems, and sensors.

[0036] The data center system includes a device gateway, the device gateway is connected to a first message middleware, the first message middleware is connected to a data center; the data center is connected to a plurality of data processing service modules.

[0037] Message middleware is a supporting software system that provides synchronous or asynchronous, reliable message transmission for application systems in a network environment based on queue and message passing technology. Message middleware uses efficient and reliable message passing mechanisms for platform-independent data exchange and integrates distributed systems based on data communication. By providing message passing and message queuing models, it can expand inter-process communication in a distributed environment. Message middleware is suitable for distributed environments that require reliable data transmission. In a system using the message middleware mechanism, different objects activate each other's events by passing messages to complete corresponding operations. The sender sends the message to the message server, which stores the message in several queues and forwards it to the receiver at the appropriate time. Message middleware can communicate between different platforms. It is often used to shield the characteristics between various platforms and protocols and realize the collaboration between applications. Its advantage is that it can provide synchronous and asynchronous connections between clients and servers, and can transmit or store and forward messages at any time, which is why it goes one step further than remote procedure calls.

[0038] The data processing service module includes a stream processing module, a third message middleware, a data storage module and a batch processing module. The stream processing module includes a data cleaning module, a data analysis module, an alarm judgment module and a status judgment module connected in sequence. The data storage module includes an HDFS original database, a CassandraNoSQL database, an RDBMS business database and a Redis real-time database. The batch processing module includes a Spark data analysis module, a Spark ML machine learning module and a data mining module.

[0039] Data cleaning is the final step in the process of discovering and correcting identifiable errors in data files, including checking data consistency, handling invalid and missing values, etc. Unlike questionnaire review, post-entry data cleaning is generally done by computers rather than humans. Data cleaning is the process of re-examining and verifying data in order to remove duplicate information, correct existing errors, and provide data consistency.

[0040] In the process of network communication, data needs to be transmitted. There are two common data formats: JSON and XML. Cocos2d-x provides support for parsing these two data formats, mainly including: JSON data parsing and XML data parsing. The process of JSON data parsing is as follows: First, create a JSON file, then include the document.h and cocos-ext.h header files in the class, then obtain the JSON file path through FileUtils, and parse the JSON data through the Document object, and finally obtain data values of different types. The process of XML data parsing is as follows: First, create an XML file, then include the header file and use the named file in the class, then obtain the full path of the XML file, and load the XML file, and finally obtain and parse the elements.

[0041] The Hadoop Distributed File System (HDFS) is a Distributed File System designed to run on commodity hardware. It has many commonalities with existing distributed file systems. At the same time, its differences from other distributed file systems are also obvious. HDFS is a highly fault-tolerant system suitable for deployment on inexpensive machines. HDFS can provide high-throughput data access and is very suitable for applications on large-scale data sets. HDFS relaxes some POSIX constraints to achieve the purpose of streaming access to file system data. HDFS was initially developed as the infrastructure for the Apache Nutch search engine project. HDFS is part of the Apache Hadoop Core project. HDFS has the characteristics of being highly fault-tolerant and is designed to be deployed on low-cost hardware. Moreover, it provides high throughput to access application data and is suitable for applications with extremely large data sets. HDFS relaxes the POSIX requirements so that it can achieve streaming access to data in the file system.

[0042] Apache Cassandra is a major NoSQL distributed database management system that powers many modern business applications today. It offers continuous availability, high scalability and performance, strong security, and operational simplicity while reducing the total cost of ownership. Cassandra has a decentralized architecture. Any node can perform any operation. It offers AP (availability and partition tolerance) in the CAP principle. Cassandra has excellent single-row read performance as long as eventual consistency semantics are sufficient for the use case. Cassandra quorum reads are required for strict consistency and are naturally not as fast as Hbase reads. Cassandra does not support range-based row scans, which may be limiting in some use cases. Cassandra is well-suited to support single-row queries or select multiple rows based on column value indexes. If data is stored in columns in Cassandra to support range scans, the actual limit on row size in Cassandra is 10MB. Rows larger than this number can cause problems in terms of compression overhead and time.

[0043] RDBMS, also known as relational database management system, refers to a database built on the relational model that processes data in the database through mathematical concepts and methods such as set algebra. Common RDBMS products include: Mysql: The most widely used database in the Web era; Oracle: In previous large projects, such as in applications in the banking and telecommunications industries. Databases are managed through RDBMS. The RDBMS relational database management system is divided into a client and a server. The client manages data through SQL statements.

[0044] Redis is an open-source, networked, in-memory, optional persistent key-value store database written in ANSI C. Since June 2015, the development of Redis has been sponsored by Redis Labs, and from May 2013 to June 2015, its development was sponsored by Pivotal. Before May 2013, its development was sponsored by VMware. According to data from the monthly ranking website DB-Engines.com, Redis is the most popular key-value store database.

[0045] The Spark machine learning library package is divided into two: MLlib and ML. The MLlib package is based on RDD (Resilient Distributed Datasets), and the ML package is based on DataFrame. The process of Spark machine learning is the same as the traditional machine learning process, namely: data processing - modeling - model evaluation.

[0046] The cloud application system includes a second message middleware, which is connected to an RDBMS; the RDBMS is connected to an application server, and the application server is connected to a digital twin application module and a background management module; the application server is connected to a data center, and the second message middleware is connected to the first message middleware. The second message middleware is connected to a Redis cache module.

[0047] The digital twin application module can use BIM+GIS to build a building information model for the buildings in the park, and visually display the data feedback from all sensors installed in the park and the historical operation data.

[0048] The digital twin application module includes a product investment promotion module, an operation service module, a commercial consumption module, a smart Internet of Things module, an online platform operation status module, a park activity operation module, a procurement operation module, a park energy consumption module, and a smart parking module.

[0049] The data of each sub-module of the digital twin application module is interconnected, which is beneficial to the overall operation of the park. Here is an example to illustrate: The commercial consumption module includes a monitoring device, a data acquisition and preprocessing sub-unit, a data processing and modeling unit, and a data sub-transmission module. Specifically:

[0050] The monitoring device collects the personnel flow in the commercial area of the park.

[0051] The data acquisition and preprocessing sub-unit obtains the data of each store in the park, classifies the stores (such as Chinese cuisine, Western cuisine, hot pot, snack fast food restaurants, milk tea shops, etc.), and maps the information of each store to the corresponding building information model through the data processing center. Classifying and summarizing the stores can clearly find out which types of stores are in short supply / redundant, so that the staff in charge of the operation module and the investment promotion module can adopt different strategies to maintain the operation of the park, such as eliminating redundant and less competitive stores or introducing new stores.

[0052] The data processing and modeling unit obtains the data of the detection device, classifies the commercial areas into category one, category two, and category three according to the number of personnel flow from large to small, and marks and displays different categories of commercial areas with different colors in the building information model. It reads the data of the data acquisition and preprocessing value unit, and establishes a commercial consumption model based on the daily turnover status and customer consumption list of each store in the past.

[0053] This commercial consumption model includes the best-selling products of each merchant, the daily turnover of the merchant, and customer consumption habit information, and feeds back the best-selling products of the merchant to the merchant to facilitate the merchant to purchase materials. This commercial consumption model also has a warning function. For example, the sales volume of a certain store continuously declines compared with the same period, and this information will be sent to the operation service module. Then, the staff of the operation service module and the park activity operation module will intervene to understand the situation and assist in the operation of the store. For example, let the store place advertisements in a certain commercial area or organize corresponding activities to help the merchant increase the exposure rate.

[0054] The data sub-transmission module transmits the data of the data processing and modeling unit to the data processing center. The data processing center processes the data transmitted by the data sub-transmission module and outputs a business investment promotion operation report to the product investment promotion module and the operation service module. Among them, the data processing center can analyze the relationship viscosity between the turnover of the merchant and the store location. Generally speaking, there is a great relationship between the turnover of the merchant and the geographical location. For example, if the merchant is located in a first-class area with a large flow of people, the exposure rate will increase and the principle of nearby consumption will apply, so the passenger flow will also increase relatively. And according to different geographical locations, the rent of the store is adjusted, and the rent adjustment information is sent to the product investment promotion module.

[0055] This embodiment is based on the concept of digital twin construction of spatio-temporal geographic information, providing comprehensive services for data, applications, and AI analysis, and meeting the full range of needs of park planning, construction, management, and operation. The digital twin ecosystem of the smart park empowers digital construction.

[0056] Through the digital twin model, this embodiment combines engineering data, can trace historical engineering construction information, and brings auxiliary help to the subsequent park construction updates, maintenance, and repairs.

[0057] Based on the digital twin model, this embodiment builds display platforms for park investment promotion, Party building, cultural industries, 5G industries, etc., providing a digital and online display window for the park's external investment promotion and brand promotion.

[0058] Based on the digital twin model, this embodiment integrates the correlation of all user behavior data and business data in the park, combines big data analysis, and improves the service efficiency and operation income of the operation service; at the same time, it deeply explores new businesses and brings more scenario possibilities.

[0059] Based on the digital twin model, this embodiment conducts real-time data collection and monitoring of park energy consumption, passenger flow, Internet of Things devices (including electromechanical), park monitoring, etc., combines AI intelligent analysis and scenario integration, effectively saves manpower while improving safety management efficiency and preventing the occurrence of events.

[0060] Through the construction of an intelligent park, it helps the park to establish a unified organizational management coordination framework, a business management platform, and an internal and external service operation platform in terms of informatization.

[0061] This embodiment establishes a unified work process, collaboration, scheduling, and sharing mechanism. Through the integration of the cloud platform, with the cloud platform as the hub, a closely connected whole is formed to obtain efficient, collaborative, interactive, and overall benefits.

[0062] This embodiment establishes two major service and two major management systems of unified emergency management and daily management, internal and external services.

[0063] This embodiment establishes a unified integrated management platform, and in response to application requirements such as the safety, environmental protection, emergency, energy, economy, park, and enterprise office of the park, a park integrated management service system is established.

[0064] The above has schematically described the present invention and its implementation manners. This description is not restrictive. What is shown in the drawings is only one of the implementation manners of the present invention, and the actual structure is not limited thereto. Therefore, if those of ordinary skill in the art are inspired by it and, without departing from the purpose of the present invention, creatively design a structural manner and an embodiment similar to this technical solution, they shall fall within the protection scope of the present invention.

Claims

1. Digital twin platform system for smart park, characterized in that: It includes a park Internet of Things system, a data center system, and a cloud application system; the data center system includes a device gateway, the device gateway is connected to a first message middleware, and the first message middleware is connected to a data center; the cloud application system includes a second message middleware, and the second message middleware is connected to an RDBMS business database; the RDBMS business database is connected to an application server, and the application server is connected to a digital twin application module and a background management module; the application server is connected to the data center, and the second message middleware is connected to the first message middleware; the digital twin application module can use the Building Information Model (BIM) and Geographic Information System (GIS) to build a building information model for the buildings in the park, and visually display the data fed back by all sensors installed in the park and the historical operation data. The commercial consumption module includes a monitoring device, a data acquisition and preprocessing subunit, a data processing and modeling unit, and a data sub-transmission module. The monitoring device collects the personnel flow in the commercial area of the park. The data acquisition and preprocessing subunit obtains the data of each store in the park, classifies and summarizes the stores, and displays each store in the corresponding building information model. The data processing and modeling unit obtains the data of the monitoring device, divides the commercial area according to the number of personnel flow, and marks different types of commercial areas with different colors in the building information model, reads the data of the data acquisition and preprocessing subunit, and establishes a commercial consumption model based on the daily turnover status and customer consumption list of each store's history. The data sub-transmission module transmits the data of the data processing and modeling unit to the data processing center, and the data processing center processes the data and outputs a business investment promotion and operation report to the investment promotion module and operation service module of the product. Dividing the commercial area according to the number of personnel flow means dividing the commercial area into Class I, Class II, and Class III from large to small according to the number of personnel flow.

2. The digital twin platform system of the smart park according to claim 1, wherein: The digital twin application module includes an investment promotion module, an operation service module, a commercial consumption module, a smart Internet of Things module, an online platform operation status module, a park activity operation module, a procurement operation module, a park energy consumption module, and a smart parking module.

3. The digital twin platform system for the smart park according to claim 2, wherein: The park Internet of Things system includes multiple projects, and the projects are connected to corresponding edge servers.

4. The digital twin platform system for smart park according to claim 3, characterized in that: The project includes Internet of Things devices, a sub-control system, and sensors.

5. The digital twin platform system for an intelligent park according to claim 4, wherein: The data center is connected to multiple data processing service modules.

6. The digital twin platform system of the smart park according to claim 5, wherein: The second message middleware is connected to a Redis cache module.

7. The digital twin platform system of the smart park according to claim 6, characterized in that: The data processing service module includes a stream processing module, a third message middleware, a data storage module, and a batch processing module.

8. The digital twin platform system of the smart park according to claim 7, characterized in that: The stream processing module includes a data cleaning module, a data parsing module, an alarm judgment module, and a status judgment module connected in sequence.

9. The digital twin platform system for an intelligent park according to claim 8, wherein: The data storage module includes an HDFS raw database, a Cassandra NoSQL database, an RDBMS business database, and a Redis real-time database.

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