Digital park infrastructure management system based on GIS

Abstract

The invention discloses a GIS-based digital park infrastructure management system, and relates to the technical field of geographic information systems. In order to solve the problems that spatial data, facility operation states and energy consumption data cannot be effectively integrated, and a real-time and dynamic monitoring and early warning mechanism cannot be provided, so that maintenance and safety management of park facilities are not timely enough. Spatial data from various data acquisition terminals are efficiently integrated and managed through the spatial data processing unit, the park facility supervision unit realizes real-time monitoring of the operation state of park facilities by using a sensor network, and historical data are analyzed through data processing, so that potential faults or problems can be timely found and prevented, and the safety of the park facilities is improved. According to the system and the method, efficient and stable operation of park facilities is ensured, the energy consumption statistical evaluation unit performs energy consumption optimization management based on an evaluation result, energy consumption reduction is facilitated, and the visual display unit displays complex spatial data, facility operation states and energy consumption data to users in a visual manner.

Description

Technical Field

[0001] The present invention relates to the technical field of geographic information systems, and in particular to a digital park infrastructure management system based on GIS. Background Art

[0002] With the acceleration of urbanization, the infrastructure management of various digital parks is becoming increasingly complex. For example, the patent application with announcement number: CN114693490A discloses a digital park intelligent inspection method and system, which uses the cloud platform of the building integrated management system to access the digital park equipment information in the three-dimensional simulation panoramic map. The digital twin of the park equipment is used for fault warning and intelligent maintenance; the real-time monitoring of the traffic and pedestrian flow and the thermal analysis results are used for safety maintenance and crisis warning, which provides the possibility for the parallel processing of park services and artificial intelligence.

[0003] Although the above patent solves the problems of low efficiency and delayed decision-making in traditional manual management methods, it is unable to effectively integrate spatial data, facility operating status and energy consumption data, and cannot provide real-time and dynamic monitoring and early warning mechanisms, resulting in the maintenance and safety management of park facilities being insufficiently timely. Summary of the invention

[0004] The purpose of the present invention is to provide a digital park infrastructure management system based on GIS, which provides accurate digital park spatial data through a spatial data processing unit to provide a basis for facility supervision and energy consumption analysis. The real-time monitoring and historical data analysis of the park facility supervision unit can improve the safety and maintenance efficiency of the park facilities. The energy consumption statistical evaluation unit can help the park achieve refined energy management, reduce energy consumption costs, and improve energy utilization efficiency, so as to solve the problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions: Digital park infrastructure management system based on GIS, including: The spatial data processing unit is used to obtain the spatial data of the digital park from various data collection terminals based on the Internet of Things, and to pre-process and classify the collected spatial data to generate basic layers for GIS analysis; The park facility monitoring unit is used to monitor the operating status of facilities in the digital park in real time based on the sensor network and process the operating status data. At the same time, it analyzes and predicts the operating status of facilities in the digital park based on historical data; Energy consumption statistics and evaluation unit, used to collect energy consumption data in the digital park, analyze and evaluate the acquired energy consumption data, and perform energy consumption optimization management based on the energy consumption analysis and evaluation results; The visualization display unit is used to visualize the data output by the spatial data processing unit, the park facility supervision unit and the energy consumption statistical evaluation unit.

[0006] Furthermore, the spatial data processing unit comprises: The spatial data acquisition module is used to determine the required spatial data type according to the digital park, install corresponding sensors on each data acquisition terminal based on the required spatial data type, and perform spatial data acquisition; The spatial data classification module is used to preprocess the collected spatial data, extract key features of the preprocessed spatial data, classify and label the data according to the key features, and obtain spatial data of different categories; The basic layer generation module is used to integrate the classified spatial data, generate a complete data set, and vectorize and attribute the data set; The basic layer generation module is also used to create blank layers based on dataset categories in combination with GIS, and to overlay vectorized data and attribute information onto the blank layers to generate basic layers for GIS analysis.

[0007] Furthermore, the spatial data classification module is specifically: Reading the spatial data, determining the data type of the spatial data, and matching corresponding spatial data samples in a digital park database according to the data type of the spatial data; Reading the spatial data sample, and determining a constraint condition for data verification of the spatial data sample; Performing data verification on the corresponding spatial data based on the constraint conditions, marking the spatial data that does not meet the constraint conditions based on the verification results, and eliminating the spatial data; The key features of the spatial data are extracted, and a data classification identifier is determined based on the key features. At the same time, the spatial data is classified based on the data classification identifier to obtain multiple sub-data sets, each of which contains spatial data of the same category.

[0008] Furthermore, the basic layer generation module vectorizes the data set and performs attribute assignment processing, specifically: Integrate and generate a data set based on the spatial data category of each sub-data set, determine the vector data format of the data set, and convert the format of the integrated data set according to the vector data format; Identify the spatial elements of the vector data after format conversion, generate corresponding point, line and surface vector data according to the data type of the spatial elements, and establish the topological relationship between the vector data; Determine the corresponding data source based on the data set, obtain attribute information corresponding to the spatial data from the data source, and perform standardization on the attribute information; Determine the characteristics of spatial elements based on their data types, establish an association between the characteristics of spatial elements and attribute information, and assign corresponding attribute information to spatial elements based on the association.

[0009] Furthermore, the park facility supervision unit includes: The facility information extraction module is used to extract basic information of the facilities from the park facility database, establish a data interaction channel between the sensor network and the park facilities, and determine the sensor information carried by the park facilities based on the data interaction channel; The facility operation monitoring module is used to monitor the operation status data of each facility in the digital park in real time based on the sensor network, and set the corresponding warning threshold and warning mechanism based on the sensor information; The historical data analysis module is used to store and manage the operating status data of the park facilities, establish a historical operation database of the facilities, extract historical data from the historical operation database of the facilities, analyze the operating status of the park facilities, and identify the operating trends, periodic changes and potential problems of the park facilities.

[0010] Furthermore, a data exchange channel between the sensor network and the park facilities is established, including: Extract basic information of the facility and obtain the total number of devices; Determine the data transmission rate setting coefficient according to the amount of data corresponding to the basic information of each device stored in the park facility database; The data transmission rate setting coefficient is obtained by the following formula: ; Where S represents the data transmission rate setting coefficient; n represents the total number of devices; D i Indicates the amount of data corresponding to the basic information of the i-th device; D i+1 Indicates the amount of data corresponding to the basic information of the i+1th device; P i+1 represents the device response delay rate of i+1 devices; P i represents the device response delay rate of the i-th device; g i Indicates the value of the device operation correlation between the preset i-th device and the i+1-th device; g max Indicates the maximum value of the device operation correlation degree among the device operation correlation degrees with the i+1th device; comparing the data transmission rate setting coefficient with a preset coefficient reference value; Setting a data transmission rate value between a data interaction channel between a sensor network and a park facility according to a comparison result between the data transmission rate setting coefficient and the preset coefficient reference value; After the data transmission rate value is set, setting the maximum allowable variation range of the data transmission rate value; The data interaction channel between the sensor network and the park facility is established by using the data transmission rate value and the maximum allowable variation range of the data transmission rate value between the data interaction channel between the sensor network and the park facility as one of the connection parameters.

[0011] Further, setting the data transmission rate value between the data interaction channel between the sensor network and the park facility according to the comparison result between the data transmission rate setting coefficient and the preset coefficient reference value includes: When the comparison result between the data transmission rate setting coefficient and the preset coefficient reference value indicates that the data transmission rate setting coefficient exceeds the preset coefficient reference value, the preset bandwidth and channel transmission capacity corresponding to the data interaction channel between the sensor network and the park facilities are retrieved; The data transmission rate setting coefficient is used to obtain a data transmission rate value in combination with a preset bandwidth corresponding to the data interaction channel and a channel transmission capacity; The data transmission rate value is obtained by the following formula: ; Among them, R represents the data transmission rate value; R0 represents the preset initial data transmission rate value; C represents the channel transmission capacity; B represents the preset bandwidth corresponding to the data interaction channel between the sensor network and the park facilities; S represents the data transmission rate setting coefficient; When the comparison result between the data transmission rate setting coefficient and the preset coefficient reference value indicates that the data transmission rate setting coefficient does not exceed the preset coefficient reference value, the equipment maintenance frequency included in the basic information of the facility is retrieved; Obtaining a data transmission rate value according to the equipment maintenance frequency included in the basic information of the facility and a data transmission rate setting coefficient; The data transmission rate value is obtained by the following formula: ; Wherein, R represents the data transmission rate value; R0 represents the preset initial data transmission rate value; S represents the data transmission rate setting coefficient; S y Indicates the preset coefficient reference value; n indicates the total number of devices; f i represents the equipment maintenance frequency of the i-th equipment; f c Indicates the preset equipment maintenance frequency.

[0012] Furthermore, after the data transmission rate value is set, the maximum allowable variation range of the data transmission rate value is set, including: After the data transmission rate value is set, extracting the data transmission rate value; Retrieve and obtain parameter variables corresponding to the data transmission rate value, wherein the parameter variables are the equipment maintenance frequency included in the basic information of the facility, or the preset bandwidth and channel transmission capacity corresponding to the data interaction channel between the sensor network and the park facility; When the parameter corresponding to the data transmission rate value is the equipment maintenance frequency included in the basic information of the facility, the maximum allowable variation range of the data transmission rate value is set using the equipment maintenance frequency included in the basic information of the facility; The maximum allowable variation of the data transmission rate is obtained by the following formula: ; Among them, R f Indicates the maximum allowable variation of the data transmission rate; R 0f Indicates the preset initial maximum allowable amplitude value; n indicates the total number of devices; f i represents the equipment maintenance frequency of the i-th equipment; f c Indicates the preset equipment maintenance frequency; Y max and Y min They represent the maximum and minimum retrieval rates of the basic information of the facilities in the park facility database respectively; max Indicates the maximum value of the equipment maintenance frequency; When the parameter corresponding to the data transmission rate value is the preset bandwidth and channel transmission capacity corresponding to the data interaction channel between the sensor network and the park facilities, the maximum allowable variation range of the data transmission rate value is set using the preset bandwidth and channel transmission capacity corresponding to the data interaction channel between the sensor network and the park facilities; The maximum allowable variation of the data transmission rate is obtained by the following formula: ; Among them, R f Indicates the maximum allowable variation of the data transmission rate; R 0f It represents the preset initial maximum allowable amplitude value; R represents the data transmission rate value; R0 represents the preset initial data transmission rate value; C represents the channel transmission capacity; B represents the preset bandwidth corresponding to the data interaction channel between the sensor network and the park facilities; a represents the first constant, ranging from 0.24 to 0.53; b represents the second constant, ranging from 0.28 to 1.13.

[0013] Furthermore, the facility operation monitoring module also includes: Acquire coordinate features and time series features of the operation status data of each park facility, and determine normal operation data of the operation status data of the park facility based on the coordinate features and time series features, wherein the normal operation data corresponds one-to-one to the operation status of each park facility; Extracting operation data that does not meet the normal operation data from the operation status data of the park facilities based on the normal operation data, and comparing the extracted operation data with a preset warning threshold, and performing abnormality identification based on the comparison result; The operation status data is divided based on the basic information of the park facilities to obtain a distribution map of the monitoring data of the park facilities, and the coordinates of the monitoring data distribution map are marked based on the coordinate characteristics of the operation status data of each park facility; Based on the time series characteristics of the operation status data of each park facility, the monitoring data distribution map is time-marked, and finally, a marked distribution map of the park facility operation monitoring data is obtained.

[0014] Furthermore, the energy consumption statistics evaluation unit includes: The energy consumption data extraction module is used to classify the data collection terminals deployed in the park, monitor the operating power of each data collection terminal in real time, calculate the cumulative power and operating time of the data collection terminal based on its historical operating power, calculate the energy consumption based on the cumulative power and operating time, and collect energy consumption data; The energy consumption analysis module is used to process and analyze the collected energy consumption data, compare the energy consumption calculation results with the preset energy consumption abnormality threshold, analyze the daily, weekly and monthly energy consumption data of various data collection terminals, and extract the peak and valley periods of energy consumption based on the data characteristics of the energy consumption data; An energy consumption assessment module is used to compare the energy consumption data with preset energy consumption parameters based on the data characteristics of the energy consumption data, evaluate the energy consumption level in the digital park based on the comparison results, and generate an energy consumption assessment report; The energy consumption optimization module is used to formulate energy consumption optimization strategies based on energy consumption analysis results and evaluation reports, and to adjust and optimize the infrastructure of the digital park according to the energy consumption optimization strategies.

[0015] Furthermore, the visual display unit further includes: Overlay the basic layer data of the spatial data processing unit with the facility location information of the park facility supervision unit to create a comprehensive information layer; Establishing an association relationship between the energy consumption data of the energy consumption statistical evaluation unit and the facility operation status data, associating the energy consumption data with the spatial location based on the association relationship, and drawing a heat map on the comprehensive information layer; Compared with the prior art, the present invention has the following beneficial effects: The spatial data processing unit efficiently integrates and manages spatial data from a variety of data collection terminals. The park facility supervision unit uses the sensor network to achieve real-time monitoring of the operating status of park facilities, and through data processing and analysis of historical data, predicts the operating status of facilities, which helps to timely discover and prevent potential faults or problems, and ensure the efficient and stable operation of park facilities. The energy consumption statistics and evaluation unit collects energy consumption data through smart meters and other equipment, and conducts energy consumption analysis and evaluation. Energy consumption optimization management based on the evaluation results helps to reduce energy consumption, improve energy efficiency, and achieve green and sustainable development. The visualization display unit displays complex spatial data, facility operating status and energy consumption data to users in an intuitive way, and improves user experience through an interactive interface. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a module diagram of the GIS-based digital park infrastructure management system of the present invention. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] In order to solve the technical problem of not being able to effectively integrate spatial data, facility operation status and energy consumption data, and not being able to provide real-time, dynamic monitoring and early warning mechanisms, resulting in insufficiently timely maintenance and safety management of park facilities, please refer to Figure 1 , this embodiment provides the following technical solutions: Digital park infrastructure management system based on GIS, including: The spatial data processing unit is used to obtain the spatial data of the digital park from various data collection terminals based on the Internet of Things, including GPS positioning data, remote sensing image data, drone inspection data, etc., and various data collection terminals such as drones, satellite images, ground measurements, etc., and pre-process and classify the collected spatial data to generate basic layers for GIS analysis; The park facility monitoring unit is used to monitor the operating status of facilities in the digital park in real time based on the sensor network and process the operating status data. At the same time, it analyzes and predicts the operating status of facilities in the digital park based on historical data; Energy consumption statistics and evaluation unit, used to collect energy consumption data in the digital park using smart meters and other equipment, and to analyze and evaluate the acquired energy consumption data, and to optimize energy consumption management based on the results of energy consumption analysis and evaluation; The visualization display unit is used to visualize the data output by the spatial data processing unit, the park facility supervision unit, and the energy consumption statistical evaluation unit. At the same time, it provides an interactive interface to improve the user experience. In this embodiment, the visual display unit further includes: Overlay the basic layer data of the spatial data processing unit with the facility location information of the park facility supervision unit to create a comprehensive information layer; Establish an association relationship between the energy consumption data of the energy consumption statistical evaluation unit and the facility operation status data, such as mapping between the facility ID and the energy consumption data and the geographical location, so as to analyze the relationship between energy consumption and the facility operation status; associate the energy consumption data with the spatial location based on the association relationship, and draw a heat map on the comprehensive information layer; In this embodiment, the data output by the spatial data processing unit, the park facility supervision unit and the energy consumption statistical evaluation unit are integrated and fused to ensure the consistency and integrity of the data and provide data support for visual display; the integrated data is visualized in the form of charts, maps, dashboards, etc., including spatial data layers, facility operation status, energy consumption statistical charts, etc., to help users intuitively understand the operation of the park infrastructure; an interface for users to interact with the system is provided, including data query, parameter setting, report export, alarm notification and other functions to enhance user experience, meet the needs of different users, and ensure that users can obtain the required information anytime and anywhere.

[0019] In this embodiment, the spatial data processing unit efficiently integrates and manages spatial data from various data collection terminals. The park facility supervision unit uses the sensor network to realize real-time monitoring of the operation status of the park facilities, and predicts the operation status of the facilities through data processing and analysis of historical data, which helps to timely discover and prevent potential faults or problems and ensure the efficient and stable operation of the park facilities. The energy consumption statistics and evaluation unit collects energy consumption data through smart meters and other equipment, and performs energy consumption analysis and evaluation. Energy consumption optimization management based on the evaluation results helps to reduce energy consumption, improve energy efficiency, and achieve green and sustainable development. The visualization display unit displays complex spatial data, facility operation status and energy consumption data to users in an intuitive way, and improves user experience through an interactive interface.

[0020] In this embodiment, the spatial data processing unit includes: The spatial data acquisition module is used to determine the required spatial data type according to the digital park, such as high-precision GPS positioning data, high-resolution remote sensing image data, drone inspection data, etc. Based on the required spatial data type, the corresponding sensor is installed on each data acquisition terminal to collect spatial data; The spatial data classification module is used to pre-process the collected spatial data, including data format conversion, data cleaning, etc., to remove noise and abnormal data, ensure data quality, and extract key features of the pre-processed spatial data, classify and label according to the key features, and obtain spatial data of different categories, specifically: Reading the spatial data, determining the data type of the spatial data, and matching corresponding spatial data samples in a digital park database according to the data type of the spatial data; Reading the spatial data sample, and determining a constraint condition for data verification of the spatial data sample; Performing data verification on the corresponding spatial data based on the constraint conditions, marking the spatial data that does not meet the constraint conditions based on the verification results, and eliminating the spatial data; Extracting key features of the spatial data, and determining a data classification identifier based on the key features, and classifying the spatial data based on the data classification identifier to obtain multiple sub-data sets, each of which contains spatial data of the same category; The basic layer generation module is used to integrate the classified spatial data, generate a complete data set, and vectorize and attribute the data set. Specifically: Integrate and generate a data set based on the spatial data category of each sub-data set, determine the vector data format of the data set, and convert the format of the integrated data set according to the vector data format; Identify the spatial elements of the vector data after format conversion, such as buildings, roads, vegetation, etc., generate corresponding point, line, and surface vector data according to the data type of the spatial elements, and establish topological relationships between vector data, such as adjacent, intersecting, and containing, to ensure the logical consistency of the data; Determine the corresponding data source based on the data set, obtain attribute information corresponding to the spatial data from the data source, such as facility name, type, purpose, ownership, etc., and standardize the attribute information; Determine the characteristics of spatial elements based on their data types, establish the association between the characteristics of spatial elements and attribute information, and assign corresponding attribute information to spatial elements based on the association; The basic layer generation module is also used to create blank layers based on data set categories, such as buildings, roads, vegetation, etc., combined with GIS, and superimpose vectorized data and attribute information into the blank layers to generate basic layers for GIS analysis, such as land use layers, transportation network layers, etc.

[0021] In this embodiment, through the generation of basic layers, the comprehensive integration and optimization of the digital park spatial data is achieved, which not only ensures the quality and accuracy of the data, but also establishes a logically consistent and information-rich spatial data model through vectorization and attribute assignment processing. The high-precision GPS positioning data is superimposed with the high-resolution remote sensing image data to generate a basic layer containing more information, and integrates spatial data from different data sources, such as drone inspection data, ground measurement data, etc., to enrich the content of the basic layer, providing intuitive and efficient data support for the digital park infrastructure management, greatly improving the intelligent level of park planning, operation and maintenance, and helping park managers to make more scientific and reasonable decisions, thereby achieving the optimal allocation and sustainable development of park resources.

[0022] In this embodiment, the park facility supervision unit includes: The facility information extraction module is used to extract basic information of the facilities from the park facility database, including facility name, type, specification, installation location, maintenance record, etc., establish a data interaction channel between the sensor network and the park facilities, and determine the sensor information carried on the park facilities based on the data interaction channel, such as sensor type, monitoring parameters, data transmission frequency, etc.; The facility operation monitoring module is used to monitor the operation status data of each facility in the digital park in real time based on the sensor network, including parameters such as temperature, pressure, flow, and voltage. The corresponding warning thresholds and warning mechanisms are set based on the sensor information to promptly detect abnormal operation of the facility and trigger alarm notifications. Specifically, establish a data exchange channel between the sensor network and the park facilities, including: Extract basic information of the facility and obtain the total number of devices; Determine the data transmission rate setting coefficient according to the amount of data corresponding to the basic information of each device stored in the park facility database; The data transmission rate setting coefficient is obtained by the following formula: ; Where S represents the data transmission rate setting coefficient; n represents the total number of devices; D i Indicates the amount of data corresponding to the basic information of the i-th device; D i+1 Indicates the amount of data corresponding to the basic information of the i+1th device; P i+1 represents the device response delay rate of i+1 devices; P i represents the device response delay rate of the i-th device; g i Indicates the value of the device operation correlation between the preset i-th device and the i+1-th device; g max Indicates the maximum value of the device operation correlation degree among the device operation correlation degrees with the i+1th device; comparing the data transmission rate setting coefficient with a preset coefficient reference value; Setting a data transmission rate value between a data interaction channel between a sensor network and a park facility according to a comparison result between the data transmission rate setting coefficient and the preset coefficient reference value; After the data transmission rate value is set, setting the maximum allowable variation range of the data transmission rate value; The data interaction channel between the sensor network and the park facility is established by using the data transmission rate value and the maximum allowable variation range of the data transmission rate value between the data interaction channel between the sensor network and the park facility as one of the connection parameters.

[0023] The technical effect of the above technical solution is: by calculating the data transmission rate setting coefficient, the technical solution can dynamically adjust the data transmission rate between the sensor network and the park facilities according to the data volume corresponding to the basic information of each device in the park, the device response delay rate, and the operation correlation between the devices. This method ensures the efficiency and accuracy of data transmission and avoids resource waste or data loss caused by improper data transmission rate. Considering that the data volume and response delay rate of different devices may be different, the technical solution allocates a suitable data transmission rate to each device or device combination through careful calculation and comparison. This personalized data transmission rate setting helps to improve the overall data transmission efficiency, so that key data can be processed and utilized faster. The technical solution not only considers the data transmission requirements of a single device, but also the operation correlation between devices. By introducing the numerical value and maximum value of the device operation correlation, the solution can more comprehensively evaluate the complexity and requirements of data transmission, thereby enhancing the flexibility and adaptability of the system. By dynamically adjusting the data transmission rate, the technical solution can reduce unnecessary resource waste while ensuring the quality of data transmission. This helps to reduce the maintenance cost of the system and improve the overall economic benefits. This technical solution provides a scientific and reasonable connection parameter setting method for data interaction between sensor networks and park facilities, which helps promote the intelligent management of park facilities. By real-time monitoring and analyzing data, managers can more accurately understand the operating status of facilities and make more informed decisions.

[0024] In summary, this technical solution realizes dynamic optimization and personalized setting of the data transmission rate between the sensor network and the park facilities by comprehensively considering multiple factors such as the amount of device data, response delay rate, and device operation correlation, thereby improving data transmission efficiency, enhancing system flexibility, reducing maintenance costs, and promoting intelligent management of park facilities.

[0025] Specifically, setting the data transmission rate value between the data interaction channel between the sensor network and the park facility according to the comparison result between the data transmission rate setting coefficient and the preset coefficient reference value includes: When the comparison result between the data transmission rate setting coefficient and the preset coefficient reference value indicates that the data transmission rate setting coefficient exceeds the preset coefficient reference value, the preset bandwidth and channel transmission capacity corresponding to the data interaction channel between the sensor network and the park facilities are retrieved; The data transmission rate setting coefficient is used to obtain a data transmission rate value in combination with a preset bandwidth corresponding to the data interaction channel and a channel transmission capacity; The data transmission rate value is obtained by the following formula: ; Among them, R represents the data transmission rate value; R0 represents the preset initial data transmission rate value; C represents the channel transmission capacity; B represents the preset bandwidth corresponding to the data interaction channel between the sensor network and the park facilities; S represents the data transmission rate setting coefficient; When the comparison result between the data transmission rate setting coefficient and the preset coefficient reference value indicates that the data transmission rate setting coefficient does not exceed the preset coefficient reference value, the equipment maintenance frequency included in the basic information of the facility is retrieved; Obtaining a data transmission rate value according to the equipment maintenance frequency included in the basic information of the facility and a data transmission rate setting coefficient; The data transmission rate value is obtained by the following formula: ; Wherein, R represents the data transmission rate value; R0 represents the preset initial data transmission rate value; S represents the data transmission rate setting coefficient; S y Indicates the preset coefficient reference value; n indicates the total number of devices; f i represents the equipment maintenance frequency of the i-th equipment; f c Indicates the preset equipment maintenance frequency.

[0026] The technical effect of the above technical solution is: the technical solution flexibly adjusts the data transmission rate value between the sensor network and the park facilities according to the comparison result between the data transmission rate setting coefficient and the preset coefficient reference value. This dynamic adjustment mechanism ensures that the data transmission rate can be optimized according to the actual situation, and improves the efficiency and reliability of data transmission. When the data transmission rate setting coefficient exceeds the preset value, the scheme calculates the data transmission rate value by calling the preset bandwidth and channel transmission capacity corresponding to the data interaction channel between the sensor network and the park facilities, combined with the data transmission rate setting coefficient. This method can make full use of channel resources and ensure the smoothness and stability of data transmission. At the same time, when the data transmission rate setting coefficient does not exceed the preset value, the scheme adjusts the data transmission rate according to the equipment maintenance frequency to avoid unnecessary waste of resources. The technical solution also considers the impact of the equipment maintenance frequency on the data transmission rate. When the data transmission rate setting coefficient is low, the scheme adjusts the data transmission rate by combining the equipment maintenance frequency to ensure that the data transmission will not be greatly affected during the equipment maintenance period. This adjustment method considering the equipment maintenance needs helps to extend the service life of the equipment and reduce the interruption of data transmission caused by equipment failure. The technical solution improves the adaptability and flexibility of the system by introducing multiple parameters such as the data transmission rate setting coefficient, preset bandwidth, channel transmission capacity and equipment maintenance frequency. This multi-parameter adjustment method can meet the data transmission requirements in different scenarios and ensure that the system can maintain efficient and stable data transmission under various circumstances. By reasonably adjusting the data transmission rate, this technical solution can reduce the maintenance costs caused by poor data transmission or waste of resources. At the same time, the adjustment method that considers the frequency of equipment maintenance can also help reduce the maintenance costs caused by equipment failures.

[0027] In summary, this technical solution achieves efficient and stable data transmission between the sensor network and park facilities by flexibly adjusting the data transmission rate, optimizing resource utilization, considering equipment maintenance needs, improving system adaptability and reducing maintenance costs.

[0028] Specifically, after the data transmission rate value is set, the maximum allowable variation range of the data transmission rate value is set, including: After the data transmission rate value is set, extracting the data transmission rate value; Retrieve and obtain parameter variables corresponding to the data transmission rate value, wherein the parameter variables are the equipment maintenance frequency included in the basic information of the facility, or the preset bandwidth and channel transmission capacity corresponding to the data interaction channel between the sensor network and the park facility; When the parameter corresponding to the data transmission rate value is the equipment maintenance frequency included in the basic information of the facility, the maximum allowable variation range of the data transmission rate value is set using the equipment maintenance frequency included in the basic information of the facility; The maximum allowable variation of the data transmission rate is obtained by the following formula: ; Among them, R f Indicates the maximum allowable variation of the data transmission rate; R 0f Indicates the preset initial maximum allowable amplitude value; n indicates the total number of devices; f i represents the equipment maintenance frequency of the i-th equipment; f c Indicates the preset equipment maintenance frequency; Y max and Y min They represent the maximum and minimum retrieval rates of the basic information of the facilities in the park facility database respectively; max Indicates the maximum value of the equipment maintenance frequency; When the parameter corresponding to the data transmission rate value is the preset bandwidth and channel transmission capacity corresponding to the data interaction channel between the sensor network and the park facilities, the maximum allowable variation range of the data transmission rate value is set using the preset bandwidth and channel transmission capacity corresponding to the data interaction channel between the sensor network and the park facilities; The maximum allowable variation of the data transmission rate is obtained by the following formula: ; Among them, R f Indicates the maximum allowable variation of the data transmission rate; R 0f It represents the preset initial maximum allowable amplitude value; R represents the data transmission rate value; R0 represents the preset initial data transmission rate value; C represents the channel transmission capacity; B represents the preset bandwidth corresponding to the data interaction channel between the sensor network and the park facilities; a represents the first constant, ranging from 0.24 to 0.53; b represents the second constant, ranging from 0.28 to 1.13.

[0029] The technical effect of the above technical solution is that the solution can dynamically adjust the maximum allowable variation of the data transmission rate according to the basic information of the facility (such as the equipment maintenance frequency) or the characteristics of the data interaction channel between the sensor network and the park facilities (such as the preset bandwidth and channel transmission capacity). This dynamic adjustment mechanism helps to ensure the stability and efficiency of data transmission while adapting to the needs of different facilities and communication environments. By considering the equipment maintenance frequency, the solution can reflect the maintenance status and maintenance needs of the facility, thereby adjusting the variation of the data transmission rate to avoid data transmission interruption or delay caused by equipment maintenance. At the same time, by utilizing the characteristics of the data interaction channel between the sensor network and the park facilities, the data transmission rate can be further optimized and the reliability and flexibility of data transmission can be improved. By accurately calculating the maximum allowable variation of the data transmission rate, the solution can more effectively utilize communication resources such as bandwidth and channel transmission capacity. This helps to reduce resource waste and improve the efficiency and performance of data transmission. The solution provides a relatively simple and easy-to-implement method to set the maximum allowable variation of the data transmission rate. At the same time, because it takes into account multiple factors (such as equipment maintenance frequency, channel transmission capacity, etc.), it has good scalability and can adapt to more complex or more diverse communication environments that may appear in the future. By dynamically adjusting the maximum allowable variation of the data transmission rate, this solution helps to enhance the stability of the entire system. It can reduce the risk of system instability or failure caused by excessive fluctuations in data transmission rates, thereby improving the overall performance and reliability of the system.

[0030] In summary, this technical solution improves the reliability and flexibility of data transmission, optimizes resource utilization, enhances system stability, and is easy to implement and expand by dynamically adjusting the maximum allowable change range of the data transmission rate. These technical effects make this solution have significant advantages in data transmission rate management and optimization.

[0031] In this embodiment, the facility operation monitoring module further includes: Acquire coordinate features and time series features of the operation status data of each park facility, and determine normal operation data of the operation status data of the park facility based on the coordinate features and time series features, wherein the normal operation data corresponds one-to-one to the operation status of each park facility; Extracting operation data that does not meet the normal operation data from the operation status data of the park facilities based on the normal operation data, and comparing the extracted operation data with a preset warning threshold, and performing abnormality identification based on the comparison result; The operation status data is divided based on the basic information of the park facilities to obtain a distribution map of the monitoring data of the park facilities, and the coordinates of the monitoring data distribution map are marked based on the coordinate characteristics of the operation status data of each park facility; Based on the time series characteristics of the operation status data of each park facility, the monitoring data distribution map is time-stamped, and finally, a marked distribution map of the park facility operation monitoring data is obtained; The historical data analysis module is used to store and manage the operating status data of the park facilities, establish a historical operation database of the facilities, extract historical data from the historical operation database of the facilities, analyze the operating status of the park facilities, such as cluster analysis, association rule mining, etc., identify the operating trends, periodic changes and potential problems of the park facilities, such as the predicted value and confidence interval of the operating status in the future.

[0032] In this embodiment, the facility operation status is monitored in real time through the sensor network, and the early warning threshold is set, so that facility anomalies can be discovered in time, the safety and reliability of the park can be improved, and the coordinate characteristics and time series characteristics of the facility operation data can be obtained, providing the park manager with a detailed facility operation status, which is convenient for quickly locating problems and formulating maintenance plans. By comparing the normal operation data with the actual operation data, combined with the early warning threshold, the facility anomalies can be accurately identified, and false alarms and missed alarms can be reduced. The use of the marked distribution map of the park facility operation monitoring data improves management efficiency and response speed, and through historical data analysis, the facility operation status in the future can be predicted, which helps park managers plan maintenance activities in advance, reduce the risk of sudden failures, and more reasonably allocate resources and adjust operation strategies to improve energy utilization efficiency and operational efficiency.

[0033] In this embodiment, the energy consumption statistics evaluation unit includes: The energy consumption data extraction module is used to classify the data collection terminals deployed in the park, monitor the operating power of each data collection terminal in real time, calculate the cumulative power and operating time of the data collection terminal based on its historical operating power, calculate the energy consumption based on the cumulative power and operating time, and collect energy consumption data, including the consumption of various energy sources such as electricity, water resources, and gas; Energy consumption analysis module, used to process and analyze the collected energy consumption data, including data cleaning, data standardization, energy consumption trend analysis, energy consumption structure analysis, etc., based on the comparison of energy consumption calculation results with preset energy consumption abnormality thresholds, analyze the daily, weekly and monthly energy consumption data of various data collection terminals, and extract energy consumption peak and valley periods based on the data characteristics of energy consumption data; The energy consumption assessment module is used to compare the energy consumption data with the preset energy consumption parameters based on the data characteristics of the energy consumption data, including total energy consumption, peak power, average power, energy consumption time distribution, equipment operation time, temperature, humidity, etc. Based on the comparison results, the energy consumption level in the digital park is evaluated, including energy consumption intensity, energy efficiency ratio, energy saving and emission reduction effects, etc., and an energy consumption assessment report is generated to provide a basis for park energy management; The energy consumption optimization module is used to formulate energy consumption optimization strategies based on energy consumption analysis results and evaluation reports, including adjusting the energy use structure, improving equipment operation mode, implementing energy-saving transformation projects, etc., to achieve energy consumption reduction and cost savings, and adjust and optimize the infrastructure of the digital park according to the energy consumption optimization strategy.

[0034] In this embodiment, through energy consumption trend and structure analysis, the patterns and potential problems of energy consumption are revealed, so that park managers can promptly discover energy consumption anomalies and take corresponding measures, compare the actual energy consumption data with the preset parameters, and comprehensively evaluate the energy consumption level and energy efficiency of the park. Based on the analysis results and evaluation reports, targeted energy consumption optimization strategies are formulated, which not only help the park to reduce energy consumption and save costs, but also promote the adjustment and optimization of the park's infrastructure, and improve the overall energy utilization efficiency and sustainable development capabilities of the park.

[0035] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. The digital park infrastructure management system based on GIS is characterized by: include: The spatial data processing unit is used to obtain the spatial data of the digital park from various data collection terminals based on the Internet of Things, and to pre-process and classify the collected spatial data to generate basic layers for GIS analysis; The park facility monitoring unit is used to monitor the operating status of facilities in the digital park in real time based on the sensor network and process the operating status data. At the same time, it analyzes and predicts the operating status of facilities in the digital park based on historical data; Energy consumption statistics and evaluation unit, used to collect energy consumption data in the digital park, analyze and evaluate the acquired energy consumption data, and perform energy consumption optimization management based on the energy consumption analysis and evaluation results; The visualization display unit is used to visualize the data output by the spatial data processing unit, the park facility supervision unit and the energy consumption statistical evaluation unit.

2. The GIS-based digital park infrastructure management system according to claim 1, characterized in that: Spatial data processing unit, including: The spatial data acquisition module is used to determine the required spatial data type according to the digital park, install corresponding sensors on each data acquisition terminal based on the required spatial data type, and perform spatial data acquisition; The spatial data classification module is used to preprocess the collected spatial data, extract key features of the preprocessed spatial data, classify and label the data according to the key features, and obtain spatial data of different categories; The basic layer generation module is used to integrate the classified spatial data, generate a complete data set, and vectorize and attribute the data set; The basic layer generation module is also used to create a blank layer based on the dataset category and in combination with GIS, and to overlay the vectorized data and attribute information into the blank layer to generate a basic layer for GIS analysis; The spatial data classification module is specifically: Read the spatial data, determine the data type of the spatial data, and match corresponding spatial data samples in the digital park database according to the data type of the spatial data; Reading the spatial data sample, and determining a constraint condition for data verification of the spatial data sample; Performing data verification on the corresponding spatial data based on the constraint conditions, marking the spatial data that does not meet the constraint conditions based on the verification results, and eliminating the spatial data; The key features of the spatial data are extracted, and a data classification identifier is determined based on the key features. At the same time, the spatial data is classified based on the data classification identifier to obtain multiple sub-data sets, each of which contains spatial data of the same category.

3. The GIS-based digital park infrastructure management system according to claim 2, characterized in that: The basic layer generation module vectorizes the data set and performs attribute assignment processing, specifically: Integrate and generate a data set based on the spatial data category of each sub-data set, determine the vector data format of the data set, and convert the format of the integrated data set according to the vector data format; Identify the spatial elements of the vector data after format conversion, generate corresponding point, line and surface vector data according to the data type of the spatial elements, and establish the topological relationship between the vector data; Determine the corresponding data source based on the data set, obtain attribute information corresponding to the spatial data from the data source, and perform standardization on the attribute information; Determine the characteristics of spatial elements based on their data types, establish an association between the characteristics of spatial elements and attribute information, and assign corresponding attribute information to spatial elements based on the association.

4. The GIS-based digital park infrastructure management system according to claim 3, characterized in that: The park facility supervision unit includes: The facility information extraction module is used to extract basic information of the facilities from the park facility database, establish a data interaction channel between the sensor network and the park facilities, and determine the sensor information carried by the park facilities based on the data interaction channel; The facility operation monitoring module is used to monitor the operation status data of each facility in the digital park in real time based on the sensor network, and set the corresponding warning threshold and warning mechanism based on the sensor information; The historical data analysis module is used to store and manage the operating status data of the park facilities, establish a historical operation database of the facilities, extract historical data from the historical operation database of the facilities, analyze the operating status of the park facilities, and identify the operating trends, periodic changes and potential problems of the park facilities.

5. The GIS-based digital park infrastructure management system according to claim 4, characterized in that: Establish data exchange channels between the sensor network and park facilities, including: Extract basic information of the facility and obtain the total number of devices; Determine the data transmission rate setting coefficient according to the amount of data corresponding to the basic information of each device stored in the park facility database; The data transmission rate setting coefficient is obtained by the following formula: ； Where S represents the data transmission rate setting coefficient; n represents the total number of devices; D i Indicates the amount of data corresponding to the basic information of the i-th device; D i+1 Indicates the amount of data corresponding to the basic information of the i+1th device; P i+1 represents the device response delay rate of i+1 devices; P i represents the device response delay rate of the i-th device; g i Indicates the value of the device operation correlation between the preset i-th device and the i+1-th device; g max Indicates the maximum value of the device operation correlation degree among the device operation correlation degrees with the i+1th device; comparing the data transmission rate setting coefficient with a preset coefficient reference value; Setting a data transmission rate value between a data interaction channel between a sensor network and a park facility according to a comparison result between the data transmission rate setting coefficient and the preset coefficient reference value; After the data transmission rate value is set, setting the maximum allowable variation range of the data transmission rate value; The data interaction channel between the sensor network and the park facility is established by using the data transmission rate value and the maximum allowable variation range of the data transmission rate value between the data interaction channel between the sensor network and the park facility as one of the connection parameters.

6. The GIS-based digital park infrastructure management system according to claim 5, characterized in that: The data transmission rate value between the sensor network and the data interaction channel of the park facility is set according to the comparison result between the data transmission rate setting coefficient and the preset coefficient reference value, including: When the comparison result between the data transmission rate setting coefficient and the preset coefficient reference value indicates that the data transmission rate setting coefficient exceeds the preset coefficient reference value, the preset bandwidth and channel transmission capacity corresponding to the data interaction channel between the sensor network and the park facilities are retrieved; The data transmission rate setting coefficient is used to obtain a data transmission rate value in combination with a preset bandwidth corresponding to the data interaction channel and a channel transmission capacity; The data transmission rate value is obtained by the following formula: ； Among them, R represents the data transmission rate value; R0 represents the preset initial data transmission rate value; C represents the channel transmission capacity; B represents the preset bandwidth corresponding to the data interaction channel between the sensor network and the park facilities; S represents the data transmission rate setting coefficient; When the comparison result between the data transmission rate setting coefficient and the preset coefficient reference value indicates that the data transmission rate setting coefficient does not exceed the preset coefficient reference value, the equipment maintenance frequency included in the basic information of the facility is retrieved; Obtaining a data transmission rate value according to the equipment maintenance frequency included in the basic information of the facility and a data transmission rate setting coefficient; The data transmission rate value is obtained by the following formula: ； Wherein, R represents the data transmission rate value; R0 represents the preset initial data transmission rate value; S represents the data transmission rate setting coefficient; S y Indicates the preset coefficient reference value; n indicates the total number of devices; f i represents the equipment maintenance frequency of the i-th equipment; f c Indicates the preset equipment maintenance frequency.

7. The GIS-based digital park infrastructure management system according to claim 6, characterized in that: After the data transmission rate value is set, the maximum allowable variation range of the data transmission rate value is set, including: After the data transmission rate value is set, extracting the data transmission rate value; Retrieve and obtain parameter variables corresponding to the data transmission rate value, wherein the parameter variables are the equipment maintenance frequency included in the basic information of the facility, or the preset bandwidth and channel transmission capacity corresponding to the data interaction channel between the sensor network and the park facility; When the parameter corresponding to the data transmission rate value is the equipment maintenance frequency included in the basic information of the facility, the maximum allowable variation range of the data transmission rate value is set using the equipment maintenance frequency included in the basic information of the facility; The maximum allowable variation of the data transmission rate is obtained by the following formula: ； Among them, R f Indicates the maximum allowable variation of the data transmission rate; R 0f Indicates the preset initial maximum allowable amplitude value; n indicates the total number of devices; f i represents the equipment maintenance frequency of the i-th equipment; f c Indicates the preset equipment maintenance frequency; Y max and Y min They represent the maximum and minimum retrieval rates of the basic information of the facilities in the park facility database respectively; max Indicates the maximum value of the equipment maintenance frequency; When the parameter corresponding to the data transmission rate value is the preset bandwidth and channel transmission capacity corresponding to the data interaction channel between the sensor network and the park facilities, the maximum allowable variation range of the data transmission rate value is set using the preset bandwidth and channel transmission capacity corresponding to the data interaction channel between the sensor network and the park facilities; The maximum allowable variation of the data transmission rate is obtained by the following formula: ； Among them, R f Indicates the maximum allowable variation of the data transmission rate; R 0f It represents the preset initial maximum allowable amplitude value; R represents the data transmission rate value; R0 represents the preset initial data transmission rate value; C represents the channel transmission capacity; B represents the preset bandwidth corresponding to the data interaction channel between the sensor network and the park facilities; a represents the first constant, ranging from 0.24 to 0.53; b represents the second constant, ranging from 0.28 to 1.

13.

8. The GIS-based digital park infrastructure management system according to claim 4, characterized in that: The facility operation monitoring module also includes: Acquire coordinate features and time series features of the operation status data of each park facility, and determine normal operation data of the operation status data of the park facility based on the coordinate features and time series features, wherein the normal operation data corresponds one-to-one to the operation status of each park facility; Extracting operation data that does not meet the normal operation data from the operation status data of the park facilities based on the normal operation data, and comparing the extracted operation data with a preset warning threshold, and performing abnormality identification based on the comparison result; The operation status data is divided based on the basic information of the park facilities to obtain a distribution map of the monitoring data of the park facilities, and the coordinates of the monitoring data distribution map are marked based on the coordinate characteristics of the operation status data of each park facility; Based on the time series characteristics of the operation status data of each park facility, the monitoring data distribution map is time-marked, and finally, a marked distribution map of the park facility operation monitoring data is obtained.

9. The GIS-based digital park infrastructure management system according to claim 1, characterized in that: Energy consumption statistics evaluation unit, including: The energy consumption data extraction module is used to classify the data collection terminals deployed in the park, monitor the operating power of each data collection terminal in real time, calculate the cumulative power and operating time of the data collection terminal based on its historical operating power, calculate the energy consumption based on the cumulative power and operating time, and collect energy consumption data; The energy consumption analysis module is used to process and analyze the collected energy consumption data, compare the energy consumption calculation results with the preset energy consumption abnormality threshold, analyze the daily, weekly and monthly energy consumption data of various data collection terminals, and extract the peak and valley periods of energy consumption based on the data characteristics of the energy consumption data; An energy consumption assessment module is used to compare the energy consumption data with preset energy consumption parameters based on the data characteristics of the energy consumption data, evaluate the energy consumption level in the digital park based on the comparison results, and generate an energy consumption assessment report; The energy consumption optimization module is used to formulate energy consumption optimization strategies based on energy consumption analysis results and evaluation reports, and to adjust and optimize the infrastructure of the digital park according to the energy consumption optimization strategies.

10. The GIS-based digital park infrastructure management system according to claim 1, characterized in that: The visual display unit also includes: Overlay the basic layer data of the spatial data processing unit with the facility location information of the park facility supervision unit to create a comprehensive information layer; An association relationship is established between the energy consumption data of the energy consumption statistical evaluation unit and the facility operation status data, the energy consumption data is associated with the spatial position based on the association relationship, and a heat map is drawn on the comprehensive information layer.

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