A data processing method for a smart emergency command platform

Abstract

The present invention discloses a data processing method for a smart emergency command platform, which relates to the technical field of emergency command data processing. The present invention comprises the following steps: when an event response occurs on the smart emergency command platform, a plurality of data import interfaces are activated, a data interaction key is issued, and uploaded data of the plurality of data import interfaces are extracted; the maximum data capacity per unit time of the smart emergency command platform is determined; the uploaded data of the plurality of extracted data import interfaces are subjected to periodic segmented import processing to determine access data within a unit period; based on the access data within the unit period, data features of the access data within the unit period are extracted, the call data type is determined in a hybrid storage database, and the data capacity ratio of single data and composite data is determined; a reference plan decision for an emergency event is formed and fed back to an administrator port. The present invention can effectively solve the data pressure problem of the smart emergency command platform when an emergency event occurs, when data suddenly increases.

Description

Technical Field

[0001] The present invention relates to the technical field of emergency command data processing, and in particular to a data processing method for an intelligent emergency command platform. Background Art

[0002] With the acceleration of urbanization and the increasing frequency of natural disasters, accidents, calamities, public health incidents, and other emergencies, traditional emergency management models are no longer able to meet the demands for rapid response and precise decision-making. The Smart Emergency Command Platform leverages technologies such as big data, artificial intelligence, and the Internet of Things to enable real-time monitoring, early warning analysis, and intelligent dispatch of emergency events.

[0003] However, when emergencies occur, the amount of data grows exponentially, posing significant challenges to the platform's stability, computing power, and decision-making efficiency. When an emergency occurs, data sources are diverse and the volume surges. A large amount of heterogeneous, multi-source data flows in, including sensor data, video surveillance data, drone aerial photography data, social media sentiment, and emergency communication data. Simultaneously, the scale of data surges. Current smart emergency command platforms often rely on large amounts of historical data combined with real-time data transmission to build decision support models when making decisions. Unrestricted access to the same type of historical data on top of this massive amount of real-time data generates a massive amount of raw data for the data model, leading to data congestion on the emergency command platform. Controlling access to these data lacks control standards, and there's no guarantee that the raw data being used meets modeling requirements.

[0004] Therefore, in the current smart emergency command platform, the data calling process still lacks certain research and processing. How to balance the status between the platform data capacity and data modeling during the data calling process is one of the problems that the current smart emergency command platform needs to solve. Summary of the Invention

[0005] The purpose of the present invention is to provide a data processing method for an intelligent emergency command platform to solve the problems raised in the prior art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a data processing method for an intelligent emergency command platform, the method comprising the following steps:

[0007] S1. When an event occurs on the smart emergency command platform, several data import interfaces are activated, data interaction keys are issued, and uploaded data from several data import interfaces is extracted;

[0008] S2. Determine the maximum data capacity per unit time of the smart emergency command platform based on the rated data interaction threshold of the smart emergency command platform and the issued decision-making party data resource occupancy value;

[0009] S3. Establish a hybrid storage database to store all data on emergency command events in historical events. Based on the maximum data capacity per unit time of the smart emergency command platform, perform periodic segmented import processing on the uploaded data extracted from several data import interfaces to determine the access data within a unit period.

[0010] S4. Based on the access data within the unit period, extract the data features of the access data within the unit period, determine the call data type in the hybrid storage database, the data type includes single data and composite data, and determine the data capacity ratio of the single data and composite data based on the maximum data capacity per unit time of the smart emergency command platform;

[0011] S5. Based on the historical data called in the hybrid storage database, a reference plan decision for emergency events is formed and fed back to the administrator port.

[0012] According to the above technical solution, when there is an event response on the smart emergency command platform, several data import interfaces are activated, data interaction keys are issued, and uploaded data of several data import interfaces are extracted, including:

[0013] When there is an incident response, the smart emergency command platform builds several data import interfaces based on the system settings, sets a data interaction key for each data import interface, and is uniformly issued by the administrator. Each data import interface realizes data interaction with the administrator based on its own data interaction key and uploads the incident scene data. The smart emergency command platform uniformly extracts the uploaded data of several data import interfaces.

[0014] According to the above technical solution, the maximum data capacity per unit time of the smart emergency command platform is determined based on the rated data interaction threshold of the smart emergency command platform and the issued decision-making party data resource occupancy value, including:

[0015] The system establishes the maximum data resource occupancy of a single decision-maker. Based on the number of decision-makers established in real time under different events, the decision-maker data resource occupancy value is calculated. The maximum data capacity per unit time of the smart emergency command platform is determined by the difference between the rated data interaction threshold of the smart emergency command platform and the issued decision-maker data resource occupancy value.

[0016] According to the above technical solution, based on the maximum data capacity per unit time of the smart emergency command platform, the uploaded data of the extracted data input interfaces are periodically segmented and processed, and the access data within the unit period is determined to include:

[0017] The maximum data capacity per unit time based on the smart emergency command platform is divided into the maximum upload flow and the maximum call flow. The uploaded data of several data import interfaces are processed based on the maximum upload flow. If the total amount of uploaded data of several data import interfaces per unit time is not higher than the maximum upload flow, then the access data within the unit period is determined to be equal to the total amount of uploaded data of several data import interfaces; if the total amount of uploaded data of several data import interfaces per unit time is higher than the maximum upload flow, the data are imported periodically according to the maximum upload flow per unit time.

[0018] According to the above technical solution, extracting data features of the access data within the unit period based on the access data within the unit period and determining the call data type in the hybrid storage database includes:

[0019] Access data within a unit period is obtained, and feature extraction is performed on the access data based on unstructured data feature extraction and emergency field-specific feature extraction, wherein the unstructured data feature extraction includes text data features, video data features, and voice data features; the emergency field-specific features include event evolution features, resource scheduling features, and event situation assessment features;

[0020] The event evolution characteristics include event diffusion parameters, impact range boundaries, and event level evaluation indicators; the resource scheduling characteristics include demand and resource matching, path accessibility analysis characteristics, and resource utility evaluation; the event situation assessment characteristics include event comprehensive risk index and event-related impact area;

[0021] Access data within a unit period is obtained, data features present in the access data are determined, and based on the data features present in the access data, event history data with the same data features is called in the hybrid storage database.

[0022] According to the above technical solution, the single data refers to data containing a single data feature; the composite data refers to data containing all existing data features.

[0023] According to the above technical solution, the data capacity ratio of single data and composite data is determined based on the maximum data capacity per unit time of the smart emergency command platform, including:

[0024] Obtain data features present in access data within a unit period, set a first data analysis port, set a data feature ratio threshold, calculate the capacity ratio of the data features present in the access data within the unit period in the access data within the unit period, and select data with a ratio greater than the data feature ratio threshold to proceed to the next stage;

[0025] The next stage of processing includes:

[0026] If there is only one set of data features in the access data from the start of the event response to the current unit period, the event history data corresponding to the set of data features will be called in the hybrid storage database until the data capacity reaches the maximum data capacity per unit time of the smart emergency command platform; if there are multiple sets of data features, a number of single data and a set of composite data will be formed. The single data refer to each data feature type existing in the access data within the current unit period, and the composite data refers to all data feature types existing in the access data from the start of the event response to the current unit period;

[0027] Construct digital modeling and create a digital modeling database. The database contains several groups of data, each group of data has at least one data feature, and several groups of data can have the same data feature:

[0028] S701. Construct an emergency event processing model based on data in a digital modeling database, and test the loss function of the emergency event processing model using real data. The real data includes various single data of data features existing in the database and composite data of all data features existing in the database. For each test, output the average of the loss function outputs of the various single data and composite data.

[0029] S702, each time taking a number of data groups and adding them to the digital modeling database, ensuring that each number of data groups added can add only one data feature to the digital modeling database, and repeating step S701 until the number of additions set by the system is reached;

[0030] S703, based on the average value of the loss function output of each type of single data and composite data in each test, perform data fitting, analyze the functional relationship between the change of the loss function of the composite data and the number of data features in the composite data, and establish a linear fitting relationship;

[0031] Construct a composite data capacity relation:

[0032]

[0033] in, is the composite data capacity of the current cycle; is the composite data capacity of the previous cycle; Represents the average value of the loss function when the number of data features in the composite data is x-1; Represents the average value of the loss function when the number of data features in the composite data is x;

[0034] If there is only one data feature in the first cycle, the composite data capacity of the first cycle is defined as half of the maximum data capacity per unit time of the smart emergency command platform;

[0035] The composite data capacity of the current cycle is removed from the maximum data capacity per unit time of the smart emergency command platform, and the remaining data capacity is divided according to the proportion of each single data capacity.

[0036] According to the above technical solution, the historical data called from the hybrid storage database is used to form a reference plan decision for emergency events, and the feedback to the administrator port includes:

[0037] Call the emergency command reference model configured by the system administrator, and form a reference plan decision for emergency events based on the historical event data called from the hybrid storage database;

[0038] If there is a set of composite data that cannot call any event history data in the hybrid storage database, an alarm is triggered to the administrator port.

[0039] Compared with existing technologies, this invention offers the following advantages: it can address the challenge of rapidly increasing data volumes faced by smart emergency command platforms during emergencies. By combining technologies such as big data storage, intelligent analysis, and data collaboration, it builds an efficient and stable data processing system to support rapid and accurate emergency decision-making. It also effectively balances the platform's data capacity and data modeling during data retrieval, providing stronger support for data management within the emergency command platform. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 The figure is a schematic diagram of the steps of a data processing method for an intelligent emergency command platform of the present invention. DETAILED DESCRIPTION

[0041] Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative work shall fall within the scope of protection of the present invention.

[0042] Specifically, in this embodiment, a data processing method for a smart emergency command platform is provided, the method comprising: activating a plurality of data import interfaces when an event response occurs on the smart emergency command platform, issuing a data interaction key, and extracting uploaded data from the plurality of data import interfaces;

[0043] When an event response occurs on the smart emergency command platform, the steps of activating several data import interfaces, issuing data interaction keys, and extracting uploaded data from the several data import interfaces include:

[0044] When there is an incident response, the smart emergency command platform builds several data import interfaces based on the system settings, sets a data interaction key for each data import interface, and is uniformly issued by the administrator. Each data import interface realizes data interaction with the administrator based on its own data interaction key and uploads the incident scene data. The smart emergency command platform uniformly extracts the uploaded data of several data import interfaces.

[0045] Determine the maximum data capacity per unit time of the smart emergency command platform based on the rated data interaction threshold of the smart emergency command platform and the data resource occupancy value issued to the decision-maker.

[0046] Determining the maximum data capacity per unit time of the smart emergency command platform based on the rated data interaction threshold of the smart emergency command platform and the issued decision-making party data resource occupancy value includes:

[0047] The system establishes the maximum data resource occupancy of a single decision-maker. Based on the number of decision-makers established in real time under different events, the decision-maker data resource occupancy value is calculated. The maximum data capacity per unit time of the smart emergency command platform is determined by the difference between the rated data interaction threshold of the smart emergency command platform and the issued decision-maker data resource occupancy value.

[0048] Establish a hybrid storage database to store all data of emergency command events in historical events. Based on the maximum data capacity per unit time of the smart emergency command platform, perform periodic segmented import processing on the uploaded data of several data import interfaces to determine the access data within a unit period.

[0049] Based on the maximum data capacity per unit time of the smart emergency command platform, the uploaded data of the extracted data input interfaces are periodically segmented and processed, and the access data within the unit period is determined to include:

[0050] The maximum data capacity per unit time based on the smart emergency command platform is divided into the maximum upload flow and the maximum call flow. The uploaded data of several data import interfaces are processed based on the maximum upload flow. If the total amount of uploaded data of several data import interfaces per unit time is not higher than the maximum upload flow, then the access data within the unit period is determined to be equal to the total amount of uploaded data of several data import interfaces; if the total amount of uploaded data of several data import interfaces per unit time is higher than the maximum upload flow, the data are imported periodically according to the maximum upload flow per unit time.

[0051] Based on the access data within a unit period, extract the data features of the access data within the unit period, determine the call data type in the hybrid storage database, the data type includes single data and composite data, and determine the data capacity ratio of single data and composite data based on the maximum data capacity per unit time of the smart emergency command platform;

[0052] The extracting data features of the access data within the unit period based on the access data within the unit period and determining the call data type in the hybrid storage database includes:

[0053] Access data within a unit period is obtained, and feature extraction is performed on the access data based on unstructured data feature extraction and emergency field-specific feature extraction, wherein the unstructured data feature extraction includes text data features, video data features, and voice data features; the emergency field-specific features include event evolution features, resource scheduling features, and event situation assessment features;

[0054] The event evolution characteristics include event diffusion parameters, impact range boundaries, and event level evaluation indicators; the resource scheduling characteristics include demand and resource matching, path accessibility analysis characteristics, and resource utility evaluation; the event situation assessment characteristics include event comprehensive risk index and event-related impact area;

[0055] Access data within a unit period is obtained, data features present in the access data are determined, and based on the data features present in the access data, event history data with the same data features is called in the hybrid storage database.

[0056] The single data refers to data containing a single data feature; the composite data refers to data containing all existing data features.

[0057] The maximum data capacity per unit time of the smart emergency command platform determines the data capacity ratio of single data and composite data, including:

[0058] Obtain data features present in access data within a unit period, set a first data analysis port, set a data feature ratio threshold, calculate the capacity ratio of the data features present in the access data within the unit period in the access data within the unit period, and select data with a ratio greater than the data feature ratio threshold to proceed to the next stage;

[0059] The next stage of processing includes:

[0060] If there is only one set of data features in the access data from the start of the event response to the current unit period, the event history data corresponding to the set of data features will be called in the hybrid storage database until the data capacity reaches the maximum data capacity per unit time of the smart emergency command platform; if there are multiple sets of data features, a number of single data and a set of composite data will be formed. The single data refer to each data feature type existing in the access data within the current unit period, and the composite data refers to all data feature types existing in the access data from the start of the event response to the current unit period;

[0061] Construct digital modeling and create a digital modeling database. The database contains several groups of data, each group of data has at least one data feature, and several groups of data can have the same data feature:

[0062] S701. Construct an emergency event processing model based on data in a digital modeling database, and test the loss function of the emergency event processing model using real data. The real data includes various single data of data features existing in the database and composite data of all data features existing in the database. For each test, output the average of the loss function outputs of the various single data and composite data.

[0063] S702, each time taking a number of data groups and adding them to the digital modeling database, ensuring that each number of data groups added can add only one data feature to the digital modeling database, and repeating step S701 until the number of additions set by the system is reached;

[0064] S703, based on the average value of the loss function output of each type of single data and composite data in each test, perform data fitting, analyze the functional relationship between the change of the loss function of the composite data and the number of data features in the composite data, and establish a linear fitting relationship;

[0065] Construct a composite data capacity relation:

[0066]

[0067] in, is the composite data capacity of the current cycle; is the composite data capacity of the previous cycle; Represents the average value of the loss function when the number of data features in the composite data is x-1; Represents the average value of the loss function when the number of data features in the composite data is x;

[0068] If there is only one data feature in the first cycle, the composite data capacity of the first cycle is defined as half of the maximum data capacity per unit time of the smart emergency command platform;

[0069] The composite data capacity of the current cycle is removed from the maximum data capacity per unit time of the smart emergency command platform, and the remaining data capacity is divided according to the proportion of each single data capacity.

[0070] Based on the historical data called from the hybrid storage database, a reference plan for emergency events is formed and fed back to the administrator port, including:

[0071] Call the emergency command reference model configured by the system administrator, and form a reference plan decision for emergency events based on the historical event data called from the hybrid storage database;

[0072] If there is a set of composite data that cannot call any event history data in the hybrid storage database, an alarm is triggered to the administrator port.

[0073] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the platforms, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0074] In the embodiments of this application, prefixes such as "first" and "second" are used only to distinguish different description objects and have no limiting effect on the position, order, priority, quantity, or content of the described objects. The use of prefixes such as ordinal numbers to distinguish description objects in the embodiments of this application does not constitute a limitation on the described objects. For a statement of the described objects, please refer to the description in the context of the claims or embodiments, and the use of such prefixes should not constitute an unnecessary limitation.

[0075] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0076] In the various embodiments of the present application, unless otherwise specified or there is a logical conflict, the terms and / or descriptions between the various embodiments are consistent and can be referenced by each other. The technical features in different embodiments can be combined to form new embodiments according to their inherent logical relationships.

[0077] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of the solution of this embodiment according to actual needs.

[0078] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0079] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A data processing method for a smart emergency command platform, characterized by: The method comprises the following steps: S1. When an event occurs on the smart emergency command platform, several data import interfaces are activated, data interaction keys are issued, and uploaded data from several data import interfaces is extracted; S2. Determine the maximum data capacity per unit time of the smart emergency command platform based on the rated data interaction threshold of the smart emergency command platform and the issued decision-making party data resource occupancy value; S3. Establish a hybrid storage database to store all data on emergency command events in historical events. Based on the maximum data capacity per unit time of the smart emergency command platform, perform periodic segmented import processing on the uploaded data extracted from several data import interfaces to determine the access data within a unit period. S4. Based on the access data within the unit period, extract the data features of the access data within the unit period, determine the call data type in the hybrid storage database, the data type includes single data and composite data, and determine the data capacity ratio of the single data and composite data based on the maximum data capacity per unit time of the smart emergency command platform; S5. Based on the historical data called from the hybrid storage database, a reference plan decision for emergency events is formed and fed back to the administrator port; The single data refers to data containing a single data feature; the composite data refers to data containing all existing data features; The maximum data capacity per unit time of the smart emergency command platform determines the data capacity ratio of single data and composite data, including: Obtain data features present in access data within a unit period, set a first data analysis port, set a data feature ratio threshold, calculate the capacity ratio of the data features present in the access data within the unit period in the access data within the unit period, and select data with a ratio greater than the data feature ratio threshold to proceed to the next stage; The next stage of processing includes: If there is only one set of data features in the access data from the start of the event response to the current unit period, the event history data corresponding to the set of data features will be called in the hybrid storage database until the data capacity reaches the maximum data capacity per unit time of the smart emergency command platform; if there are multiple sets of data features, a number of single data and a set of composite data will be formed. The single data refer to each data feature type existing in the access data within the current unit period, and the composite data refers to all data feature types existing in the access data from the start of the event response to the current unit period; Construct digital modeling and create a digital modeling database. The database contains several groups of data, each group of data has at least one data feature, and several groups of data can have the same data feature: S701. Construct an emergency event processing model based on data in a digital modeling database, and test the loss function of the emergency event processing model using real data. The real data includes various single data of data features existing in the database and composite data of all data features existing in the database. For each test, output the average of the loss function outputs of the various single data and composite data. S702, each time taking a number of data groups and adding them to the digital modeling database, ensuring that each number of data groups added can add only one data feature to the digital modeling database, and repeating step S701 until the number of additions set by the system is reached; S703, based on the average value of the loss function output of each type of single data and composite data in each test, perform data fitting, analyze the functional relationship between the change of the loss function of the composite data and the number of data features in the composite data, and establish a linear fitting relationship; Construct a composite data capacity relation: in, is the composite data capacity of the current cycle; is the composite data capacity of the previous cycle; Represents the average value of the loss function when the number of data features in the composite data is x-1; Represents the average value of the loss function when the number of data features in the composite data is x; If there is only one data feature in the first cycle, the composite data capacity of the first cycle is defined as half of the maximum data capacity per unit time of the smart emergency command platform; The composite data capacity of the current cycle is removed from the maximum data capacity per unit time of the smart emergency command platform, and the remaining data capacity is divided according to the proportion of each single data capacity.

2. The data processing method for a smart emergency command platform according to claim 1, characterized in that: When an event response occurs on the smart emergency command platform, the steps of activating several data import interfaces, issuing data interaction keys, and extracting uploaded data from the several data import interfaces include: When there is an incident response, the smart emergency command platform builds several data import interfaces based on the system settings, sets a data interaction key for each data import interface, and is uniformly issued by the administrator. Each data import interface realizes data interaction with the administrator based on its own data interaction key and uploads the incident scene data. The smart emergency command platform uniformly extracts the uploaded data of several data import interfaces.

3. The data processing method for a smart emergency command platform according to claim 1, characterized in that: Determining the maximum data capacity per unit time of the smart emergency command platform based on the rated data interaction threshold of the smart emergency command platform and the issued decision-making party data resource occupancy value includes: The system establishes the maximum data resource occupancy of a single decision-maker. Based on the number of decision-makers established in real time under different events, the decision-maker data resource occupancy value is calculated. The maximum data capacity per unit time of the smart emergency command platform is determined by the difference between the rated data interaction threshold of the smart emergency command platform and the issued decision-maker data resource occupancy value.

4. The data processing method for a smart emergency command platform according to claim 1, characterized in that: Based on the maximum data capacity per unit time of the smart emergency command platform, the uploaded data of the extracted data input interfaces are periodically segmented and processed, and the access data within the unit period is determined to include: The maximum data capacity per unit time based on the smart emergency command platform is divided into the maximum upload flow and the maximum call flow. The uploaded data of several data import interfaces are processed based on the maximum upload flow. If the total amount of uploaded data of several data import interfaces per unit time is not higher than the maximum upload flow, then the access data within the unit period is determined to be equal to the total amount of uploaded data of several data import interfaces; if the total amount of uploaded data of several data import interfaces per unit time is higher than the maximum upload flow, the data are imported periodically according to the maximum upload flow per unit time.

5. The data processing method for a smart emergency command platform according to claim 1, characterized in that: The extracting data features of the access data within the unit period based on the access data within the unit period and determining the call data type in the hybrid storage database includes: Access data within a unit period is obtained, and feature extraction is performed on the access data based on unstructured data feature extraction and emergency field-specific feature extraction, wherein the unstructured data feature extraction includes text data features, video data features, and voice data features; the emergency field-specific features include event evolution features, resource scheduling features, and event situation assessment features; The event evolution characteristics include event diffusion parameters, impact range boundaries, and event level evaluation indicators; the resource scheduling characteristics include demand and resource matching, path accessibility analysis characteristics, and resource utility evaluation; the event situation assessment characteristics include event comprehensive risk index and event-related impact area; Access data within a unit period is obtained, data features present in the access data are determined, and based on the data features present in the access data, event history data with the same data features is called in the hybrid storage database.

6. The data processing method for a smart emergency command platform according to claim 1, characterized in that: The historical data called from the hybrid storage database is used to form a reference plan decision for emergency events and the feedback to the administrator port includes: Call the emergency command reference model configured by the system administrator, and form a reference plan decision for emergency events based on the historical event data called from the hybrid storage database; If there is a set of composite data that cannot call any event history data in the hybrid storage database, an alarm is triggered to the administrator port.

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