CN116681281A - Sudden public health event acquisition system and method based on context awareness - Google Patents
Sudden public health event acquisition system and method based on context awareness Download PDFInfo
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Abstract
The invention discloses a sudden public health event acquisition system and method based on context awareness, and the sudden public health event acquisition system comprises a data cleaning frame, wherein the data cleaning frame is used for acquiring sudden public health event basic data in a crawling and external interface calling mode, the data source hierarchy is enriched, then the data cleaning frame based on network knowledge is built, and the data cleaning frame is used for building a multi-source heterogeneous data fusion sudden public health event risk assessment model based on a deep neural network. The emergency public health event collecting system and the emergency public health event collecting method based on context awareness can further develop an emergency public health event assessment and emergency decision application platform, are practice of emergency rescue research of emergency public health events, are effective ways for rapidly improving emergency rescue capability of the emergency public health events, can accelerate construction steps of emergency systems of the emergency public health events, and drive subjects in different fields to cross development.
Description
Technical Field
The invention relates to the technical field of information acquisition, in particular to a sudden public health event acquisition system and method based on context awareness.
Background
In recent years, sudden public health events frequently occur, and when the events occur, unpredictable risks are brought to human beings if the events are not handled in time, and the risk assessment and emergency rescue are implemented, so that the key is that the casualties are effectively lightened, the events are prevented from being further expanded, and the people are quickly and peacefully stabilized. However, in the initial stage of the emergent public health event, due to insufficient information grasping, risk assessment cannot be performed accurately and efficiently, and management units cannot well coordinate the forces of all parties, so that the development of rescue work is directly affected, and the rescue efficiency of the emergent public health event is greatly reduced.
Therefore, it is important and urgent to pay attention to sudden public health event risk assessment and efficient emergency decision making. In general, at present, the risk assessment and emergency decision system of sudden public health events in China is in a development stage, an attempt of solving the risk assessment and emergency decision problems by adopting a multi-source heterogeneous data fusion technology is not yet seen, especially, text data is taken as a part of heterogeneous data mixing, and research of integrating the fields into comprehensive application of sudden public health events at home and abroad does not appear.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a sudden public health event acquisition system and a sudden public health event acquisition method based on context awareness, which solve the problem that the sudden public health event acquisition system has poor effect.
In order to achieve the above purpose, the invention is realized by the following technical scheme: the system comprises a data cleaning frame, wherein the data cleaning frame is used for collecting basic data of the sudden public health event by crawling and calling external interfaces and the like, enriching data source layers, and then constructing a data cleaning frame based on network knowledge, the data cleaning frame is used for constructing a multi-source heterogeneous data fusion sudden public health event risk assessment model based on a deep neural network, and the multi-source heterogeneous data fusion sudden public health event risk assessment model based on the deep neural network comprises risk assessment basic theory analysis, knowledge base research and construction, risk assessment model research and multi-source heterogeneous data dynamic intelligent emergency decision model research.
Preferably, when the basic data of the sudden public health event is collected, firstly, the tuples in the local relation data are classified, the correct tuple data are determined and sampled, and interaction is performed on the WEB, the fuzzy matching based on the internet retrieval content is taken as a means to obtain the corresponding text mode knowledge, and then the found mode knowledge is utilized to clean the data with quality problems in the local data based on the network knowledge.
Preferably, the risk assessment basic theory analysis is related concept definition and resolution of risk assessment, and the influence factors and influence mechanism analysis of various data of sudden public health events on casualties.
Preferably, the research and construction of the knowledge base refer to a historical sudden public health event information base, and the constructed knowledge base mainly comprises historical sudden public health events, event processing flows, disposal methods, corresponding plans and the like, and is the basis for constructing a deep learning model and performing model training and cross validation.
Preferably, the risk assessment model researches analyze the influence of various data on the event according to the preprocessed data, a risk assessment model is built by adopting a sudden public health event analysis technology, a preliminary risk assessment result is quickly generated, then multi-layer features are extracted from a knowledge base and the preprocessed data, a deep learning model fused by multi-source heterogeneous data is built by adopting a deep neural network through researching and analyzing feature transformation, feature selection, feature classification and feature combination methods, finally, in order to avoid the fusion failure problem caused by feature selection errors, the risk assessment model result is analyzed by adopting a mode of combining sudden public health event analysis with the deep learning model, namely, weights are determined according to the accuracy of training of the deep learning model, weighted averages are carried out on the preliminary risk assessment result which is quickly generated, and finally, a sudden public health event risk assessment report is generated.
Preferably, the dynamic intelligent emergency decision model research based on the multi-source heterogeneous data comprises emergency plan matching, rescue personnel scheduling and emergency resource scheduling.
The invention also discloses a sudden public health event collecting method based on context awareness, which comprises the following steps of;
s1, firstly, analyzing application of a multi-source data fusion technology in domestic and foreign emergency rescue construction, and determining effectiveness and feasibility of the technology in emergency rescue of sudden public health events;
s2, when the sudden public health event occurs, attempting to analyze the multi-source heterogeneous sudden public health event data (such as data acquired by a crawling technology, an external interface, the Internet of things and other technologies) acquired in real time by adopting a big data processing platform, establishing a deep learning model of multi-source heterogeneous data fusion, realizing effective data processing, and providing basis for plan matching and emergency decision;
and S3, finally, establishing a deep learning model according to the historical sudden public health event data, reasonably combining the deep learning model with the multi-source heterogeneous data, realizing scientific and reasonable risk assessment, finally, matching a reasonable emergency plan according to the sudden public health event risk assessment result, combining the real-time multi-source real-time sudden public health event data, and scheduling rescue personnel and emergency resources by adopting an optimization theory and a multi-objective decision theory.
Advantageous effects
The invention provides a sudden public health event acquisition system and method based on context awareness. Compared with the prior art, the method has the following beneficial effects:
according to the emergency public health event collecting system and method based on context awareness, key links such as quantitative analysis and intelligent decision making are applied to emergency rescue by adopting the Internet of things, big data and artificial intelligence technology, so that the capability of data collection, transmission and processing can be improved, meanwhile, information of a plurality of departments and other social institutions on the emergency public health event can be integrated, an emergency public health event response county assessment report can be rapidly given out and a related emergency plan can be matched by analyzing the information, decision basis is provided for rapid development of emergency rescue, an emergency public health event assessment and emergency decision making application platform can be further developed, the system is the practice of emergency rescue research of the emergency public health event, an effective approach for rapidly improving the emergency rescue capability of the emergency public health event is provided, and the construction steps of the emergency public health event emergency system can be quickened, so that the subjects in different fields can be driven to cross develop.
Drawings
Fig. 1 is a schematic block diagram of the system architecture of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the present invention provides a technical solution: a sudden public health event acquisition system and method based on context awareness, comprising a data cleaning frame, characterized in that: the data cleaning framework collects basic data of sudden public health events in a crawling and external interface calling mode, the data source hierarchy is enriched, then a data cleaning framework based on network knowledge is built, the data cleaning framework builds a multi-source heterogeneous data fusion sudden public health event risk assessment model based on a deep neural network, and the multi-source heterogeneous data fusion sudden public health event risk assessment model based on the deep neural network comprises risk assessment basic theory analysis, knowledge base research and construction, risk assessment model research and dynamic intelligent emergency decision model research based on multi-source heterogeneous data.
When the basic data of the sudden public health event is collected, firstly, the tuples in the local relation data are classified, the correct tuple data are determined and sampled, interaction is carried out on the WEB, the fuzzy matching based on the internet retrieval content is taken as a means, the corresponding text mode knowledge is obtained, and then the found mode knowledge is utilized to clean the data with quality problems in the local data based on the network knowledge.
In the invention, the risk assessment basic theory analysis is the related concept definition and resolution of risk assessment, and the influence factors and influence mechanism analysis of various data of sudden public health events on casualties.
In the invention, the research and construction of the knowledge base refer to a historical sudden public health event information base, and the constructed knowledge base mainly comprises historical sudden public health events, event processing flows, disposal methods, corresponding plans and the like, and is the basis for constructing a deep learning model and performing model training and cross validation.
According to the invention, the risk assessment model research analyzes the influence of various data on an event according to the preprocessed data, a risk assessment model is built by adopting a sudden public health event analysis technology, a preliminary risk assessment result is quickly generated, then multi-layer features are extracted from a knowledge base and the preprocessed data, a deep learning model fused by multi-source heterogeneous data is built by adopting a deep neural network through research and analysis of feature transformation, feature selection, feature classification and feature combination methods, finally, in order to avoid the fusion failure problem caused by feature selection errors, the risk assessment model result is analyzed by adopting a mode of combining sudden public health event analysis with the deep learning model, namely, weight is determined according to the accuracy of training of the deep learning model, weighted average is carried out on the obtained result and the quickly generated preliminary risk assessment result, and finally, a sudden public health event risk assessment report is generated.
In the invention, the dynamic intelligent emergency decision model research based on the multi-source heterogeneous data comprises emergency plan matching, rescue personnel scheduling and emergency resource scheduling.
Specifically, after the emergency plan is matched with the sudden public health event, according to the collected multi-source heterogeneous event data and the historical sudden public health event information base, when the system can identify event classification in the knowledge base, the similar plans are intelligently matched, otherwise, the alternative plans are adjusted and modified in an expert intervention mode, after the alternative plans are selected, the implementation of the alternative plans is monitored, in the implementation process, if the requirements cannot be met, the expert can still adjust the plans, rescue personnel schedule and determine various indexes of the capability of the rescue personnel to evaluate, then the weight of each evaluation index is determined by utilizing a combined weighting method, and a scientific personnel evaluation system is established. After the sudden public health event occurs, starting from the current situation of the event, constructing an intelligent scheduling model of rescue workers according to the sudden public health event information and risk reports obtained in real time and the personnel capability evaluation result, adopting a data visualization technology to realize intelligent scheduling of the rescue workers, comprehensively considering the sudden public health event and risk evaluation condition in emergency resource scheduling, determining the allocation priority degree of emergency resources of the sudden public health event, and scientifically and reasonably allocating and optimizing emergency resources in consideration of participation conditions of social emergency resources; in the aspect of scheduling optimization of rescue vehicles, a transportation route is planned according to information such as weather, road conditions and the like, the shortest time and the least rescue points are taken as targets, a multi-target decision optimization model is established according to an emergency resource scheduling algorithm, and intelligent scheduling of emergency resources is realized by adopting a data visualization technology.
The invention also discloses a sudden public health event collecting method based on context awareness, which comprises the following steps of;
s1, firstly, analyzing application of a multi-source data fusion technology in domestic and foreign emergency rescue construction, and determining effectiveness and feasibility of the technology in emergency rescue of sudden public health events;
s2, when the sudden public health event occurs, attempting to analyze the multi-source heterogeneous sudden public health event data (such as data acquired by a crawling technology, an external interface, the Internet of things and other technologies) acquired in real time by adopting a big data processing platform, establishing a deep learning model of multi-source heterogeneous data fusion, realizing effective data processing, and providing basis for plan matching and emergency decision;
and S3, finally, establishing a deep learning model according to the historical sudden public health event data, reasonably combining the deep learning model with the multi-source heterogeneous data, realizing scientific and reasonable risk assessment, finally, matching a reasonable emergency plan according to the sudden public health event risk assessment result, combining the real-time multi-source real-time sudden public health event data, and scheduling rescue personnel and emergency resources by adopting an optimization theory and a multi-objective decision theory.
For the occurrence of sudden public health events, a risk assessment and emergency decision model is studied. The method comprises the steps of collecting data through an information system, wearable equipment, intelligent equipment, the Internet and other modes in the emergency rescue field of the sudden public health event, analyzing and integrating basic data of various sudden public health events by adopting a big data technology, constructing a sudden public health event risk assessment and emergency decision model, generating a risk assessment report and matching a related medical health emergency plan, and providing basis for emergency rescue command decision, so that the sudden public health emergency rescue efficiency is improved.
And comprehensively utilizing the big data processing platform to study the risk assessment and emergency rescue decision of the sudden public health event. In the aspect of data preprocessing, a data preprocessing mechanism is constructed mainly by adopting a network knowledge theory and a context awareness theory aiming at the characteristics of the multi-source heterogeneous sudden public health event data, and the multi-source heterogeneous sudden public health event data are cleaned and data integrated respectively. In the aspect of risk assessment, a risk assessment model is built by adopting a neural network method according to historical sudden public health event data and multi-source heterogeneous sudden public health event data, the effectiveness of risk assessment is determined by using an application case research method, and an actual risk assessment result is compared and analyzed with an actual case. In the aspect of emergency decision, a sudden public health event visualization platform is constructed according to multi-source real-time sudden public health event data, an optimization theory and a multi-target decision theory are adopted to study emergency decision problems in consideration of participation of social emergency resources, and the emergency rescue flow is optimized. Finally, the risk assessment and emergency decision model of the sudden public health event are realized in a software Demo mode.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (10)
1. The utility model provides a sudden public health event collection system based on context awareness, includes data cleaning frame, its characterized in that: the data cleaning framework collects basic data of sudden public health events in a crawling and external interface calling mode, the data source hierarchy is enriched, then a data cleaning framework based on network knowledge is built, the data cleaning framework builds a multi-source heterogeneous data fusion sudden public health event risk assessment model based on a deep neural network, and the multi-source heterogeneous data fusion sudden public health event risk assessment model based on the deep neural network comprises risk assessment basic theory analysis, knowledge base research and construction, risk assessment model research and dynamic intelligent emergency decision model research based on multi-source heterogeneous data.
2. A context awareness based sudden public health event acquisition system according to claim 1, wherein: when the basic data of the sudden public health event is collected, firstly, the tuples in the local relation data are classified, the correct tuple data are determined and sampled, and interaction is carried out on the WEB, so that fuzzy matching of the content retrieved based on the Internet is taken as a means.
3. A context awareness based sudden public health event acquisition system according to claim 2, wherein: and obtaining corresponding text mode knowledge, and then cleaning the data with quality problems in the local data based on network knowledge by using the found mode knowledge.
4. A context awareness based sudden public health event collection system according to claim 3, wherein: the risk assessment basic theory analysis is related concept definition and resolution of risk assessment, and the influence factors and influence mechanism analysis of various data of sudden public health events on casualties.
5. The context awareness based sudden public health event collection system according to claim 4, wherein: the research and construction of the knowledge base refer to a historical sudden public health event information base, and the constructed knowledge base mainly comprises historical sudden public health events, event processing flows, treatment methods, corresponding plans and the like, and is the basis for constructing a deep learning model and performing model training and cross verification.
6. The context awareness based sudden public health event collection system according to claim 5, wherein: the risk assessment model researches that influence of various data on the event is analyzed according to the preprocessed data, a risk assessment model is built by adopting a sudden public health event analysis technology, and a preliminary risk assessment result is rapidly generated.
7. The context awareness based sudden public health event collection system of claim 6, wherein: then, multi-layer features are extracted from the knowledge base and the preprocessed data, and a deep learning model of multi-source heterogeneous data fusion is constructed by adopting a deep neural network through research and analysis of feature transformation, feature selection, feature classification and feature combination methods.
8. The context awareness based sudden public health event collection system of claim 7, wherein: finally, in order to avoid the fusion failure problem caused by the feature selection error, the problem adopts a mode of combining sudden public health event analysis with a deep learning model to analyze the risk assessment model result, namely, weight is determined according to the training accuracy of the deep learning model, weighted average is carried out on the weight and the rapidly generated preliminary risk assessment result, and finally, a sudden public health event risk assessment report is generated.
9. The context awareness based sudden public health event collection system of claim 8, wherein: the dynamic intelligent emergency decision model research based on the multi-source heterogeneous data comprises emergency plan matching, rescue personnel scheduling and emergency resource scheduling.
10. A context awareness based sudden public health event collection system according to any one of claims 1-9, wherein: the acquisition method specifically comprises the following steps of,
s1, firstly, analyzing application of a multi-source data fusion technology in domestic and foreign emergency rescue construction, and determining effectiveness and feasibility of the technology in emergency rescue of sudden public health events;
s2, when the sudden public health event occurs, attempting to analyze the multi-source heterogeneous sudden public health event data (such as data acquired by a crawling technology, an external interface, the Internet of things and other technologies) acquired in real time by adopting a big data processing platform, establishing a deep learning model of multi-source heterogeneous data fusion, realizing effective data processing, and providing basis for plan matching and emergency decision;
and S3, finally, establishing a deep learning model according to the historical sudden public health event data, reasonably combining the deep learning model with the multi-source heterogeneous data, realizing scientific and reasonable risk assessment, finally, matching a reasonable emergency plan according to the sudden public health event risk assessment result, combining the real-time multi-source real-time sudden public health event data, and scheduling rescue personnel and emergency resources by adopting an optimization theory and a multi-objective decision theory.
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| CN117455745A (en) * | 2023-12-26 | 2024-01-26 | 四川省大数据技术服务中心 | Public safety event sensing method and system based on multidimensional fusion data analysis |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117455745A (en) * | 2023-12-26 | 2024-01-26 | 四川省大数据技术服务中心 | Public safety event sensing method and system based on multidimensional fusion data analysis |
| CN117455745B (en) * | 2023-12-26 | 2024-03-19 | 四川省大数据技术服务中心 | Public safety event sensing method and system based on multidimensional fusion data analysis |
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