TWI582718B - A method and system of data mining with climate and air pollution data integrated for respiratory disease prevention - Google Patents

Description

Data exploration method and system for integrating respiratory and air pollution data for respiratory disease prevention

The invention relates to a data exploration method and a system for integrating respiratory and air pollution data for respiratory disease prevention, in particular to a general user, a patient, a medical staff and the like, which can be used by a user in a short time. Investigate recent historical data such as climate, air pollution, respiratory diseases, etc., to achieve early prevention, prevention and reduction of respiratory diseases.

Modern people are busy, which leads to the inability to worry about air quality. Many children, adults and adults suffer from respiratory diseases such as allergies and asthma, and in today's living environment, the exhaust emissions of steam locomotives and the pollution of factories produce Air pollution is becoming more and more serious. Therefore, there are many surrounding products that monitor air quality, such as air cleaners. However, there is a wireless air quality monitoring system and air quality prediction method, such as the Republic of China Invention Patent No. I498553 : "Wireless Air Quality Monitoring System and Air Quality Prediction Method", the wireless air quality monitoring system includes a remote end. The server, the complex sensor node, the complex sensing transmission board, a smart sensing module and a gateway. The remote server has a receiving database. The sensing transmission boards each detect a concentration value of a pollution source. The smart sensing module is coupled to the sensing transmitting boards and includes a wireless communication module, an electrical data sheet, and an adjustable front circuit. The gateway device is connected to the sensing transmission board, the smart sensing module and the remote server, and collects concentration values of the pollution sources by the smart sensing module, and the pollution sources are The concentration value is transmitted to the receiving database, but the wireless air quality monitoring system can only bring information about the indoor air quality of the indoor worker, and fails to bring information to the outdoor worker for prevention. Therefore, the present invention provides a data exploration method and system for integrating respiratory and air pollution data for respiratory disease prevention, and in particular, a method for a general user, a patient, a medical staff, and the like to be used by different users. In a short period of time, we will look up historical data such as climate, air pollution, and respiratory diseases that have been integrated in the near future to achieve early prevention, prevention, and reduction of respiratory diseases.

The invention provides a data exploration method and a system for integrating respiratory and air pollution data for respiratory disease prevention, and the data exploration method enables different users such as ordinary people, patients and medical personnel to enter the exploration system through an operation unit. The exploration system is linked to a database, allowing users to inquire about historical data such as climate, air pollution, respiratory diseases and other recent data that have been integrated in a short period of time to achieve early prevention, prevention and reduction of respiratory diseases.

(100) ‧‧‧ users

(10)‧‧‧Exploration system

(1) ‧ ‧ climatic and air pollution web page data exploration subsystem

(11) ‧ ‧ historical climate web page capture module

(12) ‧‧‧ Historical Air Pollution Webpage

(13) ‧‧‧Historical Respiratory Diseases Database

(14) ‧‧‧ Instant climate web page capture module

(15) ‧‧‧ Instant air pollution web page

(16) ‧‧‧ Instant Respiratory Diseases Database

(17) ‧ ‧ climatic factor screening module

(18)‧‧‧Respiratory disease factor screening module

(2) ‧ ‧ respiratory disease cluster classification subsystem

(21)‧‧‧K-MEAN respiratory disease cluster classification module

(22) ‧‧‧APRIOR climatic and respiratory diseases association rules exploration module

(23) ‧‧‧Genetic algorithm respiratory disease cluster classification module

(3) ‧ ‧ respiratory disease prevention subsystem

(31)‧‧‧Prevention module

(4) ‧ ‧ database

(41) ‧ ‧ Climate Database

(42) ‧ ‧ emptiness database

(43) ‧ ‧ Respiratory Diseases Database

(44) ‧‧‧Weather factor screening database

(45) ‧‧‧Respiratory disease factor screening database

(46) ‧‧‧K-MEAN Respiratory Diseases Cluster Classification Database

(47) ‧‧‧APRIOR meteorological and respiratory diseases association rules exploration database

(48) ‧‧‧Genetic Algorithms for Classification of Respiratory Diseases

(49) ‧ ‧ prevention database

(51) ‧ ‧ climatic and air pollution pages

(52) ‧ ‧ tidy up the list of climate and air pollution

(53) ‧‧‧ Forecasting Optimization Portfolio Recommendations

(531) ‧ ‧ collocation with respiratory diseases

(532)‧‧‧Confirmation of forecast information list

(54) ‧‧‧Recommended prevention targets

(55) ‧ ‧ Best preventive measures

(56) ‧ ‧ Adjust climate and air pollution list

(57) ‧‧‧Adjustment of forecasting optimization combinations

(571)‧‧‧Renewal of respiratory diseases list

(572)‧‧‧Confirmation of forecast information list

(58) ‧ ‧ implement preventive measures

(59) End of ‧‧

(61) ‧‧‧ History/immediate climate page

(611) ‧ ‧ tidy climate list

(62)‧‧‧Looking for historical/immediate air pollution pages

(621) ‧‧ ‧ Sorting up the air pollution list

(63) ‧ ‧ 历史 History / Instant Respiratory Diseases webpage

(631) ‧ ‧ List of respiratory diseases

(64) ‧‧ ‧Integration of climate, air pollution, respiratory diseases list

(65) ‧ ‧ updated list of climate, air pollution, respiratory diseases

(66) ‧ ‧ Meteorological factor screening

(661)‧‧‧Respiratory disease factor screening

(67) ‧‧‧Adjusting the optimal combination

(671)‧‧‧Weather factor screening

(672)‧‧‧Respiratory disease factor screening

(673)‧‧‧Confirmation information list

(68)‧‧‧Confirmation of forecast information list

(69) End of ‧‧

(71)‧‧‧K-MEAN respiratory disease data

(72) ‧ ‧ arranging analytical data

(73) ‧ ‧ provide the most appropriate information

(74) ‧ ‧ reorganization analysis data

(75) ‧‧‧APRIOR meteorological clusters

(76) ‧‧‧APRIOR meteorological classification

(77)‧‧‧Recommended forecasting combinations

(78) End of ‧‧

(81) ‧‧ ‧Revision of respiratory diseases

(82)‧‧‧System verification information

(83) ‧ ‧ prediction verification recommendation

(84)‧‧‧Re-verification

(85) ‧‧‧ best predictive measures

(86) ‧ ‧ recommended preventive measures

(87) End of ‧‧

(A) ‧‧‧Operating unit

First Figure: is a block diagram of the architecture of the present invention.

The second figure is a block diagram of the architecture of the climate and air pollution webpage data exploration subsystem of the present invention.

The third figure is a block diagram of the architecture of the respiratory disease cluster classification subsystem of the present invention.

Figure 4 is a block diagram showing the architecture of the respiratory disease prevention subsystem of the present invention.

Figure 5 is a block diagram of the database structure of the present invention.

Figure 6 is a block diagram of the system flow of the present invention.

The seventh figure is a block diagram of the process of the climate and air pollution webpage data exploration subsystem of the present invention.

Figure 8 is a block diagram of the flow classification subsystem of the respiratory disease of the present invention.

Figure 9 is a block diagram showing the flow of the respiratory disease prevention subsystem of the present invention.

In order to understand the present invention in more detail, please refer to the first figure, the present invention provides a A data mining method and system for integrating respiratory and air pollution data for respiratory disease prevention, the data exploration method is such that different users, such as ordinary people, patients, medical personnel, etc., enter the exploration system 10 through an operation unit A, the exploration The system 10 is linked to a database 4, and allows the user 100 to inquire about historical data such as climate, air pollution, respiratory diseases and the like that have recently been integrated in a short period of time, and to achieve early prevention, prevention, and reduction of respiratory diseases.

The operating unit A can be a computer, a smart phone, etc., and the operating unit A can be operated by the user to enter the exploration system 10.

The exploration system 10 includes a climate and air pollution webpage data exploration subsystem 1, a respiratory disease cluster classification subsystem 2, and a respiratory disease prevention subsystem 3, and the climate and air pollution webpage data exploration subsystem 1 is used The historical data collection data is collected, and the respiratory disease cluster classification subsystem 2 is a group classification model for respiratory diseases, and the respiratory disease prevention subsystem 3 integrates climate and air pollution information with prevention information provided by respiratory diseases. Provide users 100 with the best predictive measures.

Please refer to the second figure, the climate and air pollution webpage data mining subsystem 1, which includes a historical climate webpage extraction module 11, a historical air pollution webpage extraction module 12, and a historical respiratory disease database. The sifting module 13, an instant climate webpage sifting module 14, a real-time smuggling webpage sifting module 15, an instant respiratory disease database culling module 16, a climatic factor screening module 17 and a respiratory disease The factor screening module 18, the climate and air pollution web page data mining subsystem 1 is used to collect historical data such as climate, air pollution, respiratory diseases and to integrate data.

Referring to the third figure, the respiratory disease cluster classification subsystem 2 includes a K-MEAN respiratory disease cluster classification module 21, an APRIOR climate and respiratory disease association rule exploration module 22, and a genetic algorithm respiratory channel. The disease group classification module 23, the respiratory disease group classification subsystem 2, is a cluster classification model for a wide range of respiratory diseases.

Please refer to the fourth figure, the respiratory disease prevention subsystem 3 is equipped with a preventive model. Group 31, which integrates climate and air pollution information and provides prevention information provided by respiratory diseases to provide users with the best predictive measures.

Referring to FIG. 5, the foregoing database 4 includes a climate database 41, an air pollution database 42, a respiratory disease database 43, a meteorological factor screening database 44, and a respiratory disease factor screening database 45. , a K-MEAN respiratory disease cluster classification database 46, an APRIOR meteorological and respiratory disease association rule exploration database 47, a genetic algorithm respiratory disease cluster classification database 48 and a prevention database 49, which are available for storage of all Consolidate the information.

The flow chart of the data exploration method for integrating respiratory and air pollution data for respiratory disease prevention according to the present invention is as shown in the sixth figure, so that the exploration system 10 selects the climate and air pollution page 51 and then sorts the climate and air pollution list 52, and selects whether to predict or not. The combination recommendation 53 is selected, "Yes" is selected to match the respiratory disease list 531, and then the confirmation prediction information list 532 is selected, and if "No" is selected, the confirmation prediction information list 532 is directly performed, and the exploration system 10 displays whether or not the recommended prevention is selected. Target 54, select "Yes" for best preventive action guide 55, and allow user 100 to implement preventive measures 58, and select "No" to allow user 100 to adjust climate, air pollution list 56, and then select whether or not The prediction optimization combination 57 is adjusted, "Yes" is selected to update the respiratory disease list 571, and if "No" is selected, the confirmation prediction information list 572 is directly executed, and then the user 100 is implemented with the preventive measure 58 and finally ends 59.

The flow chart of the climate and air pollution webpage data exploration subsystem 1 of the present invention is as shown in the seventh figure, so that the climate and air pollution webpage data exploration subsystem 1 of the exploration system 10 respectively extracts the history/immediate climate page 61 and then organizes The climate list 611, the history/immediate air pollution page 62, then the emptying list 621, the history/immediate respiratory disease page 63, and then the respiratory disease list 631, and then integrate the climate, air pollution, respiratory disease list 64, select whether Update climate, air pollution, respiratory disease list 65, select "Yes" to directly perform meteorological factor screening 66 and respiratory disease factor screening 661, then confirm the forecast information list 68, and select "No" to select whether The optimization combination 67 is adjusted. When "Yes" is selected, the weather factor screening 671 and the respiratory disease factor screening 672 are selected, and then the information list 673 is confirmed, and when "No" is selected, the information list 673 can be directly confirmed, and further confirmation is made. Information list 68, and finally ended 69.

The flow chart of the respiratory disease cluster classification subsystem 2 of the present invention is as shown in the eighth figure, so that the respiratory disease group classification subsystem 2 of the exploration system 10 displays the K-MEAN respiratory disease data 71, and then the analysis data 72 is performed. And choose whether to provide the most appropriate information 73, when selecting "No" to carry out the reorganization analysis data 74, then enter the APRIOR meteorological grouping 75, APRIOR meteorological classification 76, and display the recommended prediction combination 77, and when selecting "Yes" is directly Enter APRIOR meteorological group 75, APRIOR meteorological classification 76, then display recommended prediction combination 77, and finally end 78.

The flowchart of the respiratory disease prevention subsystem 3 of the present invention is as shown in the ninth diagram, and the respiratory disease prevention subsystem 3 of the exploration system 10 sorts the respiratory disease data 81, and then the system verification information 82, and then selects whether to accept the prediction verification recommendation. 83. When "No" is selected for revalidation 84, then the best predictive measure 85 is performed, and then recommended preventive measures 86 are provided, and when "Yes" is selected, the best predictive measure is directly applied 85, followed by recommended preventive measures 86 And finally ended 87.

In summary, when a different user 100 such as a general person, a patient, a medical staff member, or the like enters the exploration system 10 through an operation unit A, the user 100 can query the climate and air pollution that have been recently integrated in a short time. Historical data such as respiratory diseases, to achieve early prevention, prevention and reduction of respiratory diseases.

(100) ‧‧‧ users

(10)‧‧‧Exploration system

(1) ‧ ‧ climatic and air pollution web page data exploration subsystem

(2) ‧ ‧ respiratory disease cluster classification subsystem

(3) ‧ ‧ respiratory disease prevention subsystem

(4) ‧ ‧ database

Claims (6)

A data exploration method and system for integrating respiratory and air pollution data for respiratory disease prevention, the data exploration method enables different users such as ordinary people, patients, medical personnel, etc. to enter the exploration system through an operation unit, so that the user In a short period of time, we can find out the historical data such as climate, air pollution, respiratory diseases and other diseases that have been integrated in the near future to achieve early prevention, prevention and reduction of respiratory diseases. The exploration system includes a climate and air pollution webpage data exploration subsystem. The respiratory disease cluster classification subsystem and a respiratory disease prevention subsystem, the climate and air pollution web data exploration subsystem is used to collect historical data integration data, and the respiratory disease cluster classification subsystem is to group large-scale respiratory diseases data. The classification model, the respiratory disease prevention subsystem, integrates climate and air pollution information with the prevention information provided by respiratory diseases, and provides users with the best predictive measures. The exploration system is linked to a database. A method and system for data exploration for integrating respiratory and air pollution data for respiratory disease prevention according to claim 1 of the patent application scope, wherein the operation unit is a computer and a smart phone, and the operation unit is for allowing a user The operation enters the exploration system. The data mining method and system for integrating respiratory and air pollution data for respiratory disease prevention according to claim 1 of the patent application scope, wherein the climate and air pollution webpage data exploration subsystem includes a historical climate webpage Module, a historical air pollution webpage capture module, a historical respiratory disease database library module, an instant climate webpage extraction module, a real-time air pollution webpage extraction module, and an instant respiratory disease database The module, a climatic factor screening module and a respiratory disease factor screening module are used to collect historical data such as climate, air pollution, respiratory diseases and integrate data. A method and system for data exploration of respiratory disease prevention according to the integration of climate and air pollution data as described in claim 1 of the patent application, wherein the respiratory disease cluster classification The system comprises a K-MEAN respiratory disease cluster classification module, an APRIOR climate and respiratory disease association rule exploration module and a genetic algorithm respiratory disease cluster classification module, the respiratory disease cluster classification subsystem is a respiratory disease Large-scale data is used for group classification. The method and system for data exploration for respiratory disease prevention according to the integration of climate and air pollution data as described in claim 1 of the patent scope, wherein the respiratory disease prevention subsystem is provided with a prevention module, which can integrate climate and air The information is combined with the prevention information provided by respiratory diseases to provide users with the best predictive measures. The method for exploring data and methods for integrating respiratory and air pollution data for respiratory disease prevention according to claim 1 of the patent application scope, wherein the foregoing database includes a climate database, an air pollution database, and a respiratory disease data. Library, a meteorological factor screening database, a respiratory disease factor screening database, a K-MEAN respiratory disease cluster classification database, an APRIOR meteorological and respiratory disease association rule exploration database, a genetic algorithm respiratory disease cluster classification database And a prevention database for storing all the collection data.