Foggy weather early warning auxiliary reminding system

Abstract

A foggy weather early warning auxiliary reminding system comprises a data acquisition module, a data analysis module, an early warning judgment module, a notification module, a historical data storage module and a system management module. The data acquisition module acquires key meteorological parameters from a meteorological service intranet and measures environmental data with high precision through various meteorological sensors. And the data analysis module performs data preprocessing, feature extraction and real-time analysis. The early warning judgment module automatically judges early warning conditions and levels through an intelligent algorithm according to a preset standard and makes a decision. The notification module automatically notifies a watch keeper in the modes of short messages, calls and the like when conditions are met. The historical data storage module can store data in a classified mode, provide query, conduct analysis and comparison and mine potential rules. And the system management module realizes user management, parameter setting and system monitoring and maintenance. The operation process of the system software comprises the steps of obtaining weather early warning information, screening heavy fog early warning, obtaining haze data, comparing early warning levels, generating prompt information, judging whether to send a short message or not, sending the short message, recording a log and the like. The system has the beneficial effects of improving the early warning timeliness and accuracy, ensuring that information transmission is free of omission, relieving the working pressure of watchmen, reducing traffic accidents, optimizing the working efficiency of meteorological departments and the like.

Description

Technical Field

[0001] The invention relates to the technical field of meteorological monitoring and early warning, and in particular to a foggy weather early warning auxiliary reminder system. Background Art

[0002] Traditional foggy weather monitoring and early warning work relies on manual duty, which is not only labor-intensive, but also prone to late or missed warning signals at night or when visibility changes dramatically, affecting public safety and smooth traffic. With the continuous deterioration of the social ecological environment, meteorological disasters are becoming more and more serious in life. It is crucial to accurately, timely and efficiently release meteorological disaster early warning information. Although my country has fully realized the automation of ground meteorological observation business, the release of meteorological disaster early warning information still requires grassroots meteorological business personnel to pay attention to various meteorological elements at all times, especially when observing foggy weather at night. County bureau duty officers need to stay on duty all night, which is time-consuming and labor-intensive. At the same time, it is easy to cause problems such as late issuance or missed issuance of fog warnings due to negligence of business personnel, and untimely changes in fog warning levels. It is urgent to establish a computer active reminder mechanism for visibility exceeding the threshold value to further improve the level of intelligence. Summary of the invention

[0003] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0004] In view of the above problems and / or the problems existing in the prior art, the present invention is proposed.

[0005] Therefore, the purpose of the present invention is to overcome the deficiencies in the prior art and provide a foggy weather warning auxiliary reminder system.

[0006] As a preferred solution described in the present invention, the present invention provides a heavy fog weather warning auxiliary reminder system, which includes: a data acquisition module, a data analysis module, a warning judgment module, a notification module, a historical data storage module and a system management module.

[0007] As a preferred solution described in the present invention, the data acquisition module includes a data source unit and a data acquisition device unit.

[0008] As a preferred solution described in the present invention, the data analysis module includes a data preprocessing unit, a feature extraction unit and a real-time analysis unit.

[0009] As a preferred solution described in the present invention, the early warning judgment module includes an early warning standard unit, an intelligent judgment unit and a decision-making unit.

[0010] As a preferred solution described in the present invention, the notification module has the function of automatically notifying the duty officer via text message, phone call, etc. when the warning condition is reached or the warning level needs to be changed.

[0011] As a preferred solution described in the present invention, the historical data storage module includes a data storage unit, a data query unit, a data analysis and comparison unit, and a data mining unit.

[0012] As a preferred solution described in the present invention, the system management module includes a user management unit, a parameter setting unit, a system monitoring unit, and a system maintenance unit.

[0013] As a preferred solution of the present invention, the operation process of the foggy weather warning auxiliary reminder system software is as follows:

[0014] 1. Get Started

[0015] Start process, indicating that the system is started.

[0016] 2. Obtain weather warning information

[0017] Action: Call history_warning_signal or living_warning_signal (depending on whether historical or real-time data is needed).

[0018] Input: User name, password, time range (optional), administrative area code (such as Changfeng County).

[0019] Output: Warning information list (SignalInfo object array).

[0020] 3. Screening of heavy fog warnings

[0021] Action: Traverse the warning information list and filter out the warnings with the signal name "heavy fog".

[0022] Output: heavy fog warning information list.

[0023] 4. Obtain haze data

[0024] Action: Call the GetFogDaasDatas method to obtain the smog data of the specified area (such as Changfeng County).

[0025] Input: Area code or name.

[0026] Output: haze data list, including visibility and other information.

[0027] 5. Compare warning levels

[0028] Action: For each piece of haze data, compare the warning level corresponding to its visibility with the current heavy fog warning level.

[0029] Logic: Use compare_levels function to compare warning levels.

[0030] Output: Decision on whether to issue or change an alert.

[0031] 6. Generate prompt information

[0032] Action: Generate prompt information based on the comparison results to remind the duty officer to issue a warning signal or update the visibility, warning level, warning content, etc. of the existing warning signal.

[0033] 7. Determine whether to send a text message

[0034] Logic: If new prompt information is generated, continue; otherwise, end the process.

[0035] 8. Send SMS

[0036] Action: Call the send_message function to send a text message through the serial port.

[0037] Input: receiving mobile phone number, SMS content (including warning information).

[0038] Output: Information returned by the GSM module (such as sending status).

[0039] 9. Keep a log

[0040] Action: Record the generated warning information, the results of sending SMS, etc. into the log file.

[0041] 10. End

[0042] Ending the process means that the system has completed the task of providing auxiliary reminder for heavy fog weather warning.

[0043] The foggy weather warning auxiliary reminder system of the present invention has the following beneficial effects:

[0044] 1. Improve the timeliness and accuracy of early warning: Combining real-time monitoring with intelligent judgment, the system can continuously monitor changes in meteorological data and respond to the emergence and evolution of foggy weather in a timely manner. According to the preset early warning standards, the intelligent algorithm automatically determines whether the current weather conditions meet the early warning conditions and determines the corresponding early warning level, effectively reducing the delays and omissions that may occur due to manual judgment, and improving the timeliness and accuracy of meteorological early warnings.

[0045] 2. Ensure that information is not missed: Multiple notification methods ensure that warning information is delivered to the duty officer in a timely and accurate manner. The system supports notification methods such as SMS and phone calls. When the warning conditions are met or the warning level needs to be changed, the duty officer is automatically notified through these methods, which improves the emergency response speed and avoids omissions in information delivery.

[0046] 3. Reduce the work pressure of duty officers: Allow duty officers to rest at night and no longer need to stay on duty all night to pay attention to meteorological factors. The system automatically monitors and issues early warning signals, which greatly reduces the workload of duty officers and improves the intelligence level of ground meteorological observation services.

[0047] 4. Reduce traffic accidents: By issuing early warning signals in a timely and accurate manner, the public can prepare for low-visibility weather in advance, effectively reduce traffic accidents caused by low-visibility weather, and protect the safety of public life and property.

[0048] 5. Optimize the work efficiency of the meteorological department: improve the efficiency and quality of meteorological services and reduce labor costs. The automated operation of the system reduces the reliance on manual labor, enabling the meteorological department to work more efficiently and provide better meteorological services to the society. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying creative work.

[0050] Figure 1 It is a schematic diagram of a flow chart in one embodiment of the present invention;

[0051] Figure 2 This is a schematic diagram of an operation flow in one embodiment of the present invention;

[0052] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings in conjunction with the embodiments. DETAILED DESCRIPTION

[0053] The following will be combined with the accompanying drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the present invention. It should be understood that the specific implementation methods described here are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0054] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the embodiments of the specification.

[0055] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0056] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0057] As a preferred solution described in the present invention, the present invention provides a heavy fog weather warning auxiliary reminder system, which includes: a data acquisition module, a data analysis module, a warning judgment module, a notification module, a historical data storage module and a system management module.

[0058] As a preferred solution described in the present invention, the data acquisition module includes a data source unit and a data acquisition device unit.

[0059] Data source unit: The data source unit in the data acquisition module establishes a connection with the meteorological business intranet and continuously obtains key meteorological parameters including visibility, humidity, temperature, wind direction and speed from the meteorological business intranet. These key meteorological parameters are the basic data for judging the heavy fog weather conditions and provide important data support for the entire heavy fog weather warning auxiliary reminder system. If there is no data source unit to obtain these key meteorological parameters from the meteorological business intranet, the system will not be able to accurately judge the heavy fog weather conditions and provide effective data support for subsequent analysis and warning work.

[0060] Collection device unit: The collection device unit in the data collection module integrates a variety of meteorological sensors, such as visibility meters, humidity sensors, etc. These meteorological sensors can measure various parameters of the surrounding environment with high precision under different environmental conditions. The collection device unit accurately transmits the measured data to the core processing unit of the system to ensure the timeliness and reliability of the data. The existence of the collection device unit enables the system to obtain accurate meteorological data, providing a strong guarantee for subsequent data analysis and early warning judgment.

[0061] As a preferred solution described in the present invention, the data analysis module includes a data preprocessing unit, a feature extraction unit and a real-time analysis unit.

[0062] Data preprocessing unit: After the system receives the raw data from the data acquisition module, the data preprocessing unit in the data analysis module performs a series of processing operations on the raw data. The data preprocessing unit first cleans the data to remove the noise and erroneous data that may exist in the raw data to ensure the accuracy of the data. Then it verifies the integrity and accuracy of the data to ensure that the data meets the requirements of the system. Finally, it formats the data into a unified format for subsequent analysis and processing. The role of the data preprocessing unit is to provide high-quality and reliable data for subsequent analysis work to ensure the accuracy and effectiveness of data analysis.

[0063] Feature extraction unit: The feature extraction unit in the data analysis module uses complex algorithms to extract key features related to foggy weather from a large amount of data. These key features include the changing trend of visibility, the correlation between humidity and visibility, etc. The key features extracted by the feature extraction unit provide an important basis for subsequent early warning judgment, allowing the system to more accurately judge the conditions of foggy weather and improve the accuracy and reliability of early warning.

[0064] Real-time analysis unit: The real-time analysis unit in the data analysis module has powerful real-time analysis capabilities and can continuously monitor changes in meteorological data. The real-time analysis unit captures the emergence and evolution of foggy weather at the first time and responds to various changes in a timely manner. The role of the real-time analysis unit is to ensure that the system can respond instantly when foggy weather occurs, buy precious time for timely release of warning information, and improve the timeliness and effectiveness of the system's warning.

[0065] As a preferred solution described in the present invention, the early warning judgment module includes an early warning standard unit, an intelligent judgment unit and a decision-making unit.

[0066] Warning standard unit: The warning standard unit in the warning judgment module presets multi-level fog warning standards. These warning standards are based on the analysis and summary of historical meteorological data, and are combined with the experience of experts and relevant meteorological specifications. The multi-level fog warning standards preset in the warning standard unit can accurately reflect the severity and potential impact of foggy weather, and provide a clear reference for judging whether to issue a warning and determining the warning level.

[0067] Intelligent judgment unit: The intelligent judgment unit in the early warning judgment module uses advanced intelligent algorithms to automatically make judgments based on real-time meteorological data and preset early warning standards. The intelligent judgment unit can quickly and accurately analyze whether the current weather conditions meet the early warning conditions and determine the corresponding early warning level based on the specific situation. The role of the intelligent judgment unit is to provide scientific and reasonable decision-making support for subsequent early warning releases to ensure the accuracy and reliability of early warning information.

[0068] Decision-making unit: The decision-making unit in the early warning judgment module automatically makes a decision to issue an early warning signal when the system determines that the early warning conditions are met. The decision-making unit determines the type, level and release scope of the early warning signal to ensure that the early warning information can be accurately conveyed to the people in need. The role of the decision-making unit is to ensure that the early warning information can be delivered in a timely and effective manner, reminding relevant personnel to take corresponding measures to protect people's lives and property.

[0069] As a preferred solution of the present invention, the notification module is used to automatically notify the duty officer through SMS, phone calls, etc. when the warning condition is reached or the warning level needs to be changed. The system supports multiple notification methods, including SMS, phone calls, etc., which can ensure that the warning information is conveyed to the duty officer in a timely and accurate manner.

[0070] As a preferred solution described in the present invention, the historical data storage module includes a data storage unit, a data query unit, a data analysis and comparison unit, and a data mining unit.

[0071] Data storage unit: The system uses advanced database technology to classify and store the collected meteorological data, analysis results, warning records and other information. These data are stored in a structured manner for quick retrieval and query. At the same time, in order to ensure the security of the data, the system also performs regular backup.

[0072] Data query unit: Relevant personnel can easily query historical data through the query interface provided by the system. They can filter according to time, location, warning level and other conditions to quickly obtain the required information.

[0073] Data analysis and comparison unit: Using the stored historical data, the system can analyze and compare data in different time periods and regions. Through comparison, the changing trend of foggy weather and the effectiveness of early warning strategies can be discovered, providing a basis for further optimizing the system.

[0074] Data mining unit: By mining a large amount of historical data, the system can discover the potential laws and patterns hidden in the data. For example, it can find the correlation between foggy weather and certain specific meteorological conditions, providing new ideas for more accurate early warning judgments.

[0075] As a preferred solution described in the present invention, the system management module includes a user management unit, a parameter setting unit, a system monitoring unit, and a system maintenance unit.

[0076] User management unit: System administrators can manage users, including adding and deleting users, setting user permissions, etc. Different users can access different functional modules and data according to their responsibilities and permissions to ensure the security and confidentiality of the system.

[0077] Parameter setting unit: The administrator can set various parameters of the system according to the actual situation. For example, adjust the warning standard, the priority of the notification method, etc. The settings of these parameters can be customized according to the characteristics and needs of different regions to improve the adaptability of the system.

[0078] System monitoring unit: The system monitors its own operating status in real time, including data collection, analysis, warning release, etc. Once an abnormal situation is found, the system will issue an alarm in time, and the administrator can quickly take measures to ensure the stable operation of the system.

[0079] System maintenance unit: Regularly maintain the system, including software upgrades, database optimization, hardware equipment inspection, etc. Through maintenance, ensure that the system always maintains good performance and reliability, and provide continuous and stable services for fog weather warning.

[0080] The operation process of the fog weather warning auxiliary reminder system software is as follows: Figure 2 As shown, the process is explained below.

[0081] 1. Get Started

[0082] Start process, indicating that the system is started.

[0083] 2. Obtain weather warning information

[0084] Action: Call history_warning_signal or living_warning_signal (depending on whether historical or real-time data is needed).

[0085] The instructions for history_warning_signal and living_warning_signal are explained as follows:

[0086] (1) history_warning_signal: The main function of this program is to query and process weather warning information within a specific time period. It interacts with an API interface, receives query parameters (such as username, password, time range, etc.), and requests weather warning data within that time period. The program parses the returned JSON format weather warning data and converts each warning information into a SignalInfo object, which contains detailed information such as the warning platform ID, status, organization name, signal name, level, occurrence time, title, and content. Finally, the program stores all the processed warning information objects in a list and returns them for further use or display.

[0087] (2) living_warning_signal: The main function of this program is to query and obtain the currently valid weather warning information in a specific administrative area (specified by the org_code parameter). It interacts with an API interface (http: / / 10.129.18.202:8084 / api / Effectiveyujing) and sends a POST request containing information such as username, password, and administrative number. The program receives the returned weather warning data in JSON format, parses the data, and converts each warning information into a SignalInfo object, which contains detailed information such as organization name, signal name (obtained through signal_id mapping), warning level, occurrence time, title, and content. Finally, the program stores all the parsed warning information objects in a list and returns them for further use or display.

[0088] Input: User name, password, time range (optional), administrative area code (such as Changfeng County).

[0089] Output: Warning information list (SignalInfo object array).

[0090] 3. Screening of heavy fog warnings

[0091] Action: Traverse the warning information list and filter out the warnings with the signal name "heavy fog".

[0092] Output: heavy fog warning information list.

[0093] 4. Obtain haze data

[0094] Action: Call the GetFogDaasDatas method to obtain the smog data of the specified area (such as Changfeng County).

[0095] Input: Area code or name.

[0096] Output: haze data list, including visibility and other information.

[0097] 5. Compare warning levels

[0098] Action: For each piece of haze data, compare the warning level corresponding to its visibility with the current heavy fog warning level.

[0099] Logic: Use compare_levels function to compare warning levels.

[0100] Output: Decision on whether to issue or change an alert.

[0101] 6. Generate prompt information

[0102] Action: Generate prompt information based on the comparison results to remind the duty officer to issue a warning signal or update the visibility, warning level, warning content, etc. of the existing warning signal.

[0103] 7. Determine whether to send a text message

[0104] Logic: If new prompt information is generated, continue; otherwise, end the process.

[0105] 8. Send SMS

[0106] Action: Call the send_message function to send a text message through the serial port.

[0107] The send_message command is explained as follows:

[0108] send_message: This program is used to send text messages through the serial port (for example, the COM4 port connected to the GSM module). The user needs to specify the mobile phone number and the content of the message. The program first sets the GSM module to text mode (AT+CMGF=1), then sets the number to receive the message (through the AT+CMGS command), then enters the message content and adds CTRL+Z (ASCII code is 0x1A) after the content as the terminator to send the message. After sending, the program will try to read and print the information returned by the GSM module (such as the sending status), and finally close the serial port connection. In this way, the user can send text messages to the specified mobile phone number through this program.

[0109] Input: receiving mobile phone number, SMS content (including warning information).

[0110] Output: Information returned by the GSM module (such as sending status).

[0111] 9. Keep a log

[0112] Action: Record the generated warning information, the results of sending SMS, etc. into the log file.

[0113] 10. End

[0114] Ending the process means that the system has completed the task of providing auxiliary reminder for heavy fog weather warning.

[0115] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A foggy weather warning auxiliary reminder system, characterized in that: It includes: data collection module, data analysis module, early warning judgment module, notification module, historical data storage module and system management module.

2. The foggy weather warning auxiliary reminder system according to claim 1, characterized in that: The data acquisition module includes a data source unit and a collection device unit. The data source unit obtains key meteorological parameters from the meteorological business intranet. The collection device unit integrates multiple meteorological sensors and transmits data to the system core processing unit.

3. The foggy weather warning auxiliary reminder system according to claim 1, characterized in that: The early warning judgment module includes an early warning standard unit, an intelligent judgment unit and a decision-making unit, presets multi-level early warning standards, and automatically judges and makes early warning decisions based on real-time data and standards.

4. The foggy weather warning auxiliary reminder system according to claim 1, characterized in that: The historical data storage module includes a data storage unit, a data query unit, a data analysis and comparison unit, and a data mining unit, which classify and store data, provide query, analyze and compare data, and mine potential rules.

5. A foggy weather warning auxiliary reminder system according to claims 1-5, characterized in that: The operation process of the foggy weather warning auxiliary reminder system software is as follows: (1) Start Start process, indicating that the system is started. (2) Obtaining weather warning information Action: Call history_warning_signal or living_warning_signal (depending on whether historical or real-time data is needed). Input: User name, password, time range (optional), administrative area code (such as Changfeng County). Output: Warning information list (SignalInfo object array). (3) Screening of heavy fog warnings Action: Traverse the warning information list and filter out warnings with the signal name "heavy fog". Output: heavy fog warning information list. (4) Obtaining haze data Action: Call the GetFogDaasDatas method to obtain the smog data of the specified area (such as Changfeng County). Input: Area code or name. Output: haze data list, including visibility and other information. (5) Comparison of warning levels Action: For each piece of haze data, compare the warning level corresponding to its visibility with the current heavy fog warning level. Logic: Use compare_levels function to compare warning levels. Output: Decision on whether to issue or change an alert. (6) Generate prompt information Action: Generate prompt information based on the comparison results to remind the duty officer to issue a warning signal or update the visibility, warning level, warning content, etc. of the existing warning signal. (7) Determine whether to send a text message Logic: If new prompt information is generated, continue; otherwise, end the process. (8) Send SMS Action: Call the send_message function to send a text message through the serial port. Input: receiving mobile phone number, SMS content (including warning information). Output: Information returned by the GSM module (such as sending status). (9) Recording logs Action: Record the generated warning information, the results of sending SMS, etc. into the log file. (10) End Ending the process means that the system has completed the task of providing auxiliary reminder for heavy fog weather warning.

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