A method and system for evaluating urban safety risks

Abstract

The present invention discloses a method and system for assessing urban safety risks, and relates to the technical field of safety risk assessment, including collecting urban safety risk information of a certain area through urban Internet of Things devices; an urban safety risk assessment center obtains the urban safety risk information collected by the Internet of Things devices, and compares it with historical data in a database to identify the urban safety risk category; after confirming the urban safety risk category, the detailed information of the risk source is collected through the Internet of Things devices to assess the urban safety risk level and send a notification. The beneficial effects of the present invention are: the present invention uses the Internet of Things devices to monitor the urban environment in real time, collect various types of safety risk information, and compare and analyze with historical data in the database to identify the risk type and assess the risk level. For risks of different levels, the assessment center can issue early warning notifications in a timely manner and initiate emergency response plans, thereby reducing the impact of risks on cities and residents.

Description

Technical Field

[0001] The present invention relates to the technical field of safety risk assessment, and in particular to a method and system for evaluating urban safety risks. Background Art

[0002] In modern society, urban safety risk assessment is a particularly important issue. As an important place for human life, work and entertainment, the safety of cities directly affects people's quality of life and social stability. With the rapid development of information technology and Internet of Things technology, we have the ability to connect more and more devices to the network and use these devices to collect a large amount of data. These data include various types of risk factors, such as traffic flow, air quality, public safety incidents, etc. They can all provide valuable information for urban safety risk assessment. Existing urban safety risk assessment technology is mainly based on manual analysis and judgment of the collected risk information. This method is inefficient and easily affected by human factors. The accuracy and timeliness of the assessment results are difficult to guarantee. 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 existing urban safety risk assessment methods, the present invention is proposed.

[0005] Therefore, the problem to be solved by the present invention is that the existing urban safety risk assessment technology is mainly based on manual analysis and judgment of the collected risk information. This method is inefficient and easily affected by human factors, and the accuracy and timeliness of the assessment results are difficult to guarantee.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: a method for assessing urban safety risks, comprising collecting urban safety risk information of a certain area through urban Internet of Things devices;

[0007] The Urban Security Risk Assessment Center obtains urban security risk information collected by IoT devices and compares it with historical data in the database to identify urban security risk categories;

[0008] After confirming the city security risk category, collect detailed information on risk sources through IoT devices to assess the city security risk level and send notifications;

[0009] Implement urban safety risk management measures based on the notification issued and record the data in the historical database.

[0010] As a preferred solution of the urban safety risk assessment method described in the present invention, the urban Internet of Things devices include sensors, surveillance cameras, drones, mobile communication devices, and other devices that can collect, transmit and process information related to urban safety risks, including smart vehicles, smart home devices, smart transportation equipment, and portable devices equipped with global positioning systems, wireless communication technologies, and data collection and processing functions.

[0011] As a preferred solution of the urban safety risk assessment method of the present invention, the urban safety risk assessment center obtains urban safety risk information collected by the Internet of Things device and compares it with historical data in the database to identify the urban safety risk category, including the following three situations:

[0012] If the safety risk information collected by the Urban Safety Risk Assessment Center is compared with historical data and identified as the same, the safety risk level will be assessed;

[0013] If the safety risk information collected by the Urban Safety Risk Assessment Center is not identical to all the data in the historical database, the safety risk information will be fully recorded in the database and marked as a new category, and the staff will be notified to conduct inspection and confirmation;

[0014] If the safety risk information collected by the Urban Safety Risk Assessment Center fails to be identified by comparison with the historical data in the database, the staff will be notified to manually identify the category of safety risk information.

[0015] As a preferred solution of the urban safety risk assessment method of the present invention, the assessment of the urban safety risk level includes the following steps:

[0016] After the IoT device collects detailed information about the risk source, it confirms the risk attribute value Q through historical data and collected information in the database;

[0017] After confirming the attribute value Q, the initial state difference ΔZ(0) is obtained and the instantaneous state difference ΔZ(t) is calculated. The Lyapunov exponent is calculated by the following formula:

[0018] lyapunov index=lim(t->∞)(1 / t)*ln(|ΔZ(t) / ΔZ(0)|)

[0019] Where t is time, |ΔZ(t) / ΔZ(0)| represents the ratio of the absolute values ​​of the state difference;

[0020] After calculating the Lyapunov index, the Lyapunov index and the risk attribute value Q are substituted into the following formula to calculate the risk value S;

[0021] S = ∑(attribute value Q*Lyapunov index)

[0022] Where S is the risk value calculated by the risk source, and the level of the risk source is judged and divided according to the value of the risk value S:

[0023] If the risk value S is lower than 1, the city risk source is judged to be in a low-risk state. The City Safety Risk Assessment Center continues to collect risk source information through IoT devices for monitoring and informs staff of the risk source status.

[0024] If the risk value S is between 1 and 2, the city risk source is judged to be in a medium-risk state. The City Safety Risk Assessment Center sends detailed information and warning notices of the risk source to staff and risk elimination personnel, and sends warning notices to people around the risk source;

[0025] If the risk value S is higher than 2, the city risk source is judged to be in a high-risk state. The Urban Safety Risk Assessment Center sends detailed information and danger notifications of the hazard source to the staff and risk elimination personnel, sends evacuation notices to people in the area around the risk source, and simultaneously records the hazard source information and treatment measures in the historical database.

[0026] As a preferred solution of the urban safety risk assessment method described in the present invention, the urban safety risk assessment center will implement real-time dynamic adjustments during the process of comparing and identifying the acquired risk source information with the historical data in the database. As the real-time risk information collected by the Internet of Things devices is continuously updated, the urban safety risk assessment center will update and adjust the risk categories in real time to ensure accurate assessment and rapid response to the current risk situation.

[0027] As a preferred solution of the urban safety risk assessment method described in the present invention, the urban safety risk sources are monitored in real time through Internet of Things devices, and artificial intelligence algorithms are used to perform real-time analysis and preprocessing on the collected data, including sorting, filtering and compressing the collected risk information, so as to improve the data processing speed and efficiency, reduce the pressure of data storage and transmission, and enable the urban safety risk assessment center to identify and process risk source information more quickly.

[0028] As a preferred solution of the urban safety risk assessment method described in the present invention, after confirming the urban safety risk level, the urban safety risk assessment center will automatically trigger the corresponding emergency response plan according to the risk level, including initiating emergency resource allocation, organizing emergency rescue teams, and implementing risk source containment measures. At the same time, the urban safety risk assessment center will also evaluate and feedback the results and effects of the emergency response to continuously optimize and improve the emergency response strategies and measures.

[0029] In a second aspect, the present invention provides a city safety risk assessment system, which includes: an acquisition module for collecting city safety risk information in real time and transmitting the collected information to a city safety risk assessment center for analysis;

[0030] An identification module is used to compare the collected urban safety risk information with the data in the historical urban safety risk information database to identify the risk category;

[0031] The analysis module is used to analyze and evaluate the city's safety risk level based on the acquired detailed information after the risk category is determined, and issue a notification or warning based on the evaluation results after the evaluation is completed;

[0032] The early warning module is used to issue early warning evacuation notices to people in the area where urban safety risks occur, and to issue early warning notices of safety risk category levels to people who have eliminated safety risks, based on the signals sent by the urban safety risk assessment center and the preset notification rules, and to store safety risk information and processing methods in a historical database.

[0033] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and wherein the processor implements the steps of the underground water supply pipeline data supervision method as described above when executing the computer program.

[0034] A computer-readable storage medium having a computer program stored thereon, characterized in that when the computer program is executed by a processor, the steps of the underground water supply pipeline data supervision method as described above are implemented.

[0035] The beneficial effects of the present invention are as follows: the present invention utilizes Internet of Things devices to monitor the urban environment in real time, collects various types of security risk information, identifies risk types and evaluates risk levels by comparing and analyzing historical data in a database, and for different levels of risks, the assessment center can issue early warning notifications in a timely manner and initiate emergency response plans, thereby reducing the impact of risks on cities and residents. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. 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 these drawings without creative labor. Among them:

[0037] Figure 1 Flow chart of the urban safety risk assessment method.

[0038] Figure 2 This is a flow chart of the urban safety risk assessment system. DETAILED DESCRIPTION

[0039] 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 accompanying drawings.

[0040] 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.

[0041] 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.

[0042] Example 1

[0043] Reference Figure 1 , which is the first embodiment of the present invention, and provides a city safety risk assessment method, the city safety risk assessment method comprising:

[0044] S1. Collect urban security risk information of a certain area through urban IoT devices;

[0045] It should be noted that the urban Internet of Things devices include sensors, surveillance cameras, drones, mobile communication devices, and other devices that can collect, transmit and process information related to urban safety risks, including smart vehicles, smart home devices, smart transportation equipment, and portable devices equipped with global positioning systems (GPS), wireless communication technologies (such as Wi-Fi, 5G, etc.), and data collection and processing functions.

[0046] S2. The Urban Security Risk Assessment Center obtains urban security risk information collected by IoT devices and compares it with historical data in the database to identify urban security risk categories;

[0047] It should be noted that the urban safety risk assessment center obtains urban safety risk information collected by IoT devices and compares it with historical data in the database to identify urban safety risk categories, including the following three situations:

[0048] If the safety risk information collected by the Urban Safety Risk Assessment Center is compared with historical data and identified as the same, the safety risk level will be assessed;

[0049] If the safety risk information collected by the Urban Safety Risk Assessment Center is not identical to all the data in the historical database, the safety risk information will be fully recorded in the database and marked as a new category, and the staff will be notified to conduct inspection and confirmation;

[0050] If the safety risk information collected by the Urban Safety Risk Assessment Center fails to be identified by comparison with the historical data in the database, the staff will be notified to manually identify the category of safety risk information.

[0051] It should also be noted that the Urban Safety Risk Assessment Center will implement real-time dynamic adjustments during the process of comparing and identifying the acquired risk source information with the historical data in the database. As the real-time risk information collected by IoT devices is continuously updated, the Urban Safety Risk Assessment Center will update and adjust the risk categories in real time to ensure accurate assessment and rapid response to current risk conditions.

[0052] It should also be noted that the real-time monitoring of urban safety risk sources is carried out through IoT devices, and artificial intelligence algorithms are used to conduct real-time analysis and pre-processing of the collected data, including sorting, filtering and compressing the collected risk information, so as to improve the data processing speed and efficiency, reduce the pressure of data storage and transmission, and enable the Urban Safety Risk Assessment Center to identify and process risk source information more quickly.

[0053] S3. After confirming the city security risk category, collect detailed information on risk sources through IoT devices to assess the city security risk level and send a notification;

[0054] It should be noted that the assessment of the urban safety risk level includes the following steps:

[0055] After the IoT device collects detailed information about the risk source, it confirms the risk attribute value Q through historical data and collected information in the database;

[0056] After confirming the attribute value Q, the initial state difference ΔZ(0) is obtained and the instantaneous state difference ΔZ(t) is calculated. The Lyapunov exponent is calculated by the following formula:

[0057] lyapunov index=lim(t->∞)(1 / t)*ln(|ΔZ(t) / ΔZ(0)|)

[0058] Where t is time, |ΔZ(t) / ΔZ(0)| represents the ratio of the absolute values ​​of the state difference;

[0059] After calculating the Lyapunov index, the Lyapunov index and the risk attribute value Q are substituted into the following formula to calculate the risk value S;

[0060] S = ∑(attribute value Q*Lyapunov index)

[0061] Where S is the risk value calculated by the risk source, and the level of the risk source is judged and divided according to the value of the risk value S:

[0062] If the risk value S is lower than 1, the city risk source is judged to be in a low-risk state. The City Safety Risk Assessment Center continues to collect risk source information through IoT devices for monitoring and informs staff of the risk source status.

[0063] If the risk value is between 1 and 2, the city risk source is judged to be in a medium-risk state. The City Safety Risk Assessment Center sends detailed information and warning notices of the risk source to staff and risk elimination personnel, and sends warning notices to people around the risk source;

[0064] If the risk value is higher than 2, the city risk source is judged to be in a high-risk state. The Urban Safety Risk Assessment Center sends detailed information and danger notifications of the hazard source to staff and risk elimination personnel, sends evacuation notices to people in the area around the risk source, and simultaneously records the hazard source information and treatment measures in the historical database.

[0065] S4. Implement urban safety risk treatment measures according to the notification issued and record the data in the historical database;

[0066] It should be noted that after confirming the city’s safety risk level, the City Safety Risk Assessment Center will automatically trigger the corresponding emergency response plan based on the risk level, including initiating emergency resource allocation, organizing emergency rescue teams, and implementing risk source containment measures. At the same time, the City Safety Risk Assessment Center will also evaluate and provide feedback on the results and effects of the emergency response in order to continuously optimize and improve emergency response strategies and measures.

[0067] Example 2

[0068] Reference Figure 2 , which is the second embodiment of the present invention, is different from the previous embodiment in that it provides a city safety risk assessment system, including: an acquisition module, an identification module, an analysis module and an early warning module.

[0069] The acquisition module is used to collect urban safety risk information in real time and transmit the collected information to the urban safety risk assessment center for analysis;

[0070] An identification module is used to compare the collected urban safety risk information with the data in the historical urban safety risk information database to identify the risk category;

[0071] The analysis module is used to analyze and evaluate the city's safety risk level based on the acquired detailed information after the risk category is determined, and issue a notification or warning based on the evaluation results after the evaluation is completed;

[0072] The early warning module is used to issue early warning evacuation notices to people in the area where urban safety risks occur, and to issue early warning notices of safety risk category levels to people who have eliminated safety risks, based on the signals sent by the urban safety risk assessment center and the preset notification rules, and to store safety risk information and processing methods in a historical database.

[0073] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0074] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0075] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0076] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiment, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0077] Example 3

[0078] This is the third embodiment of the present invention. This embodiment provides a city safety risk assessment method. In order to verify the beneficial effects of the present invention, experiments were conducted to demonstrate that three cities were selected for the method of this embodiment under a preset equivalent experimental environment. The information obtained is the risk information of the city at the beginning and end of a certain month, as shown in the following table.

[0079] Urban Risk Information Assessment Form

[0080] initial Finish Attribute ValueQ ΔZ(0) ΔZ(t) t S City 1 6 15 15 6 9 30 0.27 City 2 3 21 21 3 18 30 2.42 City 3 11 32 32 11 21 30 1.60

[0081] According to the above table, it can be determined that when the city risk value S is less than 1, the increase in urban safety risk accidents is low, and the city is in a low-risk state; when the city risk value S is between 1 and 2, the increase in urban safety risk accidents is medium, and the city is in a medium-risk state; when the city risk value S is higher than 2, the increase in urban safety risk accidents is high, and the city is in a high-risk state, which meets the judgment threshold proposed by this method, thereby demonstrating the judgment method proposed by the present invention.

[0082] 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 method for assessing urban safety risks, characterized in that: include, Collect urban security risk information in a certain area through urban IoT devices; The Urban Security Risk Assessment Center obtains urban security risk information collected by IoT devices and compares it with historical data in the database to identify urban security risk categories; After confirming the city security risk category, collect detailed information on risk sources through IoT devices to assess the city security risk level and send notifications; Implement urban safety risk treatment measures according to the notification issued and record the data in the historical database; The urban IoT devices include sensors, surveillance cameras, drones, mobile communication devices, and other devices that can collect, transmit and process information related to urban safety risks, including smart vehicles, smart home devices, smart transportation devices, and portable devices equipped with global positioning systems, wireless communication technologies, and data collection and processing functions; The urban safety risk assessment center obtains urban safety risk information collected by IoT devices and compares it with historical data in the database to identify urban safety risk categories, including the following three situations: If the safety risk information collected by the Urban Safety Risk Assessment Center is compared with historical data and identified as the same, the safety risk level will be assessed; If the safety risk information collected by the Urban Safety Risk Assessment Center is not identical to all the data in the historical database, the safety risk information will be fully recorded in the database and marked as a new category, and the staff will be notified to conduct inspection and confirmation; If the safety risk information collected by the Urban Safety Risk Assessment Center fails to be compared with the historical data in the database, the staff will be notified to manually identify the category of safety risk information; The assessment of the urban safety risk level includes the following steps: After the IoT device collects detailed information about the risk source, it confirms the risk attribute value Q through historical data and collected information in the database; After confirming the attribute value Q, the initial state difference ΔZ(0) is obtained and the instantaneous state difference ΔZ(t) is calculated. The Lyapunov exponent is calculated by the following formula: Lyapunov index=lim(t->∞)(1 / t)*ln(|ΔZ(t) / ΔZ(0)|) Where t is time, |ΔZ(t) / ΔZ(0)| represents the ratio of the absolute values ​​of the state difference; After calculating the Lyapunov index, the Lyapunov index and the risk attribute value Q are substituted into the following formula to calculate the risk value S; S = ∑(attribute value Q*Lyapunov index) Where S is the risk value calculated by the risk source, and the level of the risk source is judged and divided according to the value of the risk value S: If the risk value S is lower than 1, the city risk source is judged to be in a low-risk state. The City Safety Risk Assessment Center continues to collect risk source information through IoT devices for monitoring and informs staff of the risk source status. If the risk value S is between 1 and 2, the city risk source is judged to be in a medium-risk state. The City Safety Risk Assessment Center sends detailed information and warning notices of the risk source to staff and risk elimination personnel, and sends warning notices to people around the risk source; If the risk value S is higher than 2, the city risk source is judged to be in a high-risk state. The Urban Safety Risk Assessment Center sends detailed information and danger notifications of the hazard source to the staff and risk elimination personnel, sends evacuation notices to people in the area around the risk source, and simultaneously records the hazard source information and treatment measures in the historical database.

2. The urban safety risk assessment method according to claim 1, characterized in that: The Urban Safety Risk Assessment Center will also implement real-time dynamic adjustments during the process of comparing and identifying the acquired risk source information with the historical data in the database. As the real-time risk information collected by IoT devices is continuously updated, the Urban Safety Risk Assessment Center will update and adjust the risk categories in real time to ensure accurate assessment and rapid response to current risk conditions.

3. The urban safety risk assessment method according to claim 2, characterized in that: The real-time monitoring of urban safety risk sources is carried out through Internet of Things devices, and artificial intelligence algorithms are used to perform real-time analysis and preprocessing of the collected data, including sorting, filtering and compressing the collected risk information, so as to improve the data processing speed and efficiency, reduce the pressure of data storage and transmission, and enable the Urban Safety Risk Assessment Center to identify and process risk source information more quickly.

4. The urban safety risk assessment method according to claim 3, characterized in that: After confirming the city's safety risk level, the City Safety Risk Assessment Center will automatically trigger the corresponding emergency response plan based on the risk level, including initiating emergency resource allocation, organizing emergency rescue teams, and implementing risk source containment measures. At the same time, the City Safety Risk Assessment Center will also evaluate and provide feedback on the results and effects of the emergency response to continuously optimize and improve emergency response strategies and measures.

5. A city safety risk assessment system, based on the city safety risk assessment method according to any one of claims 1 to 4, characterized in that: include, The acquisition module is used to collect urban safety risk information in real time and transmit the collected information to the urban safety risk assessment center for analysis; An identification module is used to compare the collected urban safety risk information with the data in the historical urban safety risk information database to identify the risk category; The analysis module is used to analyze and evaluate the city's safety risk level based on the acquired detailed information after the risk category is determined, and issue a notification or warning based on the evaluation results after the evaluation is completed; The early warning module is used to issue early warning evacuation notices to people in the area where urban safety risks occur, and to issue early warning notices of safety risk category levels to people who have eliminated safety risks, based on the signals sent by the urban safety risk assessment center and the preset notification rules, and to store safety risk information and processing methods in a historical database.

6. A computer device comprising: Memory and processor; The memory stores a computer program, wherein the processor implements the steps of the method according to any one of claims 1 to 4 when executing the computer program.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 4 are implemented.

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