Urban emergency command and dispatch system based on Internet of Things perception

Abstract

The embodiment of the invention provides a city emergency command and dispatch system based on Internet of Things perception, which comprises a data acquisition module, a data processing and analysis module, an emergency resource management module, a command decision module, a communication dispatch module and a visual display module, the data acquisition module acquires and preprocesses multi-source heterogeneous data through various sensors and an intelligent terminal; the data processing and analysis module analyzes data by using technologies such as big data, predicts the trend of an emergency, identifies risks, and generates a report and an early warning; the command decision-making module generates and optimizes a command decision-making scheme according to the early warning and the pre-arranged plan; the emergency resource management module manages resources and deploys the resources according to a scheme; the communication scheduling module realizes high-speed transmission and equipment interconnection based on various communication technologies; and the visual display module is used for visually displaying related information by virtue of a GIS (Geographic Information System) and a three-dimensional modeling technology. Through cooperation of all the modules, the urban emergency processing capacity can be improved.

Description

Technical Field

[0001] This document relates to the field of emergency command technology, and in particular to an urban emergency command and dispatch system based on Internet of Things perception. Background Art

[0002] In the current urban development process, various emergencies such as natural disasters, public health incidents, accidents and disasters occur frequently, posing a serious threat to the safety and stability of the city and the lives and property of residents. The traditional urban emergency command and dispatch system gradually exposed many deficiencies in the face of complex and changeable emergency situations.

[0003] Emergency command includes crisis management systems, command and control centers, and various communication and information technology tools, with the goal of achieving rapid and effective decision-making and resource dispatch in emergency situations. Emergency command technology involves multiple components, such as data collection, real-time monitoring, resource allocation, and automation of command operations, which work together to ensure an orderly response in disasters, public safety incidents, or crises, emphasizing cross-departmental cooperation and information integration to ensure that all relevant departments can share key information and make a coordinated response.

[0004] Existing emergency command technologies have certain limitations in terms of rapid response and efficient resource allocation. They rely on traditional data processing and analysis methods, resulting in slow response times in extreme situations and insufficient information updates, making it difficult for decision makers to quickly obtain a full picture of the accident. Resource scheduling is static or relies on pre-set protocols, lacking sufficient flexibility to respond to sudden changes, which is particularly evident in natural disasters or large-scale public safety incidents. In terms of information transmission, the inability to effectively handle large data flows leads to communication congestion and information transmission delays, affecting the efficiency and accuracy of on-site command, slowing down response speed, and affecting the success rate of rescue operations at critical moments, increasing risks and potential losses.

[0005] To sum up, these limitations of traditional urban emergency command and dispatch systems urgently require a new technical solution to break through in order to improve the efficiency and effectiveness of urban emergency management and better respond to various emergencies. Summary of the invention

[0006] One or more embodiments of this specification provide a city emergency command and dispatch system based on IoT perception, including: a data acquisition module, a data processing and analysis module, an emergency resource management module, a command decision module, a communication dispatch module, and a visualization display module;

[0007] The data acquisition module is used to collect multi-source heterogeneous data including environmental data, equipment operation status data and personnel real-time location data from the urban environment through various sensors and intelligent terminals, and perform preliminary preprocessing on the collected data;

[0008] The data processing and analysis module is used to: process and analyze the pre-processed data through big data analysis technology, artificial intelligence algorithms and machine learning models, predict the development trend of emergencies, identify potential risk factors, and generate analysis reports and warning information based on the analysis results;

[0009] The command decision module is used to: generate a command suggestion plan based on the early warning information and the emergency plan, dynamically adjust and optimize the content of the command suggestion plan according to the actual situation, and obtain a command decision plan;

[0010] The emergency resource management module is used to manage various emergency resources, obtain the status and location information of resources in real time, and start the resource allocation process according to the command decision plan;

[0011] The communication scheduling module is used to: realize high-speed transmission of voice, video, and data and interconnection of various communication devices based on various communication technologies;

[0012] The visualization display module is used to visualize the analysis report and warning information, command decision-making plan, various emergency resource status information and resource allocation process through charts, maps and three-dimensional scenes based on the geographic information system GIS and three-dimensional modeling technology.

[0013] Furthermore, the sensors and intelligent terminals of the data acquisition module include temperature sensors, humidity sensors, gas sensors, location sensors and video monitoring equipment. The collected environmental data include meteorological information, air quality data and geographical environment parameters; the equipment status data include operating parameters of power equipment, transportation facilities and industrial production equipment; the personnel location data is obtained through GPS, Beidou positioning system or indoor positioning technology;

[0014] The preliminary preprocessing of the collected data includes: cleaning, denoising and calibrating the collected data to remove invalid data and interference information.

[0015] Furthermore, the data processing and analysis module is specifically used for:

[0016] Identify complex event patterns and anomalies through artificial intelligence algorithms;

[0017] Evaluate and predict risks through support vector machines (SVM) or decision trees;

[0018] Through comprehensive analysis of historical data and real-time data, the development trend of emergencies is predicted, potential risks are identified, and analysis reports are generated. The analysis reports include detailed information of the events, scope of impact and risk level, and the warning information is conveyed to relevant personnel through multiple channels such as text messages, system pop-ups or alarms.

[0019] Furthermore, the emergency resource management module is specifically used for:

[0020] The database is used to manage emergency resources and record the detailed attribute information of each type of resource, including: the model, performance parameters, maintenance records, and storage location of fire-fighting equipment; the type, quantity, validity period, and manufacturer of medical supplies; the personnel composition, professional skills, equipment, and response time of the rescue team;

[0021] Real-time tracking of resource status and location is carried out through IoT technology, sensors are used to monitor the status of firefighting equipment, and the location information of rescue teams and material transport vehicles is obtained with the help of positioning systems;

[0022] Intelligent allocation and dynamic adjustment of resources are achieved based on resource demand analysis and optimization algorithms.

[0023] Furthermore, the command decision module is specifically used to:

[0024] According to the standard procedures and disposal plans in the emergency plan library, rapid matching and adjustment are carried out in combination with the type, scale, location and time of the incident;

[0025] During the decision-making process, dynamic adjustment mechanisms such as adaptive control algorithms and feedback regulation mechanisms are used to optimize the decision content based on on-site feedback information and event developments.

[0026] Furthermore, the communication scheduling module integrates multiple communication technologies such as 5G, satellite communication, wired communication, and wireless ad hoc network to achieve high-definition voice transmission, smooth video playback, fast data exchange, and interconnection of various communication devices such as walkie-talkies, telephones, video conferencing terminals, mobile terminals, etc.;

[0027] The communication scheduling module is specifically used to: assign priorities according to the urgency of the event and the importance of the information, adopt priority queues and dynamic priority adjustment algorithms, and give priority to transmitting key information; the communication scheduling module also includes a backup communication link, which automatically switches to the backup communication link when the communication network fails or is congested.

[0028] Furthermore, the visual display module is specifically used for:

[0029] Draw city maps based on GIS technology and mark the locations of emergency resources, incident locations, and dangerous areas on the maps;

[0030] Use 3D modeling technology to construct 3D models of urban buildings, infrastructure and topography;

[0031] In terms of information display, resource distribution and event statistics information are displayed through charts such as bar charts, line charts or pie charts;

[0032] It displays multi-dimensional information in a linked manner. In response to clicking on the event location on the map, detailed information about the location, surrounding resources, and related video surveillance images will automatically pop up. It also supports interactive operations, including map zooming, perspective switching, and information query.

[0033] Furthermore, the system also includes a historical case management module, which is specifically used to:

[0034] Through data collection and collation, a historical case database is constructed, including various types of cases such as natural disasters, accidents and disasters, public health incidents, and social security incidents;

[0035] Use text mining technology to extract key information from historical cases, including the cause of the incident, the handling process, lessons learned, and key factors for success, and organize and manage the cases through case classification, cluster analysis, and other methods;

[0036] Based on the characteristics of current events, similarity matching is carried out with historical cases, and case-based reasoning methods are used to provide reference and reference for command decisions. Historical cases are studied and summarized to improve the historical case database and emergency response knowledge system.

[0037] Furthermore, the system further includes a system security management module, which is specifically used to:

[0038] Use the role-based access control (RBAC) model or the attribute-based access control (ABAC) model to manage user rights, assign corresponding rights to different user roles, and conduct regular audits and updates on rights.

[0039] Furthermore, the system security management module is also used to:

[0040] Use a combination of symmetric and asymmetric encryption to encrypt data transmitted and stored in the system;

[0041] By deploying security equipment, including firewalls, intrusion detection systems IDS or intrusion prevention systems IPS, we can prevent network attacks, and use vulnerability scanning and security patch management measures to ensure the safe and stable operation of the system.

[0042] By adopting the embodiment of the present invention, the acquisition module can quickly collect multi-source heterogeneous data, which can be quickly analyzed by the processing and analysis module. The command decision module can generate solutions in time, and the communication scheduling module ensures high-speed information transmission, which greatly shortens the emergency response time and enables rapid action at the early stage of an emergency. By deeply analyzing data with big data, artificial intelligence and machine learning technologies and combining the experience of the historical case management module, the decisions generated by the command decision module are more scientific and reasonable, and can effectively respond to complex and changeable emergency situations and improve the success rate of handling. The emergency resource management module controls the status and location of resources in real time, and uses intelligent algorithms to accurately allocate resources to avoid idle or wasted resources, ensuring that key resources are quickly in place in an emergency. It integrates multiple With advanced communication technology, the communication dispatch module realizes all-round communication guarantee. Even when the network is damaged or under high load, it can still maintain stable communication between the command center and the site, ensuring accurate transmission of instructions and timely feedback of information. The system security management module builds a solid security line from multiple levels to prevent data leakage and illegal access, effectively ensuring the stable operation of the emergency command and dispatch system at critical moments, and avoiding emergency response delays or errors caused by security issues. The visualization display module presents rich information in an intuitive way, supports multi-dimensional interactive operations, and assists command personnel to quickly grasp the overall situation, make accurate decisions, and improve the efficiency and quality of emergency command. In large-scale natural disaster rescue, they can clearly understand the disaster-stricken areas and resource distribution, and reasonably dispatch rescue forces.

[0043] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate one or more embodiments of this specification 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 recorded in this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0045] Figure 1 A schematic diagram of the composition of a city emergency command and dispatch system based on IoT perception provided in one or more embodiments of this specification;

[0046] Figure 2 A flowchart of a city emergency command and dispatch method based on Internet of Things perception is provided for one or more embodiments of this specification. DETAILED DESCRIPTION

[0047] In order to enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the following will be combined with the drawings in one or more embodiments of this specification to clearly and completely describe the technical solutions in one or more embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on one or more embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this document.

[0048] System Example

[0049] According to an embodiment of the present invention, a city emergency command and dispatch system based on IoT perception is provided. Figure 1 A schematic diagram of the composition of a city emergency command and dispatch system based on IoT perception provided in one or more embodiments of this specification, such as Figure 1 As shown, the urban emergency command and dispatch system based on IoT perception according to an embodiment of the present invention specifically includes: a data acquisition module 101, a data processing and analysis module 102, an emergency resource management module 103, a command decision module 104, a communication dispatch module 105 and a visualization display module 106.

[0050] The data acquisition module 101 is used to collect multi-source heterogeneous data including environmental data, equipment operation status data and personnel real-time location data from the urban environment through various sensors and intelligent terminals, and perform preliminary preprocessing on the collected data.

[0051] The sensors and intelligent terminals of the data acquisition module include temperature sensors, humidity sensors, gas sensors, position sensors and video monitoring equipment. The collected environmental data include meteorological information, air quality data and geographical environment parameters: temperature and humidity sensors are responsible for collecting meteorological information and providing data for meteorological monitoring and analysis. Gas sensors focus on detecting air quality data to assist in urban air quality assessment. Position sensors combine relevant technologies to obtain geographical environment parameters, covering geographical location, topography, etc., to provide support for urban planning and environmental research. Video monitoring equipment extracts environmental feature information through image recognition technology; equipment status data includes operating parameters of power equipment, transportation facilities, and industrial production equipment: sensors or monitoring devices are installed on power equipment, transportation facilities, and industrial production equipment to collect operating parameters in real time. These parameters can reflect the operating status of the equipment in real time, help to promptly discover hidden dangers of equipment failures, ensure the normal operation of the equipment, and thus ensure the stable operation of key urban infrastructure; personnel location data is obtained through GPS, Beidou positioning system or indoor positioning technology: outdoors, personnel carry devices that support GPS or Beidou positioning system and receive satellite signals in real time to determine their location; indoors, indoor positioning systems based on Bluetooth, Wi-Fi and other technologies are used to accurately locate personnel positions;

[0052] The preliminary preprocessing of the collected data includes: cleaning, denoising and calibrating the collected data to remove invalid data and interference information. The collected data is screened according to the set threshold range and logical rules; the rate of change of the equipment operating parameters is monitored, and if the change is abnormal, the corresponding data is removed to ensure the authenticity and reliability of the data; digital signal processing technology and filtering algorithms are used to remove noise interference in the data, and for the wind speed data in the meteorological information, a low-pass filter is used to remove high-frequency noise to make the data smoother and more accurate; for the data collected by the gas sensor, an adaptive filtering algorithm is used to automatically adjust the filter parameters according to the statistical characteristics of the data to improve the accuracy of the data; the collected data is calibrated by comparing with standard data or reference equipment; the personnel location data is compared and calibrated with the precise geographic location information to improve the positioning accuracy and ensure the accuracy and availability of the data.

[0053] The data processing and analysis module 102 is used to: process and analyze the pre-processed data through big data analysis technology, artificial intelligence algorithms and machine learning models, predict the development trend of emergencies, identify potential risk factors, and generate analysis reports and warning information based on the analysis results.

[0054] The data processing and analysis module is specifically used to: identify complex event patterns and abnormal situations through artificial intelligence algorithms. For example, by analyzing data such as meteorological information, traffic flow, and gathering of people, it is determined whether there is a pattern that may cause large-scale traffic congestion or public safety incidents, or the operating parameters of power equipment suddenly exceed the normal range, and the environmental monitoring data fluctuates abnormally, etc., to provide support for timely discovery of potential problems. Risks are evaluated and predicted through support vector machines (SVMs) or decision trees. Support vector machines (SVMs) separate data of different categories by finding an optimal classification hyperplane, thereby classifying and evaluating risks. Decision tree algorithms classify and predict according to the characteristics of data by constructing a tree structure. SVM and decision tree algorithms quantitatively evaluate the risks of various events based on historical data and real-time data. For example, in emergency management scenarios, by analyzing information such as the location, time, type, and surrounding environment of the accident, the risk level of casualties, property losses, etc. that may be caused by the accident is predicted, providing a basis for formulating response strategies. Through comprehensive analysis of historical data and real-time data, the development trend of emergencies is predicted, potential risks are identified, and analysis reports are generated. The analysis reports include the details of the incident, the scope of impact, and the risk level. The warning information is conveyed to relevant personnel through multiple channels such as text messages, system pop-ups, or alarms. Through data analysis of similar past events, combined with the real-time progress of current events, time series analysis, machine learning and other methods are used to predict the possible development direction of the event, changes in the scope of impact, etc. At the same time, a detailed analysis report is generated based on the analysis results. The report content includes the details of the event, such as the cause, process, and current status of the event; the scope of impact, such as the geographical area affected by the event, the personnel and facilities involved, etc.; the risk level, through quantitative assessment to determine the risk level of the event, the warning information obtained from the analysis is conveyed to relevant personnel through multiple channels.

[0055] The emergency resource management module 103 is used to manage various emergency resources, obtain the status and location information of resources in real time, and start the resource allocation process according to the command decision plan.

[0056] The emergency resource management module 103 is specifically used for:

[0057] The database is used to implement refined management of emergency resources and to record the attribute information of each type of resource in detail. For fire-fighting equipment, its model, performance parameters, maintenance records and storage location are accurately recorded to facilitate the rapid identification of applicable fire-fighting equipment and its location when fire and other accidents occur; medical supplies are recorded in terms of type, quantity, validity period and manufacturer, etc., to ensure the safety and sufficient supply of medical rescue supplies; the personnel composition, professional skills, equipment and response time of the rescue team are also recorded in detail, providing a solid data foundation for the reasonable arrangement of rescue forces;

[0058] The Internet of Things technology is used to track the status and location of resources in real time. Sensors are used to monitor the status of firefighting equipment, such as whether the equipment is operating normally and whether maintenance is required. The positioning system is used to obtain the location information of rescue teams and material transport vehicles, ensuring that managers can grasp the dynamics of resources at any time and provide accurate basis for emergency decision-making.

[0059] Intelligent allocation and dynamic adjustment of resources are achieved based on resource demand analysis and optimization algorithms. When an emergency occurs, the resource demand analysis is performed based on factors such as the type and scale of the event to accurately determine the type and quantity of resources required. At the same time, the optimization algorithm is used to select the optimal solution from a variety of resource allocation schemes to achieve efficient use of resources. For example, in large-scale disaster relief, the allocation of medical supplies and rescue teams is dynamically adjusted according to the affected area and the progress of the rescue.

[0060] The command decision module 104 is used to generate a command suggestion plan according to the early warning information and the emergency plan, dynamically adjust and optimize the content of the command suggestion plan according to the actual situation, and obtain a command decision plan.

[0061] The command decision module is specifically used for:

[0062] According to the standard processes and disposal plans in the emergency plan library, rapid matching and adjustment are carried out in combination with the type, scale, location and time of the event; for example, for different types of natural disasters (earthquakes, floods, etc.) and accident disasters (traffic accidents, industrial accidents, etc.), preliminary command recommendation plans are generated according to their characteristics and on-site conditions.

[0063] In the process of decision-making and execution, according to the feedback information from the scene and the development and changes of events, dynamic adjustment mechanisms such as adaptive control algorithms and feedback adjustment mechanisms are used to optimize the content of decisions. If it is found that the disaster area has expanded or new dangerous situations have emerged during the rescue process, the rescue strategy and resource allocation will be adjusted in time to ensure that the command decision is always in line with actual needs.

[0064] The communication scheduling module 105 is used to: based on multiple communication technologies, realize high-speed transmission of voice, video, and data and interconnection of various communication devices, ensure smooth emergency communication, and ensure timely and accurate transmission of information between all participants.

[0065] The communication scheduling module integrates multiple communication technologies such as 5G, satellite communication, wired communication, and wireless ad hoc network to achieve high-definition voice transmission, smooth video playback, fast data exchange, and interconnection of various communication devices such as walkie-talkies, telephones, video conferencing terminals, and mobile terminals to meet communication needs in different scenarios. For example, in remote areas or when the communication network is damaged, satellite communication can be used to maintain contact.

[0066] The communication scheduling module is specifically used to: assign priorities according to the urgency of the event and the importance of the information, use priority queues and dynamic priority adjustment algorithms to give priority to the transmission of key information; in major disaster rescue, important information such as life rescue and dangerous area conditions will be transmitted first to ensure that the command decision-making level can obtain key intelligence in a timely manner.

[0067] The communication scheduling module also includes a backup communication link. When the communication network fails or is congested, it automatically switches to the backup communication link to ensure the continuity of communication. For example, when the 5G network is damaged by a disaster, it automatically switches to backup communication methods such as satellite communication or wireless ad hoc network.

[0068] The visualization display module 106 is used to visualize the analysis report and warning information, command decision-making plan, various emergency resource status information and resource allocation process through charts, maps and three-dimensional scenes based on the geographic information system GIS and three-dimensional modeling technology, so as to provide decision makers with intuitive and comprehensive information presentation and assist them in making scientific decisions.

[0069] The visual display module is specifically used for:

[0070] Based on GIS technology, city maps are drawn, and the locations of emergency resources, incident locations, and dangerous areas are marked on the maps. Decision makers can use the maps to intuitively understand the relationship between resource distribution and the location of the incident site, and quickly plan rescue routes and resource allocation plans.

[0071] 3D modeling technology is used to build 3D models of urban buildings, infrastructure and topography to provide a more realistic and intuitive display of emergency scenarios. When simulating disaster scenarios or planning rescue operations, the impact of environmental factors on rescue can be more accurately assessed.

[0072] In terms of information display, resource distribution and event statistics can be displayed through charts such as bar charts, line charts or pie charts to make the data more intuitive and easy to understand. For example, a bar chart can be used to display the number of emergency supplies reserves in different regions, and a line chart can be used to reflect the trend of related data changes during the development of an event.

[0073] The multi-dimensional information is displayed in a linked manner. When you click on the event location on the map, detailed information about the location, surrounding resources, and related video surveillance images will automatically pop up, making it easier for decision makers to fully understand the on-site situation. At the same time, users can perform interactive operations such as map zooming, perspective switching, and information query to obtain more detailed and accurate information.

[0074] The system further includes a historical case management module, which is specifically used for:

[0075] Through data collection and collation, we have collected a wide range of cases of natural disasters, accidents, public health incidents, social security incidents, etc., and built a historical case database. These cases cover emergency events of different scales and types, including natural disasters, accidents, public health incidents, social security incidents and other types, providing rich materials for subsequent analysis and reference.

[0076] Text mining technology is used to extract key information from historical cases, including the cause of the incident, the handling process, lessons learned, and key factors for success. Cases are organized and managed through case classification, cluster analysis, and other methods to facilitate rapid retrieval and query of related cases. For example, earthquake-related cases are grouped into one category, and then further subdivided according to factors such as the size of the earthquake and the area where it occurred.

[0077] According to the characteristics of the current event and the historical cases, the similarity is matched, and the case-based reasoning method is used to provide reference and reference for command decision-making. When facing new emergency events, the system can quickly find similar historical cases, refer to their handling experience, and formulate more reasonable command decision-making plans. Learn and summarize historical cases, improve the historical case database and emergency handling knowledge system, and enhance emergency management capabilities.

[0078] The system further includes a system security management module, which is specifically used for:

[0079] Use the role-based access control (RBAC) model or the attribute-based access control (ABAC) model to manage user rights. According to the user's role in emergency management, such as decision maker, rescuer, information entry clerk, etc., assign corresponding rights to ensure that only authorized users can access and operate related functions and data. At the same time, perform regular rights audits and updates to promptly discover and correct unreasonable rights allocation and ensure system data security.

[0080] The system security management module is also used for:

[0081] The system uses a combination of symmetric and asymmetric encryption to encrypt data transmitted and stored in the system. During the data transmission process, such as emergency resource information, command decision instructions, etc., encryption technology is used to prevent data from being stolen or tampered with. For key data stored in the system, encrypted storage is also used to ensure data confidentiality and integrity.

[0082] By deploying security equipment, including firewalls, intrusion detection systems IDS or intrusion prevention systems IPS, network attacks can be prevented. Firewalls can prevent illegal external network access, and IDS and IPS can monitor network traffic in real time, promptly discover and prevent potential attacks. At the same time, vulnerability scanning and security patch management measures are used to promptly discover and repair system vulnerabilities, ensure the safe and stable operation of the system, and ensure the security and reliability of the emergency management system in the face of complex network environments.

[0083] The specific implementation method of the urban emergency command and dispatch system based on IoT perception is as follows: Figure 2 As shown:

[0084] S1. Collect multi-source heterogeneous data including environmental data, equipment operation status data and personnel real-time location data from the urban environment through the data acquisition module, and perform preliminary preprocessing on the collected data.

[0085] S2. Through big data analysis technology, artificial intelligence algorithms and machine learning models, the pre-processed data is processed and analyzed to predict the development trend of emergencies, identify potential risk factors, and generate analysis reports and early warning information based on the analysis results.

[0086] S3. Generate a command suggestion plan based on the early warning information and emergency plan, dynamically adjust and optimize the content of the command suggestion plan according to the actual situation, and obtain a command decision plan;

[0087] S4. Manage various emergency resources, obtain the status and location information of resources in real time, and start the resource allocation process according to the command decision plan;

[0088] S5. Based on the Geographic Information System (GIS) and three-dimensional modeling technology, the analysis report and warning information, command decision-making plan, various emergency resource status information and resource allocation process are visualized through charts, maps and three-dimensional scenes.

[0089] The beneficial effects of the present invention are as follows:

[0090] By adopting the embodiment of the present invention, the acquisition module can quickly collect multi-source heterogeneous data, which can be quickly analyzed by the processing and analysis module. The command decision module can generate solutions in time, and the communication scheduling module ensures high-speed information transmission, which greatly shortens the emergency response time and enables rapid action at the early stage of an emergency. By deeply analyzing data with big data, artificial intelligence and machine learning technologies and combining the experience of the historical case management module, the decisions generated by the command decision module are more scientific and reasonable, and can effectively respond to complex and changeable emergency situations and improve the success rate of handling. The emergency resource management module controls the status and location of resources in real time, and uses intelligent algorithms to accurately allocate resources to avoid idle or wasted resources, ensuring that key resources are quickly in place in an emergency. It integrates a variety of advanced Communication technology, the communication dispatch module realizes all-round communication guarantee. Even when the network is damaged or under high load, it can still maintain stable communication between the command center and the site, ensuring accurate transmission of instructions and timely feedback of information; the system security management module builds a solid security line from multiple levels to prevent data leakage and illegal access, effectively ensuring the stable operation of the emergency command and dispatch system at critical moments, and avoiding emergency response delays or errors caused by security issues; the visualization display module presents rich information in an intuitive way, supports multi-dimensional interactive operations, and assists command personnel to quickly grasp the overall situation and make accurate decisions, thereby improving the efficiency and quality of emergency command. In large-scale natural disaster rescue, it can clearly understand the disaster-stricken areas and resource distribution, and reasonably dispatch rescue forces.

[0091] Finally, 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 aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A city emergency command and dispatch system based on IoT perception, characterized in that: include: Data acquisition module, data processing and analysis module, emergency resource management module, command decision module, communication dispatch module and visualization display module; The data acquisition module is used to collect multi-source heterogeneous data including environmental data, equipment operation status data and personnel real-time location data from the urban environment through various sensors and intelligent terminals, and perform preliminary preprocessing on the collected data; The data processing and analysis module is used to: process and analyze the pre-processed data through big data analysis technology, artificial intelligence algorithms and machine learning models, predict the development trend of emergencies, identify potential risk factors, and generate analysis reports and warning information based on the analysis results; The command decision module is used to: generate a command suggestion plan based on the early warning information and the emergency plan, dynamically adjust and optimize the content of the command suggestion plan according to the actual situation, and obtain a command decision plan; The emergency resource management module is used to manage various emergency resources, obtain the status and location information of resources in real time, and start the resource allocation process according to the command decision plan; The communication scheduling module is used to: realize high-speed transmission of voice, video, and data and interconnection of various communication devices based on various communication technologies; The visualization display module is used to visualize the analysis report and warning information, command decision-making plan, various emergency resource status information and resource allocation process through charts, maps and three-dimensional scenes based on the geographic information system GIS and three-dimensional modeling technology.

2. The urban emergency command and dispatch system based on IoT perception according to claim 1 is characterized in that: The sensors and intelligent terminals of the data acquisition module include temperature sensors, humidity sensors, gas sensors, location sensors and video monitoring equipment. The collected environmental data include meteorological information, air quality data and geographical environment parameters; the equipment status data include operating parameters of power equipment, transportation facilities and industrial production equipment; Personnel location data is obtained through GPS, Beidou positioning system or indoor positioning technology; The preliminary preprocessing of the collected data includes: cleaning, denoising and calibrating the collected data to remove invalid data and interference information.

3. The urban emergency command and dispatch system based on IoT perception according to claim 1 is characterized in that: The data processing and analysis module is specifically used for: Identify complex event patterns and anomalies through artificial intelligence algorithms; Evaluate and predict risks through support vector machines (SVM) or decision trees; Through comprehensive analysis of historical data and real-time data, the development trend of emergencies is predicted, potential risks are identified, and analysis reports are generated. The analysis reports include detailed information of the events, scope of impact and risk level, and the warning information is conveyed to relevant personnel through multiple channels such as text messages, system pop-ups or alarms.

4. The urban emergency command and dispatch system based on IoT perception according to claim 1 is characterized in that: The emergency resource management module is specifically used for: The database is used to manage emergency resources and record the detailed attribute information of each type of resource, including: the model, performance parameters, maintenance records, and storage location of fire-fighting equipment; the type, quantity, validity period, and manufacturer of medical supplies; the personnel composition, professional skills, equipment, and response time of the rescue team; Real-time tracking of resource status and location is carried out through IoT technology, sensors are used to monitor the status of firefighting equipment, and the location information of rescue teams and material transport vehicles is obtained with the help of positioning systems; Intelligent allocation and dynamic adjustment of resources are achieved based on resource demand analysis and optimization algorithms.

5. The urban emergency command and dispatch system based on IoT perception according to claim 1 is characterized in that: The command decision module is specifically used for: According to the standard procedures and disposal plans in the emergency plan library, rapid matching and adjustment are carried out in combination with the type, scale, location and time of the incident; During the decision-making process, dynamic adjustment mechanisms such as adaptive control algorithms and feedback regulation mechanisms are used to optimize the decision content based on on-site feedback information and event developments.

6. The urban emergency command and dispatch system based on IoT perception according to claim 1 is characterized in that: The communication scheduling module integrates multiple communication technologies such as 5G, satellite communication, wired communication, and wireless ad hoc network to achieve high-definition voice transmission, smooth video playback, fast data exchange, and interconnection of various communication devices such as walkie-talkies, telephones, video conferencing terminals, mobile terminals, etc. The communication scheduling module is specifically used to: assign priorities according to the urgency of the event and the importance of the information, adopt priority queues and dynamic priority adjustment algorithms, and give priority to transmitting key information; the communication scheduling module also includes a backup communication link, which automatically switches to the backup communication link when the communication network fails or is congested.

7. The urban emergency command and dispatch system based on IoT perception according to claim 1 is characterized in that: The visual display module is specifically used for: Draw city maps based on GIS technology and mark the locations of emergency resources, incident locations, and dangerous areas on the maps; Use 3D modeling technology to construct 3D models of urban buildings, infrastructure and topography; In terms of information display, resource distribution and event statistics information are displayed through charts such as bar charts, line charts or pie charts; It displays multi-dimensional information in a linked manner. In response to clicking on the event location on the map, detailed information about the location, surrounding resources, and related video surveillance images will automatically pop up. It also supports interactive operations, including map zooming, perspective switching, and information query.

8. The urban emergency command and dispatch system based on IoT perception according to claim 1 is characterized in that: The system further includes a historical case management module, which is specifically used for: Through data collection and collation, a historical case database is constructed, including various types of cases such as natural disasters, accidents and disasters, public health incidents, and social security incidents; Use text mining technology to extract key information from historical cases, including the cause of the incident, the handling process, lessons learned, and key factors for success, and organize and manage the cases through case classification, cluster analysis, and other methods; Based on the characteristics of current events, similarity matching is carried out with historical cases, and case-based reasoning methods are used to provide reference and reference for command decisions. Historical cases are studied and summarized to improve the historical case database and emergency response knowledge system.

9. The urban emergency command and dispatch system based on IoT perception according to claim 1 is characterized in that: The system further includes a system security management module, which is specifically used for: Use the role-based access control (RBAC) model or the attribute-based access control (ABAC) model to manage user rights, assign corresponding rights to different user roles, and conduct regular audits and updates on rights.

10. The urban emergency command and dispatch system based on IoT perception according to claim 9 is characterized in that: The system security management module is also used for: Use a combination of symmetric and asymmetric encryption to encrypt data transmitted and stored in the system; By deploying security equipment, including firewalls, intrusion detection systems IDS or intrusion prevention systems IPS, we can prevent network attacks, and use vulnerability scanning and security patch management measures to ensure the safe and stable operation of the system.

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