Risk and hidden danger dual prevention and treatment platform and method

Abstract

The invention discloses a risk and hidden danger dual prevention and treatment platform and method, and relates to the technical field of community safety management, and the treatment platform comprises a data integration and display module which is used for constructing a unified database through multi-source data aggregation, building a multi-role interaction portal, achieving the centralized management and two-way circulation of community safety data, and providing a data management and management module; basic data support is provided for each module of the platform; risks and governance data are monitored in real time through the prediction, early warning and optimization module, an early warning mechanism is triggered in time when abnormity is found, early warning information is issued to different roles through multiple channels, community residents and managers can make precaution preparation in advance, and through the synergistic effect of the dual prevention mechanisms, the community safety is improved. According to the invention, community safety accidents can be effectively prevented and reduced, the safety guarantee capability of the community is enhanced, and a safe and stable living environment is created for community residents.

Description

Technical Field

[0001] This invention relates to the field of community safety management technology, specifically to a dual-prevention and management platform and method for risks and hidden dangers. Background Technology

[0002] As the basic unit of residents' lives, the community is an important part of society. Its safety and stability are directly related to the quality of life of residents and the harmonious development of society. Community safety management covers many key areas, including fire safety, which is related to the protection of residents' lives and property in emergencies such as fires; facility safety, which involves the normal operation of various public facilities in the community and avoids safety accidents caused by facility failures; and public health safety, which protects residents' health in terms of infectious disease prevention and control and environmental sanitation. With the acceleration of urbanization and the expansion of community size, the complexity and importance of community safety management are becoming increasingly prominent. How to carry out community safety management work efficiently and comprehensively has become an important issue that urgently needs to be addressed.

[0003] In existing community safety management practices, traditional technologies have many limitations and are unable to meet the complex needs of current community safety management. First, in terms of risk identification, traditional methods mainly rely on manual inspections and periodic checks. This approach is not only inefficient but also easily affected by human factors, leading to untimely and incomplete risk identification, and many potential safety hazards cannot be discovered in a timely manner. Second, there is a lack of a closed-loop mechanism for hazard management. In the traditional model, the discovery, reporting, handling, and acceptance of hazards are often disconnected, and information transmission is not smooth, resulting in a lack of effective tracking and supervision of the hazard management process, making it difficult to ensure that hazards are thoroughly rectified. In addition, traditional technologies also have significant deficiencies in risk prediction and early warning capabilities. Due to the lack of in-depth mining and analysis of historical and real-time data, it is impossible to accurately predict potential safety risks within the community and to take effective preventive measures in advance. These problems make traditional community safety management methods inadequate in dealing with complex and ever-changing safety risks, and unable to comprehensively and effectively protect the lives and safety of community residents. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of existing technologies and provide a dual-prevention and management platform and method for risks and hazards. Driven by data, it integrates and displays various safety-related data within the community through a data integration and display module, constructing a unified safety management database and building a multi-role interactive portal to achieve centralized data management and two-way data flow. The risk intelligent analysis and prediction module uses data mining and intelligent analysis models, combined with preset and customized risk level rules, to intelligently identify, determine the level of, and predict trends of community risks. The hazard management module, based on risk prediction results, collects hazard information through standardized checklist templates, achieving automatic hazard classification and transfer, forming a standardized management chain. The task and governance execution module, through a special and routine task management mechanism combined with risk classification and control strategies, tracks and manages the entire hazard governance process in a closed loop. The prediction, early warning, and optimization module, based on risk prediction and governance execution data, triggers dynamic early warnings for multiple roles and continuously optimizes the parameters and templates of each module through data analysis and review, achieving iterative upgrades to governance capabilities.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a dual prevention and control platform for risks and hidden dangers, the platform comprising: Data integration and display module: By aggregating data from multiple sources, a unified database is built, and a multi-role interactive portal is established to realize centralized management and two-way flow of community security data, providing basic data support for various modules of the platform; Risk intelligent analysis and prediction module: includes risk level configuration unit and risk prediction modeling unit. Based on the data provided by the data integration and display module, it realizes intelligent identification, level determination and trend prediction of community risks through preset and customized risk level rules, combined with data mining and intelligent analysis models. The hazard management module includes a hazard standardization construction unit and a hazard level determination and transfer unit. Combining information reported by residents and risk prediction results, it collects hazard information through standardized checklist templates and realizes automatic hazard classification and transfer based on risk level rules, forming a standardized management link from hazard discovery to disposal. Task and Governance Execution Module: Includes a full-cycle task management unit and a dual-prevention closed-loop governance unit. It receives handling tasks from the hazard management module and achieves full-process tracking and closed-loop management of hazard governance through special and routine task management mechanisms combined with risk classification and control strategies. Prediction, early warning and optimization module: Includes dynamic early warning triggering unit and continuous optimization iteration unit. It triggers dynamic early warning for multiple roles based on risk prediction and governance execution data, and continuously optimizes prediction models, checklist templates and control measures through data analysis and review.

[0006] Furthermore, the data integration and display module gathers various safety-related data within the community, including fire-fighting facility status data, public facility inspection data, health and epidemic prevention data, resident-reported information, and inspection personnel data, constructing a unified safety management database and building a multi-role interactive portal for residents, managers, and property management personnel. The resident end supports hazard reporting and safety knowledge inquiry, the manager end is configured with task assignment and data analysis tools, and the property management end links facility inspection and maintenance records, realizing two-way data interaction and data interoperability between different roles.

[0007] Furthermore, the intelligent risk analysis and prediction module includes a risk level configuration unit and a risk prediction modeling unit. The risk level configuration unit identifies potential risk types within the community, including fire, facility malfunction, and public health risks. Based on the probability of occurrence and the scope of harm, it presets risk level determination rules and supports custom risk levels using formulas through comprehensive risk level assessment for different scenarios. The risk prediction modeling unit integrates data mining technology and intelligent analysis models to construct a risk prediction model. Based on received historical fault data, seasonal change data, and population flow data, it analyzes relevant risks within the community, outputs short-term and long-term risk prediction results, and generates a risk heat map to provide directional guidance for hazard investigation.

[0008] Furthermore, the risk level configuration unit defines the risk level using a formula based on a comprehensive risk level assessment for different scenarios. The formula is as follows: ,in, This is the overall risk level value, ranging from 0 to 10. This is the probability coefficient of risk occurrence, ranging from 0 to 3, reflecting the frequency of similar risks occurring in the past. This is the risk impact range coefficient, with a value ranging from 0 to 3, derived based on community population density and facility distribution. This is a risk urgency coefficient, with a value ranging from 0 to 3. These are the weighting coefficients.

[0009] Furthermore, the risk prediction modeling unit integrates data mining technology and intelligent analysis models to construct a risk prediction model, the formula of which is: ,in, For the future Risk forecast value for the period This represents the current risk level value. For the past Related influencing factors over time periods For the influence factor weights, For historical data backtracking period, This is a scene correction factor.

[0010] Furthermore, the hazard management module includes a hazard standardization construction unit and a hazard level determination and transfer unit. The hazard standardization construction unit designs hazard inspection form templates for different scenarios, including fire exits and elevator facilities, clearly defining the inspection items for each template and supporting the addition and deletion of custom inspection items. Based on the templates, it generates fillable forms for inspection personnel to input hazard information via mobile devices. The forms have built-in photo and location functions to record the location and current status of hazards, and the input information is synchronized to the data integration and display module. The hazard level determination and transfer unit is linked to the judgment rules in the risk intelligent analysis and prediction module, automatically determining the level of the input hazard information. The judgment results include general hazards and major hazards, and the corresponding handling process is triggered based on the judgment results, transferring the hazard information to the task and governance execution module.

[0011] Furthermore, the hazard level determination and the intelligent risk analysis and prediction module associated with the transfer unit automatically determine the level of the entered hazard information using the following determination rules: ,in, This is the final hazard level value, ranging from 0 to 5. The basic level of potential hazards is based on the preset checklist template. The on-site correction factor for potential hazards is calculated based on the photo location information. The associated risk level value is taken from the output of the risk intelligent analysis and prediction module. For risk correlation coefficient, when <2.5 is judged as a general hidden danger, when If the value is ≥2.5, it is considered a major hidden danger.

[0012] Furthermore, the task and governance execution module includes a task full-cycle management unit and a dual-prevention closed-loop governance unit. The task full-cycle management unit manages special tasks and routine tasks. Special tasks are set for specific risk situations, include specific task items, and are associated with corresponding responsible persons and completion deadlines. Routine tasks include elevator inspections and sanitation disinfection, which are automatically dispatched according to a set cycle and have task reminder and overdue warning functions. The dual-prevention closed-loop governance unit constructs a risk-level control and hidden danger closed-loop governance mechanism. For high-risk points identified by the risk intelligent analysis and prediction module, it pushes corresponding control measures. During the hidden danger governance process, it tracks the rectification plan and acceptance results, generates a closed-loop record of the hidden danger from discovery to rectification to cancellation, and feeds back the governance results to the data integration and display module.

[0013] Furthermore, the prediction, early warning, and optimization module includes a dynamic early warning triggering unit and a continuous optimization and iteration unit. The dynamic early warning triggering unit relies on the risk prediction model in the risk intelligent analysis and prediction module and the real-time governance data in the task and governance execution module. When abnormal data is detected, an early warning mechanism is triggered, and early warning information is released through platform pop-ups, SMS, and community announcements. Different early warning information is released for different roles, including residents and managers, and the early warning records are synchronized to the data integration and display module. The continuous optimization and iteration unit regularly extracts data such as risk prediction accuracy and hazard governance completion rate from the data integration and display module for review and analysis. Based on the analysis results, the parameters of the risk prediction model are optimized, and the hazard checklist template in the hazard management module and the risk control measures in the task and governance execution module are adjusted to form a closed loop of continuous improvement.

[0014] On the other hand, a dual prevention and control method for risks and hidden dangers, the method comprising: Data collection and aggregation: Through the data integration and display module, fire sensors, video surveillance and other equipment are deployed to collect facility parameters and environmental data in the community. Information reporting portals are opened for residents and inspection personnel. Data is aggregated through multiple channels to build a safety management database and provide data interaction interfaces for different roles. Risk identification and judgment: The risk intelligent analysis and prediction module calls the risk prediction model to analyze the data obtained in the data collection and aggregation stage, and combines it with the preset risk level judgment rules to identify potential risks in the community and make a level judgment, and output the risk prediction results and risk heat map. Hazard identification and mitigation: The hazard management module determines the key areas for investigation based on the risk identification and assessment results, uses standardized checklists to carry out hazard identification work, enters the identified hazard information into the system, automatically determines the risk level by associating it with the risk level assessment rules, and then transfers the hazard information to the task and mitigation execution module; Task execution and closed-loop management: After receiving the hidden danger information, the task and governance execution module dispatches the corresponding governance tasks, tracks the progress of hidden danger rectification, conducts acceptance in accordance with the acceptance standards, generates a closed-loop record from discovery to rectification to cancellation, and feeds back the governance results to the data integration and display module. Dynamic early warning and iterative optimization: The prediction, early warning and optimization module triggers multi-channel early warnings when anomalies are detected based on the risk identification and judgment results and real-time data during task execution. It also regularly reviews and analyzes the risk prediction data and hidden danger management data in the data integration and display module, and optimizes the risk prediction model, hidden danger checklist template and risk control measures based on the analysis results, so as to continuously improve the governance system.

[0015] Compared with existing technologies, this dual-prevention and control platform and method for risks and hazards has the following beneficial effects: I. This invention comprehensively identifies and grades potential risks within a community through a risk intelligent analysis and prediction module. Based on factors such as the probability of occurrence and the scope of harm, risks are classified into different levels, and corresponding control measures are pushed to high-risk points. This enables community managers to clearly understand the status of various risks within the community and take targeted preventive measures to control risks within an acceptable range. In terms of closed-loop management of hidden dangers, the hidden danger management module collects hidden danger information through standardized checklist templates, realizing automatic classification and transfer of hidden dangers. The task and management execution module tracks the entire process of hidden danger management, generating a closed-loop record from discovery to rectification to closure, ensuring the implementation of hidden danger management work and avoiding the omission and recurrence of hidden dangers.

[0016] Second, this invention monitors risk and governance data in real time through a prediction, early warning, and optimization module. When an anomaly is detected, an early warning mechanism is triggered in a timely manner, and early warning information is released to different roles through multiple channels, enabling community residents and management personnel to make preventive preparations in advance. Through the synergistic effect of the dual prevention mechanism, this invention can effectively prevent and reduce the occurrence of community safety accidents, enhance the community's safety guarantee capabilities, and create a safe and stable living environment for community residents.

[0017] Other advantages, objectives and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination or study, or may be learned from the practice of the invention. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0019] Figure 1 This is a structural diagram of a dual prevention and control platform for risks and hidden dangers. Figure 2 This is a schematic diagram of a risk intelligent analysis and prediction module for a dual-prevention and management platform for potential risks. Figure 3 This is a schematic diagram of the tasks and governance execution modules of a dual prevention and control platform for risks and hidden dangers; Figure 4 This is a flowchart of a dual prevention and control method for potential risks. Detailed Implementation

[0020] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.

[0021] This invention provides a dual-prevention and management platform and method for potential risks, such as... Figure 1 As shown, the platform includes a data integration and display module, a risk intelligent analysis and prediction module, a hidden danger management module, a task and governance execution module, and a prediction, early warning, and optimization module. The data integration and display module aggregates various safety-related data within the community, constructs a unified safety management database, and builds a multi-role interactive portal to achieve centralized data management and two-way data flow. The risk intelligent analysis and prediction module uses data mining and intelligent analysis models, combined with preset and custom risk level rules, to intelligently identify, determine the level of, and predict trends in community risks. The hidden danger management module, based on risk prediction results, collects hidden danger information through standardized checklist templates, achieving automatic hazard classification and transfer, forming a standardized management chain. The task and governance execution module, through special and routine task management mechanisms, combined with risk classification and control strategies, tracks and manages the entire hidden danger governance process in a closed loop. The prediction, early warning, and optimization module, based on risk prediction and governance execution data, triggers dynamic early warnings for multiple roles and continuously optimizes the parameters and templates of each module through data analysis and review, achieving iterative upgrades to governance capabilities.

[0022] I. Working Principle (I) Data Integration and Display Module Data Aggregation: This module aggregates various safety-related data within the community, including fire safety facility status data, public facility inspection data, health and epidemic prevention data, resident-reported information, and data entered by inspection personnel. By aggregating multi-source data, a unified safety management database is built, providing a comprehensive and accurate data foundation for the operation of subsequent modules.

[0023] Portal Setup: A multi-role interactive portal was built, encompassing residents, management personnel, and property management staff. The resident side supports hazard reporting and safety knowledge queries, facilitating resident participation in community safety management and access to relevant safety information. The management side is equipped with task assignment and data analysis tools, enabling managers to allocate tasks and analyze community safety data. The property management side links to facility inspection and maintenance records, achieving effective facility management. Through these portals, two-way data interaction and data interoperability between different roles are achieved, ensuring that each role can access and use the necessary data.

[0024] Data support: This module provides basic data support for all modules of the platform, enabling other modules to carry out risk analysis, hazard management and other tasks based on this data.

[0025] Multi-source data integration aggregates various types of safety-related data within the community, constructing a unified database, breaking down data silos, and achieving centralized data management, providing a rich data foundation for comprehensive analysis of the community's safety status. The establishment of a multi-role interactive portal meets the needs of different roles, promoting data exchange and collaboration among residents, management personnel, and property staff, thereby improving participation and efficiency in community safety management.

[0026] (II) Risk Intelligent Analysis and Prediction Module Risk level configuration unit Risk type classification: Classify the types of risks that may exist in the community, including fire, facility failure, and public health risks.

[0027] Preset rules: Based on the probability of risk occurrence and the scope of harm, preset rules are set for determining the risk level.

[0028] Custom risk levels: Supports the use of formulas to customize risk levels based on a comprehensive risk assessment of different scenarios (see the application in subsequent examples for details).

[0029] Risk prediction modeling unit Model building: Integrating data mining techniques with intelligent analysis models, a risk prediction model is built (see the application in subsequent embodiments for details).

[0030] Risk Analysis and Prediction: Based on received historical fault data, seasonal variation data, and population flow data, relevant risks within the community are analyzed, short-term and long-term risk prediction results are output, and a risk heat map is generated to provide directional guidance for hazard investigation.

[0031] By pre-setting and customizing risk level rules, combined with data mining and intelligent analysis models, the system enables intelligent identification, level determination, and trend prediction of community risks. This allows for the early detection of potential risks, providing a scientific basis for hazard investigation and mitigation. It supports customizing risk levels according to different scenarios, and the formulaic risk assessment method allows for flexible adjustment of risk assessment standards based on actual conditions, improving the accuracy and adaptability of risk assessment. The system generates risk heat maps, visually displaying the risk distribution within the community, providing clear directional guidance for hazard investigation and improving its efficiency.

[0032] (III) Hazard Management Module Standardized construction unit for hidden dangers Template Design: Design hazard inspection checklist templates for different scenarios, including fire exits and elevator facilities, clearly define the inspection items for each template, and support the addition and deletion of custom inspection items.

[0033] Information collection: A fillable form is generated based on a template, allowing inspection personnel to enter hazard information via mobile devices. The form has built-in photo and location functions to record the location and current status of hazards, and the entered information is synchronized to the data integration and display module.

[0034] Hazard Level Assessment and Transfer Unit Level Determination: The judgment rules in the associated risk intelligent analysis and prediction module automatically determine the level of the entered hazard information (see subsequent examples for application details). When (H < 2.5), it is determined as a general hazard; when... It was determined to be a major hidden danger.

[0035] Task flow: Based on the judgment result, the corresponding handling process is triggered, and the hidden danger information is transferred to the task and governance execution module.

[0036] By designing checklist templates for standardized hazard management units, the collection of hazard information has been standardized, facilitating unified management and analysis of hazards. The hazard level assessment and transfer unit can automatically classify hazards and trigger corresponding handling procedures based on the level, achieving automation and standardization of hazard management and improving the efficiency of hazard control.

[0037] (iv) Task and Governance Execution Module Task lifecycle management unit Special task management: Set up special tasks for specific risk situations, including specific task items, and associate them with the corresponding responsible persons and completion deadlines.

[0038] Routine task management: Routine tasks include elevator inspections, sanitation and disinfection, etc., which are automatically assigned according to the set cycle and have task reminder and overdue warning functions.

[0039] Dual prevention closed-loop management unit Control measures push: For high-risk points identified by the risk intelligent analysis and prediction module, corresponding control measures are pushed.

[0040] Closed-loop record generation: During the hazard management process, the rectification plan and acceptance results are tracked to generate a closed-loop record of the hazard from discovery to rectification to cancellation, and the management results are fed back to the data integration and display module.

[0041] The full-cycle task management unit comprehensively manages both special and routine tasks, including task assignment, reminders, and overdue warnings, ensuring timely completion and improving the efficiency and quality of task execution. The dual-prevention closed-loop governance unit establishes a risk-level control and hidden danger closed-loop governance mechanism, enabling full-process tracking and management of hidden dangers from discovery to rectification and eventual elimination, ensuring thorough remediation.

[0042] (v) Prediction, Early Warning and Optimization Module Dynamic early warning triggering unit Warning Trigger: Based on the risk prediction model in the risk intelligent analysis and prediction module and the real-time governance data in the task and governance execution module, an early warning mechanism is triggered when abnormal data is detected.

[0043] Information dissemination: Warning information is disseminated through platform pop-ups, SMS messages, and community announcements. Different warning information is disseminated to different roles, including residents and management personnel, and warning records are synchronized to the data integration and display module.

[0044] Continuous optimization of iterative units Data review: Regularly extract data such as the accuracy rate of risk prediction and the completion rate of hidden danger management from the data integration and display module for review and analysis.

[0045] Continuous improvement: Optimize the parameters of the risk prediction model based on the analysis results, adjust the hazard checklist template in the hazard management module and the risk control measures in the task and governance execution module to form a closed loop of continuous improvement.

[0046] The dynamic early warning triggering unit can monitor data anomalies in real time, promptly trigger the early warning mechanism, and issue different warning information to different roles, improving the timeliness and relevance of early warnings. The continuous optimization and iteration unit continuously optimizes risk prediction models, checklist templates, and control measures through regular review and analysis of data, enabling the platform to adapt to changes in community security conditions and achieve continuous improvement.

[0047] The application and implementation of this method will be described below with reference to specific examples.

[0048] Example 1 This invention's platform is applied to a mixed-use community comprising 6 residential buildings, 12 shops (including restaurants and convenience stores), and a small plaza. The data integration and display module collects data on the status of fire sprinklers and gas leak alarms in the shops, video surveillance data from the plaza area, and sanitation data from garbage sorting points in the residential area. It also receives electricity safety information reported by merchants and facility damage information reported by residents, constructs a safety management database, and provides an operational portal for the community committee, property management, merchants, and residents.

[0049] like Figure 2 As shown, the risk intelligent analysis and prediction module identifies risk types such as shop fire safety, public area crowd gathering, and hygiene and epidemic prevention at garbage sorting points. It presets risk level determination rules and uses a dynamic risk level determination formula when analyzing the risk of crowd gathering in public activity areas during holidays. ,in The value is 2.8 (based on the frequency of crowd gatherings in the square over the past three weekends). Take 2.5 (the square can accommodate 800 people, with an average weekend foot traffic of 650 people). Take 2.2 (the rate of increase in pedestrian traffic during holidays is 30% faster than on weekdays). , , Calculated At the same time, through the risk trend prediction formula Combining pedestrian flow data from the past three weekends ( , , , (0.3, 0.4, and 0.3 respectively) Using 1.2 (adjusted for holiday scenarios), predict the risk value for next weekend. The system outputs risk prediction results and heat map, showing that there is a high risk of crowd gathering in the square area on weekends.

[0050] The hazard management module includes templates for inspection forms such as fire safety checks for shops, public facility inspections, and hygiene and epidemic prevention inspections. Community safety inspectors used these templates to identify potential hazards, including a minor crack in a barbecue restaurant's gas hose, messy wiring in the electrical box, and damaged fitness equipment in the plaza. This information was entered into the system and synchronized to the data integration and display module. The hazard level determination and transfer unit uses a hazard level matching formula. To determine potential hazards in shops: (Basic level of gas hazard) (The length of the crack on site accounts for 15% of the total length of the hose) (Shop fire safety associated risk level) (Coupling degree between gas and electrical hazards), calculated as follows It was determined to be a major hidden danger; regarding the hidden dangers of fitness equipment, , , , Calculated If it is determined to be a general hidden danger, it will be transferred to the task and governance execution module.

[0051] like Figure 3 As shown, the task lifecycle management unit of the task and governance execution module assigns a special task to the person in charge of the shop to replace fire extinguishers, requiring completion within 24 hours; and assigns a task to the property maintenance personnel to repair fitness equipment, setting a completion time of 3 days. The dual prevention closed-loop governance unit tracks the rectification status, generates rectification acceptance records, and feeds them back to the data integration and display module.

[0052] When the prediction, early warning, and optimization module detects that the pedestrian density in the plaza area is close to the warning threshold, it issues staggered activity reminders to residents through community broadcasts and the APP, sends crowd control task reminders to management personnel, continuously optimizes and iterates the unit analysis data, adjusts the impact parameters of holiday crowd flow in the risk prediction model, optimizes the inspection items in the shop fire safety inspection checklist, and improves the pedestrian flow control measures in public areas.

[0053] Example 2 A high-rise residential community consists of 10 buildings, each with 18 floors, housing approximately 3,000 residents. This invention's platform is being used for risk and hazard management, such as... Figure 4 As shown, the data integration and display module collects fire protection data in real time through smoke and temperature sensors deployed in the corridors and elevators of each building; it also obtains data such as elevator speed and vibration amplitude through vibration sensors and operation status monitoring devices in the elevators; at the same time, residents can upload graphic and textual information such as objects piled up in the corridors, water seepage on the walls, and objects thrown from high-rise buildings through a mobile APP. This data is aggregated into a unified safety management database, providing residents with an entry point for reporting hazards and viewing safety notices, providing property management personnel with a data statistical analysis interface, and granting risk handling permissions to community safety specialists. The risk intelligent analysis and prediction module, tailored to the high-rise characteristics of this community, focuses on risks such as fire, elevator malfunction, falling objects from heights, and aging pipes. Based on elevator malfunction records from the past 12 months, it was found that the elevators in Buildings 3 and 5 experienced significantly more malfunctions than those in other buildings due to their high usage frequency, with an increased probability of malfunctions during the low-temperature winter months. By analyzing the data, the module outputs risk prediction results for the coming week. Specifically, the elevator in Unit 2 of Building 3 may experience operational abnormalities due to component wear, and Building 5 poses a fire hazard due to flammable materials stored in the corridors. A risk heat map is also generated to mark high-risk areas.

[0054] The checklist template for the hazard management module is tailored to the characteristics of high-rise buildings, detailing inspection items such as elevator operating noise, fire escape width, and signs of exterior wall peeling. During routine inspections, property patrol personnel discovered that the elevator in Unit 2 of Building 3 was making abnormal noises and stopping at the wrong floor. They used a mobile device to record the information and take a video. At the same time, they found that cardboard boxes and other debris were piled up in the corridor on the 3rd floor of Building 5. They took photos, recorded the information, and uploaded it to the system. The hazard level assessment and transfer unit determined, according to the rules, that the elevator problem was a major hazard requiring emergency handling, while the debris piled up in the corridor was a general hazard and handled according to the standard procedure. The information was then distributed to the elevator maintenance team and the property cleaning department respectively. After receiving information, the task and governance execution module creates a special task for the elevator maintenance team, requiring them to arrive on-site within 2 hours with spare parts, and the property management personnel follow up throughout the process; it also assigns routine tasks to the cleaning department, specifying that the cleaning must be completed within 12 hours. The dual prevention closed-loop governance unit updates the task status in real time. After the elevator maintenance is completed, it uploads the model of the replaced parts and a trial operation video, and the loop is closed after the community safety specialist approves it; after the corridor debris is cleared, the inspection personnel take photos for confirmation, forming a closed-loop record that is fed back to the database. When the prediction, early warning and optimization module detected that the vibration data of the elevator in Building 3 exceeded the normal range, it immediately sent a red alert to the property management personnel and simultaneously informed residents through the unit building's bulletin board not to use the elevator. During the end-of-month analysis, the module continuously optimized and iterated the unit and found that the accuracy of the prediction of the risk of objects falling from heights was low. Therefore, it increased the weight of balcony monitoring data, adjusted relevant parameters, and added a balcony railing stability check item to the checklist to improve the accuracy of risk control.

[0055] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A dual-prevention and management platform for risks and hidden dangers, characterized in that, The governance platform includes: Data integration and display module: By aggregating data from multiple sources, a unified database is built, and a multi-role interactive portal is established to realize centralized management and two-way flow of community security data, providing basic data support for various modules of the platform; Risk intelligent analysis and prediction module: includes risk level configuration unit and risk prediction modeling unit. Based on the data provided by the data integration and display module, it realizes intelligent identification, level determination and trend prediction of community risks through preset and customized risk level rules, combined with data mining and intelligent analysis models. The hazard management module includes a hazard standardization construction unit and a hazard level determination and transfer unit. Combining information reported by residents and risk prediction results, it collects hazard information through standardized checklist templates and realizes automatic hazard classification and transfer based on risk level rules, forming a standardized management link from hazard discovery to disposal. Task and Governance Execution Module: Includes a full-cycle task management unit and a dual-prevention closed-loop governance unit. It receives handling tasks from the hazard management module and achieves full-process tracking and closed-loop management of hazard governance through special and routine task management mechanisms combined with risk classification and control strategies. Prediction, early warning and optimization module: Includes dynamic early warning triggering unit and continuous optimization iteration unit. It triggers dynamic early warning for multiple roles based on risk prediction and governance execution data, and continuously optimizes prediction models, checklist templates and control measures through data analysis and review.

2. The risk and hazard dual prevention and control platform according to claim 1, characterized in that, The data integration and display module gathers various safety-related data within the community, including fire-fighting facility status data, public facility inspection data, health and epidemic prevention data, resident-reported information, and inspection personnel data. It constructs a unified safety management database and builds a multi-role interactive portal for residents, managers, and property management personnel. The resident side supports hazard reporting and safety knowledge inquiry, the manager side is configured with task assignment and data analysis tools, and the property management side links facility inspection and maintenance records, realizing two-way data interaction and data interoperability between different roles.

3. The risk and hazard dual prevention and control platform according to claim 1, characterized in that, The intelligent risk analysis and prediction module includes a risk level configuration unit and a risk prediction modeling unit. The risk level configuration unit identifies potential risk types within the community, including fire, facility malfunction, and public health risks. Based on the probability of occurrence and the scope of harm, it presets risk level determination rules and supports custom risk levels using formulas through comprehensive risk level assessment for different scenarios. The risk prediction modeling unit integrates data mining technology and intelligent analysis models to construct a risk prediction model. Based on received historical fault data, seasonal change data, and population flow data, it analyzes relevant risks within the community, outputs short-term and long-term risk prediction results, and generates a risk heat map to provide directional guidance for hazard investigation.

4. The risk and hazard dual prevention and control platform according to claim 3, characterized in that, The risk level configuration unit defines risk levels according to different scenarios through a comprehensive risk level assessment using a formula, which is as follows: ,in, This is the overall risk level value, ranging from 0 to 10. This is the probability coefficient of risk occurrence, ranging from 0 to 3, reflecting the frequency of similar risks occurring in the past. This is the risk impact range coefficient, with a value ranging from 0 to 3, derived based on community population density and facility distribution. This is the risk urgency coefficient, with a value ranging from 0 to 3. These are the weighting coefficients.

5. The risk and hazard dual prevention and control platform according to claim 3, characterized in that, The risk prediction modeling unit integrates data mining technology and intelligent analysis models to construct a risk prediction model, the formula of which is: ,in, For the future Risk forecast value for the period This represents the current risk level value. For the past Related influencing factors over time periods For the influence factor weights, For historical data backtracking period, This is a scene correction factor.

6. The risk and hazard dual prevention and control platform according to claim 1, characterized in that, The hazard management module includes a hazard standardization construction unit and a hazard level determination and transfer unit. The hazard standardization construction unit designs hazard inspection form templates for different scenarios, including fire exits and elevator facilities. It clearly defines the inspection items for each template and supports the addition and deletion of inspection items. Based on the template, it generates a fillable form for inspection personnel to enter hazard information via mobile devices. The form has built-in photo and location functions to record the location and current status of hazards, and the entered information is synchronized to the data integration and display module. The hazard level determination and transfer unit is linked to the judgment rules in the risk intelligent analysis and prediction module. It automatically determines the level of the entered hazard information. The judgment results include general hazards and major hazards. Based on the judgment results, it triggers the corresponding handling process and transfers the hazard information to the task and governance execution module.

7. The risk and hazard dual prevention and control platform according to claim 6, characterized in that, The hazard level determination and transfer unit-related risk intelligent analysis and prediction module uses a determination rule to automatically determine the level of the entered hazard information. The determination formula is as follows: ,in, This is the final hazard level value, ranging from 0 to 5. The basic level of potential hazards is based on the preset checklist template. The on-site correction factor for potential hazards is calculated based on the photo location information. The associated risk level value is taken from the output of the risk intelligent analysis and prediction module. For risk correlation coefficient, when <2.5 is judged as a general hidden danger, when If the value is ≥2.5, it is considered a major hidden danger.

8. The risk and hazard dual prevention and control platform according to claim 1, characterized in that, The task and governance execution module includes a task full-cycle management unit and a dual-prevention closed-loop governance unit. The task full-cycle management unit manages special tasks and routine tasks. Special tasks are set for specific risk situations, include specific task items, and are associated with corresponding responsible persons and completion deadlines. Routine tasks include elevator inspections and sanitation disinfection, which are automatically dispatched according to a set cycle and have task reminder and overdue warning functions. The dual-prevention closed-loop governance unit constructs a risk-level control and hidden danger closed-loop governance mechanism. For high-risk points identified by the risk intelligent analysis and prediction module, it pushes corresponding control measures. During the hidden danger governance process, it tracks the rectification plan and acceptance results, generates a closed-loop record of hidden dangers from discovery to rectification to cancellation, and feeds back the governance results to the data integration and display module.

9. The risk and hazard dual prevention and control platform according to claim 1, characterized in that, The prediction, early warning and optimization module includes a dynamic early warning triggering unit and a continuous optimization and iteration unit. The dynamic early warning triggering unit relies on the risk prediction model in the risk intelligent analysis and prediction module and the real-time governance data in the task and governance execution module. When abnormal data is detected, the early warning mechanism is triggered, and early warning information is released through platform pop-ups, SMS, and community announcements. Different early warning information is released for different roles, including residents and managers, and the early warning records are synchronized to the data integration and display module. The continuous optimization and iteration unit regularly extracts data such as risk prediction accuracy and hazard management completion rate from the data integration and display module for review and analysis. Based on the analysis results, it optimizes the parameters of the risk prediction model, adjusts the hazard checklist template in the hazard management module and the risk control measures in the task and management execution module, forming a closed loop of continuous improvement.

10. A method for dual prevention and control of risks and hazards, applicable to the dual prevention and control platform for risks and hazards as described in any one of claims 1-9, characterized in that, The method includes: Data collection and aggregation: Through the data integration and display module, fire sensors, video surveillance and other equipment are deployed to collect facility parameters and environmental data in the community. Information reporting portals are opened for residents and inspection personnel. Data is aggregated through multiple channels to build a safety management database and provide data interaction interfaces for different roles. Risk identification and judgment: The risk intelligent analysis and prediction module calls the risk prediction model to analyze the data obtained in the data collection and aggregation stage, and combines it with the preset risk level judgment rules to identify potential risks in the community and make a level judgment, and output the risk prediction results and risk heat map. Hazard identification and mitigation: The hazard management module determines the key areas for investigation based on the risk identification and assessment results, uses standardized checklists to carry out hazard identification work, enters the identified hazard information into the system, automatically determines the risk level by associating it with the risk level assessment rules, and then transfers the hazard information to the task and mitigation execution module; Task execution and closed-loop management: After receiving the hidden danger information, the task and governance execution module dispatches the corresponding governance tasks, tracks the progress of hidden danger rectification, conducts acceptance in accordance with the acceptance standards, generates a closed-loop record from discovery to rectification to cancellation, and feeds back the governance results to the data integration and display module. Dynamic early warning and iterative optimization: The prediction, early warning and optimization module triggers multi-channel early warnings when anomalies are detected based on the risk identification and judgment results and real-time data during task execution. It also regularly reviews and analyzes the risk prediction data and hidden danger management data in the data integration and display module, and optimizes the risk prediction model, hidden danger checklist template and risk control measures based on the analysis results, so as to continuously improve the governance system.

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