Big data-based one-stop emergency safety service platform

Abstract

The invention relates to the technical field of emergency safety service, and discloses a one-stop emergency safety service platform based on big data, which comprises a user module, a demand module, a center module, a service provider module, an assistant module, a shopping mall module, a propaganda module, a supervision module and an early warning module, the demand module is used for a user to send an emergency safety service demand, the center module is used for data processing, the service provider module is used for providing an emergency safety service, the assistant module replies problems in an AI mode, the shopping mall module is used for selling materials, and the propaganda module is used for propagandizing emergency safety knowledge. The system is not limited to comprehensive services such as safety production, occupational health, educational training and emergency rescue, almost covers each corner of the emergency management field, simplifies the process of obtaining the required service by the user, and can combine online convenience and offline safety.

Description

Technical Field

[0001] The present invention relates to the technical field of emergency safety services, and more particularly to a one-stop emergency safety service platform based on big data. Background Art

[0002] Since the establishment of the emergency department, the two sectors of enterprise safety production management and grass-roots disaster prevention and mitigation have always been the top priorities of current emergency management work. Emergency safety work requires the coordinated cooperation of the government and social service agencies. The following technical bottlenecks need to be urgently broken through in the current emergency safety service field: First, data islands and low efficiency in collaboration. Existing emergency safety service platforms mostly adopt an independent construction model in vertical fields. There is a lack of unified data standards and interaction protocols among systems such as emergency response, emergency safety technical services, emergency material dispatching, monitoring and early warning by regulatory departments, and emergency science popularization and publicity. Data between departments is not interconnected, and cross-departmental collaboration relies on manual docking. There is a lack of an intelligent matching mechanism between the demand side (government / enterprise / individual) and the supply side (experts / institutions / volunteers). Second, the level of intelligence is insufficient. Traditional platforms mostly rely on manual experience for decision-making, with significant defects, including lagging risk assessment, hidden danger identification relying on manual inspections, low discovery rates of hidden risks in scenarios such as construction sites and hazardous chemical industrial parks, poor early warning accuracy, high false alarm rates of existing monitoring equipment, and inability to effectively identify compound risks such as smoke and flame forms and abnormal temperature rises of equipment. Coarse resource matching, and service supply and demand matching mostly adopts the "keyword search + manual screening" mode, and core parameters such as geographical location, service capabilities, and cost-effectiveness are not quantitatively modeled. Third, there is a break in the full-chain service. Market solutions generally have a tendency of "emphasizing emergency and neglecting prevention". There is a lack of an active prevention and control system covering "risk identification - training and education - pre-plan deduction" in the prevention stage. In the disposal stage, on-site command relies on voice communication, and there is a delay of more than 10 minutes in real-time situation awareness and resource dispatching instructions transmission.

[0003] The above problems lead to the difficulty of existing systems in coping with the following challenges: First, emergency response in complex scenarios, lacking the ability to jointly handle new risks such as multi-disaster coupling accidents in industrial parks. Second, optimal resource allocation, with an imbalance between the supply and demand of emergency resources under the emergency safety needs of enterprises. Third, the need for long-term governance, which requires breaking through key technologies such as data fusion and intelligent decision-making.

[0004] The proposal of the present invention is precisely to build a one-stop emergency safety service platform based on big data, and through technological innovations such as multi-modal data fusion, intelligent matching algorithms, and full-process closed-loop management, to achieve a leapfrog upgrade from "fragmented response" to "systematic governance". Summary of the Invention

[0005] In order to overcome the above-mentioned defects of the prior art, the embodiments of the present invention provide a one-stop emergency safety service platform based on big data to solve the technical problems proposed in the background art.

[0006] To achieve the above object, the present invention provides the following technical solution: A one-stop emergency safety service platform based on big data, including a user module, a demand module, a center module, a service provider module, an assistant module, a mall module, a publicity module, a supervision module, and an early warning module. The user module is used for users to log in to the platform. The demand module is used for users to send emergency safety service demands. The center module is used for data processing. The service provider module is used for providing emergency safety services. The assistant module replies to questions in an AI manner. The mall module is used for selling materials. The publicity module is used for publicizing emergency safety knowledge. The supervision module conducts on-site safety supervision. The early warning module is used for giving an alarm when there is a safety hazard on-site;

[0007] The demand module sends the demand information sent by the user module to the center module. The service provider module sends the service information that the service provider module can provide to the center module. The center module matches the demand information with the service information and calculates a matching value PP. The calculation formula for the matching value PP is where k1 and K2 are both weights, JL is the geographical location distance between the demand information and the service information, JE is the amount difference between the commission provided by the demand information and the commission required by the service information, PZ is the average score of the service information in the latest ten times, YZ is the consistency between the skills provided by the service information and the skills required by the demand information, and sgn is a rounding function.

[0008] In a preferred embodiment, the user module includes a personal unit, an enterprise unit, and a government unit. The personal unit is used for an individual to log in on their own behalf. The enterprise unit is used for an individual to log in on behalf of the enterprise they belong to. The government module is used for an individual to log in on behalf of the government unit they belong to. The personal unit, the enterprise unit, and the government unit can all send demand information through the demand module after logging in to the user module.

[0009] In a preferred embodiment, after the center module calculates the matching value PP, the center module compares the calculated matching value PP with the internal matching threshold PY. The center module matches the demand information and the service information with a matching value PP ≥ the matching threshold PY. The center module matches the demand information and the service information with a matching value PP < the matching threshold PY.

[0010] In a preferred embodiment, within the central module, when the skills provided by the service information are consistent with the demand information, the consistency degree YZ is 1; when the skills provided by the service information are different from the demand information, the consistency degree YZ is 0. The average score PZ of the service information in the latest ten times is the average calculated value of the scores given by the user module after the service provider module has provided services in the latest ten times, and the scores given by the user module are any integers from 0 to 100.

[0011] In a preferred embodiment, the service provider module includes a technical service institution unit, an expert unit, and a digital intelligent safety officer unit. The technical service provider module is used for the technical service institution to provide emergency safety services. The expert unit is used for experts to provide emergency safety services personally. The digital intelligent safety officer unit consists of safety management personnel of enterprise and institution units, registered safety engineers, and freelance engineers who provide safety services after applying to enter the platform. When each unit of the service provider module provides safety services, it is required to undergo qualification review and service assessment. For the qualification review, it is necessary to detect the certification materials provided by each unit within the service provider module during the entry process. Only after the certification materials pass the detection can they enter the technical service institution unit, the digital intelligent safety officer unit, or the expert unit.

[0012] In a preferred embodiment, when the service provider module conducts service assessment, it calculates a service value FW. The calculation formula for the service value FW is FW = BZ × SL × YJ, where YJ is the number of successful services SL provided by the service provider within a month, the average service duration of the service provider within a month, and the ratio BZ of the number of positive reviews to the number of negative reviews of the service provider within a month. The service provider module compares the calculated service value FW with the service threshold FY within it. When the service value FW ≥ the service threshold FY, the service provider module does not take any action. When the service value FW < the service threshold FY, the service provider module suspends the service qualification of this service provider in the next month. When the service value FW < the service threshold FY occurs continuously three times for a service provider, the service provider module deletes this service provider.

[0013] In a preferred embodiment, the assistant module communicates with the user module through AI, and the assistant module answers questions and provides opinions in the way of AI. Emergency supplies are sold in the mall module, and the supplies sold in the mall module include daily necessities and professional safety rescue equipment, and the sold supplies can be provided to individuals and teams.

[0014] In a preferred embodiment, the publicity module is used for the service provider module to conduct emergency safety knowledge publicity, and an emergency safety knowledge base and knowledge short videos are set in the publicity module. The user module can conduct online live broadcasts, knowledge quizzes, and online reading through the publicity module.

[0015] In a preferred embodiment, the supervision module includes an identification unit and a patrol inspection unit. The user module of the identification unit can obtain the hidden danger results on the mobile phone side by taking actual photos and uploading on-site hidden danger pictures through the identification unit. The patrol inspection unit is linked with cameras for intelligent patrol inspection, and the patrol inspection unit automatically identifies the unsafe behaviors of on-site personnel and the unsafe states of objects and the environment. When the identification unit and the patrol inspection unit discover safety hazards, they send danger instructions to the warning module, and the warning module accepts the danger information and gives an alarm.

[0016] Technical effects and advantages of the present invention:

[0017] 1. When the present invention is in use, it is not limited to all-round services such as work safety, occupational health, education and training, and emergency rescue, and almost covers every corner of the emergency management field. Such a one-stop solution greatly simplifies the process for users to obtain the required services, and can combine the convenience of the online and the safety of the offline, enabling each user to have a good experience;

[0018] 2. The present invention matches the demand information with the service information, and when performing the matching, the matching value PP is calculated. The larger the matching value PP, the easier it is to complete the matching, and the easier it is for the two to cooperate. Therefore, the present application matches the demand information and service information with the matching value PP ≥ the matching threshold PY to increase the probability of cooperation;

[0019] 3. The present invention is provided with a digital intelligent safety officer unit. When the digital intelligent safety officer unit is in use, safety management personnel, registered safety engineers, and freelance engineers in enterprises and institutions can provide services. After the digital intelligent safety officer applies to enter the platform through the platform, relying on professional training and cutting-edge AI tools, traditional safety officers are transformed into modern safety management experts proficient in cutting-edge technologies such as AI, big data analysis, and the Internet of Things, enabling them to implement safety management and services in an intelligent manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a schematic diagram of the overall composition structure of the platform of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0021] Next, the technical solutions in the present invention will be clearly and completely described in conjunction with the drawings in the present invention. In addition, the forms of each structure described in the following embodiments are only examples, and a one-stop emergency safety service platform related to the present invention is not limited to the structures described in the following embodiments. All other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present invention.

[0022] Refer toFigure 1 , the present invention provides a one-stop emergency safety service platform based on big data, including a user module, a demand module, a central module, a service provider module, an assistant module, a mall module, a publicity module, a supervision module, and an early warning module. The user module is used for users to log in to the platform. The demand module is used for users to send emergency safety service demands. The central module is used for data processing. The service provider module is used for providing emergency safety services. The assistant module replies to questions in an AI manner. The mall module is used for selling materials. The publicity module is used for publicizing emergency safety knowledge. The supervision module conducts on-site safety supervision. The early warning module is used for giving an alarm when a safety hazard appears on-site.

[0023] In the embodiments of the present application, when the platform of the present application is in use, but not limited to all-round services such as work safety, occupational health, education and training, and emergency rescue, it almost covers every corner of the field of emergency management. Such a one-stop solution greatly simplifies the process for users to obtain the required services, and can combine the convenience of the online and the safety of the offline, enabling each user to have a good experience.

[0024] Referring to Figure 1 , the demand module sends the demand information sent by the user module to the central module, and the service provider module sends the service information that the service provider module can provide to the central module. The central module matches the demand information and the service information and calculates a matching value PP. The calculation formula for the matching value PP is In the formula, both k1 and K2 are weights, JL is the geographical location distance between the demand information and the service information, JE is the amount difference between the commission provided by the demand information and the commission required by the service information, PZ is the average score of the service information in the latest ten times, YZ is the consistency between the skills provided by the service information and the skills required by the demand information, sgn is the rounding function. After the central module calculates the matching value PP, the central module compares the calculated matching value PP with the matching threshold PY inside it. The central module matches the demand information and the service information with the matching value PP ≥ the matching threshold PY, and the central module matches the demand information and the service information with the matching value PP < the matching threshold PY.

[0025] In the embodiments of the present application, the demand module sends demands, and the service provider module provides service information that it can offer. However, currently, the two cannot be well matched, the service demands of users cannot be met, and service providers cannot offer their services. The present application matches demand information with service information. When the present application performs the matching, it calculates a matching value PP. When calculating the matching value PP, it is calculated by using the geographical location distance JL between the demand information and the service information, the amount difference JE between the commission provided by the demand information and the commission required by the service information, and the average score PZ. When the geographical location distance JL is smaller, it is easier for users and service providers to conduct transactions. When the amount difference JE is smaller, the transaction between the demand information and the service information is more likely to be concluded. The larger the average score PZ, the better the services that service providers can offer. Therefore, the larger the matching value PP calculated by the present application, the easier it is to complete the matching, and the easier it is for the two to cooperate. Therefore, the present application matches the demand information and the service information with the matching value PP≥matching threshold PY, increasing the probability of cooperation conclusion.

[0026] Refer to Figure 1 , within the central module, when the skills provided by the service information are the same as the demand information, the consistency YZ is 1. When the skills provided by the service information are different from the demand information, the consistency YZ is 0. The average score PZ of the service information in the current latest ten times is the average calculation value of the scores given by the user module after the service provider module has provided services in the latest ten times, and the scores given by the user module are any integers from 0 to 100.

[0027] In the embodiments of the present application, when calculating the matching value PP, the sgn rounding function is used. When the sgn function is used, it outputs 1 when the input is a positive number and outputs 0 when the input is 0. Therefore, when 0 is input inside sgn, the skills provided by the service information are different from the demand information. At this time, even if the calculated amount difference JE between the two is very small and the distance is relatively close, they cannot be matched, ensuring the accuracy of the matching itself.

[0028] Refer to Figure 1 , the user module includes a personal unit, an enterprise unit, and a government unit. The personal unit is used for an individual to log in on their own behalf. The enterprise unit is used for an individual to log in on behalf of the enterprise to which they belong. The government module is used for an individual to log in on behalf of the government unit to which they belong. After the personal unit, the enterprise unit, and the government unit log in to the user module, they can all send demand information through the demand module.

[0029] In the embodiments of the present application, the user module includes an individual unit, an enterprise unit, and a government unit. Therefore, different usage types can adopt different login methods, which makes it easier to find the type of emergency safety service provider they need, and makes it more convenient for different users to use.

[0030] Referring to Figure 1 , the service provider module includes a technical service institution unit, an expert unit, and a digital intelligent safety officer unit. The technical service provider module is used for the technical service institution to provide emergency safety services. The expert unit is used for experts to provide emergency safety services. The digital intelligent safety officer unit consists of safety management personnel of enterprise and institution units, registered safety engineers, and freelance engineers, who provide safety services after applying for entry through the platform. When each unit of the service provider module provides safety services, it needs to undergo qualification review and service assessment. For the qualification review, the supporting documents provided by each unit within the service provider module during entry need to be inspected. Only after the inspection of the supporting documents passes can they enter the technical service institution unit, the digital intelligent safety officer unit, or the expert unit. For the digital intelligent safety officer unit, when the service provider module conducts service assessment, it will calculate the service value FW. The calculation formula for the service value FW is FW = BZ × SL × YJ, where YJ is the number of successful services provided by the service provider within a month, SL is the average service duration of the service provider within a month, and BZ is the ratio of the number of positive reviews to the number of negative reviews of the service provider within a month. The service provider module compares the calculated service value FW with the internal service threshold FY. When the service value FW ≥ service threshold FY, the service provider module does not take any action. When the service value FW < service threshold FY, the service provider module suspends the service qualification of this service provider in the next month. When the service provider continuously has three times of service value FW < service threshold FY, the service provider module deletes this service provider.

[0031] In the embodiments of the present application, the service provider module includes a technical service institution unit, an expert unit, and a digital intelligent safety officer unit. Different service providers can provide different services. Therefore, the present application classifies different service providers into three categories to enable different service providers to provide good services. When the digital intelligent safety officer unit is in use, safety management personnel, registered safety engineers, and freelance engineers in enterprise and institution units can provide services. After the digital intelligent safety officer applies to enter the platform through the platform, relying on professional training and cutting-edge AI tools, the traditional safety officer is transformed into a modern safety management expert proficient in frontier technologies such as AI, big data analysis, and the Internet of Things, enabling them to implement safety management and services in an intelligent manner, aiming to lead the entire emergency safety field industry towards a highly intelligent development path. The service providers are evaluated, and the service value FW is calculated. The larger the calculated service value FW, the better the recent performance of the service provider. When the service value FW < service threshold FY, it indicates that the service provider has performed poorly recently. Therefore, the service qualification of the service provider in the next month is suspended. When the service value FW < service threshold FY occurs three times in a row for a service provider, the service provider module deletes the service provider to prevent some service providers with bad behaviors from affecting the image of all service providers.

[0032] Refer to Figure 1 , the assistant module communicates with the user module through AI, and the assistant module answers questions and provides opinions in the form of AI. Emergency supplies are sold in the mall module, and the supplies sold in the mall module include daily necessities and professional safety rescue equipment. The sold supplies can be provided to individuals and teams. The publicity module is used to publicize emergency safety knowledge for the service provider module, and an emergency safety knowledge base and knowledge short videos are set in the publicity module. The user module can conduct online live broadcasts, knowledge quizzes, and online reading through the publicity module.

[0033] In the embodiments of the present application, when the assistant module of the present application is in use, an AI assistant is set up. The AI assistant is built based on the work safety database. The AI assistant can achieve dialogue and interaction with people, answer questions, and provide suggested solutions, efficiently and conveniently helping people master and apply work safety knowledge and skills. The publicity module is committed to providing comprehensive, flexible, and efficient knowledge sharing services for emergency safety practitioners, with senior expert technical support and a vast emergency safety knowledge base, sharing industry safety knowledge, skills and techniques, advanced concepts and technologies, the latest industry information and trends through online live broadcasts, knowledge quizzes, online reading, new media publicity, etc., providing users with a convenient and easy learning and sharing experience.

[0034] Refer to Figure 1, the supervision module includes an identification unit and a patrol inspection unit. The user module of the identification unit can obtain potential hazard results on the mobile phone side by taking on-site photos and uploading on-site potential hazard pictures through the identification unit. The patrol inspection unit is linked with cameras for intelligent patrol inspection. Moreover, the patrol inspection unit automatically identifies the unsafe behaviors of on-site personnel and the unsafe states of objects and the environment. When the identification unit and the patrol inspection unit discover potential safety hazards, they send a danger instruction to the early warning module, and the early warning module receives the danger information and issues an alarm.

[0035] In the embodiment of the present application, when the identification unit is in use, on the mobile phone side, it supports taking on-site photos or uploading on-site potential hazard pictures, and uses AI recognition Figure 1 to quickly obtain the results. The corresponding potential hazard descriptions and rectification suggestions are clear at a glance. Even safety novices can easily get started and quickly complete potential hazard investigation, effectively solving the problems of insufficient professionalism of inspectors and low inspection efficiency. The patrol inspection unit will be linked with cameras for intelligent patrol inspection, and automatically identify the unsafe behaviors of on-site personnel, and the unsafe states of objects and the environment, such as employees not wearing safety helmets, smoking, sleeping on duty, playing with mobile phones, overcrowding recognition, flame and smoke recognition, electric vehicle entering the elevator recognition, fire extinguisher configuration recognition, etc. When abnormalities are found, intelligent early warning is issued, and the corresponding person in charge is timely reminded to handle it in the form of sending text messages, platform message notifications or voice broadcasts.

[0036] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The units and algorithm steps described in the examples of the embodiments can be implemented by electronic hardware or a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0037] In several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed mutual coupling or direct coupling or communication connection can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be in electrical, mechanical or other forms.

[0038] As described above, it is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of changes or substitutions, which should all be covered within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims described above.

[0039] Finally: The above description is only the preferred embodiment of the present invention and is not used to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A one-stop emergency safety service platform based on big data, characterized in that: It includes a user module, a demand module, a central module, a service provider module, an assistant module, a mall module, a publicity module, a supervision module, and an early warning module. The user module is used for users to log in to the platform. The demand module is used for users to send emergency safety service demands. The central module is used for data processing. The service provider module is used for providing emergency safety services. The assistant module replies to questions in an AI manner. The mall module is used for selling materials. The publicity module is used for publicizing emergency safety knowledge. The supervision module conducts on-site safety supervision. The early warning module is used for giving an alarm when there are safety hazards on-site; The requirement module sends the requirement information sent by the user module to the central module, and the service provider module sends the service information that the service provider module can provide to the central module. The central module matches the requirement information with the service information and calculates a matching value PP. The calculation formula for the matching value PP is In the formula, both k1 and K2 are weights, JL is the geographical location distance between the requirement information and the service information, JE is the amount difference between the commission provided by the requirement information and the commission required by the service information, PZ is the average score of the service information in the latest ten times, YZ is the consistency between the skills provided by the service information and the skills required by the requirement information, and sgn is the rounding function.

2. The one-stop emergency safety service platform based on big data according to claim 1, characterized in that: The user module includes an individual unit, an enterprise unit, and a government unit. The individual unit is used for an individual to log in on their own behalf. The enterprise unit is used for an individual to log in on behalf of their affiliated enterprise. The government module is used for an individual to log in on behalf of their affiliated government unit. After logging in to the user module, the individual unit, the enterprise unit, and the government unit can all send demand information through the demand module.

3. The one-stop emergency security service platform based on big data according to claim 2, characterized in that: After the central module calculates the matching value PP, the central module compares the calculated matching value PP with the internal matching threshold PY. The central module matches the demand information with a matching value PP ≥ matching threshold PY with service information, and the central module matches the demand information with a matching value PP < matching threshold PY with service information.

4. The one-stop emergency safety service platform based on big data according to claim 3, characterized in that: Within the central module, when the skills provided by the service information are the same as those of the demand information, the consistency degree YZ is 1. When the skills provided by the service information are different from those of the demand information, the consistency degree YZ is 0. The average score PZ of the service information in the current latest ten times is the average calculated value of the scores given by the user module after the service provider module provides services in the latest ten times, and the scores given by the user module are any integers from 0 to 100.

5. The one-stop emergency security service platform based on big data according to claim 1, characterized in that: The service provider module includes a technical service agency unit, an expert unit, and a digital intelligent safety officer unit. The technical service provider module is used for technical service agencies to provide emergency safety services. The expert unit is used for experts to provide emergency safety services personally. The digital intelligent safety officer unit consists of safety management personnel of enterprise and institution units, certified safety engineers, and freelance engineers who provide safety services after applying to enter the platform. When each unit of the service provider module conducts safety services, it is required to conduct qualification review and service assessment. For the qualification review, it is necessary to detect the supporting materials provided by each unit in the service provider module when entering. Only after the supporting materials pass the detection can they enter the technical service agency unit, the digital intelligent safety officer unit, or the expert unit.

6. The one-stop emergency safety service platform based on big data according to claim 5, characterized in that: When the service provider module conducts service assessment, it calculates the service value FW. The calculation formula for the service value FW is FW = BZ × SL × YJ. In the formula, YJ is the number of successful services SL provided by the service provider within a month, the average service duration of the service provider within a month, and the ratio BZ of the number of positive reviews to the number of negative reviews of the service provider within a month. The service provider module compares the calculated service value FW with the service threshold FY within it. When the service value FW ≥ the service threshold FY, the service provider module does not take any action. When the service value FW < the service threshold FY, the service provider module suspends the service qualification of this service provider in the next month. When the service value FW < the service threshold FY occurs three times in a row for the service provider, the service provider module deletes this service provider.

7. The one-stop emergency safety service platform based on big data according to claim 1, characterized in that: The assistant module conducts conversations with the user module through AI, and the assistant module provides question answers and opinions in the way of AI. Emergency supplies are sold in the mall module, and the sold supplies in the mall module include daily necessities and professional safety rescue equipment. The sold supplies can be provided to individuals and teams.

8. The one-stop emergency safety service platform based on big data according to claim 1, characterized in that: The publicity module is used for the service provider module to conduct emergency safety knowledge publicity. An emergency safety knowledge base and knowledge short videos are set in the publicity module. The user module can conduct online live broadcasts, knowledge quizzes, and online reading through the publicity module.

9. The one-stop emergency safety service platform based on big data according to claim 1, characterized in that: The supervision module includes an identification unit and an inspection unit. The user module of the identification unit can obtain the hidden danger results on the mobile phone side by taking actual photos and uploading on-site hidden danger pictures. The inspection unit is linked with cameras for intelligent inspection, and the inspection unit automatically identifies the unsafe behaviors of on-site personnel and the unsafe states of objects and the environment. When the identification unit and the inspection unit discover safety hazards, they send a danger instruction to the warning module, and the warning module accepts the danger quality and issues an alarm.

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