CN116976832A - Intelligent fire-fighting centralized unified supervision platform based on AI, big data and Internet of things - Google Patents
Intelligent fire-fighting centralized unified supervision platform based on AI, big data and Internet of things Download PDFInfo
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Abstract
The invention relates to an intelligent fire-fighting centralized unified supervision platform based on AI, big data and the Internet of things, which belongs to the technical field of fire-fighting safety management, and comprises a data acquisition service module, a data analysis module, an operation management module and a display module, wherein the modules are mutually matched to form a flow closed loop; the system comprises a data acquisition service module, a data analysis module, an operation management module, a display module, an operation management process and a result state, wherein the data acquisition service module is used for carrying out real-time data acquisition on data sensing equipment of an access system, monitoring data acquired through computer resources, storage resources and network resources are uploaded to the data analysis module through the Internet of things, the data analysis module is uploaded to the operation management module through the obtained hidden danger condition and is displayed on the display module, and the operation management process and the result state are displayed on the display module and are updated and stored in the data acquisition service module.
Description
Technical Field
The invention belongs to the technical field of fire safety management, relates to an intelligent fire control centralized unified supervision platform based on AI, big data and the Internet of things, and particularly relates to an intelligent fire control cloud platform system for an internet of things based on artificial intelligence, big data and the Internet of things.
Background
Fire is an injury caused by burning which is out of control in time or space and causes great loss of personnel safety and property, so fire safety is highly necessary in order to reduce the loss.
In recent years, with the continuous deep concept of fire safety, the management work of fire safety in each area is more and more paid attention to, and the fire safety management is more and more systematic and centralized.
Property is the most basic and most extensive link in the whole fire control management chain, but at present, property fire control management basically depends on civil air defense, and a large number of management loopholes and pain points exist as follows:
1: the fire control supervision work points are wide in multiple surfaces, the fire control supervision work points are difficult to cover the whole surfaces, and the management of the handles/tools and the memory and the mind are lacked.
2: the hidden danger is difficult to treat, and the hidden danger is lack of a tracking mechanism of the whole process.
3: poor people's consciousness, poor fire safety consciousness of common people and low willingness to assist in fire prevention work.
4: the maintenance is opaque, and due to the limitation of fire protection professionals, the quality of the real maintenance is difficult to effectively monitor, and a large number of hidden troubles exist.
Disclosure of Invention
In view of the above, the invention provides an intelligent firefighting centralized unified supervision platform based on AI, big data and the Internet of things in order to solve the problems that the current property firefighting management basically depends on civil air defense and a large number of management loopholes and pain points exist.
In order to achieve the above purpose, the present invention provides the following technical solutions:
the intelligent fire control centralized unified supervision platform based on AI, big data and the Internet of things comprises a data acquisition service module, a data analysis module, an operation management module and a display module;
the data acquisition service module is used for carrying out real-time data acquisition on the data sensing equipment of the access system, acquiring monitoring data through computer resources, storage resources and network resources, and uploading the monitoring data to the data analysis module through the Internet of things;
the data analysis module comprises fire control data, water system data, video data and big data processing; the data analysis module uploads the obtained hidden danger situation to the operation management module and displays the hidden danger situation on the display module;
the operation management module comprises fire alarm management, supervision project fire safety, unit facility equipment management and fire maintenance management, wherein the operation management process and the result state are displayed in the display module and updated and stored in the data acquisition service module;
the display module has the functions of positioning, supervision, system management and visualization;
the data acquisition service module, the data analysis module, the operation management module and the display module are mutually matched to form a flow closed loop.
Further, the data acquisition service module comprises a fire control data acquisition module and an AI algorithm analysis module, wherein the fire control data acquisition module comprises a fire automatic alarm system data acquisition, a fire hydrant system data acquisition, a spraying system data acquisition, an electric fire monitoring system data acquisition and other intelligent sensing equipment data acquisition, the AI algorithm analysis module is a video monitoring AI algorithm analysis data acquisition, and the fire control data acquisition module and the AI algorithm analysis module acquire data which are uploaded to the data analysis module through the Internet of things.
Further, the data acquisition of the automatic fire alarm system can intelligently identify equipment protocols of various brands and models through intelligent equipment of fire-fighting hosts installed on different brands and models, and the equipment protocols are converted into standard data and uploaded; the data acquisition of the fire hydrant system is that intelligent equipment is arranged at the most unfavorable point at the tail end of the fire hydrant, a sensor acquires pressure data in a fire hydrant pipe network in real time, and whether a monitoring value changes or not is compared in real time; the data acquisition of the spraying system is that intelligent equipment is arranged at the position of the least adverse point at the tail end of spraying, a sensor acquires pressure data in a spraying pipe network in real time, and whether a monitoring value changes or not is compared in real time; the electrical fire monitoring system data acquisition is that an electrical fire detection intelligent device is additionally arranged in a power distribution cabinet, when the electrical fire detection intelligent device is abnormal or current, temperature and voltage parameters of a wire are suddenly changed, the electrical fire monitoring device acquires the information, outputs signals to a monitoring host after processing, and sends out fire alarm signals when the fire alarm signals are recognized, judged, compared and confirmed to exceed a set value through the monitoring host, and an alarm indicator lamp is lightened, alarm sounds are sent out, and data are uploaded; other intelligent sensing equipment data acquisition comprises smoke monitoring system data acquisition and temperature monitoring system data acquisition, wherein the smoke monitoring system data acquisition and temperature monitoring system data acquisition are implemented by installing smoke detection equipment and temperature detection equipment at key monitoring positions, and when the smoke concentration detected by a smoke monitoring unit is greater than a set threshold value or the temperature detected by a temperature monitoring unit is greater than a set threshold value, the monitored data are uploaded;
Further, the video monitoring AI algorithm analyzes data acquisition, and video streaming is transmitted and uploaded by installing cameras in a fire control room and a fire control channel.
Further, the fire data comprises cloud monitoring and fire alarm information on the point positions; the water system data comprises liquid level, water pressure monitoring and water trend analysis; the video data comprises a video AI algorithm and detection alarm information; big data processing includes data mining, processing and storage, and data algorithms, sharing and research.
Further, based on fire alarm information, the fire alarm information is divided into three stages of general fire alarm, abnormal fire alarm and suspected fire alarm, wherein the data sensing equipment is a fire detector, and when the general fire alarm is a fire alarm signal reported by the fire detector, whether the fire alarm exists in the same loop within five minutes is researched, judged and analyzed, and if not, the general fire alarm is judged; when the fire disaster abnormality is detected and the fire detector reports a fire alarm signal, the fire disaster abnormality is judged by researching, judging and analyzing that more than five fire detectors report an alarm continuously within five minutes; when the suspected fire alarm is a fire alarm signal reported by the fire detector, the fire detector continuously alarms in more than five fire detectors on the same loop within five minutes after the analysis is performed, and if the suspected fire alarm is judged to be the suspected fire alarm.
Further, the water system data adopts a data acquisition mechanism, a daily data acquisition mechanism and an alarm data acquisition, wherein the data acquisition mechanism carries out issuing threshold after the data sensing equipment is activated, data of the data sensing equipment is acquired every five minutes, the data is compared with the issuing threshold after being acquired, and the data is uploaded to the operation management module in a changed mode; the daily data acquisition mechanism is that the data acquired by the data sensing equipment is unchanged from the last data, and the operation management module acquires and reports the current data once every twelve hours for archiving; the alarm data acquisition is that the data acquired by the data sensing equipment changes with the last data, the data are immediately reported to the operation management module, and the operation management module judges whether the data exceeds or is lower than the set threshold value to alarm.
Further, the data analysis module further comprises an intelligent power utilization system, the monitored numerical values of the intelligent power utilization system mainly comprise voltage, current, residual current and temperature, a data acquisition mechanism and alarm data acquisition are specifically adopted, the data acquisition mechanism acquires the values of the voltage, the current, the residual current and the temperature once every five minutes for the data sensing equipment, the values are reported to the operation management module, the alarm data acquisition is performed by comparing the acquired values with a set threshold value, and if the alarm data acquisition is performed by performing alarm pushing when the alarm data acquisition is higher than or lower than the threshold value, recording and archiving are performed in the period.
Further, the fire alarm management comprises real-time pushing of fire alarm information, whole alarm process treatment, alarm treatment supervision mechanism and abnormal monitoring of fire water; the supervision project fire safety comprises fire hidden danger level reporting, fire safety research and judgment analysis, remote fire monitoring and week report, month report and year report; the management of the unit facility equipment comprises fire protection and fire protection inspection, facility equipment replacement, point location fault maintenance and hidden danger inspection treatment; the fire-fighting maintenance management comprises maintenance electronic archives, transparency of maintenance processes and closed-loop treatment of maintenance hidden troubles.
Further, the whole alarming process is that an operation management module collects fire alarm signals of a fire engine, pushes notifications to project fire control personnel and patrol personnel within thirty seconds, meanwhile, a remote networking seat telephone is sent to a fire control room, the patrol personnel receives notification to check alarm point position information, and the fire control is confirmed by getting to the scene at the first time, photographing, rechecking and signing uploading; if the alarm information is not rechecked for more than ten minutes, reporting the alarm information to a project manager or a supervisor, performing supervision treatment, and if the alarm information is not rechecked for twenty minutes, pushing the alarm information to a first-stage patch responsible person, and if the alarm information is not rechecked for thirty minutes, reporting the alarm information to a group headquarter responsible person.
Further, fire protection and fire protection inspection is carried out by establishing an inspection task, selecting an inspection point position and a designated date to finish establishing a monthly fire protection inspection for a project manager, and carrying out daily fire protection inspection; after the task is formulated successfully, patrol personnel on the same day of the task receive notification of the patrol task; after a patrol personnel arrives at the patrol position site, scanning a two-dimensional code of the landing point for checking an inspection item, checking hidden danger items, photographing and recording site conditions, and synchronizing to the cloud to form a patrol record; hidden danger found by inspection is also notified by the mobile phone of the engineer, the engineer can intuitively know specific conditions through the mobile phone, and the on-line maintenance tool can be directly carried out to process, so that the processing efficiency is improved; and after the processing of the engineering personnel is completed, the situation after the on-site photographing record maintenance is carried out, and the situation is uploaded to the cloud to form a hidden danger rectifying and modifying processing record.
Further, the display module comprises a fire-fighting large screen display and a mobile phone display; the fire control data, the water system data and the video data of each project are gathered to the display module, a comprehensive supervision platform of fire control 'one picture' is realized, the fire control safety condition, the alarm condition and the fire protection inspection working condition of units are displayed through the picture, headquarter management personnel have visual knowledge of the fire control working condition of each project, hierarchical supervision management, hidden danger investigation and risk early warning full coverage are realized, project fire control conditions are summarized and notified through periodic pushing of weekly report, monthly report, quarternary report and annual report, important support is provided for headquarter scientific decision making and fire control management strategy making, and intelligent, digital and intensive comprehensive supervision level of property groups is improved.
The invention has the beneficial effects that:
1. according to the intelligent fire-fighting centralized unified supervision platform based on the AI, the big data and the Internet of things, which is disclosed by the invention, all project data are uploaded to the display module of the headquarter in a unified way, the headquarter manager can check the fire-fighting working condition of each project in real time through a big screen and a small program, the project in which the problem is concentrated is preferably checked and corrected, the time and the labor are not required to be wasted again and the project point is alternately checked, the pressure of the headquarter management is reduced, and the management efficiency is improved.
2. The intelligent firefighting centralized unified supervision platform based on the AI, the big data and the Internet of things disclosed by the invention can know the operation condition of project firefighting facilities in real time, the disposal condition of basic personnel after an alarm occurs, the daily maintenance service condition of a maintenance company can be clear at a mobile phone end, and professional firefighting daily reports, weekly reports and monthly reports can be provided, so that the management efficiency is improved.
3. The intelligent fire-fighting centralized unified supervision platform based on the AI, the big data and the Internet of things disclosed by the invention clouds all fire-fighting point data, and all alarm, fault and shielding information is clear on a display module at a glance. After the alarm occurs, the fire control staff does not need to check the information of the host computer or report the point positions by using the interphone, all site security guards can process the specific point positions nearby, meanwhile, the platform and each fire control related subsystem realize seamless butt joint, the real-time pushing and calling of the fire scene video picture are realized, the fire alarm disposal efficiency is improved, and the real fire is favorably eliminated in the sprouting state.
4. The intelligent fire-fighting centralized unified supervision platform based on the AI, the big data and the Internet of things disclosed by the invention can be used for directly informing the fault-like problem on the display module, and the maintenance company can flexibly arrange shifts according to the needs and schedule timely repair and maintenance. The maintenance work progress can be synchronized to project unit management personnel, so that management parties can know maintenance contents conveniently, and the quality of service is checked.
5. The intelligent fire control centralized unified supervision platform based on AI, big data and the Internet of things disclosed by the invention integrates all data centers by utilizing an Internet communication means, builds a global coverage and global visual fire prevention and control system, is applied to a plurality of scenes of fire service, and realizes fire alarm management, fire safety supervision, equipment and facility management and video intelligent supervision. Meanwhile, through intercommunication and data sharing of the system, fire safety trend early warning prediction and differential accurate supervision are improved by utilizing the analysis, mining and research and judgment capabilities of the data.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention. The objects and other advantages of the invention may be realized and obtained by means of the instrumentalities and combinations particularly pointed out in the specification.
Drawings
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in the following preferred detail with reference to the accompanying drawings, in which:
FIG. 1 is a structural block diagram of an intelligent fire-fighting centralized unified supervision platform based on AI, big data and the Internet of things;
FIG. 2 is a block diagram of a data acquisition service module in the intelligent fire-fighting centralized monitoring platform based on AI, big data and the Internet of things;
FIG. 3 is an exemplary diagram of a data acquisition service module in the intelligent firefighting centralized unified supervision platform based on AI, big data and the Internet of things;
FIG. 4 is an exemplary diagram of an AI algorithm analysis module in the intelligent fire control centralized unified supervision platform based on AI, big data and Internet of things;
FIG. 5 is an exemplary diagram of an AI algorithm analysis module in the intelligent fire control centralized unified supervision platform based on AI, big data and the Internet of things;
FIG. 6 is an exemplary diagram of an AI algorithm analysis module in the intelligent fire control centralized unified supervision platform based on AI, big data and the Internet of things;
FIG. 7 is a diagram of an example of water system data in the intelligent firefighting centralized unified supervision platform based on AI, big data and the Internet of things;
FIG. 8 is a flow chart of the alarm whole process treatment in the intelligent fire control centralized unified supervision platform based on AI, big data and the Internet of things;
FIG. 9 is a flow chart of fire control and fire protection inspection in the intelligent fire control centralized unified supervision platform based on AI, big data and the Internet of things;
FIG. 10 is a block diagram of an operation management module in the intelligent fire control centralized unified supervision platform based on AI, big data and the Internet of things;
FIG. 11 is an exemplary diagram I of fire safety of a supervision project in an intelligent fire centralized unified supervision platform based on AI, big data and the Internet of things;
FIG. 12 is an exemplary diagram II of the fire safety of a supervision project in an intelligent fire centralized unified supervision platform based on AI, big data and the Internet of things;
FIG. 13 is an exemplary diagram III of fire safety of a supervision project in an intelligent fire centralized unified supervision platform based on AI, big data and the Internet of things;
FIG. 14 is an exemplary diagram IV of the fire safety of a supervision project in an intelligent fire centralized unified supervision platform based on AI, big data and the Internet of things;
FIG. 15 is an exemplary diagram five of the fire safety of a supervision project in an intelligent fire centralized unified supervision platform based on AI, big data and the Internet of things;
FIG. 16 is an exemplary diagram of a unit facility management in a centralized unified supervision platform for intelligent fire protection based on AI, big data and Internet of things in accordance with the present invention;
FIG. 17 is an exemplary diagram II of a unit facility management in an intelligent fire control centralized unified supervision platform based on AI, big data and the Internet of things;
FIG. 18 is an exemplary diagram III of unit facility equipment management in an intelligent firefighting centralized unified supervision platform based on AI, big data and the Internet of things;
FIG. 19 is an exemplary diagram I of fire protection maintenance management in an intelligent fire protection centralized unified supervision platform based on AI, big data and the Internet of things;
FIG. 20 is an exemplary diagram II of fire protection maintenance management in an intelligent fire protection centralized unified supervision platform based on AI, big data and the Internet of things;
FIG. 21 is an exemplary diagram of a display module in the intelligent firefighting centralized unified supervision platform based on AI, big data and the Internet of things;
FIG. 22 is a flowchart showing the fire control process according to the first embodiment;
fig. 23 is a second flowchart of the fire fighting process of the present embodiment.
Detailed Description
Other advantages and effects of the present invention will become apparent to those skilled in the art from the following disclosure, which describes the embodiments of the present invention with reference to specific examples. The invention may be practiced or carried out in other embodiments that depart from the specific details, and the details of the present description may be modified or varied from the spirit and scope of the present invention. It should be noted that the illustrations provided in the following embodiments merely illustrate the basic idea of the present invention by way of illustration, and the following embodiments and features in the embodiments may be combined with each other without conflict.
Wherein the drawings are for illustrative purposes only and are shown in schematic, non-physical, and not intended to limit the invention; for the purpose of better illustrating embodiments of the invention, certain elements of the drawings may be omitted, enlarged or reduced and do not represent the size of the actual product; it will be appreciated by those skilled in the art that certain well-known structures in the drawings and descriptions thereof may be omitted.
The same or similar reference numbers in the drawings of embodiments of the invention correspond to the same or similar components; in the description of the present invention, it should be understood that, if there are terms such as "upper", "lower", "left", "right", "front", "rear", etc., that indicate an azimuth or a positional relationship based on the azimuth or the positional relationship shown in the drawings, it is only for convenience of describing the present invention and simplifying the description, but not for indicating or suggesting that the referred device or element must have a specific azimuth, be constructed and operated in a specific azimuth, so that the terms describing the positional relationship in the drawings are merely for exemplary illustration and should not be construed as limiting the present invention, and that the specific meaning of the above terms may be understood by those of ordinary skill in the art according to the specific circumstances.
The intelligent firefighting centralized unified supervision platform based on AI, big data and the Internet of things as shown in fig. 1-21 comprises a data acquisition service module, a data analysis module, an operation management module and a display module, wherein the data acquisition service module, the data analysis module, the operation management module and the display module are mutually matched to form a flow closed loop so as to control the firefighting situation of all projects and realize centralized unified management.
The embodiment takes the Xiaoxong intelligent fire-fighting cloud platform as an example for unfolding and describing.
Referring to fig. 2-3, the data acquisition service module is configured to perform real-time data acquisition on a data sensing device of the access system, and upload monitoring data acquired through computer resources, storage resources and network resources to the data analysis module through the internet of things. The data acquisition service module comprises a fire control data acquisition module and an AI algorithm analysis module, wherein the fire control data acquisition module comprises a fire automatic alarm system data acquisition module, a fire hydrant system data acquisition module, a spraying system data acquisition module, an electric fire monitoring system data acquisition module and other intelligent sensing equipment data acquisition modules, the AI algorithm analysis module is a video monitoring AI algorithm analysis data acquisition module, and the fire control data acquisition module and the AI algorithm analysis module acquire data which are uploaded to the data analysis module of the intelligent fire control data center platform through the Internet of things.
The fire automatic alarm system data acquisition is through providing a fire control host computer intelligent device that can install at different brand models, can the equipment agreement of each brand model of intelligent identification, converts into standard data, passes through 4G network or wired network to wisdom fire control data center platform.
The intelligent equipment is installed at the most unfavorable point of the tail end of the fire hydrant, the sensor collects pressure data in the fire hydrant pipe network in real time and compares whether the monitoring value changes in real time, otherwise, a platform is not required to be reported, if yes, the intelligent fire control data center platform is reported through an NB or a 4G network, the platform judges whether the intelligent fire control data center platform is in a normal range according to a set threshold value interval, and otherwise, warning pushing related personnel are carried out.
The intelligent equipment is installed at the position of the most unfavorable point at the tail end of spraying, the sensor acquires pressure data in a spraying pipe network in real time and compares whether a monitoring value changes in real time, otherwise, a platform is not required to be reported, if yes, the intelligent fire control data center platform is reported through an NB or a 4G network, the platform judges whether the intelligent fire control data center platform is in a normal range according to a set threshold interval, and otherwise, warning pushing related personnel are carried out.
The electrical fire monitoring system data acquisition is that electrical fire detection intelligent equipment is additionally arranged in a power distribution cabinet, when the equipment is abnormal or parameters such as current, temperature and voltage of a wire are suddenly changed, the electrical fire monitoring equipment acquires the information, signals are output to a monitoring host after the information is processed, the monitoring host sends out fire alarm signals when exceeding a set value is recognized, judged, compared and confirmed through the monitoring host, an alarm indicator lamp is lightened, alarm sounds are sent out, the data are reported to an intelligent fire data center platform through a 4G network, and the platform carries out voice call and message alarm pushing on related personnel.
Other intelligent sensing equipment data collection includes smog monitoring system data collection and temperature monitoring system data collection, and smog monitoring system data collection and temperature monitoring system data collection are through installing smog detection equipment and temperature detection equipment in key monitoring position, and when smog concentration that smog monitoring unit detected is greater than the threshold value of setting or temperature monitoring unit detected is greater than the threshold value of setting, transmit the data information of monitoring to wisdom fire control data center platform through wireless communication unit, and the platform carries out voice call and message warning propelling movement personnel.
Referring to fig. 4-6, the video monitoring AI algorithm analyzes data acquisition, and transmits video streams to an intelligent fire-fighting data center platform by installing cameras in a fire-fighting control room and a fire-fighting channel, and identifies key target objects by distinguishing images in the video streams, when human body information cannot be monitored in the images, the images are reported to the platform for warning pushing, and when a fire-fighting channel image detects that an automobile is illegal to stop in a fire-fighting channel area, the data are automatically reported to the platform for warning pushing. After the video of the control room is accessed, based on the video AI algorithm technology, the off-duty sleeping condition of the staff on duty in the control room is detected in real time, and when the control room is on duty and off duty, an alarm is given, and an alarm message is pushed to a project manager. All-weather off-duty monitoring is realized, the situation that fire alarm cannot be timely processed is avoided, and finally fire disaster is caused. After the video is accessed to the fire control channel, based on intelligent video analysis, the image information is automatically analyzed and identified, the fire control channel blockage is monitored, when the condition that someone illegally occupies the fire control channel is monitored, the alarm prompt is immediately triggered, and the alarm information is simultaneously pushed to patrol posts. All-weather off-duty monitoring is realized. After the video is accessed, based on intelligent video analysis and deep learning technology, the smoke and fire in the monitoring area are identified, and real-time analysis and alarm are realized. And after the smoke and flame appear, the smoke and flame in the video monitoring area are directly and accurately identified. After identification, the alarm information is pushed to patrol personnel, control elimination personnel and project administrators, and relevant personnel quickly arrive at the site for disposal.
The data analysis module comprises fire control data, water system data, video data and big data processing; the data analysis module uploads the obtained hidden danger situation to the operation management module and displays the hidden danger situation on the display module.
The fire control data comprise point position cloud monitoring and fire alarm information, wherein the point position cloud monitoring is that the positioning data of the fire control host computer is cloud, and fire alarm data, fault data, shielding data and the like of the fire control host computer are synchronously acquired in real time.
Based on fire alarm information, the fire alarm system is divided into three stages of general fire alarm, fire abnormality and suspected fire alarm. When the equipment collects the fire alarm signal reported by the fire detector, the data analysis module performs research, judgment and analysis on whether the fire alarm exists on the same loop within five minutes, and if not, the data analysis module judges that the fire alarm exists on the same loop; the fire disaster is abnormal in two stages: when equipment collects fire alarm signals reported by fire detectors, the data analysis module performs research and judgment analysis to ensure that five or more fire detectors continuously alarm within nearly five minutes, and if the five or more fire detectors alarm, the data analysis module judges that the fire alarm is abnormal; the suspected fire alarm is three-stage, when the equipment collects the fire alarm signal reported by the fire detector, the data analysis module performs research, judgment and analysis, and five or more fire detectors on the same loop continuously alarm within five minutes, and if the fire detector alarms, the data analysis module judges the suspected fire alarm.
Referring to fig. 7, the water system data includes liquid level and water pressure monitoring and water consumption trend analysis, and is used for wireless networking of hydraulic and water pressure equipment, realizing the fire water system real-time monitoring function, and collecting monitoring values of water level and water pressure of a fire water tank, a fire pump, a spray pump and a fire partition spray terminal in real time. When the water pressure and liquid level are too low and abnormal, alarm information is pushed to engineering personnel and project management personnel, so that potential safety hazards such as insufficient water pressure of a pipe network, insufficient water level of a water tank/a water pool and the like can be timely found, and no water is available during fire-fighting rescue.
The water system data mainly aims at the liquid level monitoring of a fire fighting water tank and a fire water pond, and the pressure monitoring of the tail ends of an indoor fire hydrant, an outdoor fire hydrant and a spraying system, the hardware mainly comprises a 4G pressure gauge, an NB pressure gauge and a liquid level gauge, the hardware mainly depends on the network environment of installation points, in addition, the fact that the general service life of an aluminum battery is 2-3 years is adopted for power supply of equipment is considered, so that the data acquisition period is used for judging whether the data change or not according to the threshold value issued by a platform, the data reporting is only carried out, and a data acquisition mechanism, a daily data acquisition mechanism and alarm data acquisition are adopted, wherein the specific algorithm is as follows:
1: and the data acquisition mechanism is used for transmitting a threshold value after the equipment is activated, the equipment acquires data once every five minutes, the acquired data is compared with the transmitted threshold value, and the data is changed and is required to be uploaded to the operation management module.
2: and the daily data acquisition mechanism is used for acquiring and reporting the current data once every twelve hours for archiving, wherein the data acquired by the equipment and the last data are unchanged.
3: and (3) alarm data acquisition, wherein if the current acquired data of the equipment changes with the data of the last time, the data are immediately reported to the operation management module, and the platform judges whether the data exceeds or falls below a set threshold value to alarm.
The video data comprises a video AI algorithm and detection alarm information, and the big data processing comprises data mining, processing and storage, and data algorithm, sharing and research and judgment.
The data analysis module further comprises an intelligent power utilization system, wherein the intelligent power utilization system is mainly used for carrying out electric fire monitoring on a strong-current power distribution cabinet and an air switch, and the monitored numerical values mainly comprise voltage, current, residual current and temperature, and the intelligent power utilization system is specifically as follows:
1. data acquisition mechanism
The data sensing device can collect the values of voltage, current, residual current and temperature once every five minutes, and reports the values to the operation management module.
2. Alarm data acquisition
And when the acquired value is compared with a set threshold value, if the acquired value is higher or lower than the threshold value, the alarm pushing is carried out, and recording and archiving are carried out in the period.
Referring to fig. 8 to 21, the operation management module includes fire alarm management, supervision project fire safety, unit facility equipment management and fire maintenance management, and the operation management process and the result state are displayed in the display module and updated and stored in the data acquisition service module.
The operation management module can know worse units according to fire safety scores, the fire alarm and fault alarm numbers are higher in general fire index scores, meanwhile, the operation management module can directly enter the item to know fire specific conditions, and in statistical analysis, multi-dimensional analysis of judgment is carried out on each item, including alarm summarizing analysis on all items, fire alarm statistical analysis on all items, fire alarm false alarm higher unit analysis and fault rate higher unit analysis. And analyzing the historical fire alarm data of all projects, calculating the false alarm rate and the false alarm number, and implementing supervision based on the false alarm rate. The fault condition of the unit fire monitoring points connected to the platform is counted, the number of times and the number of fault points of each unit fault can be checked, the fault rate is calculated, the fire protection regulation fault rate is not more than 3 per mill, and the supervision can be implemented based on the fault rate.
The fire alarm management comprises the real-time pushing of fire alarm information, the whole alarm process treatment, an alarm processing supervision mechanism and the abnormal monitoring of fire water. The point location data of the fire-fighting host is collected to enable the point location data to be cloud, fire alarm data, fault data, shielding data and the like of the fire-fighting host are synchronously collected in real time, and related personnel of units can know the fire-fighting safety operation state in real time through the communication platform in combination with daily fire-fighting safety management requirements of the units. Based on fire control management system and group management requirements, fire information is reported in a hierarchical manner, the large data technology is applied to deepen the real-time alarm data of the fire control host, fire safety analysis reports of all projects are output, a reliable management grip is provided for units, and the problems of island formation, relatively weak informatization and the like of fire control management are solved.
Referring to fig. 8, the platform collects fire alarm signals of the fire engine, pushes the fire alarm signals to project fire control personnel and patrol personnel within thirty seconds, meanwhile, the remote networking agent calls the fire control room, the patrol personnel receives the notification to check the alarm point position information, and the fire control personnel arrive at the scene for confirming the fire condition at the first time, photographs, rechecks and uploads the signature. If the alarm information is not rechecked for more than ten minutes, reporting the alarm information to a project manager or a supervisor, performing supervision treatment, and if the alarm information is not rechecked for twenty minutes, pushing the alarm information to a first-stage patch responsible person, and if the alarm information is not rechecked for thirty minutes, reporting the alarm information to a group headquarter responsible person.
Referring to fig. 10, the supervision project fire safety includes fire hazard level reporting, fire safety research analysis, remote fire monitoring, weekly, monthly and annual reports.
Referring to fig. 11, when a fire alarm occurs, the fire alarm is pushed to a fire control personnel and a patrol personnel in real time through a fire communication applet, and after the patrol post arrives at the scene according to the position information, a photo is taken for rechecking, an electronic signature is carried out, and an alarm reason is uploaded, so that a cloud record is automatically formed.
Referring to fig. 12, when the fire alarm is not rechecked for 10 minutes, the push "10 minutes not rechecked" is reminded to the project manager, and the project manager will prompt the patrol personnel to go to the field for checking after receiving the push.
13-15, the alarm condition processing information synchronizes project administrators in real time, and the fire fighting conditions are consulted at any time, so that patrol posts are guaranteed to process the fire conditions in time. The fire safety report is pushed at 8 points and a half a day. The project manager receives the fire-fighting safety daily report, can know the key data such as alarm, recheck, fault rate, false alarm rate and the like on yesterday projects, can acquire the key data indexes in real time to monitor, and needs to issue and correct if fire-fighting points which cannot meet the requirements of the projects exist, so that the fire-fighting safety is comprehensively improved. Fire control management of groups on some projects has blind areas and lacks efficient management means; the fire control data of each project are communicated to the group through the internet of things technology, the fire control potential safety hazard level report is realized, the daily fire control alarm condition of each project is subjected to data statistics analysis, a report is generated, and the power assisting group easily realizes the supervision of the fire control safety of the project. And generating fire safety operation reports of groups every week, counting the alarming, fault and shielding conditions of all units one by one, and sequencing by fire safety assessment scores, so that the fire safety and hidden danger degree of each unit can be clear at a glance. The group derives the generated monthly and annual fire safety operation reports, so that fire hazards of each project can be periodically known, and correction decisions can be conveniently formed for each project. Based on various fire-fighting work data, statistical analysis is performed, a chart is output, and the work such as fire alarm analysis, fault alarm analysis, false alarm reason analysis and the like are facilitated for related personnel, meanwhile, the statistical analysis on inspection work, hidden danger inspection and the like is included, so that fire-fighting work and operation conditions can be clearly known for the whole project.
The management of the unit facility equipment comprises fire protection and fire protection inspection, facility equipment replacement, point location fault maintenance and inspection hidden danger treatment. The patrol record is carried out based on the mobile phone scanning point position two-dimension code, so that the patrol efficiency is improved, and the patrol post is ensured to be completely searched; hidden danger found by inspection is counted in real time, so that collection and collection of headquarters are facilitated.
Referring to fig. 9 and 16, the project manager completes the creation of a monthly fire check, daily fire check, by creating a patrol task, selecting a patrol point location, designated date. After the task is formulated successfully, patrol personnel on the same day of the task receive notification of the patrol task. After the patrol personnel arrive at the patrol position site, the two-dimension codes of the landing points are scanned for checking the inspection items, hidden danger items are checked, the condition of the photographed recording site is synchronized to the cloud, and the patrol records are formed. Hidden danger found by inspection is also notified by the hidden danger on the mobile phone of the engineer, and the engineer can intuitively know specific conditions through the mobile phone, so that the maintenance tool on the belt can be directly carried to process, and the processing efficiency is improved.
Referring to fig. 17, after the processing of the engineer is completed, the situation after the on-site photographing record maintenance is performed is uploaded to the cloud to form a hidden trouble rectification processing record. The group can also monitor fault maintenance and hidden trouble correction on projects, and generate hidden trouble correction report after finishing monthly correction, so that the integrity rate of each project fire-fighting facility can be known, and the condition of each project maintenance correction can be known.
Referring to fig. 18, full life cycle management is performed for fire-fighting equipment and facilities on the project, and by importing data of the expiration date of the standing account facility in the background, related personnel can be reminded to go to perform replacement, maintenance and other works in advance according to the expiration date of the equipment. Meanwhile, due replacement records and the like can be carried out for fire extinguishers and the like, so that patrol post and project manager are reminded of arranging purchase and replacement after the next due. Ensuring that the fire-fighting equipment keeps good condition.
Referring to fig. 19-20, fire maintenance management includes maintenance electronic archival, maintenance process transparency, and maintenance hidden danger closed loop handling. The maintenance end synchronizes the fire-fighting fault alarming data and the facility equipment inspection hidden trouble data on the project in real time, the maintenance personnel can know the basic conditions on the project at any time and any place, push the notification after the faults and hidden trouble occur, the maintenance personnel can know in time, and the maintenance fault maintenance and hidden trouble correction are facilitated. And meanwhile, maintenance personnel support to make a monthly maintenance plan, photograph and archive each maintenance content, automatically form maintenance records and generate a monthly maintenance report. Both units and maintenance can be consulted at any time. The maintenance end enables the process of fire maintenance work to be transparent and informationized. The unit fire control maintenance management is done to helping hand, realizes the examination to maintenance company maintenance work.
Referring to fig. 21, the display module comprises a property headquarter fire-fighting visual large-screen display and a communication small-program display, and has positioning, supervision, system management and visual functions, so that fire safety real-time comprehensive supervision is realized.
The fire control operation data of the fire automatic alarm system, the fire water system, the intelligent electricity system and the like of each project are converged to the platform, so that a comprehensive supervision platform of fire control 'one image' is realized, the working conditions of unit fire safety conditions, alarm conditions, fire protection inspection and the like can be displayed through the image, a headquarter manager can conveniently and intuitively know the fire control working conditions of each project, hierarchical supervision management, hidden danger investigation and risk early warning full coverage can be realized, project fire control conditions are summarized and notified through periodic pushing of week report, month report, quarter report and year report, important support is provided for headquarter scientific decision making and making of fire control management strategy, and the intelligent, digital and intensive comprehensive supervision level of the property group is improved
By visualizing one graph, the fire safety conditions of all the items can be monitored in real time, and the conditions of all the items can be controlled in real time based on key data indexes. And in the large screen, the fire information, the place, the time, the frequency and the like are subjected to multi-dimensional visual display. The middle GIS map displays the alarming condition of each item, and when a new alarm appears, the unit can timely and accurately display the alarming popup window and the alarming position of the map, thereby providing information support for fire prevention supervision and management and fire fighting rescue. The real-time statistics of alarm conditions including today alarm data, fault number and shielding number can be realized through the visual large-screen display of the property headquarter fire control; displaying the whole outline of the unit through a visual map, and superposing the outline on the map according to point location information for displaying after a fire alarm occurs; monitoring the condition of water system equipment in real time, and displaying in real time after abnormality occurs; and counting the frequent occurrence and fault frequent occurrence point location information of the unit in real time, and checking and connecting maintenance aiming at frequent occurrence point locations.
Referring to the flow chart of the fire control process of the fire fighting, shown in fig. 22-23, when the fire alarm signal is received by the transmitting device, the cloud platform is uploaded, the fire alarm signal is pushed to the mobile phone of the project fire control member, meanwhile, the nearest patrol member can also receive information, the fire control member silences the host and notifies the nearest patrol member again, and the patrol member can find the specific position of the alarm through the mobile phone end and go to confirmation. If ten minutes are not yet checked, the project manager is notified to prompt the nearest patrol man to go to the site for confirmation.
If the fire is actually sent on site, the patrol personnel dials 119 an alarm, simultaneously starts emergency broadcasting and changes the manual state of the host into an automatic state, starts a fire extinguishing and evacuating plan, informs a responsible person of a unit and related personnel in the interior, and photographs and records the event on site by the patrol personnel after the fire is over.
If the false alarm is generated, the reason is checked, the check record is formed by on-site photographing, the false alarm and the reason thereof are notified to the control eliminator, and if the continuous false alarm is generated, the control eliminator is notified to perform batch check.
If the maintenance overhaul is the case, notifying a control elimination member, and setting a maintenance overhaul time period by the control elimination member.
And finally resetting the host by the deghosted person.
The xiaoxun is integrated according to the basic data of alarm and recheck to form the index managed downwards by the manager. The system forms a statistical analysis table and a fire safety weekly report, is convenient for related personnel to manage, examine, collect and adopt, and comprises fire alarm analysis, fault alarm analysis, false alarm reason analysis and the like, and meanwhile comprises the statistical analysis of inspection work, hidden danger of inspection and the like, so that fire protection work and operation condition can be clearly known for the whole project.
The fire-fighting intelligent fire-fighting cloud platform is a platform based on the Internet of things technology, a fire-fighting big data system, a video AI algorithm and other front-edge technologies are deeply applied, functions of fire-fighting data real-time monitoring, fire-fighting inspection, fire-fighting on duty, emergency supervision, water monitoring, fire-fighting maintenance, video intelligent analysis and the like are integrated, early judgment, early discovery, early treatment of patients and early treatment are achieved, important units fire-fighting safety management can be rapidly conducted to achieve intensive management, cost reduction and synergy are achieved, and meanwhile digital transformation of fire-fighting management is rapidly achieved. The main functions are as follows:
1. constructing a fire-fighting automatic induction early warning mechanism, and reporting a hierarchy closed-loop management
The method breaks through the traditional artificial early warning mode, establishes an automatic induction alarm of intelligent sensing equipment, an application platform receives and pushes alarm information to a vanishing person and a patrol person, the patrol person confirms, shoots and signs on site to review the flow, meanwhile, a voice telephone informs the vanishing room, a project safety manager is reported to conduct supervision for ten minutes of early warning without review, meanwhile, a manual agent telephone informs the vanishing room, the hierarchy reporting is conducted in a closed loop mode, the constraint of traditional manual on duty is eliminated, and on-line real-time monitoring, dynamic control, active prevention and quick treatment are realized.
2. Realizing the full-chain closed loop for managing fire hidden trouble
The management flow of 'hidden danger discovery under line, hidden danger disposal under line, supervision personnel on-line spot check correction conditions' is changed, and 'supervision check, hidden danger correction, feedback check' whole-course on-line trace remaining closed-loop management is carried out, so that the transparency and the working efficiency of fire-fighting work are improved.
3. Construction responsibility collaborative fire-fighting assessment system
Based on five index data of fire alarm, fire hidden danger, fire inspection, infrastructure, fire protection maintenance and the like, a data evaluation system is formed by applying intelligent analysis and a system algorithm, and the responsibility of fire control management is compacted by responsibility main bodies in the whole industry and the whole field. The responsibility and the working limit of each post personnel are defined, the evaluation result is taken into the evaluation, and the evaluation result is hooked with the pay prize, so that the evaluation result is changed into real-time evaluation, and the people have pressure and are more motivated.
4. Realizing the supervision of the fire protection maintenance process, so that the information is more standard and transparent
By using the mobile internet technology and combining the fire-fighting maintenance standard requirements of various places, the automatic generation of the fire-fighting maintenance plan, the establishment of maintenance service files, the real-time supervision of the maintenance process, the standardization of maintenance flow and on-line approval are realized, the efficiency is improved, the maintenance work is standardized, transparent and flow, and the maintenance supervision efficiency is improved.
Finally, it is noted that the above embodiments are only for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made thereto without departing from the spirit and scope of the present invention, which is intended to be covered by the claims of the present invention.
Claims (10)
1. The intelligent fire control centralized unified supervision platform based on the AI, the big data and the Internet of things is characterized by comprising a data acquisition service module, a data analysis module, an operation management module and a display module;
the data acquisition service module is used for acquiring real-time data of the data sensing equipment of the access system, acquiring monitoring data through computer resources, storage resources and network resources, and uploading the monitoring data to the data analysis module through the Internet of things;
the data analysis module comprises fire control data, water system data, video data and big data processing; the data analysis module uploads the obtained hidden danger situation to the operation management module and displays the hidden danger situation on the display module;
the operation management module comprises fire alarm management, supervision project fire safety, unit facility equipment management and fire maintenance management, wherein the operation management process and the result state are displayed in the display module and updated and stored in the data acquisition service module;
The display module has the functions of positioning, supervision, system management and visualization;
the data acquisition service module, the data analysis module, the operation management module and the display module are mutually matched to form a flow closed loop.
2. The intelligent fire control centralized monitoring platform based on AI, big data and the Internet of things according to claim 1, wherein the data acquisition service module comprises a fire control data acquisition module and an AI algorithm analysis module, the fire control data acquisition module comprises a fire automatic alarm system data acquisition, a fire hydrant system data acquisition, a spraying system data acquisition, an electric fire monitoring system data acquisition, a smoke monitoring system data acquisition and a temperature monitoring system data acquisition, the AI algorithm analysis module is a video monitoring AI algorithm analysis data acquisition, and the fire control data acquisition module and the AI algorithm analysis module acquire data which are uploaded to the data analysis module through the Internet of things.
3. The intelligent fire control centralized unified supervision platform based on AI, big data and the Internet of things according to claim 2, wherein the automatic fire alarm system data acquisition is used for intelligently identifying equipment protocols of various brand models through intelligent fire control host equipment installed on different brand models, converting the equipment protocols into standard data and uploading the standard data; the data acquisition of the fire hydrant system is that intelligent equipment is arranged at the most unfavorable point at the tail end of the fire hydrant, a sensor acquires pressure data in a fire hydrant pipe network in real time, and whether a monitoring value changes or not is compared in real time; the data acquisition of the spraying system is that intelligent equipment is arranged at the position of the least adverse point at the tail end of spraying, a sensor acquires pressure data in a spraying pipe network in real time, and whether a monitoring value changes or not is compared in real time; the electrical fire monitoring system data acquisition is that an electrical fire detection intelligent device is additionally arranged in a power distribution cabinet, when the electrical fire detection intelligent device is abnormal or current, temperature and voltage parameters of a wire are suddenly changed, the electrical fire monitoring device acquires the information, outputs signals to a monitoring host after processing, and sends out fire alarm signals when the fire alarm signals are recognized, judged, compared and confirmed to exceed a set value through the monitoring host, and an alarm indicator lamp is lightened, alarm sounds are sent out, and data are uploaded; the data acquisition of the smoke monitoring system is that smoke detection equipment is arranged at a key monitoring position, and when the smoke concentration detected by a smoke monitoring unit is greater than a set threshold value, the monitored data is uploaded; and the temperature monitoring system data acquisition is realized by installing temperature detection equipment at a key monitoring position, and when the temperature detected by the temperature monitoring unit is greater than a set threshold value, the monitored data is uploaded.
4. The intelligent firefighting centralized unified supervision platform based on the AI, the big data and the Internet of things according to claim 2, wherein the video monitoring AI algorithm analyzes data acquisition and uploads video streaming by installing cameras in a firefighting room and a firefighting channel.
5. The intelligent firefighting centralized unified supervision platform based on the AI, the big data and the Internet of things according to claim 1, wherein the firefighting data comprises point cloud monitoring and fire alarm information; the water system data comprises liquid level, water pressure monitoring and water trend analysis; the video data comprises a video AI algorithm and detection alarm information; big data processing includes data mining, processing and storage, and data algorithms, sharing and research.
6. The intelligent fire control centralized unified supervision platform based on AI, big data and the Internet of things according to claim 5 is characterized in that based on the fire alarm information, the fire alarm information is divided into three stages of general fire alarm, abnormal fire and suspected fire alarm, the data sensing equipment is a fire detector, when the general fire alarm is a fire alarm signal on the fire detector is detected, whether the fire alarm is detected on the same loop within five minutes is studied, and if not, the general fire alarm is judged; when the fire abnormality is detected and the fire detector reports a fire alarm signal, the fire abnormality is judged by researching, judging and analyzing that more than five fire detectors report an alarm continuously within five minutes; when the suspected fire alarm is a fire alarm signal reported by a fire detector, the fire detector continuously alarms when more than five fire detectors on the same loop in five minutes are analyzed, and if the suspected fire alarm is judged to be the suspected fire alarm.
7. The intelligent fire control centralized unified supervision platform based on AI, big data and the Internet of things according to claim 5, wherein the water system data adopts a data acquisition mechanism, a daily data acquisition mechanism and an alarm data acquisition, the data acquisition mechanism performs a down-sending threshold value after the data sensing equipment is activated, data of the data sensing equipment is acquired every five minutes, the data is compared with the down-sending threshold value after the data acquisition, and the data is uploaded to the operation management module with change; the daily data acquisition mechanism is that the data acquired by the data sensing equipment is unchanged from the last data, and the operation management module acquires and reports the current data once every twelve hours for archiving; the alarm data acquisition is that the data acquired by the data sensing equipment changes with the data acquired once, the data are immediately reported to the operation management module, and the operation management module judges whether the data exceeds or is lower than a set threshold value to alarm.
8. The intelligent firefighting centralized unified supervision platform based on AI, big data and the Internet of things according to claim 1, wherein the firefighting alarm management comprises real-time push of fire alarm information, full-flow alarm treatment, alarm treatment supervision mechanism and firefighting water anomaly monitoring; the supervision project fire safety comprises fire hidden danger level reporting, fire safety research and judgment analysis, remote fire monitoring and week report, month report and year report; the management of the unit facility equipment comprises fire protection and fire protection inspection, facility equipment replacement, point location fault maintenance and hidden danger inspection treatment; the fire-fighting maintenance management comprises maintenance electronic archives, transparency of maintenance processes and closed-loop treatment of maintenance hidden troubles.
9. The intelligent fire control centralized unified supervision platform based on AI, big data and the Internet of things according to claim 8, wherein the whole alarm process is characterized in that an operation management module collects fire alarm signals of a fire control host, pushes notifications to project fire control operators and patrol operators within thirty seconds, meanwhile, a remote networking agent phone calls a fire control room, the patrol operators receive the notification to check alarm point position information, and the first time reaches the scene to confirm fire conditions, photographs, rechecks and uploads signatures; if the alarm information is not rechecked for more than ten minutes, reporting the alarm information to a project manager or a supervisor, performing supervision treatment, and if the alarm information is not rechecked for twenty minutes, pushing the alarm information to a first-stage patch responsible person, and if the alarm information is not rechecked for thirty minutes, reporting the alarm information to a group headquarter responsible person.
10. The intelligent fire-fighting centralized unified supervision platform based on AI, big data and the Internet of things as set forth in claim 1, wherein the display module comprises a fire-fighting big screen display and a mobile phone display; the fire control data, the water system data and the video data of each project are gathered to the display module, so that a comprehensive supervision platform of fire control is realized, the fire control safety condition, the alarm condition and the fire protection inspection work condition of units are displayed through the comprehensive supervision platform, headquarter management personnel have visual knowledge of the fire control work condition of each project, hierarchical supervision management, hidden danger investigation and risk early warning full coverage are realized, and the project fire control condition is summarized and notified through periodic pushing of weekly report, monthly report, quaternary report and annual report.
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| KR20190062871A (en) * | 2017-11-29 | 2019-06-07 | 유재원 | The switchboard fire prevention disaster prevention and diagnosis cloud system for IOT based system |
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| KR20190062871A (en) * | 2017-11-29 | 2019-06-07 | 유재원 | The switchboard fire prevention disaster prevention and diagnosis cloud system for IOT based system |
| CN110933376A (en) * | 2019-12-10 | 2020-03-27 | 成都蜀丽智能化安装工程有限公司 | Fire-fighting Internet of things unified supervision system and method |
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