CN114666370A - SaaS intelligent fire-fighting monitoring platform based on Internet of things technology - Google Patents
SaaS intelligent fire-fighting monitoring platform based on Internet of things technology Download PDFInfo
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- H04L67/00—Network arrangements or protocols for supporting network services or applications
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Abstract
The invention provides a SaaS intelligent fire-fighting monitoring platform based on the technology of the Internet of things, which comprises: a monitoring module: acquiring fire fighting monitoring information in a preset range based on a preset Internet of things and multi-sensor fusion technology; the SaaS analysis module comprises: performing online information type analysis and data conversion processing on the received fire protection monitoring information based on a preset SaaS platform to generate SaaS analysis data; a deployment module: and receiving the SaaS analysis data, and deploying the intelligent fire fighting monitoring platform through the SaaS analysis data.
Description
Technical Field
The invention relates to the technical field of intelligent monitoring platforms and intelligent fire fighting, in particular to a SaaS intelligent fire fighting monitoring platform based on the technology of Internet of things.
Background
The fire control monitoring platform in the prior art generally adopts a wired transmission mode, so that the fire control platform is easy to be blown out when a fire comes, the fire control platform is paralyzed, or data is not timely transmitted, the maintenance cost is high, meanwhile, the fire control monitoring platform can only discover the occurred fire, and irrecoverable manpower and material resource costs are caused.
The published patent CN 113379993 a discloses a SaaS intelligent fire monitoring platform based on internet of things technology, which is used for solving the problem that if a fire breaks out, a data transmission line may be blown out first, so that data cannot be transmitted to the SaaS platform in time, and a fire incident cannot be found in time. But the utilization of the SaaS platform is not comprehensive enough, the renting cost is high, and meanwhile, the processing facing to the fire fighting condition is not intelligent and flexible enough.
Disclosure of Invention
The invention provides a SaaS intelligent fire-fighting monitoring platform based on the technology of the Internet of things, and aims to solve the problems.
The invention provides a SaaS intelligent fire-fighting monitoring platform based on the technology of the Internet of things, which comprises:
a monitoring module: acquiring fire fighting monitoring information in a preset range based on a preset Internet of things and multi-sensor fusion technology;
the SaaS analysis module comprises: performing online information type analysis and data conversion processing on the received fire protection monitoring information based on a preset SaaS platform to generate SaaS analysis data;
a deployment module: and receiving the SaaS analysis data, and deploying the intelligent fire fighting monitoring platform through the SaaS analysis data.
As an embodiment of the present technical solution, the monitoring module includes:
fusing a sensing monitoring unit: the system comprises a plurality of sensing devices, a plurality of sensors and a controller, wherein the sensing devices are used for acquiring sensing monitoring information in a preset range through a preset multi-sensor device, fusing the sensing monitoring information based on a preset multi-sensor fusion technology and determining fused sensing monitoring information; wherein the content of the first and second substances,
the multi-sensing device at least comprises a temperature sensor, a photoelectric sensor and a displacement sensor;
image monitoring information unit: the system comprises a camera device, a display device and a control device, wherein the camera device is used for capturing image monitoring information in a preset range through a preset camera device;
fire control monitoring information unit: the system comprises a monitoring server, a monitoring server and a monitoring server, wherein the monitoring server is used for importing the fused sensing monitoring information and the image monitoring information into a preset control terminal for analysis based on a preset Internet of things, and determining fire protection monitoring information in a preset range;
a wireless transmission unit: the fire fighting online analysis module is used for transmitting the fire fighting monitoring information to the fire fighting online analysis module.
As an embodiment of the present technical solution, the SaaS analysis module includes:
an online analysis unit: the system is used for analyzing and screening the received fire protection monitoring information on line to obtain fire protection screening information;
a data conversion unit: the fire-fighting screening information processing device is used for carrying out data conversion on the fire-fighting screening information to generate fire-fighting screening data;
a data statistics unit: combing and counting fire-fighting screening data based on a preset time line, transmitting the counted fire-fighting screening data to a preset SaaS platform, and acquiring SaaS analysis data.
As an embodiment of the present technical solution, the online analysis unit includes:
information category subunit: matching the fire protection monitoring information with a preset information category to determine the information category corresponding to the fire protection monitoring information; wherein the content of the first and second substances,
the information categories include: fire monitoring sensing type and fire monitoring image type; the fire monitoring image categories include: image type, video type;
a feature extraction subunit: extracting the category characteristics of the fire protection monitoring information based on the information category corresponding to the fire protection monitoring information;
the category features include: a hazard characteristic feature, a hazard potential feature, a safety feature;
screening subunits: screening the fire monitoring information based on the category characteristics to determine a screening result; wherein the content of the first and second substances,
when the screening result is that the category characteristic of the monitoring-preventing information is a dangerous characteristic or a dangerous hidden danger characteristic, the fire-fighting screening information is obtained through screening;
and when the screening result is that the category characteristic of the monitoring-preventing information is a safety characteristic, storing the screening result into a preset cloud storage.
As an embodiment of the present technical solution, the data conversion unit includes:
a cleaning subunit: the system is used for cleaning and analyzing the fire fighting screening information and determining cleaning target information; wherein the content of the first and second substances,
the cleaning target information includes: duplicate information, missing information, abnormal information; wherein, the first and the second end of the pipe are connected with each other,
the missing information is information with missing content or missing format; the abnormal information is information with abnormal numerical value or abnormal format;
a cleaning mode subunit: the system comprises a cleaning target information acquisition module, a cleaning module and a data processing module, wherein the cleaning target information acquisition module is used for acquiring cleaning target information of a fire-fighting object; wherein the content of the first and second substances,
the cleaning mode at least comprises a redundancy removing mode and a duplication removing mode;
data transformation subunit: and the information format is used for identifying the information format of the fire-fighting cleaning information, and the fire-fighting cleaning information is converted and processed based on the information format to generate fire-fighting screening data.
As an embodiment of the present technical solution, the data conversion module is configured to identify an information format of the fire-fighting cleaning information, and perform conversion processing on the fire-fighting cleaning information based on the information format to generate fire-fighting screening data, and includes:
identifying an information format of the fire-fighting cleaning information;
performing conversion matching according to the information format and a preset format database, and determining a conversion type corresponding to the fire-fighting cleaning information;
and converting the cleaning information according to the conversion type to generate fire-fighting screening data.
As an embodiment of the present technical solution, the data statistics unit includes:
a sorting subunit: the system comprises a time marking module, a sorting module and a display module, wherein the time marking module is used for carrying out time marking on fire-fighting screening data according to a time line corresponding to the fire-fighting screening data, and sorting the corresponding fire-fighting screening data according to the size of the mark of the time marking to generate fire-fighting sorting data;
a carding subunit: the system is used for sequentially combing effective data of the fire-fighting sequencing data according to the label sequence corresponding to the fire-fighting sequencing data and determining a combing result; wherein, the first and the second end of the pipe are connected with each other,
when the fire-fighting sequencing data is valid data, the valid data is obtained;
when the fire-fighting sequencing data is invalid data, deleting the invalid data;
the SaaS analysis data subunit: and the statistical effective data are transmitted to a preset SaaS platform to obtain SaaS analysis data.
As an embodiment of the present technical solution, the SaaS analysis data subunit is configured to transmit the counted effective data to a preset SaaS platform, and acquire SaaS analysis data, and includes:
receiving a SaaS service request of a user side based on a preset SaaS platform;
comparing the SaaS service request with a preset service database, and determining the request type of the SaaS service request;
the request categories include: a dangerous characteristic request analysis category and a dangerous hidden danger request analysis category;
based on the dangerous characteristic request analysis category, transmitting corresponding dangerous characteristic effective data in the counted effective data to a preset dangerous degree analysis model to obtain dangerous degree analysis data;
based on the analysis category of the hidden danger request, transmitting corresponding hidden danger effective data in the counted effective data to a preset hidden danger risk prediction model to obtain hidden danger risk analysis data;
and determining SaaS analysis data according to the risk degree analysis data and the hidden danger risk analysis data.
As an embodiment of the present technical solution, the deployment module includes:
an acquisition unit: for obtaining SaaS analysis data set { x1′,x2′,…,xn' data set { x) of SaaS analysis time corresponding to SaaS analysis data1,x2,…,xnData set of SaaS acquisition time corresponding to analysis data of SaaS
And analyzing a time delay unit: for analyzing a data set { x by the SaaS1′,x2′,…,xn' }, data set { x of SaaS analysis time corresponding to SaaS analysis data1,x2,…,xnData set of SaaS acquisition time corresponding to analysis data of SaaS
Calculating SaaS analysis delay
Wherein the content of the first and second substances,
analyzing data x for the p-th SaaS in a data set for a SaaSp' corresponding SaaS analysis time xpAnd all acquisition times ypThe SaaS of (1) analyzes the time delay,
analyzing data x for the p-th SaaS in a data set for a SaaSp' corresponding SaaS analysis time xpAnd the q acquisition time
SaaS analysis of time delay, xpAnalyzing data x for the p-th SaaS in a data set for a SaaSp' corresponding SaaS analysis time, ypAnalyzing data x for the p-th SaaS in a data set for a SaaSp' all of the acquisition times that correspond,
analyzing data x for the p-th SaaS in a data set for a SaaSp' the corresponding q acquisition time, wherein p is variable and is more than or equal to 1 and less than or equal to n;
a minimum transmission speed for transmitting data for the SaaS platform,
analyzing time x for SaaSpIn time, SaaS analyzes data xpThe transmission speed of';
time of analysis for SaaS is xpAnd acquisition time is ypData size of transmission data of time thetapAnalyzing data x for SaaSpThe data size of the' is that tau is an initial time delay influence coefficient and gamma is the initial time delay of the data analyzed by the SaaS platform;
a deployment unit: for analyzing time delay by the SaaS
And calculating the deployment balance rho of the SaaS analysis fire-fighting monitoring platform, and deploying the intelligent fire-fighting monitoring platform based on the deployment balance rho.
As an embodiment of the present technical solution, the deployment unit includes:
average delay subunit: for analyzing the time delay according to the SaaS
And a Dirichlet function D, calculating the average time delay delta of the SaaS analysis fire fighting monitoring platform:
wherein the content of the first and second substances,
for analyzing the p-th SaaS analysis data x in the data set for the SaaSp' corresponding SaaS analysis time xpAnd the qth acquisition time
The dirichlet function of (a) is,
is composed of
Corresponding standard acquisition time; epsilon is an average time delay influence coefficient;
deploying a balanced subunit: for analyzing the time delay according to the SaaS
And SaaS analyzes the average time delay delta of the fire monitoring platform, and calculates the deployment equilibrium rho:
wherein σ is a deployment balance influence coefficient;
deploying the subunits: the intelligent fire fighting monitoring platform is used for carrying out balance adjustment on the platform running speed of the intelligent fire fighting monitoring platform through the deployment balance rho and deploying the intelligent fire fighting monitoring platform after the balance adjustment;
the operation speed of the platform at least comprises a SaaS acquisition speed, a SaaS analysis data speed and a SaaS analysis time delay.
The invention has the following beneficial effects:
compared with the prior art, the technical scheme improves the supervision efficiency of the fire platform through online service analysis, and meanwhile, based on the SaaS service platform, the cost of establishing the platform by the user is saved, and meanwhile, core products, services and solutions are improved for the user, and sustainable value and potential increase are created.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
fig. 1 is a block diagram of a SaaS intelligent fire monitoring platform based on internet of things technology in an embodiment of the present invention;
fig. 2 is a block diagram of a monitoring module in a SaaS intelligent fire monitoring platform based on internet of things technology in the embodiment of the present invention;
fig. 3 is a block diagram of a SaaS analysis module in a SaaS intelligent fire monitoring platform based on internet of things technology in an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
It will be understood that when an element is referred to as being "secured to" or "disposed on" another element, it can be directly on the other element or be indirectly on the other element. When an element is referred to as being "connected to" another element, it can be directly or indirectly connected to the other element.
It will be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like, as used herein, refer to an orientation or positional relationship indicated in the drawings that is solely for the purpose of facilitating the description and simplifying the description, and do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and is therefore not to be construed as limiting the invention.
Moreover, it is noted that, in this document, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions, and "a plurality" means two or more unless specifically limited otherwise. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Example 1:
as shown in fig. 1, an embodiment of the present invention provides an SaaS intelligent fire monitoring platform based on an internet of things technology, including:
a monitoring module: acquiring fire fighting monitoring information in a preset range based on a preset Internet of things and multi-sensor fusion technology;
the SaaS analysis module comprises: performing online information type analysis and data conversion processing on the received fire protection monitoring information based on a preset SaaS platform to generate SaaS analysis data;
a deployment module: and receiving the SaaS analysis data, and deploying the intelligent fire fighting monitoring platform through the SaaS analysis data.
The working principle of the technical scheme is as follows:
the SaaS (Software-as-a-Service) intelligent fire-fighting monitoring platform comprises a monitoring module, a SaaS analysis module and a deployment module, wherein the monitoring module acquires fire-fighting monitoring information by using a multi-sensor device, screens and processes the fire-fighting monitoring information, and acquires fire-fighting detection information of different monitoring reception by using a multi-sensor fusion technology at different monitoring nodes on an Internet of things through the monitoring module, the SaaS analysis module performs online information category analysis and data conversion processing on the received fire-fighting monitoring information based on a preset SaaS platform, the SaaS platform is a Software layout model which is specially designed for network delivery and is convenient for a user to host and deploy through the Internet, so that the Service requirement of the user can be analyzed and solved online, the SaaS platform generates SaaS analysis data, and the deployment module receives the SaaS analysis data, and deploying the intelligent fire-fighting monitoring platform through SaaS analysis data, thereby optimizing the configuration of the intelligent fire-fighting monitoring platform.
The beneficial effects of the above technical scheme are:
compared with the prior art, the technical scheme improves the supervision efficiency of the fire platform through online service analysis, and meanwhile, based on the SaaS service platform, the cost for establishing the platform by the user is saved, and meanwhile, core products, services and solutions are improved for the user, and sustainable value and potential increase are created.
Example 2:
as shown in fig. 2, the present technical solution provides an embodiment, where the monitoring module includes:
a fusion sensing monitoring unit: the system comprises a plurality of sensing devices, a plurality of sensors and a controller, wherein the sensing devices are used for acquiring sensing monitoring information in a preset range through a preset multi-sensor device, fusing the sensing monitoring information based on a preset multi-sensor fusion technology and determining fused sensing monitoring information; wherein the content of the first and second substances,
the multi-sensing device at least comprises a temperature sensor, a photoelectric sensor and a displacement sensor;
image monitoring information unit: the system comprises a camera device, a display device and a control device, wherein the camera device is used for capturing image monitoring information in a preset range through a preset camera device;
fire control monitoring information unit: the system comprises a monitoring server, a monitoring server and a monitoring server, wherein the monitoring server is used for importing the fused sensing monitoring information and the image monitoring information into a preset control terminal for analysis based on a preset Internet of things, and determining fire protection monitoring information in a preset range;
a wireless transmission unit: the fire fighting online analysis module is used for transmitting the fire fighting monitoring information to the fire fighting online analysis module.
The working principle of the technical scheme is as follows:
the technical scheme includes that the system comprises a fusion sensing monitoring unit, an image monitoring information unit, a fire protection monitoring information unit and a wireless transmission unit, wherein the wireless transmission unit is used for wirelessly transmitting fire protection monitoring information to a fire protection analysis module through the Internet of things; the fire monitoring information comprises sensing monitoring information and image monitoring information; the fire control monitoring information unit is used for acquiring sensing monitoring information and image monitoring information, the sensing monitoring information in a preset range is collected through a preset sensing device (a temperature sensor, a photoelectric sensor and a displacement sensor) and transmitted to the wireless transmission unit by the fusion sensing monitoring unit, and the image monitoring information unit is used for collecting the image monitoring information in the preset area through preset camera equipment such as a panoramic camera and transmitting the image monitoring information to the wireless transmission unit.
The beneficial effects of the above technical scheme are:
compared with the prior art, this technical scheme carries out contrast each other through camera device and sensor device, detects out the fire control situation in the monitoring range, whether for example need the fire control situation to based on corresponding fire control situation, to corresponding sensor device data acquisition, provide raw data for the analysis of following fire control situation.
Example 3:
as shown in fig. 3, the present technical solution provides an embodiment, where the SaaS analysis module includes:
an online analysis unit: the system is used for analyzing and screening the received fire protection monitoring information on line to obtain fire protection screening information;
a data conversion unit: the fire-fighting screening information processing device is used for carrying out data conversion on the fire-fighting screening information to generate fire-fighting screening data;
a data statistics unit: combing and counting fire-fighting screening data based on a preset time line, transmitting the counted fire-fighting screening data to a preset SaaS platform, and acquiring SaaS analysis data.
The working principle of the technical scheme is as follows:
the SaaS analysis module comprises an online analysis unit, a data conversion unit and a data statistics unit, wherein the online analysis unit is used for analyzing and screening received fire protection monitoring information on line to obtain fire protection screening information, screening the received fire protection monitoring information according to the fire protection monitoring information, identifying and analyzing the fire protection monitoring information according to the fire protection monitoring information category, identifying and analyzing sensing monitoring information into first fire protection monitoring information, determining the sensing monitoring category of the sensing monitoring information by comparing and classifying the sensing monitoring information in the first fire protection monitoring information, and grouping the sensing monitoring information according to the sensing monitoring category to generate a plurality of sensing data groups; image monitoring information image identification analysis is second fire control monitoring information, fire control monitoring information comprises first fire control monitoring information and second fire control monitoring information at least, the conversion unit is used for carrying out data conversion to fire control screening information, generate fire control screening data, convert the data of different data source data formats, standardized data, the data statistics unit combs and makes statistics of fire control screening data based on the time line of predetermineeing, fire control screening data after will making statistics transmit to predetermined SaaS platform, obtain SaaS analytic data, through SaaS analytic data, can match user's business demand, provide corresponding service.
The beneficial effects of the above technical scheme are: .
Compared with the prior art, the technical scheme receives the fire-fighting data and the user data through the SaaS platform, analyzes the service required by the user data, can timely acquire the fire-fighting data on line, and has timeliness and timeliness.
Example 4:
the present technical solution provides an embodiment, wherein the online analysis unit includes:
information category subunit: matching the fire protection monitoring information with a preset information category to determine the information category corresponding to the fire protection monitoring information; wherein the content of the first and second substances,
the information categories include: fire monitoring sensing type and fire monitoring image type; the fire monitoring image categories include: image type, video type;
a feature extraction subunit: extracting the category characteristics of the fire protection monitoring information based on the information category corresponding to the fire protection monitoring information;
the category features include: a hazard characteristic feature, a hazard potential feature, a safety feature;
screening subunits: screening the fire monitoring information based on the category characteristics to determine a screening result; wherein the content of the first and second substances,
when the screening result is that the category characteristic of the monitoring-preventing information is a dangerous characteristic or a dangerous hidden danger characteristic, the fire-fighting screening information is obtained through screening;
and when the screening result is that the category characteristic of the monitoring-preventing information is a safety characteristic, storing the screening result into a preset cloud storage.
The working principle of the technical scheme is as follows:
the online analysis unit comprises an information classification subunit, a feature extraction subunit and a screening subunit, wherein the information classification subunit matches the fire protection monitoring information with a preset information classification to determine the information classification corresponding to the fire protection monitoring information; the information category comprises a fire monitoring sensing category and a fire monitoring image category, and the fire monitoring image category can also divide corresponding monitoring images to determine monitoring areas corresponding to the monitoring images; the fire monitoring image category comprises an image category and an image category; the characteristic extraction subunit extracts the category characteristics of the fire monitoring information based on the information category corresponding to the fire monitoring information, extracts the corresponding characteristics about fire danger and fire hidden danger, and can also record the number of the fire hidden danger characteristics and generate a symbolic marking serial number, wherein the category characteristics comprise danger characteristic characteristics, danger hidden danger characteristics and safety characteristics; the screening subunit screens the fire monitoring information based on the category characteristics to determine a screening result; when the screening result is that the category characteristic of the monitoring-preventing information is a dangerous characteristic or a dangerous hidden danger characteristic, the fire-fighting screening information is obtained through screening; when the screening result is that the category characteristics of the monitoring-preventing information are safety characteristics, the screening result is stored in a preset cloud storage, and the fire protection condition of a monitoring area needs to be evaluated and analyzed by a fire protection monitoring platform, so that the technical scheme divides the fire protection condition into three types, namely an danger characteristic, a danger hidden danger characteristic and a safety characteristic, provides different services for users according to different characteristics, and improves user experience.
The beneficial effects of the above technical scheme are:
according to the technical scheme, the situation of the monitoring area is divided, danger occurs, namely dangerous characteristic characteristics and dangerous hidden danger characteristics are easily caused, the dangerous hidden danger and safety characteristics are divided into three grades, different model channels are used in each grade, and the problem solving efficiency is improved.
Example 5:
this technical solution provides an embodiment, and the data conversion unit includes:
a cleaning subunit: the system is used for cleaning and analyzing the fire fighting screening information and determining cleaning target information; wherein the content of the first and second substances,
the cleaning target information includes: duplicate information, missing information, abnormal information; wherein the content of the first and second substances,
the missing information is information with missing content or missing format; the abnormal information is information with abnormal numerical value or abnormal format;
a cleaning mode subunit: the system comprises a cleaning target information acquisition module, a cleaning module and a data processing module, wherein the cleaning target information acquisition module is used for acquiring cleaning target information of a fire-fighting object; wherein the content of the first and second substances,
the cleaning mode at least comprises a redundancy removing mode and a duplication removing mode;
data transformation subunit: and the information format is used for identifying the information format of the fire-fighting cleaning information, and the fire-fighting cleaning information is converted and processed based on the information format to generate fire-fighting screening data.
The working principle of the technical scheme is as follows:
the data conversion unit of the technical scheme comprises a cleaning subunit, a cleaning mode subunit and a data conversion subunit, wherein the cleaning subunit is used for cleaning and analyzing the fire fighting screening information and determining cleaning target information; the cleaning target information comprises repeated information, missing information and abnormal information; the missing information is information with missing content or missing format; the abnormal information is information with abnormal numerical value or abnormal format; the cleaning mode subunit is used for performing mode matching according to the cleaning target information and a preset cleaning database to obtain a cleaning mode corresponding to the cleaning target, performing filtering judgment according to a data error rate corresponding to the cleaning target information and an error rate allowed by the preset cleaning database, judging whether cleaning processing is needed or not, performing cleaning processing according to the cleaning mode, and generating fire-fighting cleaning information; the cleaning mode at least comprises a redundancy removing mode and a duplication removing mode and is used for improving the quality of the acquired data, the data conversion unit is used for identifying the information format of the fire-fighting cleaning information, converting the fire-fighting cleaning information based on the information format to generate fire-fighting screening data, and standardizing the fire-fighting data.
The beneficial effects of the above technical scheme are:
according to the technical scheme, the acquired data are cleaned, converted, standardized and formatted, so that the normalization of the data is improved, the data quality is improved, and high-quality and high-efficiency source data are provided for subsequent data processing and reading.
Example 6:
the technical scheme provides an embodiment, the data conversion module is used for identifying an information format of fire-fighting cleaning information, and converting the fire-fighting cleaning information based on the information format to generate fire-fighting screening data, and the data conversion module comprises:
identifying an information format of the fire-fighting cleaning information;
performing conversion matching according to the information format and a preset format database, and determining a conversion type corresponding to the fire-fighting cleaning information;
and converting the cleaning information according to the conversion type to generate fire-fighting screening data.
The working principle of the technical scheme is as follows:
the technical scheme includes that a data conversion unit is used for identifying an information format of fire-fighting cleaning information, converting the fire-fighting cleaning information based on the information format to generate fire-fighting screening data, classifying the fire-fighting cleaning information according to the format, screening fire-fighting variables according to the format type, and determining a conversion type corresponding to the fire-fighting cleaning information, wherein the information format comprises information with different formats such as different file formats, continuous or discrete formats, and ordered or unordered formats, so that the cleaning information is converted according to the conversion type preset by a SaaS platform to generate the fire-fighting screening data, and the acquired data is normalized.
The beneficial effects of the above technical scheme are:
according to the technical scheme, the fire fighting screening data are acquired, metadata are improved for standardization of the SaaS platform, different data are processed, and the precision of the SaaS platform for providing requirements for users is improved.
Example 7:
this technical solution provides an embodiment, and the data statistics unit includes:
a sorting subunit: the system comprises a time marking module, a sorting module and a display module, wherein the time marking module is used for carrying out time marking on fire-fighting screening data according to a time line corresponding to the fire-fighting screening data, and sorting the corresponding fire-fighting screening data according to the size of the mark of the time marking to generate fire-fighting sorting data;
a carding subunit: the system is used for sequentially combing effective data of the fire-fighting sequencing data according to the label sequence corresponding to the fire-fighting sequencing data and determining a combing result; wherein the content of the first and second substances,
when the fire-fighting sequencing data is valid data, the valid data is obtained;
when the fire-fighting sequencing data is invalid data, deleting the invalid data;
the SaaS analysis data subunit: and the statistical effective data are transmitted to a preset SaaS platform to obtain SaaS analysis data.
The working principle of the technical scheme is as follows:
the data statistical unit of the technical scheme comprises a sequencing subunit and a combing subunit, wherein the sequencing subunit is used for carrying out time labeling on fire-fighting screening data according to a time line corresponding to the fire-fighting screening data, the fire-fighting data can pass through a data line to further dig out a source of a fire disaster, so that the workload of workers is reduced, time labeling is carried out on the fire-fighting screening data, the corresponding fire-fighting screening data is sequenced according to the label size of the time label to generate fire-fighting sequencing data, and the fire-fighting data is sequenced in sequence, so that the time sequence logic of fire fighting can be clarified, the data can be more easily combed, the combing subunit is used for sequentially combing effective data of the fire-fighting sequencing data according to the label sequence corresponding to the fire-fighting sequencing data to determine a combing result, the effective data are data useful for analyzing the fire-fighting condition, and when a large number of data characteristics are extracted, similar images can be deleted, and the working efficiency of the terminal is improved. When the fire-fighting sequencing data is valid data, the valid data is obtained; when the fire-fighting sequencing data is invalid data, the invalid data is deleted, the SaaS analysis data subunit is used for transmitting the counted valid data to a preset SaaS platform, the SaaS analysis data are obtained, corresponding analysis is conducted on fire fighting conditions through the analysis data, and corresponding dangerous scenes are conveniently analyzed and predicted.
The beneficial effects of the above technical scheme are:
according to the technical scheme, corresponding SaaS analysis data are generated by analyzing the fire fighting condition, the corresponding fire fighting condition is deduced and predicted according to the service requirement of the user, a corresponding solution is generated, the working efficiency of workers is improved, and the workload is reduced.
Example 8:
the technical solution provides an embodiment, where the SaaS analysis data subunit is configured to transmit the counted effective data to a preset SaaS platform, and acquire SaaS analysis data, and includes:
receiving a SaaS service request of a user side based on a preset SaaS platform;
comparing the SaaS service request with a preset service database, and determining the request type of the SaaS service request;
the request categories include: a dangerous characteristic request analysis category and a dangerous hidden danger request analysis category;
based on the dangerous characteristic request analysis category, transmitting corresponding dangerous characteristic effective data in the counted effective data to a preset dangerous degree analysis model to obtain dangerous degree analysis data;
based on the analysis category of the hidden danger request, transmitting corresponding hidden danger effective data in the counted effective data to a preset hidden danger risk prediction model to obtain hidden danger risk analysis data;
and determining SaaS analysis data according to the risk degree analysis data and the hidden danger risk analysis data.
The working principle of the technical scheme is as follows:
the technical scheme includes that the counted effective data are transmitted to a preset SaaS platform, SaaS service requests of a user side are received, the service requests of the user can include monitoring of a corresponding monitoring platform, scheme analysis acquisition, hidden danger problem handling or optimization processing of an intelligent fire protection monitoring platform, the SaaS service requests are compared with a preset service database, and request types of the SaaS service requests are determined; the request categories include: a dangerous characteristic request analysis category and a dangerous hidden danger request analysis category; classifying different user service requirements so as to enter different solving channels, solving problems in multiple processes simultaneously, improving working efficiency, requesting analysis categories based on dangerous characteristics, transmitting corresponding dangerous characteristic effective data in the counted effective data to a preset dangerous degree analysis model, and acquiring dangerous degree analysis data; the risk degree analysis model is used for analyzing and dividing the degree of the occurred risks, quickly providing a solution corresponding to a user, transmitting the corresponding risk potential effective data in the counted effective data to a preset potential risk prediction model based on the risk potential request analysis category, and acquiring the risk potential risk analysis data, wherein the risk prediction model is used for processing the potential risks of the monitoring area, so that the safety of the monitoring area is improved.
The beneficial effects of the above technical scheme are: and processing the service requirements through the divided different channels, and classifying the service requirements of the users. Thereby carry out risk degree evaluation to different fire control condition, improve the efficiency analysis speed to different fire control condition, shorten the reaction time that the time takes place.
Example 9:
the technical solution provides an embodiment, where the deployment module includes:
an acquisition unit: for obtaining SaaS analysis data set { x1′,x2′,…,xn' }, data set { x of SaaS analysis time corresponding to SaaS analysis data1,x2,…,xnData set of SaaS acquisition time corresponding to analysis data of SaaS
And analyzing a time delay unit: for analyzing a data set { x by the SaaS1′,x2′,…,xn' }, data set { x of SaaS analysis time corresponding to SaaS analysis data1,x2,…,xnData set of SaaS acquisition time corresponding to analysis data of SaaS
Calculating SaaS analysis delay
Wherein the content of the first and second substances,
analyzing data x for the p-th SaaS in a data set for a SaaSp' corresponding SaaS analysis time xpAnd all acquisition times ypThe SaaS of (1) analyzes the time delay,
analyzing data x for the p-th SaaS in a data set for a SaaSp' corresponding SaaS analysis time xpAnd the q acquisition time
SaaS analysis of time delay, xpAnalyzing data x for the p-th SaaS in a data set for a SaaSp' corresponding SaaS analysis time, ypAnalyzing data x for the p-th SaaS in a data set for a SaaSp' all of the acquisition times that correspond,
analyzing data x for the p-th SaaS in a data set for a SaaSp' the corresponding q acquisition time, wherein p is variable and is more than or equal to 1 and less than or equal to n;
the minimum transmission speed for the SaaS platform to transmit data,
analyzing time x for SaaSpIn time, SaaS analyzes data xpThe transmission speed of';
time of analysis for SaaS xpAnd acquisition time is ypData size of transmission data of time thetapAnalyzing data x for SaaSpThe data size of the' is that tau is an initial time delay influence coefficient and gamma is the initial time delay of the data analyzed by the SaaS platform;
a deployment unit: for analyzing time delay by the SaaS
Calculating a deployment balance rho of the SaaS analysis fire-fighting monitoring platform, and deploying the intelligent fire-fighting monitoring platform based on the deployment balance rho;
the working principle of the technical scheme is as follows: in the prior art, single management is usually carried out on the calculation speed or transmission arrangement and transmission, although the adjustment is simple and the data processing speed is obviously changed, the optimal acquisition, transmission and analysis control of a platform is difficult to realize; in the technical scheme, the platform data analysis delay calculation is carried out through the analysis time of the platform analysis data and the acquisition time corresponding to the analyzed data, the data acquisition time and the number of the data acquisition devices can be regulated and controlled through the delay calculation, the deployment balance is calculated through the analysis delay, and the platform is deployed according to the deployment balance;
the beneficial effects of the above technical scheme are: through time delay analysis, the analysis efficiency of platform deployment is greatly improved, the influence factors of the platform efficiency are visually displayed, and the monitoring strength and the analysis strength of the platform on fire-fighting data are greatly mastered by adjusting the deployment balance.
Example 10:
the technical solution provides an embodiment, where the deployment unit includes:
average delay subunit: for analyzing the time delay according to the SaaS
And a Dirichlet function D, calculating the average time delay delta of the SaaS analysis fire-fighting monitoring platform:
wherein the content of the first and second substances,
for analyzing the p-th SaaS analysis data x in the data set for the SaaSp' corresponding SaaS analysis time xpAnd the q acquisition time
The dirichlet function of (a) is,
is composed of
Corresponding standard acquisition time; epsilon is an average time delay influence coefficient;
deploying a balancing subunit: for analyzing the time delay according to the SaaS
And SaaS analyzes the average time delay delta of the fire monitoring platform, and calculates the deployment equilibrium rho:
wherein σ is a deployment balance influence coefficient;
deploying the subunits: the intelligent fire fighting monitoring platform is used for carrying out balance adjustment on the platform running speed of the intelligent fire fighting monitoring platform through the deployment balance rho and deploying the intelligent fire fighting monitoring platform after balance adjustment;
the running speed of the platform at least comprises a SaaS acquisition speed, a SaaS analysis data speed and a SaaS analysis time delay;
the working principle of the technical scheme is as follows: in the calculation of the deployment unit, calculating average time delay by analyzing the time delay and a preset Dirichlet function, and calculating deployment balance according to the average time delay, wherein the deployment balance is used for comparison when the platform running speed of the intelligent fire-fighting monitoring platform is adjusted;
the beneficial effects of the above technical scheme are: the method improves the pertinence of deployment balance by calculating the average time delay, and can perform specific adjustment of a certain direction on platform deployment through the real-time deployment balance when the platform deployment is adjusted, thereby reducing the platform deployment difficulty and improving the deployment efficiency.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. The utility model provides a SaaS intelligence fire control monitor platform based on internet of things, includes:
a monitoring module: acquiring fire fighting monitoring information in a preset range based on a preset Internet of things and multi-sensor fusion technology;
the SaaS analysis module comprises: performing online information type analysis and data conversion processing on the received fire protection monitoring information based on a preset SaaS platform to generate SaaS analysis data;
a deployment module: and receiving the SaaS analysis data, and deploying the intelligent fire fighting monitoring platform through the SaaS analysis data.
2. The SaaS intelligent fire-fighting monitoring platform based on the Internet of things technology as claimed in claim 1, wherein the monitoring module comprises:
a fusion sensing monitoring unit: the system comprises a plurality of sensing devices, a plurality of sensors and a controller, wherein the sensing devices are used for acquiring sensing monitoring information in a preset range through a preset multi-sensor device, fusing the sensing monitoring information based on a preset multi-sensor fusion technology and determining fused sensing monitoring information; wherein the content of the first and second substances,
the multi-sensing device at least comprises a temperature sensor, a photoelectric sensor and a displacement sensor;
image monitoring information unit: the system comprises a camera device, a display device and a control device, wherein the camera device is used for capturing image monitoring information in a preset range through a preset camera device;
fire control monitoring information unit: the system comprises a monitoring server, a monitoring server and a monitoring server, wherein the monitoring server is used for importing the fused sensing monitoring information and the image monitoring information into a preset control terminal for analysis based on a preset Internet of things, and determining fire protection monitoring information in a preset range;
a wireless transmission unit: the fire fighting online analysis module is used for transmitting the fire fighting monitoring information to the fire fighting online analysis module.
3. The SaaS intelligent fire-fighting monitoring platform based on the Internet of things technology as claimed in claim 1, wherein the SaaS analysis module comprises:
an online analysis unit: the system is used for analyzing and screening the received fire protection monitoring information on line to obtain fire protection screening information;
a data conversion unit: the fire-fighting screening information processing device is used for carrying out data conversion on the fire-fighting screening information to generate fire-fighting screening data;
a data statistics unit: combing and counting fire-fighting screening data based on a preset time line, transmitting the counted fire-fighting screening data to a preset SaaS platform, and acquiring SaaS analysis data.
4. The SaaS intelligent fire-fighting monitoring platform based on the Internet of things technology as claimed in claim 3, wherein the online analysis unit comprises:
information category subunit: matching the fire protection monitoring information with a preset information category to determine the information category corresponding to the fire protection monitoring information; wherein the content of the first and second substances,
the information categories include: fire monitoring sensing type and fire monitoring image type; the fire monitoring image categories include: image type, video type;
a feature extraction subunit: extracting the category characteristics of the fire protection monitoring information based on the information category corresponding to the fire protection monitoring information;
the category features include: a hazard characteristic feature, a hazard potential feature, a safety feature;
screening subunits: screening the fire monitoring information based on the category characteristics, and determining a screening result; wherein, the first and the second end of the pipe are connected with each other,
when the screening result is that the category characteristic of the monitoring-preventing information is a dangerous characteristic or a dangerous hidden danger characteristic, the fire-fighting screening information is obtained through screening;
and when the screening result is that the category characteristic of the monitoring-preventing information is a safety characteristic, storing the screening result into a preset cloud storage.
5. The SaaS intelligent fire-fighting monitoring platform based on the Internet of things technology as claimed in claim 3, wherein the data conversion unit comprises:
a cleaning subunit: the system is used for cleaning and analyzing the fire fighting screening information and determining cleaning target information; wherein the content of the first and second substances,
the cleaning target information includes: duplicate information, missing information, abnormal information; wherein the content of the first and second substances,
the missing information is information with missing content or missing format; the abnormal information is information with abnormal numerical value or abnormal format;
a cleaning mode subunit: the system is used for carrying out mode matching according to the cleaning target information and a preset cleaning database, obtaining a cleaning mode corresponding to the cleaning target, carrying out cleaning treatment according to the cleaning mode and generating fire-fighting cleaning information; wherein the content of the first and second substances,
the cleaning mode at least comprises a redundancy removing mode and a duplication removing mode;
data transformation subunit: and the information format is used for identifying the information format of the fire-fighting cleaning information, and the fire-fighting cleaning information is converted and processed based on the information format to generate fire-fighting screening data.
6. The SaaS intelligent fire-fighting monitoring platform based on the Internet of things technology as claimed in claim 5, wherein the data conversion module is configured to identify an information format of fire-fighting cleaning information, and based on the information format, convert the fire-fighting cleaning information to generate fire-fighting screening data, and includes:
identifying the information format of the fire-fighting cleaning information;
performing conversion matching according to the information format and a preset format database, and determining a conversion type corresponding to the fire-fighting cleaning information;
and converting the cleaning information according to the conversion type to generate fire-fighting screening data.
7. The SaaS intelligent fire-fighting monitoring platform based on the Internet of things technology as claimed in claim 3, wherein the data statistics unit comprises:
a sorting subunit: the system comprises a time marking module, a sorting module and a display module, wherein the time marking module is used for carrying out time marking on fire-fighting screening data according to a time line corresponding to the fire-fighting screening data, and sorting the corresponding fire-fighting screening data according to the size of the mark of the time marking to generate fire-fighting sorting data;
a carding subunit: the system is used for sequentially combing effective data of the fire-fighting sequencing data according to the label sequence corresponding to the fire-fighting sequencing data and determining a combing result; wherein the content of the first and second substances,
when the fire-fighting sequencing data is valid data, the valid data is obtained;
when the fire-fighting sequencing data is invalid data, deleting the invalid data;
the SaaS analysis data subunit: and the statistical effective data are transmitted to a preset SaaS platform to obtain SaaS analysis data.
8. The SaaS intelligent fire-fighting monitoring platform based on the IOT technology of claim 7, wherein the SaaS analysis data subunit is used for transmitting the counted effective data to a preset SaaS platform to acquire SaaS analysis data, and comprises:
receiving a SaaS service request of a user side based on a preset SaaS platform;
comparing the SaaS service request with a preset service database, and determining the request type of the SaaS service request;
the request categories include: a dangerous characteristic request analysis category and a dangerous hidden danger request analysis category;
based on the dangerous characteristic request analysis category, transmitting corresponding dangerous characteristic effective data in the counted effective data to a preset dangerous degree analysis model to obtain dangerous degree analysis data;
based on the analysis category of the hidden danger request, transmitting corresponding hidden danger effective data in the counted effective data to a preset hidden danger risk prediction model to obtain hidden danger risk analysis data;
and determining SaaS analysis data according to the risk degree analysis data and the hidden danger risk analysis data.
9. The SaaS intelligent fire-fighting monitoring platform based on the Internet of things technology as claimed in claim 1, wherein the deployment module comprises:
an acquisition unit: the SaaS analysis system is used for acquiring SaaS analysis data, SaaS analysis time corresponding to the SaaS analysis data and SaaS acquisition time corresponding to the SaaS analysis data;
and analyzing a time delay unit: the SaaS analysis time delay calculation module is used for calculating the SaaS analysis time delay according to the SaaS analysis data, the SaaS analysis time corresponding to the SaaS analysis data and the SaaS acquisition time corresponding to the SaaS analysis data;
a deployment unit: the method is used for calculating the deployment balance of the SaaS analysis fire-fighting monitoring platform through the SaaS analysis time delay, and deploying the intelligent fire-fighting monitoring platform based on the deployment balance.
10. The SaaS intelligent fire-fighting monitoring platform based on the Internet of things technology as claimed in claim 9, wherein the deployment unit comprises:
average delay subunit: the method is used for calculating the average time delay of the SaaS analysis fire monitoring platform according to the SaaS analysis time delay and a preset Dirichlet function:
deploying a balanced subunit: and calculating the deployment balance according to the SaaS analysis time delay and the average time delay of the SaaS analysis fire-fighting monitoring platform:
deploying the subunits: the intelligent fire fighting monitoring platform is used for carrying out balance adjustment on the platform running speed of the intelligent fire fighting monitoring platform through the deployment balance and deploying the intelligent fire fighting monitoring platform after the balance adjustment;
the operation speed of the platform at least comprises SaaS acquisition speed, SaaS analysis data speed and SaaS analysis time delay.
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