CN118097549A - Access control system using big data analysis - Google Patents

Abstract

The invention relates to an admission control system applying big data analysis, comprising: the characteristic application mechanism is used for analyzing the entity width corresponding to the automobile based on various visual data on site by adopting a data analysis mode; the width identification mechanism is connected with the characteristic application mechanism and is used for sending a release prohibition instruction to an access control device of the underground garage when the entity width corresponding to the received automobile is larger than the upper limit of the width of the automobile allowed to park in the underground garage. The admission control system applying big data analysis is simple to operate, safe and reliable. The method comprises the steps that data analysis can be conducted on the basis of various field visual data to obtain the entity width of the current automobile, and then when the entity width corresponding to the current automobile is larger than the upper limit of the automobile width allowed to be parked in the underground garage, a release prohibition instruction is sent to an access control device of the underground garage, so that the intelligent level of management of the underground garage is improved.

Description

Access control system using big data analysis

Technical Field

The present invention relates to the field of big data analysis, and in particular to an access control system applying big data analysis.

Background technique

Data, also known as observations, are the results of experiments, measurements, observations, surveys, etc. The data processed in data analysis are divided into qualitative data and quantitative data. Data that can only be classified into a certain category and cannot be measured with numerical values is called qualitative data. Qualitative data that is presented as categories but not distinguished in order is categorized data, such as gender, brand, etc.; qualitative data that is presented as categories but distinguished in order is ordinal data, such as education level, quality grade of goods, etc. The purpose of data analysis is to concentrate and extract the information hidden in a large amount of seemingly chaotic data, so as to find out the internal laws of the object of study.

In the prior art, data analysis lacks reliable and effective solutions in some specific application areas. For example, for underground garages including three-dimensional parking structures, there are strict restrictions on the width of cars entering. If a car that is too wide enters the underground garage, not only will it be difficult for the car to park safely, but even if it is barely parked, it will cause damage to surrounding vehicles and components of the three-dimensional parking structure during the parking space conversion process of the three-dimensional parking structure.

Summary of the invention

In order to solve the above problems, the present invention provides an access control system using big data analysis, which introduces a specifically designed width identification mechanism for sending a prohibition release instruction to the access control device of the underground garage when the physical width corresponding to the intelligently analyzed car is greater than the upper limit of the width of the car allowed to be parked in the underground garage, and sending a run release instruction to the access control device of the underground garage when the physical width corresponding to the intelligently analyzed car is less than or equal to the upper limit of the width of the car allowed to be parked in the underground garage, thereby realizing dynamic access control of the underground garage based on the latest intelligent detection result of the width of the car requested to be parked, and improving the intelligence level of underground garage management, wherein, based on the color imaging characteristics corresponding to the car, the image block where the car is located is identified from the instant sharpened image obtained by optimizing the scene picture, the number of pixel rows and the number of pixel columns occupied by the image block are obtained, the smaller value of the two quantities is used as the width reference value, and the physical width corresponding to the car is determined based on the width reference value and the shooting focal length corresponding to the instant sharpened image, and the width reference value and the shooting focal length corresponding to the instant sharpened image are both positively correlated with the determined physical width corresponding to the car.

According to the present invention, there is provided an access control system using big data analysis, the system comprising:

A preview judgment device is used to judge whether there is a car target with an imaging depth of field shallower than a preset depth of field threshold in a low-resolution preview picture collected at the entrance opening of the underground garage, and when it is judged that there is a car target with an imaging depth of field shallower than the preset depth of field threshold, the low-resolution preview picture is switched to a high-resolution real shot picture;

A shooting execution device, connected to the preview judgment device, is used to execute the collection of preview pictures or real-shot pictures facing the entrance opening of the underground garage;

A primary mapping mechanism, connected to the shooting execution device, is used to sequentially perform a morphological process of first dilation and then erosion on the received real shot pictures to obtain and output a corresponding morphologically processed image;

A secondary mapping mechanism, connected to the primary mapping mechanism, for performing Butterworth low-pass filtering on the received morphologically processed image to obtain and output a corresponding content filtered image;

A final mapping mechanism, connected to the secondary mapping mechanism, for performing a sharpening process based on a USM filter on the received content filtered image to obtain and output a corresponding instant sharpened image;

a characteristic application mechanism connected to the final mapping mechanism and comprising a characteristic processing component, a block operation component and a parameter analysis component, wherein the block operation component is connected to the characteristic processing component and the parameter analysis component respectively, and the characteristic application mechanism is used to identify the image block where the car is located from the received instant sharpened image based on the color imaging characteristics corresponding to the car, obtain the number of pixel rows and the number of pixel columns occupied by the image block, take the smaller value of the two quantities as the width reference value, and determine the physical width corresponding to the car based on the width reference value and the shooting focal length corresponding to the instant sharpened image, wherein the width reference value and the shooting focal length corresponding to the instant sharpened image are both positively correlated with the determined physical width corresponding to the car;

A width identification mechanism, connected to the characteristic application mechanism, is used to send a prohibition release instruction to the access control device of the underground garage when the received physical width corresponding to the car is greater than the upper limit of the width of the car allowed to be parked in the underground garage;

The width identification mechanism is further used to send a run release instruction to the access control device of the underground garage when the received physical width corresponding to the car is less than or equal to the upper limit of the width of the car allowed to be parked in the underground garage;

Among them, the characteristic application mechanism is used to identify the image block where the car is located from the received instant sharpened image based on the color imaging characteristics corresponding to the car, obtain the number of pixel rows and pixel columns occupied by the image block, take the smaller value of the two quantities as the width reference value, and determine the physical width corresponding to the car based on the width reference value and the shooting focal length corresponding to the instant sharpened image. The width reference value and the shooting focal length corresponding to the instant sharpened image are both positively correlated with the determined physical width corresponding to the car, including: the color imaging characteristics corresponding to the car are the value distribution intervals corresponding to each color component of the car in the CMYK color space.

Therefore, the present invention has at least the following three beneficial technical effects:

Firstly: a characteristic application mechanism including a characteristic processing component, a block operation component and a parameter analysis component is used to provide a reliable hardware foundation for the intelligent measurement of the physical width of the automobile;

Secondly: based on the color imaging characteristics corresponding to the car, the image block where the car is located is identified from the received instant sharpened image, the number of pixel rows and the number of pixel columns occupied by the image block are obtained, the smaller value of the two quantities is used as the width reference value, and the physical width corresponding to the car is determined based on the width reference value and the shooting focal length corresponding to the instant sharpened image, and the width reference value and the shooting focal length corresponding to the instant sharpened image are both positively correlated with the determined physical width corresponding to the car;

Again: a width identification mechanism is introduced to send a prohibition release instruction to the access control device of the underground garage when the physical width corresponding to the received car is greater than the upper limit of the width of the car allowed to be parked in the underground garage; and to send an operation release instruction to the access control device of the underground garage when the physical width corresponding to the received car is less than or equal to the upper limit of the width of the car allowed to be parked in the underground garage, thereby realizing dynamic access control of the underground garage based on the latest intelligent detection result of the width of the car requested to be parked, and improving the intelligence level of underground garage management.

The access control system using big data analysis of the present invention is simple to operate, safe and reliable. Since data analysis can be performed based on various on-site visual data to obtain the physical width of the current car, when the physical width corresponding to the current car is greater than the upper limit of the width of the car allowed to be parked in the underground garage, a prohibition release instruction is sent to the access control device of the underground garage, thereby improving the intelligent level of underground garage management.

BRIEF DESCRIPTION OF THE DRAWINGS

The embodiments of the present invention will be described below with reference to the accompanying drawings, wherein:

FIG1 is a schematic diagram of the internal structure of an access control system using big data analysis according to an embodiment of an automobile of the present invention.

FIG. 2 is a schematic diagram of the internal structure of an access control system applying big data analysis according to Embodiment B of the present invention.

FIG3 is a schematic diagram of the internal structure of an access control system applying big data analysis according to Embodiment C of the present invention.

Detailed ways

The following is a detailed description of an embodiment of the access control system using big data analysis of the present invention with reference to the accompanying drawings.

FIG1 is a schematic diagram of the internal structure of an access control system using big data analysis according to an embodiment of an automobile according to the present invention, wherein the system includes:

A preview judgment device is used to judge whether there is a car target with an imaging depth of field shallower than a preset depth of field threshold in a low-resolution preview picture collected at the entrance opening of the underground garage, and when it is judged that there is a car target with an imaging depth of field shallower than the preset depth of field threshold, the low-resolution preview picture is switched to a high-resolution real shot picture;

For example, the MATLAB toolbox may be selected to simulate and implement a data processing process of judging whether there is a car target whose imaging depth of field is shallower than a preset depth of field threshold value on a low-resolution preview picture collected at the entrance opening of an underground garage, and switching the low-resolution preview picture to a high-resolution real-shot picture when judging that there is a car target whose imaging depth of field is shallower than the preset depth of field threshold value;

A shooting execution device, connected to the preview judgment device, is used to execute the collection of preview pictures or real-shot pictures facing the entrance opening of the underground garage;

A primary mapping mechanism, connected to the shooting execution device, is used to sequentially perform a morphological process of first dilation and then erosion on the received real shot pictures to obtain and output a corresponding morphologically processed image;

A secondary mapping mechanism, connected to the primary mapping mechanism, for performing Butterworth low-pass filtering on the received morphologically processed image to obtain and output a corresponding content filtered image;

A final mapping mechanism, connected to the secondary mapping mechanism, for performing a sharpening process based on a USM filter on the received content filtered image to obtain and output a corresponding instant sharpened image;

a characteristic application mechanism connected to the final mapping mechanism and comprising a characteristic processing component, a block operation component and a parameter analysis component, wherein the block operation component is connected to the characteristic processing component and the parameter analysis component respectively, and the characteristic application mechanism is used to identify the image block where the car is located from the received instant sharpened image based on the color imaging characteristics corresponding to the car, obtain the number of pixel rows and the number of pixel columns occupied by the image block, take the smaller value of the two quantities as the width reference value, and determine the physical width corresponding to the car based on the width reference value and the shooting focal length corresponding to the instant sharpened image, wherein the width reference value and the shooting focal length corresponding to the instant sharpened image are both positively correlated with the determined physical width corresponding to the car;

A width identification mechanism, connected to the characteristic application mechanism, is used to send a prohibition release instruction to the access control device of the underground garage when the received physical width corresponding to the car is greater than the upper limit of the width of the car allowed to be parked in the underground garage;

The width identification mechanism is further used to send a run release instruction to the access control device of the underground garage when the received physical width corresponding to the car is less than or equal to the upper limit of the width of the car allowed to be parked in the underground garage;

The characteristic application mechanism is used to identify the image block where the car is located from the received instant sharpened image based on the color imaging characteristics corresponding to the car, obtain the number of pixel rows and the number of pixel columns occupied by the image block, take the smaller value of the two quantities as the width reference value, and determine the physical width corresponding to the car based on the width reference value and the shooting focal length corresponding to the instant sharpened image. The width reference value and the shooting focal length corresponding to the instant sharpened image are both positively correlated with the determined physical width corresponding to the car, including: the color imaging characteristics corresponding to the car are the value distribution intervals corresponding to each color component of the car in the CMYK color space;

The preview judgment device is used to judge whether there is a car target with an imaging depth of field shallower than a preset depth of field threshold in the low-resolution preview picture collected at the entrance opening of the underground garage, and when it is judged that there is a car target with an imaging depth of field shallower than the preset depth of field threshold, the low-resolution preview picture is switched to a high-resolution real-shot picture, including: identifying one or more car targets in the low-resolution preview picture collected at the entrance opening of the underground garage based on the appearance imaging characteristics of the car target;

The preview judgment device is used to judge whether there is a car target with an imaging depth of field shallower than a preset depth of field threshold value in a low-resolution preview picture collected at the entrance opening of the underground garage, and when it is judged that there is a car target with an imaging depth of field shallower than the preset depth of field threshold value, the low-resolution preview picture is switched to a high-resolution real-shot picture, and further includes: determining the imaging depth of field of the car target based on each depth of field value corresponding to each occupied pixel point of the imaging image block of each car target in the preview picture;

Among them, determining the imaging depth of field of each automobile target in the preview screen based on the respective depth of field values corresponding to the respective occupied pixel points of the imaging image blocks of each automobile target in the preview screen includes: performing averaging processing on multiple depth of field values obtained by removing the maximum value and the minimum value of the respective depth of field values corresponding to the respective occupied pixel points of the imaging image blocks of each automobile target in the preview screen to obtain the imaging depth of field of the automobile target.

FIG. 2 is a schematic diagram of the internal structure of an access control system applying big data analysis according to Embodiment B of the present invention.

Different from FIG1 , the access control system using big data analysis in FIG2 may also include the following components:

A humidity measuring mechanism, comprising a plurality of humidity measuring units, for respectively measuring current surface humidity values of the primary mapping mechanism, the secondary mapping mechanism, the final mapping mechanism and the characteristic application mechanism;

Wherein, the humidity measuring mechanism comprises a plurality of humidity measuring units, which are used to respectively measure the current surface humidity values of the primary mapping mechanism, the secondary mapping mechanism, the final mapping mechanism and the characteristic application mechanism, including: the plurality of humidity measuring units respectively used by the primary mapping mechanism, the secondary mapping mechanism, the final mapping mechanism and the characteristic application mechanism are a plurality of non-contact humidity sensors;

Wherein, the humidity measuring mechanism comprises a plurality of humidity measuring units for respectively measuring the current surface humidity values of the primary mapping mechanism, the secondary mapping mechanism, the final mapping mechanism and the characteristic application mechanism, and further comprises: the internal structures of the plurality of non-contact humidity sensors respectively used for the primary mapping mechanism, the secondary mapping mechanism, the final mapping mechanism and the characteristic application mechanism are the same;

Wherein, the humidity measurement mechanism includes a plurality of humidity measurement units for respectively measuring the current surface humidity values of the primary mapping mechanism, the secondary mapping mechanism, the final mapping mechanism and the characteristic application mechanism, and further includes: a plurality of non-contact humidity sensors respectively used by the primary mapping mechanism, the secondary mapping mechanism, the final mapping mechanism and the characteristic application mechanism have the same humidity measurement upper limit threshold and humidity measurement lower limit threshold;

Among them, the humidity measuring mechanism includes multiple humidity measuring units, which are used to respectively measure the current surface humidity values of the primary mapping mechanism, the secondary mapping mechanism, the final mapping mechanism and the characteristic application mechanism, and also includes: the multiple non-contact humidity sensors respectively used for the primary mapping mechanism, the secondary mapping mechanism, the final mapping mechanism and the characteristic application mechanism are at equal distances from the primary mapping mechanism, the secondary mapping mechanism, the final mapping mechanism and the characteristic application mechanism.

FIG3 is a schematic diagram of the internal structure of an access control system applying big data analysis according to Embodiment C of the present invention.

Different from FIG1 , the access control system using big data analysis in FIG3 may also include the following components:

an immediate notification mechanism, connected to the plurality of non-contact humidity sensors respectively used by the primary mapping mechanism, the secondary mapping mechanism, the final mapping mechanism and the characteristic application mechanism, for executing corresponding humidity alarm actions based on humidity measurement results of the plurality of non-contact humidity sensors respectively used by the primary mapping mechanism, the secondary mapping mechanism, the final mapping mechanism and the characteristic application mechanism;

The instant notification mechanism is respectively connected to a plurality of non-contact humidity sensors respectively used by the primary mapping mechanism, the secondary mapping mechanism, the final mapping mechanism and the characteristic application mechanism, and is used to perform corresponding humidity alarm actions based on humidity measurement results of the plurality of non-contact humidity sensors respectively used by the primary mapping mechanism, the secondary mapping mechanism, the final mapping mechanism and the characteristic application mechanism, including: a humidity receiving unit, a humidity judgment unit and a notification execution unit built into the instant notification mechanism;

And wherein, the instant notification mechanism is respectively connected to multiple non-contact humidity sensors respectively used by the primary mapping mechanism, the secondary mapping mechanism, the final mapping mechanism and the characteristic application mechanism, and is used to perform corresponding humidity alarm actions based on the humidity measurement results of the multiple non-contact humidity sensors respectively used by the primary mapping mechanism, the secondary mapping mechanism, the final mapping mechanism and the characteristic application mechanism. It also includes: within the instant notification mechanism, the humidity receiving unit, the humidity judgment unit and the notification execution unit are connected in sequence.

In addition, in the access control system that applies big data analysis, the characteristic application mechanism is used to identify the image block where the car is located from the received instant sharpened image based on the color imaging characteristics corresponding to the car, obtain the number of pixel rows and the number of pixel columns occupied by the image block, take the smaller value of the two quantities as the width reference value, and determine the physical width corresponding to the car based on the width reference value and the shooting focal length corresponding to the instant sharpened image. The width reference value and the shooting focal length corresponding to the instant sharpened image are both positively correlated with the determined physical width corresponding to the car, and also include: using a numerical conversion formula to represent a one-to-two numerical conversion relationship between the determined physical width corresponding to the car and the width reference value and the shooting focal length corresponding to the instant sharpened image.

The present embodiments are to be considered in all respects as illustrative and not restrictive, and all changes coming within the meaning and equivalency range of the appended claims are intended to be embraced within their scope.

Claims (9)

1. An access control system using big data analysis, characterized in that the system comprises: A preview judgment device is used to judge whether there is a car target with an imaging depth of field shallower than a preset depth of field threshold in a low-resolution preview picture collected at the entrance opening of the underground garage, and when it is judged that there is a car target with an imaging depth of field shallower than the preset depth of field threshold, the low-resolution preview picture is switched to a high-resolution real shot picture; A shooting execution device, connected to the preview judgment device, is used to execute the collection of preview pictures or real-shot pictures facing the entrance opening of the underground garage; A primary mapping mechanism, connected to the shooting execution device, is used to sequentially perform a morphological process of first dilation and then erosion on the received real shot pictures to obtain and output a corresponding morphologically processed image; A secondary mapping mechanism, connected to the primary mapping mechanism, for performing Butterworth low-pass filtering on the received morphologically processed image to obtain and output a corresponding content filtered image; A final mapping mechanism, connected to the secondary mapping mechanism, for performing a sharpening process based on a USM filter on the received content filtered image to obtain and output a corresponding instant sharpened image; a characteristic application mechanism connected to the final mapping mechanism and comprising a characteristic processing component, a block operation component and a parameter analysis component, wherein the block operation component is connected to the characteristic processing component and the parameter analysis component respectively, and the characteristic application mechanism is used to identify the image block where the car is located from the received instant sharpened image based on the color imaging characteristics corresponding to the car, obtain the number of pixel rows and the number of pixel columns occupied by the image block, take the smaller value of the two quantities as the width reference value, and determine the physical width corresponding to the car based on the width reference value and the shooting focal length corresponding to the instant sharpened image, wherein the width reference value and the shooting focal length corresponding to the instant sharpened image are both positively correlated with the determined physical width corresponding to the car; A width identification mechanism, connected to the characteristic application mechanism, is used to send a prohibition release instruction to the access control device of the underground garage when the received physical width corresponding to the car is greater than the upper limit of the width of the car allowed to be parked in the underground garage; The width identification mechanism is further used to send a run release instruction to the access control device of the underground garage when the received physical width corresponding to the car is less than or equal to the upper limit of the width of the car allowed to be parked in the underground garage; Among them, the characteristic application mechanism is used to identify the image block where the car is located from the received instant sharpened image based on the color imaging characteristics corresponding to the car, obtain the number of pixel rows and pixel columns occupied by the image block, take the smaller value of the two quantities as the width reference value, and determine the physical width corresponding to the car based on the width reference value and the shooting focal length corresponding to the instant sharpened image. The width reference value and the shooting focal length corresponding to the instant sharpened image are both positively correlated with the determined physical width corresponding to the car, including: the color imaging characteristics corresponding to the car are the value distribution intervals corresponding to each color component of the car in the CMYK color space. 2. The access control system using big data analysis as claimed in claim 1, characterized in that: The preview judgment device is used to judge whether there is a car target with an imaging depth of field shallower than a preset depth of field threshold in a low-resolution preview picture collected at the entrance opening of the underground garage, and when it is judged that there is a car target with an imaging depth of field shallower than the preset depth of field threshold, the low-resolution preview picture is switched to a high-resolution real-shot picture, including: identifying one or more car targets in the low-resolution preview picture collected at the entrance opening of the underground garage based on the appearance imaging characteristics of the car target; The preview judgment device is used to judge whether there is a car target with an imaging depth of field shallower than a preset depth of field threshold value in a low-resolution preview picture collected at the entrance opening of the underground garage, and when it is judged that there is a car target with an imaging depth of field shallower than the preset depth of field threshold value, the low-resolution preview picture is switched to a high-resolution real-shot picture, and further includes: determining the imaging depth of field of the car target based on each depth of field value corresponding to each occupied pixel point of the imaging image block of each car target in the preview picture; Among them, determining the imaging depth of field of each automobile target in the preview screen based on the respective depth of field values corresponding to the respective occupied pixel points of the imaging image blocks of each automobile target in the preview screen includes: performing averaging processing on multiple depth of field values obtained by removing the maximum value and the minimum value of the respective depth of field values corresponding to the respective occupied pixel points of the imaging image blocks of each automobile target in the preview screen to obtain the imaging depth of field of the automobile target. 3. The access control system using big data analysis according to claim 2, characterized in that the system further comprises: A humidity measuring mechanism, comprising a plurality of humidity measuring units, for respectively measuring current surface humidity values of the primary mapping mechanism, the secondary mapping mechanism, the final mapping mechanism and the characteristic application mechanism; Among them, the humidity measuring mechanism includes multiple humidity measuring units, which are used to respectively measure the current surface humidity values of the primary mapping mechanism, the secondary mapping mechanism, the final mapping mechanism and the characteristic application mechanism, including: the multiple humidity measuring units respectively used for the primary mapping mechanism, the secondary mapping mechanism, the final mapping mechanism and the characteristic application mechanism are multiple non-contact humidity sensors. 4. The access control system using big data analysis as claimed in claim 3, characterized in that: The humidity measuring mechanism includes a plurality of humidity measuring units for respectively measuring the current surface humidity values of the primary mapping mechanism, the secondary mapping mechanism, the final mapping mechanism and the characteristic application mechanism. The mechanism also includes: the internal structures of the plurality of non-contact humidity sensors respectively used for the primary mapping mechanism, the secondary mapping mechanism, the final mapping mechanism and the characteristic application mechanism are the same. 5. The access control system using big data analysis as claimed in claim 3, characterized in that: The humidity measuring mechanism includes a plurality of humidity measuring units for respectively measuring the current surface humidity values of the primary mapping mechanism, the secondary mapping mechanism, the final mapping mechanism and the characteristic application mechanism, and further includes: a plurality of non-contact humidity sensors respectively used for the primary mapping mechanism, the secondary mapping mechanism, the final mapping mechanism and the characteristic application mechanism have the same humidity measurement upper limit threshold and humidity measurement lower limit threshold. 6. The access control system using big data analysis as claimed in claim 5, characterized in that: The humidity measuring mechanism includes a plurality of humidity measuring units for respectively measuring the current surface humidity values of the primary mapping mechanism, the secondary mapping mechanism, the final mapping mechanism and the characteristic application mechanism, and further includes: a plurality of non-contact humidity sensors respectively used for the primary mapping mechanism, the secondary mapping mechanism, the final mapping mechanism and the characteristic application mechanism are at equal distances from the primary mapping mechanism, the secondary mapping mechanism, the final mapping mechanism and the characteristic application mechanism. 7. The access control system using big data analysis according to any one of claims 3 to 6, characterized in that the system further comprises: The instant notification mechanism is respectively connected to multiple non-contact humidity sensors respectively used by the primary mapping mechanism, the secondary mapping mechanism, the final mapping mechanism and the characteristic application mechanism, and is used to perform corresponding humidity alarm actions based on the humidity measurement results of the multiple non-contact humidity sensors respectively used by the primary mapping mechanism, the secondary mapping mechanism, the final mapping mechanism and the characteristic application mechanism. 8. The access control system using big data analysis as claimed in claim 7, characterized in that: The instant notification mechanism is respectively connected to multiple non-contact humidity sensors respectively used by the primary mapping mechanism, the secondary mapping mechanism, the final mapping mechanism and the characteristic application mechanism, and is used to perform corresponding humidity alarm actions based on the humidity measurement results of the multiple non-contact humidity sensors respectively used by the primary mapping mechanism, the secondary mapping mechanism, the final mapping mechanism and the characteristic application mechanism, including: the instant notification mechanism has a built-in humidity receiving unit, a humidity judgment unit and a notification execution unit. 9. The access control system using big data analysis as claimed in claim 8, characterized in that: The instant notification mechanism is respectively connected to multiple non-contact humidity sensors respectively used by the primary mapping mechanism, the secondary mapping mechanism, the final mapping mechanism and the characteristic application mechanism, and is used to perform corresponding humidity alarm actions based on the humidity measurement results of the multiple non-contact humidity sensors respectively used by the primary mapping mechanism, the secondary mapping mechanism, the final mapping mechanism and the characteristic application mechanism. It also includes: within the instant notification mechanism, the humidity receiving unit, the humidity judgment unit and the notification execution unit are connected in sequence.