CN116362564A

CN116362564A - Method and system for generating hotel public health video supervision result

Info

Publication number: CN116362564A
Application number: CN202310348023.0A
Authority: CN
Inventors: 宗成忠; 孙海波; 陈辉; 胡绵蓉
Original assignee: Chongqing Haihuixing Technology Co ltd
Current assignee: Chongqing Haihuixing Technology Co ltd
Priority date: 2023-04-04
Filing date: 2023-04-04
Publication date: 2023-06-30
Anticipated expiration: 2043-04-04
Also published as: CN116362564B

Abstract

The hotel public health video supervision result generation method and system provided by the application integrate and translate the video monitoring example key data and the behavior data to be processed so as to obtain abundant data in the video monitoring example to a greater extent; when the integration translation is completed, real-time comparison data of the video monitoring example in the video monitoring process, namely hotel health monitoring results, are obtained, and the hotel health monitoring results are managed in real time. Performing data derivatization on limited video monitoring examples through sanitary example data in a database, so that the video monitoring examples after data derivatization can completely express corresponding important meanings and behaviors; and when the video monitoring example derived from the data is used for generating the hotel health monitoring result, the obtained hotel health monitoring result has high accuracy and reliability in behavior and important meanings, so that the hotel health monitoring result can be managed more accurately when the data is managed, and the efficiency of the data management is improved.

Description

Method and system for generating hotel public health video supervision result

Technical Field

The application relates to the technical field of data production, in particular to a method and a system for generating hotel public health video supervision results.

Background

Hotel sanitation is an important link of hotels, and when a customer checks in, the customer needs to take care of public health of the hotels, so that the user's sense of well being is increased.

At present, the public health of hotels is relatively large in scope, real-time management is difficult to carry out through the manual work, and continuous supervision can be carried out for 24 hours by means of video supervision, but when video supervision data are managed, the video supervision is difficult to manage because of large data quantity, so that the accurate position of garbage or foreign matters cannot be accurately determined, and therefore, a technical scheme is needed to improve the technical problems.

Disclosure of Invention

In order to improve the technical problems in the related art, the application provides a method and a system for generating hotel public health video supervision results.

In a first aspect, a method for generating a hotel public health video supervision result is provided, the method comprising: acquiring sanitary monitoring data in a video monitoring process to obtain a video monitoring example; performing data derivatization on each piece of sanitary monitoring data of the video monitoring example by utilizing sanitary example data in a database to obtain sanitary monitoring derivative data; the sanitary sample data in the database is a preset data set consisting of image frame data matching data; constructing description knowledge of the health monitoring derivative data to obtain health monitoring data derivative description knowledge, so as to obtain at least one health monitoring data derivative description knowledge corresponding to the video monitoring example; performing important content compression on the at least one sanitary monitoring data derivative description knowledge to obtain video monitoring example key data; performing behavioral regression analysis on the at least one sanitary monitoring data derivative description knowledge to obtain behavior data to be processed; integrating and translating the video monitoring example key data and the behavior data to be processed through the at least one health monitoring data derived descriptive knowledge to generate hotel health monitoring results; the hotel health monitoring result is real-time comparison data of the video monitoring example in the video monitoring process; and managing the hotel health monitoring result in real time.

In an independent embodiment, the data deriving each piece of health monitoring data of the video monitoring example by using the health sample data in the database to obtain health monitoring derived data includes: obtaining each continuous image frame data of each sanitary monitoring data in the video monitoring example; determining data matched with each piece of continuous image frame data from the sanitary sample data in the database to obtain sanitary sample data in a target database; calculating matching evaluation of the sanitary sample data in each staged target database of the sanitary sample data in the target database and each continuous image frame data to obtain staged target matching evaluation, thereby obtaining target matching evaluation corresponding to the sanitary sample data in the target database; the target matching evaluation comprises at least one staged target matching evaluation; according to the target matching evaluation, selecting the sanitary sample data in a set number of staged target databases from the sanitary sample data in the target databases to obtain hotel sanitary condition data; performing data derivatization on each piece of continuous image frame data through the hotel health status data to obtain image frame data derivatization data, so as to obtain the health monitoring derivatization data corresponding to each piece of health monitoring data; the health monitoring derived data includes at least one image frame data derived data; correspondingly, the construction of the description knowledge of the sanitary monitoring derivative data to obtain the sanitary monitoring data derivative description knowledge comprises the following steps: and constructing description knowledge of each image frame data derivative of the health monitoring derivative data to obtain image frame data derivative description knowledge, thereby obtaining the health monitoring data derivative description knowledge comprising at least one image frame data derivative description knowledge.

In an independent embodiment, the calculating the matching evaluation of the sanitary case data in each staged target database of sanitary case data in the target database and each continuous image frame data to obtain staged target matching evaluation includes: obtaining the sanitation grade of the sanitation example data in each stage of the sanitation example data in the target database to obtain target sanitation grade data; acquiring the association condition of the sanitary sample data in each staged target database and each continuous image frame data to obtain target association condition data; obtaining the relation credibility factors of the sanitary sample data in each staged target database to obtain target relation credibility factor data; and calculating the matching evaluation of the sanitary sample data in each staged target database and each continuous image frame data according to the target sanitary grade data, the target association condition data and the target relation credible factor data, so as to obtain the staged target matching evaluation.

In an independent embodiment, the constructing the description knowledge of each image frame data derivative of the health monitoring derivative data to obtain the description knowledge of the image frame data derivative includes: variable description is carried out on each continuous image frame data of each image frame data derivative data in the health monitoring derivative data, so that continuous image frame data variable description knowledge is obtained; performing variable description on the hotel health status data of the image frame data derived data to obtain hotel health status data variable description knowledge; calculating percentage data of the hotel health status data through the continuous image frame data variable description knowledge and the hotel health status data variable description knowledge to obtain real-time percentage data; and integrating the continuous image frame data variable description knowledge and the hotel health status data variable description knowledge through the real-time percentage data to obtain the image frame data derivative description knowledge, and completing the construction of the description knowledge of each image frame data derivative data.

In an independent embodiment, the performing behavioral regression analysis on the at least one health monitoring data derived descriptive knowledge to obtain behavior data to be processed includes: obtaining behavior description knowledge of the at least one sanitary monitoring data derivative description knowledge, and obtaining the at least one sanitary monitoring data behavior description knowledge; fusing the at least one sanitary monitoring data behavior description knowledge and the original behavior description knowledge to be processed to obtain an original behavior interaction description knowledge; the original description knowledge of the behavior to be processed is the original description knowledge corresponding to the behavior to be processed which is subjected to regression analysis; repeatedly processing the original behavior interaction description knowledge to obtain behavior interaction description knowledge; and carrying out regression analysis on the behavior to be processed according to the behavior interaction description knowledge to obtain the behavior data to be processed.

In an independent embodiment, the integrating and translating the video monitoring example key data and the behavior data to be processed by the knowledge of the description derived from the at least one health monitoring data to generate hotel health monitoring results includes: optimizing the behavior data to be processed through behavior description knowledge corresponding to the at least one hygiene monitoring data derivative description knowledge to obtain target behavior data; performing integrated translation of real-time points on the video monitoring example key data and the behavior data to be processed to obtain original real-time translation image frame data, and performing behavior reinforcement optimization on the original real-time translation image frame data through the video monitoring example key data to obtain real-time translation image frame data; integrating the target behavior data and the real-time translation image frame data to obtain a real-time image frame data fusion result; and continuously carrying out integrated translation at the next time point until the integrated translation of the video monitoring example key data and the behavior data to be processed is completed, and obtaining the hotel health monitoring result comprising at least one real-time image frame data fusion result.

In an independent embodiment, the optimizing the behavior data to be processed through the behavior description knowledge corresponding to the at least one health monitoring data derived description knowledge to obtain target behavior data includes: obtaining behavior description knowledge corresponding to each continuous image frame data from the at least one hygiene monitoring data derived description knowledge to obtain image frame data node behavior data; obtaining key data of the image frame data node behavior data to the behavior data to be processed, and obtaining the image frame data behavior key data, thereby obtaining example behavior key data comprising at least one image frame data behavior key data; optimizing the behavior data to be processed through the example behavior key data to obtain the target behavior data.

In an independent embodiment, the performing behavior enhancement optimization on the original real-time translated image frame data by using the video surveillance example key data to obtain real-time translated image frame data includes: obtaining key data corresponding to each continuous image frame data from the video monitoring example key data to obtain image frame data node key data; acquiring behavior data of the image frame data node key data to obtain behavior enhancement data; combining the behavior reinforcement data to obtain key data of the image frame data node key data to the original real-time translation image frame data, and obtaining image frame data key data, thereby obtaining example key data comprising at least one image frame data key data; and performing behavior reinforcement optimization on the original real-time translation image frame data through the example key data to obtain the real-time translation image frame data.

In an independent embodiment, the building of the description knowledge of the health monitoring derivative data obtains the health monitoring data derivative description knowledge, so as to obtain at least one health monitoring data derivative description knowledge corresponding to the video monitoring example; performing important content compression on the at least one sanitary monitoring data derivative description knowledge to obtain video monitoring example key data; performing behavioral regression analysis on the at least one sanitary monitoring data derivative description knowledge to obtain behavior data to be processed; and integrating and translating the video monitoring example key data and the behavior data to be processed through the at least one health monitoring data derived descriptive knowledge to generate hotel health monitoring results, wherein the method comprises the following steps of: constructing description knowledge of the health monitoring derivative data by utilizing a video monitoring generation thread to obtain the health monitoring data derivative description knowledge, thereby obtaining at least one health monitoring data derivative description knowledge corresponding to the video monitoring example; performing important content compression on the at least one sanitary monitoring data derivative description knowledge to obtain the video monitoring example key data; performing behavioral regression analysis on the at least one sanitary monitoring data derivative description knowledge to obtain the behavior data to be processed; and integrating and translating the video monitoring example key data and the behavior data to be processed through the at least one health monitoring data derived descriptive knowledge to obtain the hotel health monitoring result.

In an independent embodiment, the method further includes, before the creating the description knowledge of the health monitoring derivative data by using the video monitoring generation thread to create the description knowledge of the health monitoring derivative data,: obtaining a configuration example, wherein the configuration example comprises an example video monitoring example, pending behavior record data and history record data; performing data derivatization on each hygiene monitoring data example of the video monitoring example through the hygiene example data in the database to obtain hygiene monitoring data example derivatization data; constructing description knowledge of the sanitary monitoring data sample derived data by using an original video monitoring generation thread to obtain sanitary monitoring data sample derived description knowledge, thereby obtaining at least one sanitary monitoring data sample derived description knowledge corresponding to the video monitoring sample; important content compression is carried out on the derivative description knowledge of at least one hygiene monitoring data example to obtain video monitoring example key data; performing behavioral regression analysis on the derivative description knowledge of at least one sanitary monitoring data example to obtain to-be-processed behavioral example data; integrating and translating the video monitoring example key data and the behavior example data to be processed through the at least one sanitary monitoring data example derivative description knowledge to obtain historical regression analysis data; the original video monitoring generation thread is a thread to be configured; obtaining the to-be-processed behavior sample data, the to-be-processed behavior record data and the distinction between the historical regression analysis data and the historical record data to obtain a quantitative evaluation vector; and continuously repeatedly configuring the original video monitoring generation thread through the quantitative evaluation vector until the configuration is stopped when the preset configuration termination requirement is met, so as to obtain the video monitoring generation thread.

In an independent embodiment, the repeatedly configuring the original video surveillance generating thread through the quantized evaluation vector is continued until the configuration is suspended when a preset configuration termination requirement is met, and after the video surveillance generating thread is obtained, the method further includes: when a new configuration example is obtained, optimizing the video monitoring generation thread through the new configuration example; correspondingly, the construction of the description knowledge of the health monitoring derivative data by using the video monitoring generation thread to obtain the health monitoring data derivative description knowledge comprises the following steps: and constructing description knowledge of the sanitary monitoring derivative data by utilizing the optimized video monitoring generation thread to obtain the sanitary monitoring data derivative description knowledge.

In a second aspect, a system for generating hotel public health video surveillance results is provided, comprising a processor and a memory in communication with each other, the processor being configured to read a computer program from the memory and execute the computer program to implement the method described above.

After the key data and the behavior data to be processed of the video monitoring example are obtained, the key data and the behavior data to be processed of the video monitoring example are integrated and translated by using at least one health monitoring data derived description knowledge in the translation process, so that the abundant data in the video monitoring example are obtained to a greater extent; when the integration translation is completed, real-time comparison data of the video monitoring example in the video monitoring process, namely hotel health monitoring results, are obtained, and the hotel health monitoring results are managed in real time.

It can be appreciated that the limited video monitoring examples are subjected to data derivatization through the sanitary example data in the database, so that the video monitoring examples after data derivatization can completely express corresponding important meanings and behaviors; and when the video monitoring example derived from the data is used for generating the hotel health monitoring result, the obtained hotel health monitoring result has high accuracy and reliability in behavior and important meanings, so that the hotel health monitoring result can be managed more accurately when the data is managed, and the efficiency of the data management is improved.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered limiting the scope, and that other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

Fig. 1 is a flowchart of a method for generating a hotel public health video supervision result according to an embodiment of the present application.

Detailed Description

In order to better understand the technical solutions described above, the following detailed description of the technical solutions of the present application is provided through the accompanying drawings and specific embodiments, and it should be understood that the specific features of the embodiments and embodiments of the present application are detailed descriptions of the technical solutions of the present application, and not limit the technical solutions of the present application, and the technical features of the embodiments and embodiments of the present application may be combined with each other without conflict.

Referring to fig. 1, a method for generating a hotel public health video supervision result is shown, which may include the following technical solutions described in steps S101-S105.

S101, acquiring sanitary monitoring data in a video monitoring process to obtain a video monitoring example; performing data derivatization on each piece of sanitary monitoring data of the video monitoring example by utilizing sanitary example data in the database to obtain sanitary monitoring derivative data; the sanitary example data in the database is a data set composed of image frame data matching data set in advance.

It can be understood that when video monitoring is performed, hygiene monitoring data can be generated in the video monitoring process, and the hygiene monitoring data in the video monitoring process is obtained, so that a video monitoring example is obtained; in other words, the video monitoring example is a set of health monitoring data in the video monitoring process, which is a type of data to be processed.

In the present embodiment, the video monitoring example includes not less than one piece of health monitoring data; after the video monitoring example is obtained, the sanitary case data in the database is generally relied on to express the insignificant sanitary condition in the video monitoring process, so that the sanitary case data in the database identifies the video monitoring example and the behavior two-dimensional degree, and the identification accuracy is improved; thus, the data of each hygiene monitoring data in the video monitoring example is derived by using the hygiene example data in the database, so that the data expressed by each hygiene monitoring data is complete; at this time, each piece of the sanitation monitoring data after the data derivation is sanitation monitoring derived data.

S102, constructing description knowledge of the sanitary monitoring derivative data to obtain the sanitary monitoring data derivative description knowledge, so as to obtain at least one sanitary monitoring data derivative description knowledge corresponding to the video monitoring example.

In this embodiment, after the data-derived health monitoring data, that is, the health monitoring derived data, is obtained, since the health monitoring derived data can express both the display health condition (health condition expressed by the health monitoring data) and the hidden health condition (health condition expressed by the data derived data); therefore, in order to strengthen the display of the sanitary condition in the sanitary monitoring data, the description knowledge construction is carried out on the sanitary monitoring derivative data, and the sanitary monitoring data derivative description knowledge corresponding to the sanitary monitoring derivative data is obtained; when the data derivative and description knowledge construction of each sanitary monitoring data is completed, since the video monitoring example includes not less than one sanitary monitoring data, not less than one sanitary monitoring data derivative description knowledge corresponding to the video monitoring example is obtained, and the sanitary monitoring data derivative description knowledge belongs to not less than one sanitary monitoring data derivative description knowledge.

It will be appreciated that describing knowledge building refers to a process of representing health monitoring derivative data in a characteristic form, such as a continuous vectorized representation.

S103, important content compression is carried out on at least one sanitary monitoring data derivative description knowledge, and video monitoring example key data are obtained.

In this embodiment, after obtaining at least one health monitoring data derivative description knowledge, performing important content compression on at least one health monitoring data derivative description knowledge, so as to obtain at least one key data of the health monitoring data derivative description knowledge, namely, the key data of the video monitoring example.

S104, performing behavioral regression analysis on at least one sanitary monitoring data derivative description knowledge to obtain behavior data to be processed.

In this embodiment, after obtaining at least one sanitary monitoring data derivative description knowledge, performing behavioral regression analysis of the behavior to be processed on the at least one sanitary monitoring data derivative description knowledge, thereby obtaining behavior data to be processed; here, the behavior data to be processed refers to behavior data of video monitoring to be processed in the video monitoring process which is preliminarily obtained.

It will be appreciated that the behavior data to be processed is analyzed in terms of behavior dependent regression between the behavior data of the video surveillance examples and the behavior data of the video surveillance to be processed.

S105, integrating and translating the video monitoring example key data and the behavior data to be processed according to the at least one sanitary monitoring data derivative description knowledge to generate a hotel sanitary monitoring result; the hotel health monitoring result is real-time comparison data of a video monitoring example in the video monitoring process; and managing the hotel health monitoring result in real time.

In this embodiment, after obtaining the key data of the video monitoring example and the behavior data to be processed, in the translation process, integrating and translating the key data of the video monitoring example and the behavior data to be processed by using at least one health monitoring data derived description knowledge so as to obtain the abundant data in the video monitoring example to a greater extent; when the integration translation is completed, real-time comparison data of the video monitoring example in the video monitoring process, namely hotel health monitoring results, are obtained, and the hotel health monitoring results are managed in real time.

It is to be understood that the limited video monitoring examples are subjected to data derivatization through the sanitary example data in the database, so that the video monitoring examples after data derivatization can completely express corresponding important meanings and behaviors; and when the video monitoring example derived from the data is used for generating the hotel health monitoring result, the obtained hotel health monitoring result has high accuracy and reliability in behavior and important meanings, so that the hotel health monitoring result can be managed more accurately when the data is managed, and the efficiency of the data management is improved.

Further, in the embodiment S101 of the present invention, the step of deriving the data of the hygiene monitoring by using the hygiene sample data in the database and performing data derivation on each hygiene monitoring data of the video monitoring example specifically includes the steps described in S1011-S1015.

S1011, obtaining each continuous image frame data of each hygiene monitoring data in the video monitoring example.

In the present embodiment, when data derivatization is performed on each piece of the sanitation monitoring data of the video monitoring example, it is performed in units of each piece of continuous image frame data in each piece of the sanitation monitoring data; thus, each successive image frame data of each health monitoring data in the video monitoring example is first obtained for data derivatization, respectively.

S1012, determining data matched with each continuous image frame data from the sanitary sample data in the database to obtain sanitary sample data in the target database.

In this embodiment, since the sanitary case data in the database includes the image frame data matching data, the continuous image frame data is matched with the image frame data in the sanitary case data in the database, and the image frame data matching data successfully matched from the sanitary case data in the database, that is, the sanitary case data in the target database.

S1013, calculating matching evaluation of the sanitary sample data in each stage of the sanitary sample data in the target database and each continuous image frame data to obtain stage target matching evaluation, thereby obtaining target matching evaluation corresponding to the sanitary sample data in the target database; the target match evaluation includes at least one staged target match evaluation.

It is understood that, since the number of the image frame data matching each of the consecutive image frame data in the sanitation case data in the database is not less than one, the sanitation case data in the objective database includes not less than one sanitation case data in the stepwise objective database, that is, one image frame data matching each of the common image frame data.

Here, when the cleaning process is performed, the cleaning process is performed according to matching evaluation of the sanitary sample data in each stepwise object database and each continuous image frame data; in other words, matching evaluations of the sanitary example data in each stepwise object database in the sanitary example data in the object database with each continuous image frame data, i.e., stepwise object matching evaluations are calculated; thus, a target matching score corresponding to the sanitary case data in the target database and including not less than one stepwise target matching score is also obtained.

S1014, based on the target matching evaluation, selecting the sanitation case data in the set number of staged target databases from the sanitation case data in the target databases to obtain hotel sanitation condition data.

In this embodiment, since the staged object matching evaluation indicates the matching condition of the sanitary sample data in each staged object database and the continuous image frame data, the sanitary sample data in the staged object database with low matching condition belongs to the interference data, while the sanitary sample data in the staged object database with high matching condition belongs to the useful data (can assist in mining the potential sanitary condition and the potential important meaning in the video monitoring example); therefore, according to the target matching evaluation, the sanitation example data in the staged target database with the highest set number of evaluation is extracted to form hotel sanitation status data.

It is understood that hotel health status data is image frame data used to derive continuous image frame data.

S1015, performing data derivatization on each continuous image frame data by using hotel health status data to obtain image frame data derivatization data, thereby obtaining health monitoring derivatization data corresponding to each health monitoring data; the health monitoring derivative data includes at least one image frame data derivative data.

In this embodiment, after the hotel health status data corresponding to each continuous image frame data is obtained, each continuous image frame data is combined with the hotel health status data, that is, the image frame data derivative data corresponding to each continuous image frame data is obtained, and that is, the health monitoring derivative data corresponding to each health monitoring data and including at least one image frame data derivative data is obtained.

Further, in the embodiment S101 of the present invention, by using the sanitation case data in the database, each sanitation monitoring data of the video monitoring case is subjected to data derivatization to obtain sanitation monitoring derivative data, which includes: acquiring each continuous image frame data of each health monitoring data in a video monitoring example; determining data matched with each continuous image frame data from the sanitary sample data in the database to obtain sanitary sample data in the target database; obtaining external image frame data from the sanitation case data in the target database to obtain hotel sanitation status data; performing data derivatization on each continuous image frame data by using hotel health status data to obtain image frame data derivatization data so as to obtain health monitoring derivatization data corresponding to each health monitoring data; the health monitoring derivative data includes at least one image frame data derivative data.

Correspondingly, in the embodiment S102 of the present invention, description knowledge construction is performed on the sanitary monitoring derivative data to obtain sanitary monitoring data derivative description knowledge, including S1021: and constructing description knowledge of each image frame data derivative data of the health monitoring derivative data to obtain the image frame data derivative description knowledge, thereby obtaining the health monitoring data derivative description knowledge comprising at least one image frame data derivative description knowledge.

It will be appreciated that since the health monitoring derivative data includes no less than one image frame data derivative data, it is essentially a process of characterizing each image frame data derivative data before it is reintegrated.

Further, in the embodiment S1013, the step of calculating the matching evaluation of the sanitary sample data in each of the staged target databases of the sanitary sample data in the target database and each of the continuous image frame data to obtain the staged target matching evaluation may specifically include the contents described in S10131-S10134.

S10131, obtaining the sanitation grade of the sanitation sample data in each stage object database of the sanitation sample data in the object database, and obtaining the object sanitation grade data.

S10132, obtaining the association condition of the sanitary sample data and each continuous image frame data in each stage of target database, and obtaining target association condition data.

S10133, obtaining the relation credible factors of the sanitary sample data in each stage of target database, and obtaining target relation credible factor data.

In this embodiment, the third aspect according to which the staged target matching evaluation is obtained is a relationship reliability factor of the sanitary case data in each staged target database, that is, a reliability factor of the relationship between the sanitary case data in each staged target database and each continuous image frame data, which is referred to herein as target relationship reliability factor data.

S10134, calculating matching evaluation of the sanitary sample data and each continuous image frame data in each staged target database by using the target sanitary grade data, the target association condition data and the target relation credible factor data to obtain staged target matching evaluation.

In this embodiment, after the target hygiene level data, the target association condition data, and the target relationship trusted factor data are obtained, the target hygiene level data, the target association condition data, and the target relationship trusted factor data are integrated, so that the staged target matching evaluation is obtained.

Further, in the embodiment S1021 of the present invention, the step of constructing description knowledge of each image frame data derived data of the health monitoring derived data to obtain the description knowledge of the image frame data derived data may specifically include the contents described in S10211-S10214.

S10211, carrying out variable description on each continuous image frame data of each image frame data derivative data in the health monitoring derivative data to obtain continuous image frame data variable description knowledge.

It can be understood that, since each image frame data derivative data includes continuous image frame data and hotel health status data, in order to enhance the display health condition of each continuous image frame data, the feature representation is realized by locally weighting and optimizing each continuous image frame data by using the hotel health status data, so as to obtain the image frame data derivative description knowledge.

In this embodiment, variable description is first performed on each continuous image frame data of each image frame data derivative data in the hygiene monitoring derivative data, and the obtained variable description result, that is, the continuous image frame data variable description knowledge.

S10212, carrying out variable description on the hotel health status data of each image frame data derivative data to obtain hotel health status data variable description knowledge.

In this embodiment, variable description is performed on hotel health status data derived from each image frame data, and the obtained variable description result is the hotel health status data variable description knowledge.

It can be understood that the hotel health status data includes a set number of image frame data, and the variable description of the image frame data is performed on the set number of image frame data in the hotel health status data, so that the hotel health status data variable description knowledge is a feature set formed by the set number of variable description knowledge.

Here, S10211 and S10212 are not sequential in execution order.

S10213, calculating percentage data of hotel health status data by using continuous image frame data variable description knowledge and hotel health status data variable description knowledge to obtain real-time percentage data.

In the embodiment, after the disabling image frame data variable description knowledge and the hotel health status data variable description knowledge are obtained, the disabling image frame data variable description knowledge and the hotel health status data variable description knowledge are used for obtaining the percentage data for local optimization; in other words, the percentage data of the hotel health data is calculated by using the continuous image frame data variable description knowledge and the hotel health data variable description knowledge, and the real-time percentage data for the local optimization is obtained.

It can be understood that the hotel health status data comprises a set number of image frame data, the percentage data is calculated by utilizing each feature in the continuous image frame data variable description knowledge and the hotel health status data variable description knowledge, and the obtained real-time percentage data is a percentage set formed by a set number of percentage data.

S10214, integrating continuous image frame data variable description knowledge and hotel health status data variable description knowledge by using real-time percentage data to obtain image frame data derivative description knowledge, and completing construction of description knowledge of each image frame data derivative data.

In the embodiment, after the real-time percentage data, the continuous image frame data variable description knowledge and the hotel health status data variable description knowledge are obtained, the real-time percentage data is utilized to obtain the effective data in the hotel health status data variable description knowledge, and then the effective data and the continuous image frame data variable description knowledge are fused, so that the local optimization is completed; at this time, the description knowledge of the derived data of the image frame is obtained, and the construction of the description knowledge of the derived data of each image frame is completed.

It is understood that S10211-S10214 may be implemented by a graph attention mechanism.

Further, in the present embodiment, S104 may be implemented by S1041 to S1044; in other words, behavioral regression analysis is performed on at least one knowledge of the derivative description of the health monitoring data to obtain behavioral data to be processed, including the content described in S1041-S1044.

S1041, obtaining behavior description knowledge of at least one sanitary monitoring data derivative description knowledge, and obtaining the behavior description knowledge of at least one sanitary monitoring data.

In this embodiment, the behavior description knowledge of each sanitary monitoring data is obtained according to at least one sanitary monitoring data derivative description knowledge, and at least one sanitary monitoring data behavior description knowledge is obtained.

It can be understood that the no less than one sanitary monitoring data behavior description knowledge and the no less than one sanitary monitoring data derivative description knowledge are in one-to-one correspondence with the no less than one sanitary monitoring data; in addition, each of not less than one health monitor data behavior description knowledge is used to represent the behavior of one health monitor data.

S1042, fusing at least one sanitary monitoring data behavior description knowledge and an original behavior description knowledge to be processed to obtain an original behavior interaction description knowledge; the original description knowledge of the behavior to be processed is the original description knowledge corresponding to the behavior to be processed which is subjected to regression analysis.

In this embodiment, the description knowledge of the original behavior to be processed, such as a zero vector, is set in the embodiment, and is the description knowledge of the original behavior to be processed corresponding to the regression analysis; after at least one sanitary monitoring data behavior description knowledge is obtained, at least one sanitary monitoring data behavior description knowledge and the original behavior description knowledge to be processed are fused, and the fusion result is the original behavior interaction description knowledge.

S1043, repeatedly processing the original behavior interaction description knowledge to obtain the behavior interaction description knowledge.

S1044, carrying out regression analysis on the behavior to be processed according to the behavior interaction description knowledge to obtain behavior data to be processed.

In this embodiment, after the behavior interaction description knowledge is obtained, the behavior to be processed can be analyzed according to the behavior dependence between the sanitary monitoring data in the video monitoring process, and at this time, the behavior data to be processed is determined.

In this embodiment, S105 can be implemented by S1051 to S1053; in other words, the step of integrating and translating the video monitoring example key data and the behavior data to be processed to obtain the hotel health monitoring result by using at least one health monitoring data derived descriptive knowledge can specifically include the content described in S1051-S1054.

S1051, optimizing the behavior data to be processed by using behavior description knowledge corresponding to at least one hygiene monitoring data derivative description knowledge to obtain target behavior data.

In this embodiment, after the behavior data to be processed is obtained, in order to improve accuracy of the behavior data to be processed, the behavior data to be processed is optimized by using behavior description knowledge corresponding to at least one health monitoring data derived description knowledge, so as to optimize the behavior data to be processed; at this time, the target behavior data is also obtained; it is easy to know that the target behavior data is optimized behavior data to be processed.

S1052, performing integrated translation on the video monitoring example key data and the behavior data to be processed at a real-time point to obtain original real-time translated image frame data, and performing behavior reinforcement optimization on the original real-time translated image frame data by using the video monitoring example key data to obtain the real-time translated image frame data.

It will be appreciated that the translation process is iterative, with a real-time point being any point in time of integrating the translation process. In the integrated translation process of the real-time point, if the integrated translation time point is the first integrated translation time point, integrating translation is carried out on the video monitoring example key data and the behavior data to be processed to obtain a first translation result, namely original real-time translation image frame data; and if the integrated translation time point is not the first integrated translation time point, integrating and translating the previous translation result, the video monitoring example key data and the behavior data to be processed to obtain original real-time translation image frame data, wherein the previous translation result refers to the translation result of the previous integrated translation time point.

In this embodiment, after the original real-time translated image frame data is obtained, in order to improve accuracy of the original real-time translated image frame data, behavior reinforcement optimization is performed on the original real-time translated image frame data by using video monitoring example key data to optimize the original real-time translated image frame data; at this time, the translation result of the real-time point, that is, the real-time translation image frame data is obtained; it is easy to know that the real-time translated image frame data is the original real-time translated image frame data after optimization. Here, behavior-enhanced optimization refers to a process of optimizing behavior data using video surveillance example key data.

S1053, integrating the target behavior data and the real-time translation image frame data to obtain a real-time image frame data fusion result.

In this embodiment, the obtained target behavior data and the real-time translation image frame data are integrated, and the integrated result is optimized, so that a real-time image frame data fusion result is obtained. Here, the real-time image frame data fusion result refers to image frame data corresponding to a single translation time point in the hotel health monitoring result.

S1054, continuously carrying out integrated translation at the next time point until the integrated translation of the video monitoring example key data and the behavior data to be processed is completed, and obtaining a hotel health monitoring result comprising at least one real-time image frame data fusion result.

It will be appreciated that at the next point in time, the integrated translation process performs a process similar to that of the real-time point in time; in other words, processing similar to the integrated translation process of the real-time point is executed for each integrated translation time point, and when the integrated translation of all time points is completed, the integrated translation of the video monitoring example key data and the behavior data to be processed is completed; at this time, the hotel health monitoring result including at least one real-time image frame data fusion result is obtained for at least one integrated translation time point.

Further, in the present embodiment, S1051 may be realized by S10511 to S10513; in other words, the step of optimizing the behavior data to be processed to obtain the target behavior data by using the behavior description knowledge corresponding to at least one health monitoring data derived description knowledge may specifically include the content described in S10511-S10513.

S10511, obtaining behavior description knowledge corresponding to each continuous image frame data from the non-less than one hygiene monitoring data derived description knowledge to obtain the image frame data node behavior data.

It can be appreciated that the video monitoring example comprises a plurality of continuous image frame data, and that no less than one sanitary monitoring data derivative description knowledge is a characteristic representation corresponding to the video monitoring example; thus, from the knowledge of deriving description from at least one health monitoring data, knowledge of behavior description of each successive image frame data is obtained, i.e. the behavior information of the image frame data nodes is obtained.

S10512, obtaining the key data of the image frame data node behavior data to be processed, and obtaining the image frame data behavior key data, thereby obtaining the example behavior key data comprising at least one image frame data behavior key data.

In the embodiment, the behavior data of the image frame data node and the behavior data to be processed are transformed to obtain behavior transformation characteristics; and then, calculating key data of the behavior transformation characteristics, so that behavior dependence and behavior habit aiming at the behavior data to be processed are obtained: the behavior data to be processed is interfered by the behavior in the video monitoring example, and the habit of behavior expression of the behavior data to be processed in the video monitoring process is adopted. Here, the image frame data behavior key data refers to key data corresponding to one continuous image frame data, and when all the continuous image frame data corresponding key data are obtained, example behavior key data including not less than one image frame data behavior key data are obtained, the example behavior key data corresponding to a video monitoring example.

S10513, optimizing the behavior data to be processed by using the example behavior key data to obtain real-time behavior data.

In this embodiment, the example behavior key data and the behavior data to be processed are fused to optimize the behavior data to be processed using the example behavior key data; at this time, the target behavior data is also obtained. Here, the target behavior data is behavior data of real-time comparison data in the video monitoring process.

Further, in the embodiment S1052 of the present invention, the step of performing behavior enhancement optimization on the original real-time translated image frame data by using the video monitoring exemplary key data to obtain the real-time translated image frame data may specifically include the contents described in S10521-S10524.

S10521, obtaining key data corresponding to each continuous image frame data from the video monitoring example key data, and obtaining the image frame data node key data.

It can be understood that the video monitoring example comprises a plurality of continuous image frame data, and the key data of the video monitoring example corresponds to the key data of the video monitoring example; thus, key data corresponding to each successive image frame data, that is, image frame data node key data, can be obtained from the video monitoring example key data.

S10522, obtaining behavior data of the key data of the image frame data nodes, and obtaining behavior enhancement data.

In this embodiment, the behavior data is obtained for the image frame data node key data, and thus behavior enhancement data for optimizing the translation original output result, that is, the original real-time image frame data key data is obtained.

S10523, combining the behavior enhancement data to obtain the key data of the image frame data node key data to the original real-time translated image frame data, and obtaining the image frame data key data, thereby obtaining the example key data comprising at least one image frame data key data.

In the embodiment, key data of the image frame data node and original real-time translation image frame data are transformed to obtain important meaning transformation characteristics; and then, calculating key data of the important meaning transformation characteristics, so that the key data of the image frame data node key data to the key data of the original real-time translation image frame data, namely the image frame data key data, is obtained. Here, the image frame data key data refers to key data corresponding to one continuous image frame data, and when all the continuous image frame data corresponding key data are obtained, example key data including not less than one image frame data key data are obtained, the example key data corresponding to a video monitoring example.

S10524, performing behavior reinforcement optimization on the original real-time translation image frame data by using the example key data to obtain the real-time translation image frame data.

In this embodiment, the example key data and the original real-time translated image frame data are integrated to optimize the original real-time translated image frame data with the example significance; at this time, the real-time translated image frame data is also obtained.

Further, in the present embodiment, S102 to S105 may be implemented by a network thread; in other words, a preconfigured video monitoring generation thread exists in the hotel, and the video monitoring generation thread is used for generating hotel health monitoring results; therefore, constructing description knowledge of the sanitary monitoring derivative data to obtain the sanitary monitoring data derivative description knowledge, so as to obtain at least one sanitary monitoring data derivative description knowledge corresponding to the video monitoring example; important content compression is carried out on at least one sanitary monitoring data derivative description knowledge, so that video monitoring example key data are obtained; performing behavioral regression analysis on at least one sanitary monitoring data derivative description knowledge to obtain behavior data to be processed; integrating and translating the video monitoring example key data and the behavior data to be processed by using at least one sanitary monitoring data derived descriptive knowledge to generate hotel sanitary monitoring results, wherein the method comprises the following steps: constructing description knowledge of the health monitoring derivative data by utilizing a video monitoring generation thread to obtain the health monitoring data derivative description knowledge, thereby obtaining at least one health monitoring data derivative description knowledge corresponding to a video monitoring example; important content compression is carried out on at least one sanitary monitoring data derivative description knowledge, so that video monitoring example key data are obtained; performing behavioral regression analysis on at least one sanitary monitoring data derivative description knowledge to obtain behavior data to be processed; and integrating and translating the video monitoring example key data and the behavior data to be processed by using at least one sanitary monitoring data derived descriptive knowledge to obtain a hotel sanitary monitoring result.

Further, in this embodiment, the method further includes the step of configuring and obtaining the video monitoring generation thread before constructing the description knowledge of the derived data of the health monitoring by using the video monitoring generation thread to obtain the description knowledge of the derived data of the health monitoring. S106-S110, the content is described.

S106, obtaining a configuration example, wherein the configuration example comprises an example video monitoring example, pending behavior record data and history record data.

In this embodiment, when the network thread configuration is performed, a configuration data set, that is, a configuration example, is obtained first; here, the configuration example is an example pair composed of an example video monitoring example, pending behavior record data and history record data; the example video monitoring example refers to sanitary monitoring data generated in a video monitoring process in the example, the behavior record data to be processed refers to real behavior data of real-time comparison data, and the history record data refers to real-time comparison data.

And S107, performing data derivatization on each hygiene monitoring data example of the video monitoring example by using the hygiene example data in the database to obtain hygiene monitoring data example derivatization data.

It is to be understood that the implementation procedure of S107 is similar to the implementation procedure described in S101, and the embodiments of the present invention are not described herein.

S108, constructing description knowledge of the sanitary monitoring data sample derived data by using an original video monitoring generation thread to obtain sanitary monitoring data sample derived description knowledge, thereby obtaining at least one sanitary monitoring data sample derived description knowledge corresponding to a video monitoring sample; important content compression is carried out on the derivative description knowledge of at least one sanitary monitoring data example to obtain key data of a video monitoring example; performing behavioral regression analysis on at least one sanitary monitoring data example derivative description knowledge to obtain to-be-processed behavioral example data; integrating and translating the key data of the video monitoring example and the behavior example data to be processed by using the derivative description knowledge of at least one hygiene monitoring data example to obtain historical regression analysis data; the original video monitoring generating thread is the thread to be configured.

It can be understood that the implementation process of S108 is similar to the implementation process described in S102-S105 above, except that S108 is completed by the original video monitoring generation thread, and the implementation process of S102-S105 is completed by itself, which is not described herein. In addition, the original video monitoring generation thread is a thread to be configured for obtaining hotel health monitoring results.

S109, obtaining to-be-processed behavior sample data and to-be-processed behavior record data, and distinguishing between the historical regression analysis data and the historical record data to obtain a quantitative evaluation vector.

S110, repeatedly configuring an original video monitoring generation thread continuously by utilizing the quantitative evaluation vector until the configuration is in accordance with a preset configuration termination requirement, and suspending the configuration to obtain the video monitoring generation thread.

In this embodiment, after obtaining the quantized evaluation vector, adjusting coefficient data in the original video monitoring generating thread by using the quantized evaluation vector, and further, continuing to repeatedly configure by using the debugged original video monitoring generating thread and the configuration example until the value of the cost index model obtained in the configuration process is smaller than a preset target value, and determining that the cost index model meets a preset configuration termination requirement; at this time, the configuration is paused, and the configured original video monitoring generation thread, namely the video monitoring generation thread, is obtained.

In the present embodiment, S111 is further included after S110; in other words, the method for generating the hotel public health video supervision result further includes S111 after the video monitoring generating thread is obtained by suspending the configuration until the configuration termination requirement set in advance is met by repeatedly configuring the original video monitoring generating thread by using the quantized evaluation vector.

And S111, when a new configuration example is obtained, optimizing a preset original video monitoring generation thread by using the new configuration example.

It can be appreciated that when the video monitoring generating thread is obtained, the video monitoring generating thread can be optimized by obtaining a new configuration example, so as to improve the accuracy and reliability of the video monitoring generating thread.

Correspondingly, in the embodiment of the invention, the characteristic representation is carried out on the derivative data of the health monitoring by utilizing the video monitoring generation thread to obtain the derivative description knowledge of the data of the health monitoring, which comprises the following steps: and performing characteristic representation on the sanitary monitoring derivative data by utilizing the optimized video monitoring generation thread to obtain the sanitary monitoring data derivative description knowledge.

In other words, the optimized video monitoring generation thread is utilized to perform characteristic representation on the health monitoring derivative data to obtain health monitoring data derivative description knowledge, so that at least one health monitoring data derivative description knowledge corresponding to the video monitoring example is obtained; obtaining key data of at least one sanitary monitoring data derivative description knowledge to obtain video monitoring example key data; performing behavioral regression analysis on at least one sanitary monitoring data derivative description knowledge to obtain behavior data to be processed; and translating the video monitoring example key data and the behavior data to be processed to obtain hotel health monitoring results.

On the basis of the above, there is provided a generating device 200 of hotel public health video supervision results, the device comprising:

an example obtaining module 210, configured to obtain hygiene monitoring data in the video monitoring process, and obtain a video monitoring example;

the data deriving module 220 is configured to perform data derivation on each piece of health monitoring data of the video monitoring example by using the health sample data in the database, so as to obtain health monitoring derived data; the sanitary sample data in the database is a preset data set consisting of image frame data matching data;

the knowledge derivative module 230 is configured to build description knowledge of the health monitoring derivative data to obtain health monitoring data derivative description knowledge, so as to obtain at least one health monitoring data derivative description knowledge corresponding to the video monitoring example;

the data compression module 240 is configured to compress important content of the at least one health monitoring data derived description knowledge to obtain video monitoring example key data;

the data analysis module 250 is configured to perform behavioral regression analysis on the at least one sanitary monitoring data derived description knowledge to obtain behavioral data to be processed;

The result management module 260 is configured to integrate and translate the video monitoring example key data and the behavior data to be processed through the at least one health monitoring data derived description knowledge, so as to generate a hotel health monitoring result; the hotel health monitoring result is real-time comparison data of the video monitoring example in the video monitoring process; and managing the hotel health monitoring result in real time.

On the basis of the above, a system 300 for generating hotel public health video supervision results is shown, comprising a processor 310 and a memory 320 in communication with each other, the processor 310 being configured to read a computer program from the memory 320 and execute the computer program to implement the method described above.

On the basis of the above, there is also provided a computer readable storage medium on which a computer program stored which, when run, implements the above method.

In summary, after the key data of the video monitoring example and the behavior data to be processed are obtained based on the scheme, in the translation process, the key data of the video monitoring example and the behavior data to be processed are integrated and translated by utilizing at least one health monitoring data derived descriptive knowledge, so that abundant data in the video monitoring example are obtained to a greater extent; when the integration translation is completed, real-time comparison data of the video monitoring example in the video monitoring process, namely hotel health monitoring results, are obtained, and the hotel health monitoring results are managed in real time.

It should be appreciated that the systems and modules thereof shown above may be implemented in a variety of ways. For example, in some embodiments, the system and its modules may be implemented in hardware, software, or a combination of software and hardware. Wherein the hardware portion may be implemented using dedicated logic; the software portions may then be stored in a memory and executed by a suitable instruction execution system, such as a microprocessor or special purpose design hardware. Those skilled in the art will appreciate that the methods and systems described above may be implemented using computer executable instructions and/or embodied in processor control code, such as provided on a carrier medium such as a magnetic disk, CD or DVD-ROM, a programmable memory such as read only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The system and its modules of the present application may be implemented not only with hardware circuitry, such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., but also with software, such as executed by various types of processors, and with a combination of the above hardware circuitry and software (e.g., firmware).

It should be noted that, the advantages that may be generated by different embodiments may be different, and in different embodiments, the advantages that may be generated may be any one or a combination of several of the above, or any other possible advantages that may be obtained.

While the basic concepts have been described above, it will be apparent to those skilled in the art that the foregoing detailed disclosure is by way of example only and is not intended to be limiting. Although not explicitly described herein, various modifications, improvements, and adaptations of the present application may occur to one skilled in the art. Such modifications, improvements, and modifications are intended to be suggested within this application, and are therefore within the spirit and scope of the exemplary embodiments of this application.

Meanwhile, the present application uses specific words to describe embodiments of the present application. Reference to "one embodiment," "an embodiment," and/or "some embodiments" means that a particular feature, structure, or characteristic is associated with at least one embodiment of the present application. Thus, it should be emphasized and should be appreciated that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various positions in this specification are not necessarily referring to the same embodiment. Furthermore, certain features, structures, or characteristics of one or more embodiments of the present application may be combined as suitable.

Furthermore, those skilled in the art will appreciate that the various aspects of the invention are illustrated and described in the context of a number of patentable categories or circumstances, including any novel and useful procedures, machines, products, or materials, or any novel and useful modifications thereof. Accordingly, aspects of the present application may be performed entirely by hardware, entirely by software (including firmware, resident software, micro-code, etc.) or by a combination of hardware and software. The above hardware or software may be referred to as a "data block," module, "" engine, "" unit, "" component, "or" system. Furthermore, aspects of the present application may take the form of a computer product, comprising computer-readable program code, embodied in one or more computer-readable media.

The computer storage medium may contain a propagated data signal with the computer program code embodied therein, for example, on a baseband or as part of a carrier wave. The propagated signal may take on a variety of forms, including electro-magnetic, optical, etc., or any suitable combination thereof. A computer storage medium may be any computer readable medium that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code located on a computer storage medium may be propagated through any suitable medium, including radio, cable, fiber optic cable, RF, or the like, or a combination of any of the foregoing.

The computer program code necessary for operation of portions of the present application may be written in any one or more programming languages, including an object oriented programming language such as Java, scala, smalltalk, eiffel, JADE, emerald, C ++, c#, vb net, python, and the like, a conventional programming language such as C language, visualBasic, fortran2003, perl, COBOL2002, PHP, ABAP, a dynamic programming language such as Python, ruby, and Groovy, or other programming languages, and the like. The program code may execute entirely on the user's computer or as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any form of network, such as a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet), or the use of services such as software as a service (SaaS) in a cloud computing environment.

Furthermore, the order in which the elements and sequences are presented, the use of numerical letters, or other designations are used in the application and are not intended to limit the order in which the processes and methods of the application are performed unless explicitly recited in the claims. While certain presently useful inventive embodiments have been discussed in the foregoing disclosure, by way of various examples, it is to be understood that such details are merely illustrative and that the appended claims are not limited to the disclosed embodiments, but, on the contrary, are intended to cover all modifications and equivalent arrangements included within the spirit and scope of the embodiments of the present application. For example, while the system components described above may be implemented by hardware devices, they may also be implemented solely by software solutions, such as installing the described system on an existing server or mobile device.

Likewise, it should be noted that in order to simplify the presentation disclosed herein and thereby aid in understanding one or more inventive embodiments, various features are sometimes grouped together in a single embodiment, figure, or description thereof. This method of disclosure, however, is not intended to imply that more features than are presented in the claims are required for the subject application. Indeed, less than all of the features of a single embodiment disclosed above.

In some embodiments, numbers describing the components, number of attributes are used, it being understood that such numbers being used in the description of embodiments are modified in some examples by the modifier "about," approximately, "or" substantially. Unless otherwise indicated, "about," "approximately," or "substantially" indicate that the numbers allow for adaptive variation. Accordingly, in some embodiments, numerical parameters set forth in the specification and claims are approximations that may vary depending upon the desired properties sought to be obtained by the individual embodiments. In some embodiments, the numerical parameters should take into account the specified significant digits and employ a method for preserving the general number of digits. Although the numerical ranges and parameters set forth herein are approximations that may be employed in some embodiments to confirm the breadth of the range, in particular embodiments, the setting of such numerical values is as precise as possible.

Each patent, patent application publication, and other material, such as articles, books, specifications, publications, documents, etc., cited in this application is hereby incorporated by reference in its entirety. Except for application history documents that are inconsistent or conflicting with the present application, documents that are currently or later attached to this application for which the broadest scope of the claims to the present application is limited. It is noted that the descriptions, definitions, and/or terms used in the subject matter of this application are subject to such descriptions, definitions, and/or terms if they are inconsistent or conflicting with such descriptions, definitions, and/or terms.

Finally, it should be understood that the embodiments described herein are merely illustrative of the principles of the embodiments of the present application. Other variations are also possible within the scope of this application. Thus, by way of example, and not limitation, alternative configurations of embodiments of the present application may be considered in keeping with the teachings of the present application. Accordingly, embodiments of the present application are not limited to only the embodiments explicitly described and depicted herein.

The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and changes may be made to the present application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc. which are within the spirit and principles of the present application are intended to be included within the scope of the claims of the present application.

Claims

1. The method for generating the hotel public health video supervision result is characterized by comprising the following steps:

acquiring sanitary monitoring data in a video monitoring process to obtain a video monitoring example;

performing data derivatization on each piece of sanitary monitoring data of the video monitoring example by utilizing sanitary example data in a database to obtain sanitary monitoring derivative data; the sanitary sample data in the database is a preset data set consisting of image frame data matching data;

constructing description knowledge of the health monitoring derivative data to obtain health monitoring data derivative description knowledge, so as to obtain at least one health monitoring data derivative description knowledge corresponding to the video monitoring example;

performing important content compression on the at least one sanitary monitoring data derivative description knowledge to obtain video monitoring example key data;

performing behavioral regression analysis on the at least one sanitary monitoring data derivative description knowledge to obtain behavior data to be processed;

integrating and translating the video monitoring example key data and the behavior data to be processed through the at least one health monitoring data derived descriptive knowledge to generate hotel health monitoring results; the hotel health monitoring result is real-time comparison data of the video monitoring example in the video monitoring process; and managing the hotel health monitoring result in real time.

2. The method of claim 1, wherein the performing data derivatization on each piece of health monitoring data of the video monitoring example by using the health paradigm data in the database to obtain health monitoring derivatization data comprises:

obtaining each continuous image frame data of each sanitary monitoring data in the video monitoring example;

determining data matched with each piece of continuous image frame data from the sanitary sample data in the database to obtain sanitary sample data in a target database;

calculating matching evaluation of the sanitary sample data in each staged target database of the sanitary sample data in the target database and each continuous image frame data to obtain staged target matching evaluation, thereby obtaining target matching evaluation corresponding to the sanitary sample data in the target database; the target matching evaluation comprises at least one staged target matching evaluation;

according to the target matching evaluation, selecting the sanitary sample data in a set number of staged target databases from the sanitary sample data in the target databases to obtain hotel sanitary condition data;

Performing data derivatization on each piece of continuous image frame data through the hotel health status data to obtain image frame data derivatization data, so as to obtain the health monitoring derivatization data corresponding to each piece of health monitoring data; the health monitoring derived data includes at least one image frame data derived data;

correspondingly, the construction of the description knowledge of the sanitary monitoring derivative data to obtain the sanitary monitoring data derivative description knowledge comprises the following steps: and constructing description knowledge of each image frame data derivative of the health monitoring derivative data to obtain image frame data derivative description knowledge, thereby obtaining the health monitoring data derivative description knowledge comprising at least one image frame data derivative description knowledge.

3. The method of claim 2, wherein said calculating a matching score for each of the staged target databases of sanitary example data in the target database with the respective consecutive image frame data, comprises:

obtaining the sanitation grade of the sanitation example data in each stage of the sanitation example data in the target database to obtain target sanitation grade data;

Acquiring the association condition of the sanitary sample data in each staged target database and each continuous image frame data to obtain target association condition data;

obtaining the relation credibility factors of the sanitary sample data in each staged target database to obtain target relation credibility factor data;

and calculating the matching evaluation of the sanitary sample data in each staged target database and each continuous image frame data according to the target sanitary grade data, the target association condition data and the target relation credible factor data, so as to obtain the staged target matching evaluation.

4. A method according to claim 2 or 3, wherein the constructing the description knowledge of each image frame data derivative of the health monitoring derivative data to obtain the description knowledge of the image frame data derivative comprises:

variable description is carried out on each continuous image frame data of each image frame data derivative data in the health monitoring derivative data, so that continuous image frame data variable description knowledge is obtained;

performing variable description on the hotel health status data of the image frame data derived data to obtain hotel health status data variable description knowledge; calculating percentage data of the hotel health status data through the continuous image frame data variable description knowledge and the hotel health status data variable description knowledge to obtain real-time percentage data;

And integrating the continuous image frame data variable description knowledge and the hotel health status data variable description knowledge through the real-time percentage data to obtain the image frame data derivative description knowledge, and completing the construction of the description knowledge of each image frame data derivative data.

5. The method of claim 1, wherein performing behavioral regression analysis on the at least one health monitoring data derived descriptive knowledge to obtain behavioral data to be processed comprises:

obtaining behavior description knowledge of the at least one sanitary monitoring data derivative description knowledge, and obtaining the at least one sanitary monitoring data behavior description knowledge;

fusing the at least one sanitary monitoring data behavior description knowledge and the original behavior description knowledge to be processed to obtain an original behavior interaction description knowledge; the original description knowledge of the behavior to be processed is the original description knowledge corresponding to the behavior to be processed which is subjected to regression analysis;

repeatedly processing the original behavior interaction description knowledge to obtain behavior interaction description knowledge;

and carrying out regression analysis on the behavior to be processed according to the behavior interaction description knowledge to obtain the behavior data to be processed.

6. The method of claim 3, wherein the generating hotel health monitor results by integrating and translating the video monitor example key data and the behavior data to be processed by the at least one health monitor data derived descriptive knowledge comprises:

optimizing the behavior data to be processed through behavior description knowledge corresponding to the at least one hygiene monitoring data derivative description knowledge to obtain target behavior data;

performing integrated translation of real-time points on the video monitoring example key data and the behavior data to be processed to obtain original real-time translation image frame data, and performing behavior reinforcement optimization on the original real-time translation image frame data through the video monitoring example key data to obtain real-time translation image frame data;

integrating the target behavior data and the real-time translation image frame data to obtain a real-time image frame data fusion result;

and continuously carrying out integrated translation at the next time point until the integrated translation of the video monitoring example key data and the behavior data to be processed is completed, and obtaining the hotel health monitoring result comprising at least one real-time image frame data fusion result.

7. The method according to claim 6, wherein optimizing the behavior data to be processed to obtain target behavior data by the behavior description knowledge corresponding to the at least one health monitoring data derived description knowledge comprises:

obtaining behavior description knowledge corresponding to each continuous image frame data from the at least one hygiene monitoring data derived description knowledge to obtain image frame data node behavior data;

obtaining key data of the image frame data node behavior data to the behavior data to be processed, and obtaining the image frame data behavior key data, thereby obtaining example behavior key data comprising at least one image frame data behavior key data;

optimizing the behavior data to be processed through the example behavior key data to obtain the target behavior data.

8. The method according to claim 6, wherein performing behavior enhancement optimization on the original real-time translated image frame data by the video surveillance example key data to obtain real-time translated image frame data includes:

obtaining key data corresponding to each continuous image frame data from the video monitoring example key data to obtain image frame data node key data;

Acquiring behavior data of the image frame data node key data to obtain behavior enhancement data;

combining the behavior reinforcement data to obtain key data of the image frame data node key data to the original real-time translation image frame data, and obtaining image frame data key data, thereby obtaining example key data comprising at least one image frame data key data;

and performing behavior reinforcement optimization on the original real-time translation image frame data through the example key data to obtain the real-time translation image frame data.

9. A method according to claim 3, wherein the building of description knowledge of the health monitoring derivative data obtains health monitoring data derivative description knowledge, so as to obtain at least one health monitoring data derivative description knowledge corresponding to the video monitoring example; performing important content compression on the at least one sanitary monitoring data derivative description knowledge to obtain video monitoring example key data; performing behavioral regression analysis on the at least one sanitary monitoring data derivative description knowledge to obtain behavior data to be processed; and integrating and translating the video monitoring example key data and the behavior data to be processed through the at least one health monitoring data derived descriptive knowledge to generate hotel health monitoring results, wherein the method comprises the following steps of:

Constructing description knowledge of the health monitoring derivative data by utilizing a video monitoring generation thread to obtain the health monitoring data derivative description knowledge, thereby obtaining at least one health monitoring data derivative description knowledge corresponding to the video monitoring example;

performing important content compression on the at least one sanitary monitoring data derivative description knowledge to obtain the video monitoring example key data;

performing behavioral regression analysis on the at least one sanitary monitoring data derivative description knowledge to obtain the behavior data to be processed; integrating and translating the video monitoring example key data and the behavior data to be processed through the at least one health monitoring data derived descriptive knowledge to obtain the hotel health monitoring result;

the method comprises the steps of constructing description knowledge of the sanitary monitoring derivative data by utilizing a video monitoring generation thread, and before the sanitary monitoring derivative description knowledge is obtained, further comprises the steps of:

obtaining a configuration example, wherein the configuration example comprises an example video monitoring example, pending behavior record data and history record data;

Performing data derivatization on each hygiene monitoring data example of the video monitoring example through the hygiene example data in the database to obtain hygiene monitoring data example derivatization data;

constructing description knowledge of the sanitary monitoring data sample derived data by using an original video monitoring generation thread to obtain sanitary monitoring data sample derived description knowledge, thereby obtaining at least one sanitary monitoring data sample derived description knowledge corresponding to the video monitoring sample;

important content compression is carried out on the derivative description knowledge of at least one hygiene monitoring data example to obtain video monitoring example key data; performing behavioral regression analysis on the derivative description knowledge of at least one sanitary monitoring data example to obtain to-be-processed behavioral example data;

integrating and translating the video monitoring example key data and the behavior example data to be processed through the at least one sanitary monitoring data example derivative description knowledge to obtain historical regression analysis data;

the original video monitoring generation thread is a thread to be configured; obtaining the to-be-processed behavior sample data, the to-be-processed behavior record data and the distinction between the historical regression analysis data and the historical record data to obtain a quantitative evaluation vector;

Repeatedly configuring the original video monitoring generating thread continuously through the quantized evaluation vector until the configuration is in accordance with a preset configuration termination requirement, and suspending the configuration to obtain the video monitoring generating thread;

and continuously repeatedly configuring the original video monitoring generation thread through the quantitative evaluation vector until the configuration is stopped when the configuration termination requirement is met, and after the video monitoring generation thread is obtained, the method further comprises: when a new configuration example is obtained, optimizing the video monitoring generation thread through the new configuration example;

correspondingly, the construction of the description knowledge of the health monitoring derivative data by using the video monitoring generation thread to obtain the health monitoring data derivative description knowledge comprises the following steps: and constructing description knowledge of the sanitary monitoring derivative data by utilizing the optimized video monitoring generation thread to obtain the sanitary monitoring data derivative description knowledge.

10. A system for generating hotel public health video surveillance results, comprising a processor and a memory in communication with each other, the processor being adapted to read a computer program from the memory and execute it to implement the method of any of claims 1-9.