CN113240552A - Intelligent management system for construction of literary journey based on big data - Google Patents
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Abstract
The invention discloses an intelligent management system for cultural travel construction based on big data, which relates to the technical field of cultural travel construction management and solves the technical problem that the broadcasting and broadcasting work efficiency is low because scenic spots cannot be divided in the prior art, the scenic spot areas are divided by an area dividing unit, so that broadcasting and broadcasting with different interval durations are set for each area, area boundaries are set in the scenic spot areas, the areas in the area boundaries are marked as monitoring areas, the monitoring areas are divided into a plurality of sub-areas, the sub-areas are marked as i, visitor intensity coefficients Xi of each sub-area in the monitoring areas are obtained through a formula and are compared with visitor intensity coefficient thresholds; each region is divided in the scenic spot, the work efficiency of broadcast broadcasting is improved, the advertising strength of broadcast broadcasting is enhanced when the awareness of children is kept away is improved, and the actual cost is reduced when the economic development of the scenic spot is promoted.
Description
Technical Field
The invention relates to the technical field of cultural travel construction management, in particular to an intelligent management system for cultural travel construction based on big data.
Background
The novel technical revolution represented by application technologies such as the Internet of things, the mobile internet, cloud computing, big data, artificial intelligence, a block chain and a 5G communication technology has objectively promoted the higher-level requirement of the customer source market on tourism informatization, and a contract and a foundation are provided for the fusion development of the tourism industry and the information technology industry, machines and tools are remodeled by the technology A, the network supporting capacity is improved by the 5G technology, the access capacity of terminal tools is improved by the cloud computing, and convenience is improved for the interconnection of the intelligent internet of everything by the intelligent internet of things AIOT. The application of the new technology greatly improves the supply capacity of the tourism industry, and brings brand new changes to the industry. The arrival of the 5G era, the comprehensive digital upgrading of the assisted culture and the tourism supply side comprises user insight, product design, service experience, comprehensive management, intelligent brain construction and the like.
However, in the prior art, the scenic spot cannot be divided into areas, so that the broadcasting and broadcasting work efficiency is low, and the economic development of the scenic spot is not facilitated.
Disclosure of Invention
The invention aims to provide an intelligent management system for civil and tourist construction based on big data, which is characterized in that a scenic spot region is divided through a region dividing unit, so that broadcast broadcasting with different interval durations is set for each region, a region boundary is set in the scenic spot region, the region in the region boundary is marked as a monitoring region, the monitoring region is divided into a plurality of sub-regions and is marked as i, the number of visitors passing through each sub-region per hour is obtained, the average stay duration of the visitors in each sub-region is obtained, the visitor intensity coefficient Xi of each sub-region in the monitoring region is obtained through a formula, and the visitor intensity coefficient Xi of each sub-region in the monitoring region is compared with a visitor intensity coefficient threshold; each area in the scenic spot is divided, so that the working efficiency of broadcast broadcasting is improved, the prevention consciousness of children is improved, the advertising strength of broadcast broadcasting is enhanced, the economic development of the scenic spot is promoted, and the actual cost is reduced;
the purpose of the invention can be realized by the following technical scheme:
an intelligent management system for the construction of cultural and tourist based on big data comprises a region dividing unit, an environment monitoring unit, a consumption analysis unit, a cloud management platform, a registration and login unit and a database;
the regional division unit is used for carrying out regional division on the scenic spot region, thereby setting broadcast with different time intervals for each region, and the specific division setting process is as follows:
step S1: setting a region boundary in the scenic spot region, marking the region in the region boundary as a monitoring region, dividing the monitoring region into a plurality of sub-regions, and marking the sub-regions as i, i is 1, 2, … …, n, n is a positive integer;
step S2: acquiring the number of visitors passing by each sub-area per hour, and marking the number of visitors passing by each sub-area per hour as RSi;
step S3: acquiring the average stay time of the tourists in each sub-area, and marking the average stay time of the tourists in each sub-area as PSi;
step S4: by the formula
Acquiring a visitor intensity coefficient Xi of each sub-area in a monitoring area, wherein a1 and a2 are proportional coefficients, a1 is larger than a2 is larger than 0, and beta is an error correction factor and takes a value of 1.25;
step S5: comparing the guest intensity coefficients Xi of all sub-areas in the monitoring area with guest intensity coefficient thresholds:
if the guest strength coefficient Xi of the sub-area is larger than or equal to the guest strength coefficient threshold value, marking the corresponding sub-area as a high-strength area, sending the high-strength area to the cloud management platform, after receiving the high-strength area, the cloud management platform sets the broadcast time length of the corresponding high-strength area to 5 minutes, and then entering step S6;
if the visitor intensity coefficient Xi of the sub-area is smaller than the visitor intensity coefficient threshold value, marking the corresponding sub-area as a low-intensity area, sending the low-intensity area to a cloud management platform, and after receiving the low-intensity area, setting the broadcast broadcasting time length of the corresponding low-intensity area to 15 minutes by the cloud management platform;
step S6: the method comprises the steps of analyzing tourists in a high-strength area, obtaining the ratio of adults to children in the tourists all day in the high-strength area, if the ratio of adults to children in the tourists in the high-strength area is larger than 1, enabling the number of advertisement voices in broadcast broadcasting to be larger than the number of safety prompt voices, and if the ratio of adults to children in the tourists in the high-strength area is smaller than or equal to 1, enabling the number of advertisement voices in broadcast broadcasting to be smaller than the number of safety prompt voices.
Further, the environment monitoring unit is used for analyzing the environment information in each subregion to carry out environment monitoring to each subregion, and the environment information of subregion includes noise data, air data and hydrology data, and noise data is the frequency that the maximum decibel value of noise and noise produced in each subregion, and air data is the content of total suspended particles in the air in each subregion and the air quality rank that corresponds, and hydrology data is the maximum floating value of water level in each subregion and the content of suspended particles in water, and concrete analysis monitoring process is as follows:
step SS 1: acquiring the maximum decibel value of noise and the frequency of noise generation in each subarea, respectively marking the maximum decibel value of noise and the frequency of noise generation in each subarea as FBi and PLi, and acquiring a noise influence coefficient Zi in each subarea by a formula Zi FBi × b1+ PLi × b2, wherein b1 and b2 are proportional coefficients, and b1 is greater than b2 is greater than 0;
step SS 2: acquiring the content of total suspended particulate matters in the air in each subarea and the corresponding air quality grade, respectively marking the content of the total suspended particulate matters in the air in each subarea and the corresponding air quality grade as HLi and JBi, and acquiring an air influence coefficient Ki in each subarea by a formula Ki of HLi × b3+ JBi × b4, wherein b3 and b4 are proportional coefficients, and b3 is more than b4 and more than 0;
step SS 3: acquiring the maximum floating value of the water level in each sub-area and the content of suspended particles in the water, marking the maximum floating value of the water level in each sub-area and the content of the suspended particles in the water as FDi and XFi, and acquiring a hydrological influence coefficient Si in each sub-area by a formula Si of FDi × b5+ XFi × b6, wherein b5 and b6 are proportional coefficients, and b5 is greater than b6 is greater than 0;
step SS 4: summarizing the noise influence coefficient Zi, the air influence coefficient Ki and the hydrologic influence coefficient Si corresponding to each subregion, and comparing the summary with corresponding coefficient thresholds respectively:
if the corresponding influence coefficients in the sub-areas are all larger than the corresponding threshold values, marking the corresponding sub-areas as primary rectification areas;
if two corresponding influence coefficients exist in the sub-area and are larger than the corresponding threshold value, marking the corresponding sub-area as a secondary rectification area;
if one corresponding influence coefficient in the sub-area is larger than the corresponding threshold value, marking the corresponding sub-area as a three-level rectification area;
if the corresponding influence coefficients in the sub-regions are all smaller than the corresponding threshold values, marking the corresponding sub-regions as normal regions;
step SS 5: and the first-stage rectification area, the second-stage rectification area, the third-stage rectification area and the normal area are all sent to a cloud management platform, and the cloud management platform generates rectification signals and sends the rectification signals to a mobile phone terminal of a manager.
Further, the consumption analysis unit is used for monitoring and analyzing consumption data of tourists in each sub-area, the consumption data comprises age data and money data, the age data is the average frequency of the tourists consumed in each sub-area, the money data is the average money consumed by the tourists in each sub-area, and the specific monitoring and analyzing process comprises the following steps:
step T1: acquiring the average frequency of the tourists consumed in each subarea in real time, and marking the average frequency of the tourists consumed in each subarea as NLi;
step T2: acquiring the average amount of the tourist consumption in each subarea in real time, and marking the average amount of the tourist consumption in each subarea as JEi;
step T3: acquiring consumption analysis coefficients Ji of each sub-region by a formula Ji-alpha (NLi × c1+ JEi × c2), wherein c1 and c2 are proportional coefficients, c1 is larger than c2 is larger than 0, and alpha is an error correction factor and is 2.36;
step T4: comparing the consumption analysis coefficient Ji of each subregion with a consumption analysis coefficient threshold:
if the consumption analysis coefficient Ji of the subregion is larger than or equal to the consumption analysis coefficient threshold value, judging that the consumption analysis of the corresponding subregion is normal, generating a normal consumption signal and sending the normal consumption signal to a mobile phone terminal of a monitoring person;
and if the consumption analysis coefficient Ji of the sub-area is less than the consumption analysis coefficient threshold, judging that the consumption analysis of the corresponding sub-area is abnormal, generating a consumption abnormal signal and sending the consumption abnormal signal to the mobile phone terminal of the monitoring personnel.
Further, the registration login unit is used for the manager and the monitoring personnel to submit the manager information and the monitoring personnel information through the mobile phone terminals for registration, and data storage is carried out on the manager information and the monitoring personnel information which are successfully registered, the manager information comprises the name, the age, the time of entry and the mobile phone number of the real name authentication of the manager, and the monitoring personnel information comprises the name, the age, the time of entry and the mobile phone number of the real name authentication of the monitoring personnel.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the method, a region dividing unit is used for carrying out region division on scenic spot regions, so that broadcast broadcasting with different interval time lengths is set for each region, region boundaries are set in the scenic spot regions, the regions in the region boundaries are marked as monitoring regions, the monitoring regions are divided into a plurality of sub-regions, the sub-regions are marked as i, the number of visitors passing by each sub-region per hour is obtained, the average stay time length of the visitors in each sub-region is obtained, the visitor strength coefficient Xi of each sub-region in the monitoring region is obtained through a formula, and the visitor strength coefficient Xi of each sub-region in the monitoring region is compared with a visitor strength coefficient threshold; each area in the scenic spot is divided, so that the working efficiency of broadcast broadcasting is improved, the prevention consciousness of children is improved, the advertising strength of broadcast broadcasting is enhanced, the economic development of the scenic spot is promoted, and the actual cost is reduced;
2. according to the invention, the environment monitoring unit is used for analyzing the environment information in each sub-area, so that the environment of each sub-area is monitored, the maximum decibel value of noise and the frequency generated by the noise in each sub-area are obtained, and the noise influence coefficient Zi in each sub-area is obtained through a formula; acquiring the content of total suspended particulate matters in the air in each sub-area and the corresponding air quality grade, and acquiring the air influence coefficient Ki in each sub-area through a formula; acquiring the maximum floating value of the water level in each sub-area and the content of suspended particles in the water, acquiring a hydrologic influence coefficient Si in each sub-area through a formula, summarizing the noise influence coefficient Zi, the air influence coefficient Ki and the hydrologic influence coefficient Si corresponding to each sub-area, and comparing the collected values with corresponding coefficient thresholds respectively; the environment of each subregion in the scenic spot is monitored, and the quality of playing of visitor is improved, has reduced visitor's accident risk simultaneously, promotes the economic development in scenic spot.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic block diagram of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, an intelligent management system for construction of a text trip based on big data includes a region division unit, an environment monitoring unit, a consumption analysis unit, a cloud management platform, a registration unit and a database;
the registration login unit is used for submitting management personnel information and monitoring personnel information to register through mobile phone terminals by management personnel and monitoring personnel, and storing data of the management personnel information and the monitoring personnel information which are successfully registered, wherein the management personnel information comprises the name, the age, the time of entry of the management personnel and the mobile phone number of real name authentication of the person, and the monitoring personnel information comprises the name, the age, the time of entry of the monitoring personnel and the mobile phone number of real name authentication of the person;
the regional division unit is used for carrying out regional division to the sight spot region to set up the broadcast of length during different intervals to each region and report, specifically divide the setting process as follows:
step S1: setting a region boundary in the scenic spot region, marking the region in the region boundary as a monitoring region, dividing the monitoring region into a plurality of sub-regions, and marking the sub-regions as i, i is 1, 2, … …, n, n is a positive integer;
step S2: acquiring the number of visitors passing by each sub-area per hour, and marking the number of visitors passing by each sub-area per hour as RSi;
step S3: acquiring the average stay time of the tourists in each sub-area, and marking the average stay time of the tourists in each sub-area as PSi;
step S4: by the formula
Acquiring a visitor intensity coefficient Xi of each sub-area in a monitoring area, wherein a1 and a2 are proportional coefficients, a1 is larger than a2 is larger than 0, and beta is an error correction factor and takes a value of 1.25;
step S5: comparing the guest intensity coefficients Xi of all sub-areas in the monitoring area with guest intensity coefficient thresholds:
if the guest strength coefficient Xi of the sub-area is larger than or equal to the guest strength coefficient threshold value, marking the corresponding sub-area as a high-strength area, sending the high-strength area to the cloud management platform, after receiving the high-strength area, the cloud management platform sets the broadcast time length of the corresponding high-strength area to 5 minutes, and then entering step S6;
if the visitor intensity coefficient Xi of the sub-area is smaller than the visitor intensity coefficient threshold value, marking the corresponding sub-area as a low-intensity area, sending the low-intensity area to a cloud management platform, and after receiving the low-intensity area, setting the broadcast broadcasting time length of the corresponding low-intensity area to 15 minutes by the cloud management platform;
step S6: analyzing the tourists in the high-strength area to obtain the ratio of adults to children among the tourists all day in the high-strength area, if the ratio of adults to children among the tourists in the high-strength area is larger than 1, the number of the advertisement voices in the broadcast is larger than the number of the safety prompt voices, and if the ratio of adults to children among the tourists in the high-strength area is smaller than or equal to 1, the number of the advertisement voices in the broadcast is smaller than the number of the safety prompt voices;
the environment monitoring unit is used for analyzing the environmental information in each subregion, thereby carry out environmental monitoring to each subregion, the environmental information of subregion includes noise data, air data and hydrologic data, the noise data is the frequency that the maximum decibel value and the noise of each subregion noise produced, air data is total suspended particles's in the air in each subregion content and the air quality rank that corresponds, hydrologic data is the maximum floating value of each subregion water level and the content of aquatic suspended particles, concrete analysis and monitoring process is as follows:
step SS 1: acquiring the maximum decibel value of noise and the frequency of noise generation in each subarea, respectively marking the maximum decibel value of noise and the frequency of noise generation in each subarea as FBi and PLi, and acquiring a noise influence coefficient Zi in each subarea by a formula Zi FBi × b1+ PLi × b2, wherein b1 and b2 are proportional coefficients, and b1 is greater than b2 is greater than 0;
step SS 2: acquiring the content of total suspended particulate matters in the air in each subarea and the corresponding air quality grade, respectively marking the content of the total suspended particulate matters in the air in each subarea and the corresponding air quality grade as HLi and JBi, and acquiring an air influence coefficient Ki in each subarea by a formula Ki of HLi × b3+ JBi × b4, wherein b3 and b4 are proportional coefficients, and b3 is more than b4 and more than 0;
step SS 3: acquiring the maximum floating value of the water level in each sub-area and the content of suspended particles in the water, marking the maximum floating value of the water level in each sub-area and the content of the suspended particles in the water as FDi and XFi, and acquiring a hydrological influence coefficient Si in each sub-area by a formula Si of FDi × b5+ XFi × b6, wherein b5 and b6 are proportional coefficients, and b5 is greater than b6 is greater than 0;
step SS 4: summarizing the noise influence coefficient Zi, the air influence coefficient Ki and the hydrologic influence coefficient Si corresponding to each subregion, and comparing the summary with corresponding coefficient thresholds respectively:
if the corresponding influence coefficients in the sub-areas are all larger than the corresponding threshold values, marking the corresponding sub-areas as primary rectification areas;
if two corresponding influence coefficients exist in the sub-area and are larger than the corresponding threshold value, marking the corresponding sub-area as a secondary rectification area;
if one corresponding influence coefficient in the sub-area is larger than the corresponding threshold value, marking the corresponding sub-area as a three-level rectification area;
if the corresponding influence coefficients in the sub-regions are all smaller than the corresponding threshold values, marking the corresponding sub-regions as normal regions;
step SS 5: the first-stage rectification area, the second-stage rectification area, the third-stage rectification area and the normal area are all sent to a cloud management platform, and the cloud management platform generates rectification signals and sends the rectification signals to a mobile phone terminal of a manager;
the consumption analysis unit is used for monitoring and analyzing the tourist consumption data in each subregion, the consumption data comprises age data and money data, the age data is the average frequency of the tourists consumed in each subregion, the money data is the average money consumed by the tourists in each subregion, and the specific monitoring and analysis process comprises the following steps:
step T1: acquiring the average frequency of the tourists consumed in each subarea in real time, and marking the average frequency of the tourists consumed in each subarea as NLi;
step T2: acquiring the average amount of the tourist consumption in each subarea in real time, and marking the average amount of the tourist consumption in each subarea as JEi;
step T3: acquiring consumption analysis coefficients Ji of each sub-region by a formula Ji-alpha (NLi × c1+ JEi × c2), wherein c1 and c2 are proportional coefficients, c1 is larger than c2 is larger than 0, and alpha is an error correction factor and is 2.36;
step T4: comparing the consumption analysis coefficient Ji of each subregion with a consumption analysis coefficient threshold:
if the consumption analysis coefficient Ji of the subregion is larger than or equal to the consumption analysis coefficient threshold value, judging that the consumption analysis of the corresponding subregion is normal, generating a normal consumption signal and sending the normal consumption signal to a mobile phone terminal of a monitoring person;
and if the consumption analysis coefficient Ji of the sub-area is less than the consumption analysis coefficient threshold, judging that the consumption analysis of the corresponding sub-area is abnormal, generating a consumption abnormal signal and sending the consumption abnormal signal to the mobile phone terminal of the monitoring personnel.
The working principle of the invention is as follows:
the utility model provides a literary composition is wisdom management system for construction based on big data, at work, carry out regional division to the sight spot region through regional division unit, thereby set up the broadcast of different interval duration to each region and report, set up regional border in the sight spot region, and the regional mark in regional border is monitoring area, divide monitoring area into a plurality of subregion, and mark subregion as i, acquire the number of visitor's process in each subregion per hour, acquire the average length of stay of visitor in each subregion, acquire the visitor intensity coefficient Xi of each subregion in monitoring area through the formula, compare visitor intensity coefficient Xi and visitor intensity coefficient threshold value of each subregion in monitoring area.
The above formulas are all calculated by taking the numerical value of the dimension, the formula is a formula which obtains the latest real situation by acquiring a large amount of data and performing software simulation, and the preset parameters in the formula are set by the technical personnel in the field according to the actual situation.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (4)
1. An intelligent management system for the construction of a text and a travel based on big data is characterized by comprising a region dividing unit, an environment monitoring unit, a consumption analysis unit, a cloud management platform, a registration login unit and a database;
the regional division unit is used for carrying out regional division on the scenic spot region, thereby setting broadcast with different time intervals for each region, and the specific division setting process is as follows:
step S1: setting a region boundary in the scenic spot region, marking the region in the region boundary as a monitoring region, dividing the monitoring region into a plurality of sub-regions, and marking the sub-regions as i, i is 1, 2, … …, n, n is a positive integer;
step S2: acquiring the number of visitors passing by each sub-area per hour, and marking the number of visitors passing by each sub-area per hour as RSi;
step S3: acquiring the average stay time of the tourists in each sub-area, and marking the average stay time of the tourists in each sub-area as PSi;
step S4: by the formula
Acquiring a visitor intensity coefficient Xi of each sub-area in a monitoring area, wherein a1 and a2 are proportional coefficients, a1 is larger than a2 is larger than 0, and beta is an error correction factor and takes a value of 1.25;
step S5: comparing the guest intensity coefficients Xi of all sub-areas in the monitoring area with guest intensity coefficient thresholds:
if the guest strength coefficient Xi of the sub-area is larger than or equal to the guest strength coefficient threshold value, marking the corresponding sub-area as a high-strength area, sending the high-strength area to the cloud management platform, after receiving the high-strength area, the cloud management platform sets the broadcast time length of the corresponding high-strength area to 5 minutes, and then entering step S6;
if the visitor intensity coefficient Xi of the sub-area is smaller than the visitor intensity coefficient threshold value, marking the corresponding sub-area as a low-intensity area, sending the low-intensity area to a cloud management platform, and after receiving the low-intensity area, setting the broadcast broadcasting time length of the corresponding low-intensity area to 15 minutes by the cloud management platform;
step S6: the method comprises the steps of analyzing tourists in a high-strength area, obtaining the ratio of adults to children in the tourists all day in the high-strength area, if the ratio of adults to children in the tourists in the high-strength area is larger than 1, enabling the number of advertisement voices in broadcast broadcasting to be larger than the number of safety prompt voices, and if the ratio of adults to children in the tourists in the high-strength area is smaller than or equal to 1, enabling the number of advertisement voices in broadcast broadcasting to be smaller than the number of safety prompt voices.
2. The intelligent management system for civil travel construction based on big data as claimed in claim 1, wherein the environment monitoring unit is configured to analyze the environment information in each sub-area, so as to perform environment monitoring on each sub-area, and the specific analysis and monitoring process is as follows:
step SS 1: acquiring the maximum decibel value of noise and the frequency generated by the noise in each subregion, respectively marking the maximum decibel value of the noise and the frequency generated by the noise in each subregion as FBi and PLi, and acquiring a noise influence coefficient Zi in each subregion through a formula Zi-FBi × b1+ PLi × b 2;
step SS 2: acquiring the content of total suspended particulate matters in the air in each sub-area and the corresponding air quality level, respectively marking the content of the total suspended particulate matters in the air in each sub-area and the corresponding air quality level as HLi and JBi, and acquiring an air influence coefficient Ki in each sub-area by a formula of HLi × b3+ JBi × b 4;
step SS 3: acquiring the maximum floating value of the water level in each sub-area and the content of suspended particles in the water, marking the maximum floating value of the water level in each sub-area and the content of the suspended particles in the water as FDi and XFi, and acquiring a hydrological influence coefficient Si in each sub-area by a formula Si of FDi × b5+ XFi × b 6;
step SS 4: and summarizing the noise influence coefficient Zi, the air influence coefficient Ki and the hydrologic influence coefficient Si corresponding to each subarea, and comparing the collected values with corresponding coefficient thresholds respectively.
3. The intelligent management system for civil travel construction based on big data as claimed in claim 1, wherein the consumption analysis unit is used for monitoring and analyzing the consumption data of tourists in each sub-area, the consumption data includes age data and money data, the age data is the average frequency of the tourists consuming in each sub-area, the money data is the average money consumed by the tourists in each sub-area, and the specific monitoring and analysis process is as follows:
the method comprises the steps of acquiring the average frequency of tourists consuming in each subarea in real time and acquiring the average amount of tourists consuming in each subarea in real time, acquiring the consumption analysis coefficient Ji of each subarea through a formula Ji-alpha (NLi × c1+ JEi × c2), and comparing the consumption analysis coefficient Ji of each subarea with a consumption analysis coefficient threshold.
4. The intelligent management system for civil and tourism construction based on big data as claimed in claim 1, wherein the registration and login unit is used for the manager and the monitoring personnel to submit the manager information and the monitoring personnel information through the mobile phone terminal for registration, and to store the manager information and the monitoring personnel information which are successfully registered for data storage, the manager information includes the name, age, time of employment and the mobile phone number of the real name authentication of the person, and the monitoring personnel information includes the name, age, time of employment of the monitoring personnel and the mobile phone number of the real name authentication of the person.
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