CN118014444A - Intelligent park operation data analysis processing system based on Internet of things - Google Patents
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Abstract
The invention relates to the technical field of the Internet of things, in particular to an intelligent park operation data analysis processing system based on the Internet of things.
Description
Technical Field
The invention relates to the technical field of the Internet of things, in particular to an intelligent park operation data analysis processing system based on the Internet of things.
Background
Along with the advancement of global intellectualization and informatization wave, the intelligent park is taken as a core component of intelligent city construction, and gradually becomes a new engine for city development, which not only carries the aggregation and innovation of high-tech industry, but also represents the advanced concept and technical application of city management. However, in daily operation and management of an intelligent park, how to ensure the operation quality of the park, improve the resource utilization efficiency and optimize the service experience becomes an important subject in front of the manager.
The existing intelligent park operation data analysis processing system mainly aims at two levels of environment maintenance and operation management aiming at park operation quality evaluation, and has the following problems, which are specifically expressed in: 1. the prior art is lack of comprehensive and detailed analysis aiming at environmental maintenance of an enterprise park, only single dimension is focused, such as only greening environment is focused, other important aspects such as roads and building environments are ignored, even if multiple dimensions are involved, core elements and detail layers which are deep into each dimension are not analyzed, for example, only flatness and damage conditions of roads are focused on the aspect of road environment, details of lighting effects of street lamps are ignored, whether the appearance of a building is perfect or not is focused on the aspect of building environment, and key factors of operation states of internal facilities are ignored, so that the overall environmental condition of the enterprise park cannot be objectively and comprehensively reflected, and accuracy and reliability of operation quality assessment results of the enterprise park are further influenced.
2. The prior art excessively relies on the inside operation data of enterprise and index when analyzing to the operation management quality of enterprise garden, neglects personnel to flow and can directly reflect the external appeal of enterprise garden and the directly perceived influence of competitiveness as external feedback index, leads to analysis visual angle limitation to can't reflect the actual operation condition of enterprise garden comprehensively, has restricted the continuous promotion of enterprise garden operation management quality.
Disclosure of Invention
In order to overcome the defects in the background technology, the embodiment of the invention provides an intelligent park operation data analysis processing system based on the Internet of things, which can effectively solve the problems related to the background technology.
The aim of the invention can be achieved by the following technical scheme: an intelligent park operation data analysis processing system based on the internet of things, comprising: and the campus operation data uploading module is used for marking each enterprise campus in the target area as each target campus and uploading environment maintenance data, personnel flow data and enterprise management data in each target campus monitoring period.
The park environment evaluation module is used for analyzing greening environment maintenance indexes, road environment maintenance indexes and building environment maintenance indexes in each target park monitoring period according to the environment maintenance data in each target park monitoring period so as to evaluate the environment maintenance quality coefficient in each target park monitoring periodWherein/>For the number of each target campus,。
The campus operation evaluation module is used for analyzing the people flow density index and the operation activity index in each target campus monitoring period according to the people flow data and the enterprise management data in each target campus monitoring period so as to evaluate the operation management quality coefficient in each target campus monitoring period。
A park operation quality analysis module for analyzing the operation quality of the park according to the formulaAnd analyzing to obtain the comprehensive operation quality coefficient in the monitoring period of each target park.
And the campus operation quality sequence feedback module is used for generating an enterprise campus operation quality sequence in the target area monitoring period according to the sequence of the comprehensive operation quality coefficients from large to small and feeding back the enterprise campus operation quality sequence.
The cloud database is used for storing the building area of each target park, the number of buildings, the entrance positions of each building and the corresponding operation indexes of each infrastructure to reach the standard value, storing the vehicle reference passing width of a single-line road, storing the unit peak time, the unit low peak time and the unit flat peak time of the enterprise park to correspond to the reference people flow threshold, and storing the reference employment post providing number, the reference production output value and the reference park cooperation activity number of a single enterprise.
Preferably, the environmental maintenance data includes greening environmental data, road environmental data, and building environmental data.
The greening environment data comprise newly-increased vegetation coverage rate, newly-increased vegetation type quantity, maintenance period interval days, and the cleanliness and health degree of vegetation after each maintenance.
The road environment data comprises a road layout network diagram, the length, the width and the flatness of each branch, the road surface accumulated damage area occupation ratio and the maximum damage depth occupation ratio of each branch, and the night minimum illumination brightness and the accumulated illumination area of the street lamp of each branch.
The building environment data comprise the qualification degree of the water quality spot check of each building, the cleanliness of the spot check of the sanitary facilities and the monitoring value of each infrastructure corresponding to each operation index.
The personnel flow data includes the number of residents and the number of flowing persons in each monitoring period of each day.
The enterprise management data comprises an original enterprise type sequence, the types, the scale areas and the employment post providing quantity of each newly-entered enterprise, the production value of each original enterprise, the number of park cooperation activities and the stability of a park supply chain.
Preferably, the analyzing the greening environment maintenance index in each target park monitoring period includes: extracting newly increased vegetation coverage rate in greening environment data in monitoring period of each target parkAnd newly added vegetation species number/>Calculating greening improvement degree index/>, in each target park monitoring period，/>。
Acquiring the number of days corresponding to the monitoring periodExtracting maintenance period interval days/>, in greening environment data in each target park monitoring periodThe cleanliness/>, of vegetation after each maintenanceAnd health/>Wherein/>For the number of each curing time,Calculating greening maintenance degree index/>, in each target park monitoring period，Wherein/>For maintenance times,/>Is a natural constant.
Taking the accumulated value of the greening improvement degree index and the greening maintenance degree index in each target park monitoring period as the greening environment maintenance index in each target park monitoring period。
Preferably, the analyzing the road environment maintenance index in each target campus monitoring period includes: extracting road layout network diagrams in road environment data in each target park monitoring period, importing the entry positions of the buildings of each target park stored in a cloud database into corresponding road layout network diagrams, marking branches of the entry positions of the buildings in the middle of the road layout network diagrams as reachable branches, acquiring the number of the reachable branches corresponding to each building of each target park, marking a building as a road blind area building if the number of the reachable branches corresponding to a certain building is 0, and further counting the number of the road blind area buildings of each target park。
Outlining the peripheral outline of the road layout network diagram in each target park monitoring period, obtaining the area of the peripheral outline, and converting the peripheral outline according to a set proportion relation to obtain the actual occupation area of the road peripheral outline in each target park monitoring period。
Building quantity of each target park stored according to cloud databaseAnd build area/>From the formulaAnd obtaining the road coverage in each target park monitoring period.
Extracting width of each branch in road environment data in each target park monitoring periodAnd flatness/>The road surface accumulated damage area occupation ratio of each branchAnd maximum depth of failure duty cycle/>Wherein/>For the number of each branch circuit,Vehicle reference traffic width/>, according to a single line road stored in a cloud databaseCalculating road construction quality index/>, in each target park monitoring period，/>，/>Is the number of branches.
Extracting length of each branch in road environment data in each target park monitoring periodNight minimum illumination intensity of street lamp/>And cumulative illumination area/>Calculating the road illumination safety index/>, in each target park monitoring period，，/>The road surface brightness is reasonable for the preset urban road.
And then is represented by the formulaObtaining the road environment maintenance index/>, in each target park monitoring period。
Preferably, the analyzing building environment maintenance index in each target campus monitoring period includes: extracting the corresponding operation index monitoring value of each infrastructure of each building in the building environment data in each target park monitoring period, comparing the operation index monitoring value with the corresponding operation index value of each infrastructure of each building in each target park stored in the cloud database, obtaining the corresponding abnormal operation index of each infrastructure of each building in each target park monitoring period and the deviation value thereof, and counting the quantity of the abnormal infrastructures of each building in each target park monitoring periodAnd infrastructure total number/>Wherein/>Numbering for each building,/>Quality of water quality spot check qualification/>, of each building in combination with building environment data in each target park monitoring periodAnd sanitary facility spot check cleanliness/>Analyzing building environment maintenance index/>, in each target park monitoring periodThe calculation formula is as follows: /(I)，/>Is the number of buildings.
Preferably, the calculation formula of the environmental maintenance quality coefficient in each target campus monitoring period is as follows: wherein/> The weight ratio is respectively corresponding to a preset greening environment maintenance index, a road environment maintenance index and a building environment maintenance index.
Preferably, the analyzing the people stream density index in each target campus monitoring period includes: extracting resident people and mobile people in each monitoring time period of each day in the personnel flow data in each target park monitoring period, taking the accumulated value of the resident people and the mobile people as a personnel flow value, and recording the accumulated value as a personnel flow threshold according to the corresponding reference personnel flow value of the enterprise park unit peak time, the unit low peak time and the unit flat peak time stored in the cloud databaseThe peak time period, the low peak time period and the flat peak time period of each day in each target park monitoring period are obtained, the resident number, the flowing number and the duration corresponding to the peak time period, the low peak time period and the flat peak time period of each day in each target park monitoring period are counted respectively, and recorded as/>、、/>Wherein/>To monitor the number of days in a cycle,And then by the formulaAnd obtaining the people stream density index in each target park monitoring period.
Preferably, the analyzing the operation activity index in each target campus monitoring period includes: extracting original enterprise type sequence, type and scale area of each newly-resident enterprise in enterprise management data in each target park monitoring periodAnd employment post offer quantity/>Wherein/>For each new resident enterprise numbering,/>。
Comparing each new resident enterprise type with the original enterprise type sequence in each target park monitoring period, if a new resident enterprise type exists in the original enterprise type sequence in the target park, recording the corresponding business innovation factor of the new resident enterprise as 0.5, otherwise as 1, and obtaining the business innovation factor of each new resident enterprise in each target park monitoring period，/>Calculating the newly increased business activity index/>, in each target park monitoring period，Wherein/>The number is provided for a reference employment post of a single enterprise stored in the cloud database.
Extracting production and output values of original enterprises in enterprise management data in each target park monitoring periodNumber of campaigns/number of campaigns ]And park supply chain stability/>，/>Numbering for each original enterprise,/>Calculating the original business activity index/>, in each target park monitoring period，/>Wherein/>The number of reference campaigns and the reference production yields for the individual enterprises stored for the cloud database, respectively.
Taking the accumulated value of the newly increased business activity index and the original business activity index in each target park monitoring period as the operation activity index in each target park monitoring period。
Preferably, the calculation formula of the operation management quality coefficient in each target campus monitoring period is as follows:。
Compared with the prior art, the embodiment of the invention has at least the following advantages or beneficial effects: (1) According to the invention, the road coverage, the road construction quality index and the road illumination safety index in each target park monitoring period are combined, so that the road environment maintenance index in each target park monitoring period is comprehensively analyzed, the problems in road environment maintenance can be found and solved in time, the safety and the use experience of the roads of the enterprise park are improved, and the sustainable development of the enterprise park is further promoted.
(2) According to the invention, the building environment maintenance indexes in the monitoring period of each target park are comprehensively analyzed from three angles of the running state of building infrastructure, the quality qualification rate of water quality and the cleanliness of sanitary facilities, the working environment of the building in the enterprise park is objectively known, the working efficiency and quality of staff are improved, and the overall attractiveness and competitiveness of the enterprise park are enhanced.
(3) According to the invention, environmental maintenance quality evaluation in each target park monitoring period is developed from three dimensions of the greening environmental maintenance index, the road environmental maintenance index and the building environmental maintenance index, so that park managers are helped to know actual conditions of park environmental maintenance more deeply and more finely, potential problems and optimization spaces possibly existing in greening, roads and buildings are found, and the operation efficiency and the management level of park environmental maintenance are improved.
(4) According to the method, the system and the device, the people flow density index and the operation activity index in each target park monitoring period are analyzed, so that the operation management quality coefficient in each target park monitoring period is estimated, the defect of feedback index analysis aiming at the personnel flow outside in the prior art is overcome, a more comprehensive visual angle and a more accurate operation management quality estimation result are provided, further, data support is provided for comprehensive operation quality estimation in each target park monitoring period, and continuous optimization and improvement of enterprise park operation are promoted.
Drawings
The invention will be further described with reference to the accompanying drawings, in which embodiments do not constitute any limitation of the invention, and other drawings can be obtained by one of ordinary skill in the art without inventive effort from the following drawings.
Fig. 1 is a schematic diagram of the module connection of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the invention provides an intelligent park operation data analysis processing system based on internet of things, comprising: the system comprises a park operation data uploading module, a park environment assessment module, a park operation quality analysis module, a park operation quality sequence feedback module and a cloud database.
The system comprises a park operation data uploading module, a park operation quality analysis module, a cloud database and a cloud database, wherein the park operation data uploading module is respectively connected with a park environment assessment module and a park operation assessment module, the park environment assessment module and the park operation assessment module are both connected with the park operation quality analysis module, the park operation quality analysis module is connected with a park operation quality sequence feedback module, and the cloud database is respectively connected with the park environment assessment module and the park operation assessment module.
And the park operation data uploading module is used for marking each enterprise park in the target area as each target park and uploading environment maintenance data, personnel flow data and enterprise management data in each target park monitoring period.
Specifically, the environmental maintenance data includes greening environmental data, road environmental data, and building environmental data.
The greening environment data comprise newly-increased vegetation coverage rate, newly-increased vegetation type quantity, maintenance period interval days, and the cleanliness and health degree of vegetation after each maintenance.
The road environment data comprises a road layout network diagram, the length, the width and the flatness of each branch, the road surface accumulated damage area occupation ratio and the maximum damage depth occupation ratio of each branch, and the night minimum illumination brightness and the accumulated illumination area of the street lamp of each branch.
The building environment data comprise the qualification degree of the water quality spot check of each building, the cleanliness of the spot check of the sanitary facilities and the monitoring value of each infrastructure corresponding to each operation index.
It should be noted that, the coverage rate of newly-increased vegetation and the number of newly-increased vegetation types in the greening environment data in each target park monitoring period are determined by performing high-altitude remote sensing monitoring by using satellites or unmanned aerial vehicles and further using image recognition and image classification, the number of days of maintenance period intervals and the cleanliness and health of vegetation after each maintenance are extracted from the maintenance management log of the target park, and the cleanliness and health are evaluated by professional staff.
The road environment data acquisition process in each target park monitoring period comprises the following steps: the method comprises the steps of obtaining a high-resolution image of a target park by using an unmanned aerial vehicle aerial photographing technology, extracting a road network by using an image processing technology, introducing the road network into GIS software for drawing to obtain an accurate road layout network diagram, further obtaining the length and the width of each branch by using a measuring tool of the GIS software, rapidly scanning road elevation data and images by using a vehicle-mounted laser scanner, wherein the elevation data comprises flatness, automatically identifying a damaged area by using damaged features existing in an established database, calculating the accumulated damaged area and the maximum damaged area depth by using image identification, and monitoring night minimum illumination brightness and accumulated illumination area of the street lamp of each branch by using an illuminometer and a light intensity distribution measuring instrument at night by professionals.
The monitoring values of the running indexes corresponding to the infrastructures in the buildings in the building environment data in the monitoring period of each target park are obtained by integrating and taking the average value of the data of each day in the monitoring period of each building by the relevant sensors which are arranged in the infrastructures in real time, and the quality sampling inspection qualification and the sanitation sampling inspection cleanliness of the water quality are obtained by carrying out water sampling inspection and sanitation sampling inspection by professionals in the monitoring period at set sampling inspection frequency and carrying out average value calculation on the evaluation result of each sampling inspection.
Illustratively, the infrastructure of the target park building includes a power supply facility, a water supply facility, an elevator, and the like, each operation index monitoring value of the power supply facility includes a voltage value, a current load, a power factor, a power frequency, and an insulation resistance value, each operation index monitoring value of the water supply facility includes a water supply water pressure, a flow rate of a water supply pipe, and a water supply leakage signal, and each operation index monitoring value of the elevator includes an operation speed, a load capacity, a parking deviation value, an operation number, and a failure rate.
The personnel flow data includes the number of residents and the number of flowing persons in each monitoring period of each day.
It should be noted that, the above personnel flow data in each target campus monitoring period is obtained by counting and monitoring the personnel flow according to the omnibearing video monitoring cameras in the enterprise campus through the video analysis software, the video analysis software identifies and tracks the personnel flow in the picture, and detects and counts the movement and the going-out of the pedestrians at the entrance of the enterprise campus, so as to obtain the resident number and the mobile number of each monitoring period, wherein the resident number refers to the number of people which stay in the campus and do not leave in the monitoring period, the mobile number refers to the number of people which enter the campus and leave the campus in the monitoring period, and the specific unit duration of the monitoring period corresponds to the period, which can be exemplified by 12:00-13:00.
The enterprise management data comprises an original enterprise type sequence, the types, the scale areas and the employment post providing quantity of each newly-entered enterprise, the production value of each original enterprise, the number of park cooperation activities and the stability of a park supply chain.
It should be noted that, the enterprise management data in the above-mentioned each target campus monitoring period is collected by performing information investigation on each enterprise in the campus through the campus construction service platform, where the stability of the supply chain of the original enterprise is that the stability of the supply chain is determined by collecting each link data of the supply chain, such as matching degree of order content fulfillment, time of delivery, and turnover rate of stock, according to whether each link of the supply chain reaches the standard or not, and taking the ratio of the number of the stable links and the total links of the supply chain as the stability of the supply chain.
The park environment evaluation module is used for analyzing greening environment maintenance indexes, road environment maintenance indexes and building environment maintenance indexes in each target park monitoring period according to environment maintenance data in each target park monitoring period, so as to evaluate environment maintenance quality coefficients in each target park monitoring periodWherein/>For the number of each target campus,。
Specifically, the analyzing the greening environment maintenance index in each target park monitoring period comprises the following steps: extracting newly increased vegetation coverage rate in greening environment data in monitoring period of each target parkAnd newly added vegetation species number/>Calculating greening improvement degree index/>, in each target park monitoring period，/>。
Acquiring the number of days corresponding to the monitoring periodExtracting maintenance period interval days/>, in greening environment data in each target park monitoring periodThe cleanliness/>, of vegetation after each maintenanceAnd health/>Wherein/>For the number of each curing time,Calculating greening maintenance degree index/>, in each target park monitoring period，Wherein/>For maintenance times,/>Is a natural constant.
Taking the accumulated value of the greening improvement degree index and the greening maintenance degree index in each target park monitoring period as the greening environment maintenance index in each target park monitoring period。
Specifically, the analyzing the road environment maintenance index in each target campus monitoring period includes: extracting road layout network diagrams in road environment data in each target park monitoring period, importing the entry positions of the buildings of each target park stored in a cloud database into corresponding road layout network diagrams, marking branches of the entry positions of the buildings in the middle of the road layout network diagrams as reachable branches, acquiring the number of the reachable branches corresponding to each building of each target park, marking a building as a road blind area building if the number of the reachable branches corresponding to a certain building is 0, and further counting the number of the road blind area buildings of each target park。
Outlining the peripheral outline of the road layout network diagram in each target park monitoring period, obtaining the area of the peripheral outline, and converting the peripheral outline according to a set proportion relation to obtain the actual occupation area of the road peripheral outline in each target park monitoring period。
Building quantity of each target park stored according to cloud databaseAnd build area/>From the formulaAnd obtaining the road coverage in each target park monitoring period.
Extracting width of each branch in road environment data in each target park monitoring periodFlatness/>The road surface accumulated damage area occupation ratio of each branchAnd maximum depth of failure duty cycle/>Wherein/>For the number of each branch circuit,Vehicle reference traffic width/>, according to a single line road stored in a cloud databaseCalculating road construction quality index/>, in each target park monitoring period，/>，/>Is the number of branches.
Extracting length of each branch in road environment data in each target park monitoring periodNight minimum illumination intensity of street lamp/>And cumulative illumination area/>Calculating the road illumination safety index/>, in each target park monitoring period，，/>The road surface brightness is reasonable for the preset urban road.
It should be noted that, the reasonable brightness of the preset urban road pavement can be specifically referred to the standard guidelines for urban road lighting design.
And then is represented by the formulaObtaining the road environment maintenance index/>, in each target park monitoring period。
According to the method and the device for monitoring the road environment, road coverage, road construction quality indexes and road illumination safety indexes in the monitoring periods of all target parks are combined, the road environment maintenance indexes in the monitoring periods of all target parks are comprehensively analyzed, the problems in road environment maintenance can be found and solved in time, the safety and the use experience of roads of the enterprise parks are improved, and further sustainable development of the enterprise parks is promoted.
Specifically, the analyzing building environment maintenance indexes in each target park monitoring period includes: extracting the corresponding operation index monitoring value of each infrastructure of each building in the building environment data in each target park monitoring period, comparing the operation index monitoring value with the corresponding operation index value of each infrastructure of each building in each target park stored in the cloud database, obtaining the corresponding abnormal operation index of each infrastructure of each building in each target park monitoring period and the deviation value thereof, and counting the quantity of the abnormal infrastructures of each building in each target park monitoring periodAnd infrastructure total number/>Wherein/>Numbering for each building,/>Quality of water quality spot check qualification/>, of each building in combination with building environment data in each target park monitoring periodAnd sanitary facility spot check cleanliness/>Analyzing building environment maintenance index/>, in each target park monitoring periodThe calculation formula is as follows: /(I)，/>Is the number of buildings.
It should be noted that, the specific statistical process of the abnormal infrastructure quantity of each building in each target park monitoring period includes: taking the ratio of the deviation value of each infrastructure corresponding to each abnormal operation index to the standard reaching value of each building in each target park monitoring period as the operation risk degree factor of each infrastructure corresponding to each abnormal operation index of each building in each target park monitoring period, accumulating to obtain the operation risk index of each infrastructure of each building in each target park monitoring period, comparing the operation risk index with a preset reasonable operation risk index threshold value of the infrastructure, and if the operation risk index of a certain infrastructure is larger than the preset reasonable operation risk index threshold value of the infrastructure, marking the infrastructure as an abnormal infrastructure, further obtaining each abnormal infrastructure of each building in each target park monitoring period, and further counting the number of the normal infrastructures.
According to the embodiment of the invention, the building environment maintenance indexes in the monitoring period of each target park are comprehensively analyzed from three angles of the running state of building infrastructure, the quality qualification degree of water quality and the cleanliness of sanitary facilities, the working environment of the building in the enterprise park is objectively known, the working efficiency and the quality of staff are improved, and therefore the overall attractiveness and the competitiveness of the enterprise park are enhanced.
Specifically, the calculation formula of the environmental maintenance quality coefficient in each target park monitoring period is as follows: wherein/> The weight ratio is respectively corresponding to a preset greening environment maintenance index, a road environment maintenance index and a building environment maintenance index.
Illustratively, the aboveSpecifically, it may be/>。
According to the embodiment of the invention, the environmental maintenance quality evaluation in each target park monitoring period is developed from three dimensions of the greening environmental maintenance index, the road environmental maintenance index and the building environmental maintenance index, so that park managers can be helped to know actual conditions of park environmental maintenance more deeply and more carefully, potential problems and optimization spaces possibly existing in greening, roads and buildings are found, and the operation efficiency and the management level of park environmental maintenance are improved.
The park operation evaluation module is used for analyzing the people flow density index and the operation activity index in each target park monitoring period according to the people flow data and the enterprise management data in each target park monitoring period, so as to evaluate the operation management quality coefficient in each target park monitoring period。
Specifically, the analyzing the people stream density index in each target park monitoring period includes: extracting resident people and mobile people in each monitoring time period of each day in the personnel flow data in each target park monitoring period, taking the accumulated value of the resident people and the mobile people as a personnel flow value, and recording the accumulated value as a personnel flow threshold according to the corresponding reference personnel flow value of the enterprise park unit peak time, the unit low peak time and the unit flat peak time stored in the cloud databaseThe peak time period, the low peak time period and the flat peak time period of each day in each target park monitoring period are obtained, the resident number, the flowing number and the duration corresponding to the peak time period, the low peak time period and the flat peak time period of each day in each target park monitoring period are counted respectively, and recorded as/>、、/>Wherein/>To monitor the number of days in a cycle,And then by the formulaAnd obtaining the people stream density index in each target park monitoring period.
It should be noted that, the specific process of obtaining the peak period, the low peak period and the flat peak period of each day in the monitoring period of each target park is as follows: if the people flow in a certain monitoring time period is inThe monitoring time period is recorded as a peak monitoring time period, if the people flow in a certain monitoring time period is in/>The monitoring time period is recorded as a flat peak monitoring time period, and if the people flow in a certain monitoring time period is in/>And recording the monitoring time period as a low peak monitoring time period, and accordingly acquiring and integrating each peak monitoring time period, each flat peak monitoring time period and each low peak monitoring time period of each day in each target park monitoring period, so as to obtain the peak time period, the low peak time period and the flat peak time period of each day in each target park monitoring period.
Specifically, the analyzing the operation activity index in each target park monitoring period includes: extracting original enterprise type sequence, type and scale area of each newly-resident enterprise in enterprise management data in each target park monitoring periodAnd employment post offer quantity/>Wherein/>For each new resident enterprise numbering,/>。
Comparing each new resident enterprise type with the original enterprise type sequence in each target park monitoring period, if a new resident enterprise type exists in the original enterprise type sequence in the target park, recording the corresponding business innovation factor of the new resident enterprise as 0.5, otherwise as 1, and obtaining the business innovation factor of each new resident enterprise in each target park monitoring period，/>Calculating the newly increased business activity index/>, in each target park monitoring period，Wherein/>The number is provided for a reference employment post of a single enterprise stored in the cloud database.
Extracting production and output values of original enterprises in enterprise management data in each target park monitoring periodNumber of campaigns/number of campaigns ]And park supply chain stability/>，/>Numbering for each original enterprise,/>Calculating the original business activity index/>, in each target park monitoring period，/>Wherein/>The number of reference campaigns and the reference production yields for the individual enterprises stored for the cloud database, respectively.
Taking the accumulated value of the newly increased business activity index and the original business activity index in each target park monitoring period as the operation activity index in each target park monitoring period。
Specifically, the calculation formula of the operation management quality coefficient in each target park monitoring period is as follows:。
According to the embodiment of the invention, the people flow density index and the operation activity index in each target park monitoring period are analyzed, so that the operation management quality coefficient in each target park monitoring period is evaluated, the defect of the feedback index analysis aiming at the personnel flow outside in the prior art is overcome, a more comprehensive visual angle and a more accurate operation management quality evaluation result are provided, further, data support is provided for comprehensive operation quality evaluation in each target park monitoring period, and continuous optimization and improvement of enterprise park operation are promoted.
The park operation quality analysis module is used for analyzing the operation quality of the park according to the formulaAnd analyzing to obtain the comprehensive operation quality coefficient in the monitoring period of each target park.
And the campus operation quality sequence feedback module is used for generating an enterprise campus operation quality sequence in the target area monitoring period according to the sequence of the comprehensive operation quality coefficients from large to small and feeding back the enterprise campus operation quality sequence.
The cloud database is used for storing building areas of all target parks, the number of buildings, the entrance positions of all buildings and corresponding operation indexes of all infrastructures to achieve standard values, storing vehicle reference passing width of a single-line road, storing unit peak time, unit low peak time and unit flat peak time of each enterprise park to correspond to a reference people flow threshold, and storing the reference employment post providing number, the reference production output value and the reference park cooperation activity number of each enterprise.
The foregoing is merely illustrative of the structures of this invention and various modifications, additions and substitutions for those skilled in the art of describing particular embodiments without departing from the structures of the invention or exceeding the scope of the invention as defined by the claims.
Claims (9)
1. Intelligent park operation data analysis processing system based on thing networking, its characterized in that: the system comprises:
The campus operation data uploading module is used for marking each enterprise campus in the target area as each target campus and uploading environment maintenance data, personnel flow data and enterprise management data in the monitoring period of each target campus;
The park environment evaluation module is used for analyzing greening environment maintenance indexes, road environment maintenance indexes and building environment maintenance indexes in each target park monitoring period according to the environment maintenance data in each target park monitoring period so as to evaluate the environment maintenance quality coefficient in each target park monitoring period Wherein/>For the number of each target campus,；
The campus operation evaluation module is used for analyzing the people flow density index and the operation activity index in each target campus monitoring period according to the people flow data and the enterprise management data in each target campus monitoring period so as to evaluate the operation management quality coefficient in each target campus monitoring period；
A park operation quality analysis module for analyzing the operation quality of the park according to the formulaAnalyzing to obtain comprehensive operation quality coefficients in the monitoring period of each target park;
The campus operation quality sequence feedback module is used for generating an enterprise campus operation quality sequence in the target area monitoring period according to the sequence of the comprehensive operation quality coefficients from large to small and feeding back the enterprise campus operation quality sequence;
The cloud database is used for storing the building area of each target park, the number of buildings, the entrance positions of each building and the corresponding operation indexes of each infrastructure to reach the standard value, storing the vehicle reference passing width of a single-line road, storing the unit peak time, the unit low peak time and the unit flat peak time of the enterprise park to correspond to the reference people flow threshold, and storing the reference employment post providing number, the reference production output value and the reference park cooperation activity number of a single enterprise.
2. The intelligent park operation data analysis processing system based on the internet of things according to claim 1, wherein: the environment maintenance data comprises greening environment data, road environment data and building environment data;
The greening environment data comprise newly-increased vegetation coverage rate, newly-increased vegetation type quantity, maintenance period interval days, and the cleanliness and health of vegetation after each maintenance;
The road environment data comprises a road layout network diagram, the length, the width and the flatness of each branch, the road surface accumulated damage area occupation ratio and the maximum damage depth occupation ratio of each branch, and the night minimum illumination brightness and the accumulated illumination area of the road lamp of each branch;
the building environment data comprise water quality spot check qualification degree of each building, sanitary facility spot check cleanliness and monitoring values of each infrastructure corresponding to each operation index;
The personnel flow data comprise the resident number and the flowing number of each monitoring time period of each day;
The enterprise management data comprises an original enterprise type sequence, the types, the scale areas and the employment post providing quantity of each newly-entered enterprise, the production value of each original enterprise, the number of park cooperation activities and the stability of a park supply chain.
3. The intelligent park operation data analysis processing system based on the internet of things according to claim 2, wherein: the analyzing the greening environment maintenance index in each target park monitoring period comprises the following steps: extracting newly increased vegetation coverage rate in greening environment data in monitoring period of each target parkAnd newly added vegetation species number/>Calculating greening improvement degree index/>, in each target park monitoring period，/>；
Acquiring the number of days corresponding to the monitoring periodExtracting maintenance period interval days/>, in greening environment data in each target park monitoring periodThe cleanliness/>, of vegetation after each maintenanceAnd health/>Wherein/>For the number of each curing time,Calculating greening maintenance degree index/>, in each target park monitoring period，Wherein/>For maintenance times,/>Is a natural constant;
Taking the accumulated value of the greening improvement degree index and the greening maintenance degree index in each target park monitoring period as the greening environment maintenance index in each target park monitoring period 。
4. The intelligent park operation data analysis processing system based on the internet of things according to claim 3, wherein: the analyzing the road environment maintenance index in each target park monitoring period comprises the following steps: extracting road layout network diagrams in road environment data in each target park monitoring period, importing the entry positions of the buildings of each target park stored in a cloud database into corresponding road layout network diagrams, marking branches of the entry positions of the buildings in the middle of the road layout network diagrams as reachable branches, acquiring the number of the reachable branches corresponding to each building of each target park, marking a building as a road blind area building if the number of the reachable branches corresponding to a certain building is 0, and further counting the number of the road blind area buildings of each target park；
Outlining the peripheral outline of the road layout network diagram in each target park monitoring period, obtaining the area of the peripheral outline, and converting the peripheral outline according to a set proportion relation to obtain the actual occupation area of the road peripheral outline in each target park monitoring period；
Building quantity of each target park stored according to cloud databaseAnd build area/>From the formulaObtaining road coverage in each target park monitoring period;
extracting width of each branch in road environment data in each target park monitoring period And flatness/>The road surface accumulated damage area occupation ratio of each branchAnd maximum depth of failure duty cycle/>Wherein/>For the number of each branch circuit,Vehicle reference traffic width/>, according to a single line road stored in a cloud databaseCalculating road construction quality index/>, in each target park monitoring period，/>，/>The number of branches;
Extracting length of each branch in road environment data in each target park monitoring period Night minimum illumination intensity of street lamp/>And cumulative illumination area/>Calculating the road illumination safety index/>, in each target park monitoring period，，/>The road surface brightness is reasonable for the preset urban road;
And then is represented by the formula Obtaining the road environment maintenance index/>, in each target park monitoring period。
5. The intelligent park operation data analysis processing system based on the internet of things according to claim 4, wherein: the analyzing building environment maintenance indexes in each target park monitoring period comprises the following steps: extracting the corresponding operation index monitoring value of each infrastructure of each building in the building environment data in each target park monitoring period, comparing the operation index monitoring value with the corresponding operation index value of each infrastructure of each building in each target park stored in the cloud database, obtaining the corresponding abnormal operation index of each infrastructure of each building in each target park monitoring period and the deviation value thereof, and counting the quantity of the abnormal infrastructures of each building in each target park monitoring periodAnd infrastructure total number/>Wherein/>Numbering for each building,/>Quality of water quality spot check qualification/>, of each building in combination with building environment data in each target park monitoring periodAnd sanitary facility spot check cleanliness/>Analyzing building environment maintenance index/>, in each target park monitoring periodThe calculation formula is as follows: /(I)，/>Is the number of buildings.
6. The intelligent park operation data analysis processing system based on the internet of things according to claim 5, wherein: the calculation formula of the environmental maintenance quality coefficient in each target park monitoring period is as follows: wherein/> The weight ratio is respectively corresponding to a preset greening environment maintenance index, a road environment maintenance index and a building environment maintenance index.
7. The intelligent park operation data analysis processing system based on the internet of things according to claim 4, wherein: the analyzing the people stream density index in each target park monitoring period comprises the following steps: extracting resident people and mobile people in each monitoring time period of each day in the personnel flow data in each target park monitoring period, taking the accumulated value of the resident people and the mobile people as a personnel flow value, and recording the accumulated value as a personnel flow threshold according to the corresponding reference personnel flow value of the enterprise park unit peak time, the unit low peak time and the unit flat peak time stored in the cloud databaseThe peak time period, the low peak time period and the flat peak time period of each day in each target park monitoring period are obtained, the resident number, the flowing number and the duration corresponding to the peak time period, the low peak time period and the flat peak time period of each day in each target park monitoring period are counted respectively, and recorded as/>、、/>Wherein/>To monitor the number of days in a cycle,And then by the formulaAnd obtaining the people stream density index in each target park monitoring period.
8. The intelligent park operation data analysis processing system based on the internet of things according to claim 7, wherein: the analyzing the operation activity index in each target park monitoring period comprises the following steps: extracting original enterprise type sequence, type and scale area of each newly-resident enterprise in enterprise management data in each target park monitoring periodAnd employment post offer quantity/>Wherein/>For each new resident enterprise numbering,/>；
Comparing each new resident enterprise type with the original enterprise type sequence in each target park monitoring period, if a new resident enterprise type exists in the original enterprise type sequence in the target park, recording the corresponding business innovation factor of the new resident enterprise as 0.5, otherwise as 1, and obtaining the business innovation factor of each new resident enterprise in each target park monitoring period，Calculating the newly increased business activity index/>, in each target park monitoring period，Wherein/>Providing a quantity for reference employment posts of a single enterprise stored in a cloud database;
Extracting production and output values of original enterprises in enterprise management data in each target park monitoring period Number of campaigns/number of campaigns ]And park supply chain stability/>，/>Numbering for each original enterprise,/>Calculating the original business activity index/>, in each target park monitoring period，/>Wherein/>The method comprises the steps of storing the reference park cooperation activity number and the reference production yield value of a single enterprise for a cloud database respectively;
Taking the accumulated value of the newly increased business activity index and the original business activity index in each target park monitoring period as the operation activity index in each target park monitoring period 。
9. The intelligent park operation data analysis processing system based on the internet of things according to claim 8, wherein: the calculation formula of the operation management quality coefficient in each target park monitoring period is as follows:。
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