CN111967410A - Property intelligent management and allocation system based on big data - Google Patents
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Abstract
The invention discloses a property intelligent management and allocation system based on big data, which comprises a working area dividing module, a GPS positioning module, a scanning route programming module, a working state image acquisition module, an image primary processing module, an image comparison identification module, a working quality analysis and statistics module, a parameter database, a display terminal, a personnel intelligent allocation module, an early warning prompt module and a master monitoring center, wherein the system realizes intelligent allocation management of property in a cell by dividing a clean-keeping area and workers, acquiring working state images of the workers in each sub-area in a divided acquisition time period and evaluating working quality coefficients, and allocating the workers nearby when an emergency occurs in a certain area, thereby avoiding the problem that manual management is not in place, saving a large amount of manpower, and simultaneously making up the problem that manual management cannot allocate when an emergency occurs, the property management level is improved.
Description
Technical Field
The invention belongs to the technical field of property management, and relates to a property intelligent management and allocation system based on big data.
Background
With the development of city construction and improvement of living conditions, various residential districts such as various residences, commercial buildings, office buildings and the like are increased day by day, and all the residential districts face the problems of management, maintenance and renovation after delivery and use, the problems promote the generation of a property management system, the property management of China is subjected to a key period from germination to initial growth, the property is also transformed from basic charge collection management to district value-added service, and the property of the current districts generally provides various services, such as public services including basic services such as cleaning, security, greening and the like, and the agency services including water and electricity charge.
However, when the existing property management company performs the community cleaning management, the work management of each cleaning worker is manual management, the manual management cannot grasp the working state of each cleaning worker at any moment, the problem of insufficient management exists, the management efficiency is low, a large amount of manpower is wasted, and when an emergency occurs in a certain area, the unified allocation cannot be performed, so that the requirement of the existing property management is difficult to meet. In view of this, the invention provides a property intelligent management and deployment system based on big data.
Disclosure of Invention
The invention aims to solve the problems in the prior art, and provides a property intelligent management and allocation system based on big data.
The purpose of the invention is realized by adopting the following technical scheme:
a property intelligent management and allocation system based on big data comprises a working area dividing module, a working state image acquisition module, an image preliminary processing module, an image comparison identification module, a working quality analysis and statistics module, a parameter database, a display terminal and a personnel intelligent allocation module;
the working area dividing module is used for dividing a clean-keeping working area of the community property into a plurality of sub-areas according to a preset dividing mode, the sub-areas are numbered according to a preset sequence and are sequentially marked as z1, z2, a.
The working state image acquisition module is connected with the working area dividing module, the working state image acquisition module comprises a plurality of automatic tracking cameras which are respectively installed in each subregion and used for automatically monitoring the working state of workers in each subregion during working, the automatic tracking cameras can automatically identify image information, the automatic tracking cameras follow the movement to capture images when the images move so as to track moving objects, the working state image acquisition module acquires working images of the workers in each subregion according to a preset image acquisition time period to obtain working images of the workers in each time period of each subregion, and the acquired working images of the workers in each time period of each subregion are sent to the image primary processing module according to the image acquisition sequence;
the image primary processing module is connected with the working state image acquisition module, receives the working image of the working personnel in each time period of each subregion sent by the working state image acquisition module, performs image enhancement and high-definition filtering processing on the received working image of the working personnel in each time period of each subregion, performs gray processing on the processed working image, reserves the working personnel image, removes a background image, and simultaneously sends the reserved working image of each subregion to the image comparison identification module according to the image acquisition sequence;
the image comparison and identification module is connected with the image primary processing module, receives images of all sub-region workers sent by the image primary processing module, amplifies the images of all the sub-region workers received, captures hand features and leg features of the workers in the amplified images of the sub-region workers, extracts hand features and leg features corresponding to various non-standard working behaviors in the parameter database, compares and matches the captured hand features and leg features of the workers with the captured hand features and leg features one by one, if the corresponding non-standard working behaviors are not matched in the parameter database, the workers do not have the non-standard working behaviors in working, otherwise, if the corresponding non-standard working behaviors are matched in the parameter database, the matched non-standard working behaviors and the sub-region numbers are recorded, and simultaneously, the sub-region numbers of the non-standard working behaviors appearing in all the sub-regions and the matched non-standard working behaviors are counted The types of the images are sent to a working quality analysis and statistics module, meanwhile, images of workers in each sub-region in the next time period sent by the image primary processing module are received, hand features and leg features of the workers are captured, non-standard working behavior matching is carried out, and the matched non-standard working behavior types of each time period in each sub-region are sent to the working quality analysis and statistics module;
the parameter database stores the hand characteristics and the leg characteristics of the workers corresponding to various irregular working behaviors, and stores the working quality influence factors corresponding to various irregular working behaviors, wherein the various irregular working behaviors comprise playing a mobile phone, sleeping, smoking and chatting with other people;
the working quality analysis statistical module is connected with the image comparison identification module, receives the non-standard working behavior types of each time period of each sub-region which are sent by the image comparison identification module and matched with the image comparison identification module, and uniformly stores the non-standard working behavior types of the workers in each time period in the same sub-region to form a sub-region non-standard working behavior frequency set w (w) in all time periodsz1,wz2,…,wzj,...,wzm)，wzjExpressing the number w of times of occurrence of the abnormal working behaviors corresponding to the zj-th abnormal working behavior sub-region, wherein w is 1, 2.. k, extracting working quality influence factors corresponding to various abnormal working behaviors in a parameter database, counting working quality evaluation coefficients of various working personnel corresponding to the abnormal working behavior sub-regions, and sending the working quality evaluation coefficients to a display terminal;
the personnel intelligent allocation module is used for recording the number of a sub-area when an emergency or temporary heavy workload occurs in the sub-area, sending the recorded number of the sub-area with the emergency or temporary heavy workload to the master monitoring center, and dispatching the staff to the master monitoring center from other sub-areas nearby for processing;
and the display terminal is connected with the working quality analysis and statistics module, receives and displays the working quality evaluation coefficients of the workers corresponding to the sub-regions with the non-standard working behaviors, which are sent by the working quality analysis and statistics module.
According to an implementation mode of the invention, the intelligent personnel allocation system further comprises a GPS positioning module which is connected with the working area dividing module and used for positioning the boundary line geographical position of each divided sub-area and sending the acquired geographical position of the boundary line of each sub-area to the scanning route programming module and the intelligent personnel allocation module.
According to an implementation mode of the invention, the personnel intelligent allocation module is connected with the GPS positioning module, receives the geographical position of each sub-region boundary line sent by the GPS positioning module, compares the recorded sub-region number with the geographical position of each sub-region boundary line, screens the boundary line geographical position corresponding to the sub-region with the emergency or the temporarily increased workload, matches the geographical positions of other sub-region boundary lines with the geographical position of the sub-region boundary line, acquires the number of the other sub-region with the nearest distance to the sub-region with the emergency or the temporarily increased workload, and sends the number of the sub-region with the nearest distance to the total monitoring center.
According to one implementation mode of the invention, the system further comprises a master monitoring center which is connected with the intelligent personnel allocation module, receives the numbers of the sub-areas which are closest to the personnel intelligent allocation module, selects the numbers of the workers which are closest to the sub-areas according to the numbers of the workers which are corresponding to the sub-areas, and dispatches the workers to the sub-areas with emergency or temporarily increased workload for assisting work by using an interphone.
According to an implementation mode of the invention, the system further comprises a scanning route programming module which is connected with the GPS positioning module, receives the geographical position of the boundary line of each sub-region sent by the GPS positioning module, programs the received geographical position of the boundary line of each sub-region into a scanning route, inputs the programmed scanning route of the sub-region into the automatic tracking camera corresponding to each sub-region, scans by the automatic tracking camera of each sub-region according to the set scanning route, if the working personnel are not scanned in the scanning process, the working personnel corresponding to the sub-region are indicated to be not working in the specified working area, and at the moment, an early warning prompt control signal is sent to the early warning prompt module; and if the staff is scanned in the scanning process, automatically tracking the staff, and acquiring the working state image according to the image acquisition time period.
According to an implementation mode of the invention, the intelligent warning system further comprises an early warning prompting module which is connected with the scanning route programming module, receives an early warning prompting control signal sent by the scanning route programming module and intelligently prompts the staff, and the specific prompting method comprises the following steps:
h1: the early warning prompting module sends out a voice prompting signal to prompt the staff in the sub-area to return to the designated working area, and if the staff is not scanned in the scanning route by the automatic tracking camera in the sub-area after a specified time interval, the step H2 is executed;
h2: the early warning prompting module sends an early warning signal to a main monitoring center, and sends the sub-area numbers of the non-scanned workers to the main monitoring center, the main monitoring center receives the early warning signal, selects the worker numbers corresponding to the sub-areas of the non-scanned workers according to the worker numbers corresponding to the sub-areas, uses an interphone to converse with the workers to remind the workers to return to the appointed working area for working, and if the automatic tracking cameras in the sub-areas still do not scan the workers in the scanning route after a specified time interval, the step H3 is executed;
h3: the master monitoring center arranges related personnel to go to the subarea for manual processing.
According to one possible implementation manner of the invention, the calculation formula of the working quality evaluation coefficient is
The evaluation coefficient of the working quality of the staff corresponding to the zj-th sub-area with the non-standard working behavior is expressed,
and expressing the work quality influence factor corresponding to the w-th unnormalized work behavior of the worker corresponding to the zj-th unnormalized work behavior sub-region.
According to an implementation manner of the present invention, the preset image capturing time period is used for dividing the working time of the worker into a plurality of image capturing time periods according to the working time of the worker and the preset image capturing time interval.
The invention has the beneficial effects that:
(1) according to the property intelligent management allocation system based on the big data, provided by the invention, the clean area of the residential area is divided into a plurality of sub-areas, each sub-area corresponds to each worker one by one, the working state images of the workers in each sub-area are acquired by the working state image acquisition module in different acquisition time periods, whether the working state belongs to an irregular working state or not is analyzed, the working quality coefficient is evaluated, and meanwhile, when an emergency occurs in a certain area, the workers are allocated nearby for processing, so that the intelligent allocation management of the residential property is realized, the management efficiency is high, the problem that manual management is not in place is avoided, a large amount of management manpower is saved, the problem that manual management cannot be allocated when the emergency occurs is solved, the requirement of the existing property management is greatly met, and the property management level is improved.
(2) According to the property intelligent management and deployment system based on the big data, the boundary geographical position of each sub-area is obtained through the GPS positioning module, and convenience is provided for subsequent programming of an automatic tracking camera scanning route and intelligent deployment of personnel.
(3) According to the property intelligent management and allocation system based on the big data, the working quality of each worker corresponding to the sub-region with the irregular working behavior is evaluated through the working quality analysis and statistics module, the obtained working quality evaluation coefficient realizes quantitative display of the working quality of the worker, the workers can visually know the working quality of the workers and can compete and compare with each other, and meanwhile, the managers can grade the workers according to the working quality evaluation coefficient.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a block diagram of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious 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.
Referring to fig. 1, a property intelligent management and deployment system based on big data includes a working area division module, a GPS positioning module, a scanning route programming module, a working state image acquisition module, an image preliminary processing module, an image comparison identification module, a working quality analysis and statistics module, a parameter database, a display terminal, a personnel intelligent deployment module, an early warning prompt module, and a master monitoring center.
The working area dividing module is used for dividing a clean-keeping working area of the community property into a plurality of sub-areas according to a preset dividing mode, the sub-areas are numbered according to a preset sequence, the number of the sub-areas is marked as z1, z2,. seni, zn, a worker is arranged in each sub-area to clean the working area of the sub-area, meanwhile, the number of the worker is marked as p1, p2,. seni,. pn, and each sub-area corresponds to each worker one by one.
The preferred embodiment is convenient for providing reference for the working state management of each worker and the nearby deployment of the worker after the cleaning work area is divided and the corresponding worker is marked.
And the GPS positioning module is connected with the working area dividing module and used for positioning the boundary line geographical positions of the divided sub-areas and sending the acquired geographical positions of the boundary lines of the sub-areas to the scanning route programming module and the personnel intelligent allocation module, so that convenience is provided for subsequent programming of the scanning route of the automatic tracking camera and intelligent allocation of personnel.
The scanning route programming module is connected with the GPS positioning module, receives the geographical position of each sub-region boundary line sent by the GPS positioning module, programs the received geographical position of each sub-region boundary line into a scanning route, inputs the programmed sub-region scanning route to the automatic tracking camera corresponding to each sub-region, scans by the automatic tracking camera of each sub-region according to the set scanning route, if the working personnel are not scanned in the scanning process, indicates that the working personnel corresponding to the sub-region do not work in the specified working region, and sends an early warning prompt control signal to the early warning prompt module; and if the staff is scanned in the scanning process, automatically tracking the staff, and acquiring the working state image according to the image acquisition time period.
The early warning prompting module is connected with the scanning route programming module, receives an early warning prompting control signal sent by the scanning route programming module, and intelligently prompts the staff, and the specific prompting method comprises the following steps:
h1: the early warning prompting module sends out a voice prompting signal to prompt the staff in the sub-area to return to the designated working area, and if the staff is not scanned in the scanning route by the automatic tracking camera in the sub-area after a specified time interval, the step H2 is executed;
h2: the early warning prompting module sends an early warning signal to a main monitoring center, and sends the sub-area numbers of the non-scanned workers to the main monitoring center, the main monitoring center receives the early warning signal, selects the worker numbers corresponding to the sub-areas of the non-scanned workers according to the worker numbers corresponding to the sub-areas, uses an interphone to converse with the workers to remind the workers to return to the appointed working area for working, and if the automatic tracking cameras in the sub-areas still do not scan the workers in the scanning route after a specified time interval, the step H3 is executed;
h3: the master monitoring center arranges related personnel to go to the subarea for manual processing.
This preferred embodiment carries out hierarchical intelligent suggestion through the staff to not working in the work area of regulation, reminds the staff to work in the work area of regulation, has strengthened the work management to the staff, is convenient for carry out staff operating condition image acquisition at the back.
The working state image acquisition module is connected with the working area dividing module, the working state image acquisition module comprises a plurality of automatic tracking cameras which are respectively installed in each subregion and used for automatically monitoring the working state of workers in each subregion during working, the automatic tracking cameras can automatically identify image information, the automatic tracking cameras follow the movement to capture images when the images move so as to track moving objects, the working state image acquisition module acquires working images of the workers in each subregion according to a preset image acquisition time period to obtain working images of the workers in each time period of each subregion, and the acquired working images of the workers in each time period of each subregion are sent to the image primary processing module according to the image acquisition sequence.
The preset image acquisition time period mentioned in the preferred embodiment is used for dividing the working time of the staff into a plurality of image acquisition time periods according to the working time of the staff and the preset image acquisition time interval, wherein the shorter the image acquisition time interval is set, the more the acquisition time periods are acquired, the more the working state images of the staff are acquired in the working time, the more the large number of working state images can reflect the working state of the staff in the working time, and a large number of reference data are provided for the subsequent working quality analysis.
The image preliminary processing module is connected with the working state image acquisition module, receives the working images of the workers in each time period of each subregion sent by the working state image acquisition module, performs image enhancement and high-definition filtering processing on the received working images of the workers in each time period of each subregion, performs gray scale processing on the processed working images, reserves the images of the workers, removes background images, and simultaneously sends the reserved images of the workers in each subregion to the image comparison identification module according to the image acquisition sequence.
The image comparison and identification module is connected with the image preliminary processing module, receives images of workers in each sub-region sent by the image preliminary processing module, amplifies the images of the workers in each sub-region, captures the hand characteristics and the leg characteristics of the workers in the amplified images of the workers in the sub-region, extracts the hand characteristics and the leg characteristics corresponding to various non-standard working behaviors in the parameter database, compares and matches the captured hand characteristics and the leg characteristics of the workers with the hand characteristics and the leg characteristics one by one, if the corresponding non-standard working behaviors are not matched in the parameter database, the workers do not have the non-standard working behaviors in the working process, otherwise, if the corresponding non-standard working behaviors are matched in the parameter database, the matching degrees of the captured hand characteristics and the captured leg characteristics of the workers and the hand characteristics and the leg characteristics corresponding to the various non-standard working behaviors in the parameter database are counted, the method comprises the steps of screening the irregular working behavior type with the maximum matching degree, outputting the irregular working behavior type with the maximum matching degree when the screened maximum matching degree is larger than a set matching degree threshold value, recording the outputted irregular working behavior type and the sub-region number, counting the sub-region numbers with the irregular working behavior in all the sub-regions and the matched irregular working behavior type, sending the sub-region numbers to a working quality analysis counting module, receiving the images of all the sub-region workers in the next time period sent by an image primary processing module, capturing the hand characteristics and the leg characteristics of the workers, matching the irregular working behavior, and sending the matched irregular working behavior type in each time period of the sub-regions to the working quality analysis counting module.
And the parameter database stores the hand characteristics and the leg characteristics of the workers corresponding to various irregular working behaviors, and stores the working quality influence factors corresponding to various irregular working behaviors, wherein the various irregular working behaviors comprise playing a mobile phone, sleeping, smoking and chatting with other people.
The working quality analysis and statistics module is connected with the image comparison and identification module, receives the non-standard working behavior types of each time period of each sub-region which are sent by the image comparison and identification module and matched with the image comparison and identification module, and uniformly stores the non-standard working behavior types of the workers in each time period in the same sub-region to form a sub-region non-standard working behavior frequency set w (wz1,wz2,…,wzj,...,wzm)，wzjThe number of times w of occurrence of the abnormal working behaviors corresponding to the zj-th sub-region with the abnormal working behaviors is represented, wherein w is 1,2
The evaluation coefficient of the working quality of the staff corresponding to the zj-th sub-area with the non-standard working behavior is expressed,
expressed as zj th presence of irregular workAnd the work quality influence factor corresponding to the w-th non-standard work behavior of the worker corresponding to the work behavior sub-region is sent to the display terminal, and the obtained work quality evaluation coefficient realizes quantitative display of the work quality of the worker.
The display terminal is connected with the working quality analysis and statistics module, receives working quality evaluation coefficients of all the workers corresponding to the sub-regions with the non-standard working behaviors sent by the working quality analysis and statistics module, displays the working quality evaluation coefficients, facilitates the workers to visually know the working quality of the workers and compare and compete with each other, and facilitates the managers to grade the workers according to the working quality evaluation coefficients.
The personnel intelligent allocation module is connected with the GPS positioning module, receives the geographical position of the boundary line of each sub-area sent by the GPS positioning module, records the number of the sub-area when an emergency event or a temporary heavy workload occurs in a certain sub-area, compares the recorded number of the sub-area where the emergency event or the temporary heavy workload occurs with the geographical position of the boundary line of each sub-area, screens the geographical position of the boundary line corresponding to the sub-area where the emergency event or the temporary heavy workload occurs, matches the geographical positions of the geographical boundary lines of other sub-areas with the geographical position of the boundary line of the sub-area at the same time, obtains the number of the other sub-area closest to the sub-area where the emergency event or the temporary heavy workload occurs, and sends the number of the sub-area closest to the sub-area to the total monitoring center, in the embodiment, screens the sub-area closest to the sub-area, from the deployment personnel of the nearest sub-area, the time delayed on the deployment path of other sub-areas is saved, the deployment efficiency is high, meanwhile, the efficiency of handling emergencies by the sub-area with emergencies or temporary increased workload is greatly improved, the intelligent deployment management of the property of the community is realized, and the problem that manual management cannot carry out rapid deployment when emergencies occur is solved.
And the master monitoring center is connected with the intelligent personnel allocation module, receives the numbers of the sub-areas which are closest to the personnel intelligent allocation module and sent by the intelligent personnel allocation module, selects the numbers of the workers which are closest to the sub-areas according to the numbers of the workers which are corresponding to the sub-areas, and allocates the workers to the sub-areas with emergencies or temporary increased workload for assisting work by using the interphone.
According to the invention, the clean-keeping area of the residential area is divided into a plurality of sub-areas, each sub-area corresponds to each worker one by one, the working state images of the workers in each sub-area are collected in different collection time periods through the working state image collection module, whether the working state images belong to the non-standard working state is analyzed, the working quality coefficient is evaluated, and meanwhile, when an emergency occurs in a certain area, the workers are dispatched nearby for processing, so that the intelligent allocation management of the residential property is realized, the management efficiency is high, a large amount of management manpower is saved, the requirement of the current property management is greatly met, and the property management level is improved.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.
Claims (8)
1. The utility model provides a property intelligent management allotment system based on big data which characterized in that: the system comprises a working area dividing module, a working state image acquisition module, an image preliminary processing module, an image comparison identification module, a working quality analysis and statistics module, a parameter database, a display terminal and an intelligent personnel allocation module;
the working area dividing module is used for dividing a clean-keeping working area of the community property into a plurality of sub-areas according to a preset dividing mode, the sub-areas are numbered according to a preset sequence and are sequentially marked as z1, z2, a.
The working state image acquisition module is connected with the working area dividing module, the working state image acquisition module comprises a plurality of automatic tracking cameras which are respectively installed in each subregion and used for automatically monitoring the working state of workers in each subregion during working, the automatic tracking cameras can automatically identify image information, the automatic tracking cameras follow the movement to capture images when the images move so as to track moving objects, the working state image acquisition module acquires working images of the workers in each subregion according to a preset image acquisition time period to obtain working images of the workers in each time period of each subregion, and the acquired working images of the workers in each time period of each subregion are sent to the image primary processing module according to the image acquisition sequence;
the image primary processing module is connected with the working state image acquisition module, receives the working image of the working personnel in each time period of each subregion sent by the working state image acquisition module, performs image enhancement and high-definition filtering processing on the received working image of the working personnel in each time period of each subregion, performs gray processing on the processed working image, reserves the working personnel image, removes a background image, and simultaneously sends the reserved working image of each subregion to the image comparison identification module according to the image acquisition sequence;
the image comparison and identification module is connected with the image primary processing module, receives images of all sub-region workers sent by the image primary processing module, amplifies the images of all the sub-region workers received, captures hand features and leg features of the workers in the amplified images of the sub-region workers, extracts hand features and leg features corresponding to various non-standard working behaviors in the parameter database, compares and matches the captured hand features and leg features of the workers with the captured hand features and leg features one by one, if the corresponding non-standard working behaviors are not matched in the parameter database, the workers do not have the non-standard working behaviors in working, otherwise, if the corresponding non-standard working behaviors are matched in the parameter database, the matched non-standard working behaviors and the sub-region numbers are recorded, and simultaneously, the sub-region numbers of the non-standard working behaviors appearing in all the sub-regions and the matched non-standard working behaviors are counted The types of the images are sent to a working quality analysis and statistics module, meanwhile, images of workers in each sub-region in the next time period sent by the image primary processing module are received, hand features and leg features of the workers are captured, non-standard working behavior matching is carried out, and the matched non-standard working behavior types of each time period in each sub-region are sent to the working quality analysis and statistics module;
the parameter database stores the hand characteristics and the leg characteristics of the workers corresponding to various irregular working behaviors, and stores the working quality influence factors corresponding to various irregular working behaviors, wherein the various irregular working behaviors comprise playing a mobile phone, sleeping, smoking and chatting with other people;
the working quality analysis statistical module is connected with the image comparison identification module, receives the non-standard working behavior types of each time period of each sub-region which are sent by the image comparison identification module and matched with the image comparison identification module, and uniformly stores the non-standard working behavior types of the workers in each time period in the same sub-region to form a sub-region non-standard working behavior frequency set w (w) in all time periodsz1,wz2,K,wzj,K,wzm)，wzjExpressing the number w of times of occurrence of the abnormal working behaviors corresponding to the zj-th abnormal working behavior sub-region, wherein w is 1, 2.. k, extracting working quality influence factors corresponding to various abnormal working behaviors in a parameter database, counting working quality evaluation coefficients of various working personnel corresponding to the abnormal working behavior sub-regions, and sending the working quality evaluation coefficients to a display terminal;
the personnel intelligent allocation module is used for recording the number of a sub-area when an emergency or temporary heavy workload occurs in the sub-area, sending the recorded number of the sub-area with the emergency or temporary heavy workload to the master monitoring center, and dispatching the staff to the master monitoring center from other sub-areas nearby for processing;
and the display terminal is connected with the working quality analysis and statistics module, receives and displays the working quality evaluation coefficients of the workers corresponding to the sub-regions with the non-standard working behaviors, which are sent by the working quality analysis and statistics module.
2. The intelligent property management and deployment system based on big data as claimed in claim 1, wherein: the system also comprises a GPS positioning module which is connected with the working area dividing module and used for positioning the boundary line geographical position of each divided sub-area and sending the acquired geographical position of the boundary line of each sub-area to the scanning route programming module and the personnel intelligent allocation module.
3. The intelligent property management and deployment system based on big data as claimed in claim 2, wherein: the personnel intelligent allocation module is connected with the GPS positioning module, receives the geographical position of each sub-region boundary line sent by the GPS positioning module, compares the recorded sub-region number with the emergency or temporary heavy workload, screens the boundary line geographical position corresponding to the sub-region with the emergency or temporary heavy workload, matches the distance between the boundary line geographical position of other sub-regions and the boundary line geographical position of the sub-region, obtains the number of other sub-regions closest to the sub-region with the emergency or temporary heavy workload, and sends the number of the sub-region closest to the sub-region to the total monitoring center.
4. The intelligent property management and deployment system based on big data as claimed in claim 3, wherein: the intelligent dispatching system further comprises a master monitoring center which is connected with the intelligent dispatching module of the personnel, receives the numbers of the sub-areas which are sent by the intelligent dispatching module of the personnel and are closest to each other, selects the numbers of the workers which are corresponding to the sub-areas which are closest to each other according to the numbers of the workers which are corresponding to the sub-areas, and dispatches the workers to the auxiliary work of the sub-areas which are subjected to the emergency or the temporary increase of the workload by using the interphone.
5. The intelligent property management and deployment system based on big data as claimed in claim 1, wherein: the system comprises a GPS positioning module, a scanning route programming module and an early warning prompting module, wherein the scanning route programming module is connected with the GPS positioning module, receives the geographical position of each sub-region boundary line sent by the GPS positioning module, programs the received geographical position of each sub-region boundary line into a scanning route, inputs the programmed sub-region scanning route to an automatic tracking camera corresponding to each sub-region, scans by the automatic tracking camera of each sub-region according to the set scanning route, if a worker is not scanned in the scanning process, the worker corresponding to the sub-region is indicated to not work in a specified working region, and at the moment, an early warning prompting control signal is sent to the early warning prompting module; and if the staff is scanned in the scanning process, automatically tracking the staff, and acquiring the working state image according to the image acquisition time period.
6. The intelligent property management and deployment system based on big data as claimed in claim 1, wherein: the intelligent warning system also comprises a warning prompt module which is connected with the scanning route programming module, receives a warning prompt control signal sent by the scanning route programming module and intelligently prompts the staff, and the specific prompt method comprises the following steps:
h1: the early warning prompting module sends out a voice prompting signal to prompt the staff in the sub-area to return to the designated working area, and if the staff is not scanned in the scanning route by the automatic tracking camera in the sub-area after a specified time interval, the step H2 is executed;
h2: the early warning prompting module sends an early warning signal to a main monitoring center, and sends the sub-area numbers of the non-scanned workers to the main monitoring center, the main monitoring center receives the early warning signal, selects the worker numbers corresponding to the sub-areas of the non-scanned workers according to the worker numbers corresponding to the sub-areas, uses an interphone to converse with the workers to remind the workers to return to the appointed working area for working, and if the automatic tracking cameras in the sub-areas still do not scan the workers in the scanning route after a specified time interval, the step H3 is executed;
h3: the master monitoring center arranges related personnel to go to the subarea for manual processing.
7. The intelligent property management and deployment system based on big data as claimed in claim 1, wherein: the calculation formula of the working quality evaluation coefficient is
The evaluation coefficient of the working quality of the staff corresponding to the zj-th sub-area with the non-standard working behavior is expressed,
and expressing the work quality influence factor corresponding to the w-th unnormalized work behavior of the worker corresponding to the zj-th unnormalized work behavior sub-region.
8. The intelligent property management and deployment system based on big data as claimed in claim 1, wherein: the preset image acquisition time period is used for dividing the working time of the workers into a plurality of image acquisition time periods according to the working time of the workers and the preset image acquisition time interval.
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