Smart park service management system and method based on Internet of Things

Abstract

The invention discloses a smart park service management system and method based on the Internet of Things, and belongs to the technical field of service management. The system comprises a data acquisition module, a service management module, a job scheduling module and a data storage module. The data acquisition module is used for acquiring facility planar graphs of the park and historical logs and state information of objects; the service management module divides operation areas on the facility plane graph, screens sample records for each operation area according to historical logs, maps operation tracks in the sample records to the operation areas, divides convergence areas and calculates weight coefficients; the job scheduling module screens a service record for each object, maps a job track of the service record to each job area again, analyzes an intersection condition of the job track and the convergence area and calculates a matching coefficient; selecting a matching object for each operation area according to the matching coefficient, and generating an operation task for distribution; and the data storage module is used for generating a service record for each object and uploading the service record to a historical log.

Description

Technical Field

[0001] The present invention relates to the technical field of service management, and in particular to a smart park service management system and method based on the Internet of Things. Background Art

[0002] With the rapid development of technologies such as the Internet of Things, artificial intelligence, and big data, technical support has been provided for the construction of smart parks. Traditional parks often find it difficult to achieve efficient resource allocation and service optimization in management, while smart parks can improve management efficiency and service quality through digital and intelligent means, and enhance the attractiveness of parks to enterprises and residents.

[0003] At present, for the service management of the park, the task allocation method of specifying the work space with fixed objects is usually adopted. This method has certain disadvantages. On the one hand, fixed task allocation makes it impossible for the work area to dynamically adjust the execution object according to actual needs. When the owner or manager has inconsistent evaluation dimensions and standards for the quality of the operation, the fixed allocation method often cannot respond flexibly and cannot quickly match the execution object that better meets the needs, resulting in a mismatch between supply and demand and waste of resources. On the other hand, the fixed task allocation method cannot quantify the actual workload of the execution object and cannot give full play to people's subjective initiative. During the operation, the operation data is not collected throughout the process, and there is a lack of effective data logic support in task allocation and result evaluation, resulting in low utilization of human resources and poor results. Therefore, at this stage, a more intelligent and efficient park service management technology solution is needed to solve the above problems. Summary of the invention

[0004] The purpose of the present invention is to provide a smart park service management system and method based on the Internet of Things to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides a smart park service management method based on the Internet of Things, comprising the following steps:

[0006] S100, collecting the facility plan of the park and the historical log of each object, collecting the status information of the objects within the park in real time through wearable devices, and mapping the status information to the facility plan.

[0007] S200, analyzing the facility plan and dividing the operation area, selecting sample records for each operation area in the historical log, mapping the operation track in the sample record to the operation area to divide the convergence area, and calculating the weight coefficient of each convergence area.

[0008] S300, filter out service records for each object in the historical log, map the operation track of each service record to each operation area again, analyze the intersection of the operation track and the convergence area and calculate the matching coefficient. Select a matching object for each operation area according to the matching coefficient, generate an operation task and dispatch it to the wearable device of the matching object.

[0009] S400. Each object goes to the designated work area to carry out work according to the work task. The wearable device records the relevant information of this work in real time. After the work is completed, a service record is generated and uploaded to the history log.

[0010] In S100, the facility plan is a plan drawn in proportion to show the layout of facilities in the park. The history log is a service record of each work of the object, the object is a staff member, and each service record includes the work area, work track, work duration and score.

[0011] The work area refers to the area where the object carries out work, the work trajectory refers to the movement trajectory of the object when working in the work area, the work duration is the working time of the object in the work area, and the score refers to the evaluation score of this work, which is evaluated and scored by the management personnel or the owner.

[0012] Wearable devices refer to smart devices worn by workers. Wearable devices integrate sensors, processors and communication functions, can monitor the movement status and real-time location of workers, and exchange information with the data center background. Status information includes location and status. Location refers to the real-time location of the object, and status includes idle and busy.

[0013] The operation duration includes moving duration and staying duration. When the position of the object changes in the operation area, the moving duration is recorded, and when the position does not change, the staying duration is recorded. After associating the operation trajectory with the operation duration, the position of the object in the operation trajectory at any time can be obtained, as well as the staying duration and staying position each time the position does not change.

[0014] When an object enters the work area, the wearable device can collect the object's movement status and real-time location in real time, automatically set the busy status for the object, draw the work trajectory and record the work duration. When the object is not in the work area, the wearable device automatically sets the idle status for the object, collects the real-time location and uploads it to the data center, which matches the work area.

[0015] In S200, the specific steps are as follows:

[0016] S201. Analyze the areas that need to be serviced in the facility plan, and take each area that needs to be serviced as an operation area. Obtain the historical logs of all objects and filter out the operation area ZY uAll service records of the operation area are calculated based on the scores of these service records as the average value. u Average score Set the optimization coefficient e and filter out the items with a score greater than Service record as work area ZY u Sample records of .

[0017] The areas that need to be served in the facility plan are set in advance by the management personnel, and the specific division refers to the actual business needs in reality. The optimization coefficient is set in advance by the management personnel. The larger the value, the fewer sample records are screened. The specific value is determined by the number of service records in the historical log and the computer computing resources.

[0018] S202, obtain the operation area ZY u All sample records of operation tracks and operation duration are mapped to the operation area ZY in the facility plan. u Set the duration threshold t, and analyze the operation duration to take the position on the corresponding operation track where the duration is greater than t as the operation point. There are different numbers of operation points on each operation track. Analyze the operation area ZY u The distance between the work points of different work trajectories is calculated, and the distance threshold i is set. The work points with a distance less than i are connected by line segments, and a circular area is established with the connecting line segments as the diameter. The intersecting circular areas are combined as the confluence area.

[0019] The duration threshold is set in advance by the management personnel. The specific value is based on the shortest duration of each operation of the object in the operation area. When the object stays longer than the duration threshold, it is considered to be in operation. The distance threshold is set to refer to the shortest distance between the continuous operation positions of the object. The confluence area is established by connecting the operation points to deduce the location of each specific operation point in the operation area.

[0020] S203, Statistics Operation Area ZY u The total number of operation points in all operation trajectories y sum , and the number of operating points in each confluence area y. Analyze the length of stay TL of each operating point n , and the operation duration SC of the sample record corresponding to the operation trajectory n and score pf n , substitute into the formula to calculate the weight coefficient of each confluence area:

[0021]

[0022] Where QZ is the weight coefficient.

[0023] The weight coefficient indicates the importance of the convergence point. The higher the proportion of work points in the convergence point, the longer the proportion of the stay time at each work point, and the higher the score, the more important the convergence point is and the greater its influence on the final score.

[0024] In S300, the specific steps are as follows:

[0025] S301, filter out objects whose current location is in the park and whose status is idle, and obtain the object as DX r And the working area is ZY u All service records and total number of statistics sum , map the operation tracks in these service records to the operation area ZY in turn u At each operation track, the position where the stay time is greater than t is taken as the operation point. Mark the operation track with at least one operation point in the confluence area, count the number of marked operation tracks l, obtain the weight coefficient of the confluence area where each operation point is located under each marked operation track, and substitute it into the formula to calculate the operation area ZY u With Object DX r The matching coefficient XSO between them is as follows:

[0026]

[0027] In the formula, y v is the number of operating points under the vth marked operating trajectory, c v is the number of operating points in the confluence area under the vth marked operating trajectory, It is the weight coefficient of the confluence area where the g-th operation point under the v-th marked operation trajectory is located.

[0028] The matching coefficient indicates the degree of harmony between the object and the operation area. When the service record of the object working in the operation area, the larger the proportion of the number of marked operation tracks, the larger the proportion of the number of operation points in the convergence area, and the larger the weight coefficient of the convergence area, the more the object meets the requirements of the operation area, and the larger the matching coefficient.

[0029] S302, set the coefficient threshold w and establish a pre-selected set for each work area, calculate the matching coefficient between each work area and each object, and put the objects with a matching coefficient greater than w into the corresponding pre-selected set. Determine whether each object exists in at least one pre-selected set. If the result is not, reduce the coefficient threshold w until each object exists in at least one pre-selected set; if the result is yes, take all objects in the pre-selected set as pre-selected objects for the corresponding work area.

[0030] S303, analyze the historical logs of all objects and classify these service records according to whether the operation area is the same, and calculate the average score of each type of service record as the basic score JCF of the corresponding operation area. The pre-selected object with the largest matching coefficient in each pre-selected set is used as the selected object of the corresponding operation area, and it is determined whether the selected objects of each operation area are different. If they are the same, mark the corresponding operation area and enter step S304, if they are not the same, enter step S305.

[0031] S304: Obtain the basic score of each marking operation area and the maximum matching coefficient XSO in the corresponding pre-selected set max and the second largest matching coefficient XSO sec , substitute into the formula to calculate the priority index of each marking operation area. The selected object is used as the matching object of the marking operation area with the highest priority index, and the matching objects are deleted from the pre-selected set of other marking operation areas and the pre-selected object with the largest matching coefficient is re-selected as its selected object, and the step S303 is entered again for re-judgment. The priority index calculation formula is as follows:

[0032]

[0033] In the formula, YZ is the priority index, JCF ave It is the average value of the basic scores for all operating areas.

[0034] If there is only one pre-selected object in the pre-selected set of the operation area, it will be directly used as the matching object, and the operation area will not be marked and will not participate in the priority index calculation and redistribution of other marked operation areas.

[0035] S305. Select an object as a matching object for the corresponding work area and generate a work task, dispatch the work task to the wearable device of the matching object, and display the specific locations of the work area and the matching object in the facility plan through a visual interface, as well as the area location and weight coefficient of each confluence area in the work area.

[0036] In S400, each matching object goes to the designated work area of ​​the work task to carry out work, and the wearable device records the work trajectory and work duration of this work in real time. After the work is completed, the manager or owner will evaluate and score it based on the completion quality, automatically generate a service record and upload it to the historical log through the Internet of Things.

[0037] A smart park service management system based on the Internet of Things includes a data acquisition module, a service management module, a job scheduling module and a data storage module.

[0038] The data collection module is used to collect the facility floor plan of the park, as well as the historical logs and status information of the objects.

[0039] The service management module divides the operation area according to the facility plan, selects sample records for each operation area in the historical log, maps the operation trajectory in the sample record to the operation area to divide the convergence area, and calculates the weight coefficient of each convergence area.

[0040] The job scheduling module selects service records for each object, maps the job track of each service record to each job area again, analyzes the intersection of the job track and the convergence area, and calculates the matching coefficient. According to the matching coefficient, a matching object is selected for each job area, and the job task is generated and dispatched to the wearable device of the matching object.

[0041] The data storage module is used to generate service records for each object and upload them to the history log.

[0042] The data collection module includes an object information collection unit, a history log collection unit and a map data collection unit.

[0043] The object information collection unit is used to collect the state information of the object. The object refers to the staff member, and the state information includes the location and state. The location refers to the real-time location of the object, and the state includes idle and busy.

[0044] The historical log collection unit is used to collect service records of each object at each work. Each service record includes the work area, work track, work duration and score. The work area refers to the area where the object carries out work, the work track refers to the movement track of the object when working in the work area, the work duration is the working time of the object in the work area, and the score refers to the evaluation score of this work, which is evaluated and scored by the management personnel or the owner.

[0045] The map data collection unit is used to collect the facility plan of the park. The facility plan is a plan drawn in proportion to show the layout of the facilities in the park.

[0046] The service management module includes a region division unit and a weight analysis unit.

[0047] The area division unit is used to divide the working area and the merging area.

[0048] First, each area in the facility plan that needs to be serviced is taken as an operation area, and the operation area ZY is selected from the historical log. u All service records of the operation area ZY are calculated, and the average score of these service records is used as the u Average score

[0049] Secondly, set the optimization coefficient e and filter out the scores greater than Service record as work area ZY u Map the operation track in each sample record to the operation area ZY in turn.u A duration threshold t is set, and the position where the stay time on each operation trajectory is greater than t is taken as the operation point.

[0050] Finally, set the distance threshold i and set the working area ZY u Connect the line segments between the operation points with a distance less than i under different operation trajectories, establish a circular area with the connecting line segments as the diameter, and combine the intersecting circular areas as the confluence area.

[0051] The weight analysis unit is used to calculate the weight coefficient. u The total number of operation points in all operation trajectories y sum , and the number of operating points in each confluence area y. Analyze the length of stay TL of each operating point n , and the operation duration SC of the sample record corresponding to the operation trajectory n and score pf n , according to the formula Calculate the weight coefficient QZ for each confluence zone.

[0052] The job scheduling module includes a matching analysis unit and a scheduling management unit.

[0053] The matching analysis unit is used to calculate the matching coefficient between the working area and the object.

[0054] First, filter out objects that are located in the park and are in the idle state, and obtain the object DX r All service records and total number of statistics sum , map the operation tracks in these service records to the operation area ZY in turn u At each operation track, the position where the stay time is greater than t is taken as the operation point; the operation track with at least one operation point in the confluence area is marked.

[0055] Secondly, the number of marked operation trajectories l is counted, and the weight coefficient of the confluence area of ​​each operation point under each marked operation trajectory is obtained. According to the formula Calculate the work area ZY u With Object DX r The matching coefficient between them is XSO, where y v is the number of operating points under the vth marked operating trajectory, c v is the number of operating points in the confluence area under the vth marked operating trajectory, It is the weight coefficient of the confluence area where the g-th operation point under the v-th marked operation trajectory is located.

[0056] Finally, set the coefficient threshold w and establish a pre-selected set for each work area, calculate the matching coefficient between each work area and each object, and put the objects with a matching coefficient greater than w into the corresponding pre-selected set; determine whether each object exists in at least one pre-selected set. If yes, reduce the coefficient threshold w until each object exists in at least one pre-selected set; if yes, take all objects in the pre-selected set as pre-selected objects for the corresponding work area.

[0057] The scheduling management unit is used to allocate and adjust objects.

[0058] First, the service records of all objects are classified according to whether the operation area is the same, and the average score of each type of service record is calculated as the basic score JCF of the corresponding operation area. The pre-selected object with the largest matching coefficient in each pre-selected set is selected as the selected object of the corresponding operation area.

[0059] Secondly, when different work areas have the same object as the selected object, these work areas are marked, and the basic score of each marked work area and the maximum matching coefficient XSO in the pre-selected set are obtained. max and the second largest matching coefficient XSO sec , according to the formula Calculate the priority index of each marked operation area separately.

[0060] The selected object is used as the matching object of the marking operation area with the highest priority index, and the matching object is deleted from the pre-selected set of other marking operation areas and the pre-selected object with the largest matching coefficient is re-selected as the selected object, and the judgment is repeated. ave It is the average value of the basic scores for all operating areas.

[0061] Finally, when the selected objects of all work areas are different, the selected objects are used as matching objects for the corresponding work areas and work tasks are generated. The work tasks are dispatched to the wearable devices of the matching objects, and the specific locations of the work areas and matching objects in the facility plan, as well as the area location and weight coefficient of each confluence area in the work area, are displayed through a visual interface.

[0062] The data storage module is used to record the operation trajectory and operation duration of each work of the object in real time, obtain the score of the manager or owner after the work is completed, automatically generate service records and upload them to the historical log through the Internet of Things.

[0063] Compared with the prior art, the beneficial effects achieved by the present invention are:

[0064] 1. Accurate regional division: In this application, the operation area is divided by the facility plan, and sample records with higher scores are selected for each operation area. The operation point gathering place is analyzed according to the operation trajectory of different sample records, and the convergence area is further divided. The key position analysis of each operation area and the differentiation of the score impact are realized by calculating the weight coefficient of the number of operation points, the length of stay and the score in the convergence area, which is more accurate and reliable than the fixed area analysis in the prior art.

[0065] 2. Intelligent object matching: In this application, objects and work areas are associated and analyzed, and the historical service records of each object in the work area are analyzed, and the work tracks in these service records are mapped to the work area. By analyzing the intersection of the work track and the convergence area, the degree of harmony between the object and the work area is quantified and the matching coefficient is calculated, and objects are assigned to each work area according to the matching index, which is more intelligent and efficient than the fixed object allocation method in the prior art.

[0066] In summary, compared with traditional technologies, the present invention has the advantages of precise area division and intelligent object matching, and can improve the efficiency of park service management. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0068] Figure 1 It is a flow chart of a smart park service management method based on the Internet of Things of the present invention;

[0069] Figure 2 It is a structural schematic diagram of a smart park service management system based on the Internet of Things of the present invention. DETAILED DESCRIPTION

[0070] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0071] See also Figure 1 The present invention provides a smart park service management method based on the Internet of Things, comprising the following steps:

[0072] S100, collecting the facility plan of the park and the historical log of each object, collecting the status information of the objects within the park in real time through wearable devices, and mapping the status information to the facility plan.

[0073] S200, analyzing the facility plan and dividing the operation area, selecting sample records for each operation area in the historical log, mapping the operation track in the sample record to the operation area to divide the convergence area, and calculating the weight coefficient of each convergence area.

[0074] S300, filter out service records for each object in the historical log, map the operation track of each service record to each operation area again, analyze the intersection of the operation track and the convergence area and calculate the matching coefficient. Select a matching object for each operation area according to the matching coefficient, generate an operation task and dispatch it to the wearable device of the matching object.

[0075] S400. Each object goes to the designated work area to carry out work according to the work task. The wearable device records the relevant information of this work in real time. After the work is completed, a service record is generated and uploaded to the history log.

[0076] In S100, the facility plan is a plan drawn in proportion to show the layout of facilities in the park. The history log is a service record of each work of the object, the object is a staff member, and each service record includes the work area, work track, work duration and score.

[0077] The work area refers to the area where the object carries out work, the work trajectory refers to the movement trajectory of the object when working in the work area, the work duration is the working time of the object in the work area, and the score refers to the evaluation score of this work, which is evaluated and scored by the management personnel or the owner.

[0078] Wearable devices refer to smart devices worn by workers. Wearable devices integrate sensors, processors and communication functions, can monitor the movement status and real-time location of workers, and exchange information with the data center background. Status information includes location and status. Location refers to the real-time location of the object, and status includes idle and busy.

[0079] The operation duration includes moving duration and staying duration. When the position of the object changes in the operation area, the moving duration is recorded, and when the position does not change, the staying duration is recorded. After associating the operation trajectory with the operation duration, the position of the object in the operation trajectory at any time can be obtained, as well as the staying duration and staying position each time the position does not change.

[0080] When an object enters the work area, the wearable device can collect the object's movement status and real-time location in real time, automatically set the busy status for the object, draw the work trajectory and record the work duration. When the object is not in the work area, the wearable device automatically sets the idle status for the object, collects the real-time location and uploads it to the data center, which matches the work area.

[0081] In S200, the specific steps are as follows:

[0082] S201. Analyze the areas that need to be serviced in the facility plan, and take each area that needs to be serviced as an operation area. Obtain the historical logs of all objects and filter out the operation area ZY u All service records of the operation area are calculated based on the scores of these service records as the average value. u Average score Set the optimization coefficient e and filter out the items with a score greater than Service record as work area ZY u Sample records of .

[0083] The areas that need to be served in the facility plan are set in advance by the management personnel, and the specific division refers to the actual business needs in reality. The optimization coefficient is set in advance by the management personnel. The larger the value, the fewer sample records are screened. The specific value is determined by the number of service records in the historical log and the computer computing resources.

[0084] S202, obtain the operation area ZY u All sample records of operation tracks and operation duration are mapped to the operation area ZY in the facility plan. u Set the duration threshold t, and analyze the operation duration to take the position on the corresponding operation track where the duration is greater than t as the operation point. There are different numbers of operation points on each operation track. Analyze the operation area ZY u The distance between the work points of different work trajectories is calculated, and the distance threshold i is set. The work points with a distance less than i are connected by line segments, and a circular area is established with the connecting line segments as the diameter. The intersecting circular areas are combined as the confluence area.

[0085] The duration threshold is set in advance by the management personnel. The specific value is based on the shortest duration of each operation of the object in the operation area. When the object stays longer than the duration threshold, it is considered to be in operation. The distance threshold is set to refer to the shortest distance between the continuous operation positions of the object. The confluence area is established by connecting the operation points to deduce the location of each specific operation point in the operation area.

[0086] S203, Statistics Operation Area ZY u The total number of operation points in all operation trajectories y sum , and the number of operating points in each confluence area y. Analyze the length of stay TL of each operating point n , and the operation duration SC of the sample record corresponding to the operation trajectory n and score pf n , substitute into the formula to calculate the weight coefficient of each confluence area:

[0087]

[0088] Where QZ is the weight coefficient.

[0089] The weight coefficient indicates the importance of the convergence point. The higher the proportion of work points in the convergence point, the longer the proportion of the stay time at each work point, and the higher the score, the more important the convergence point is and the greater its influence on the final score.

[0090] In S300, the specific steps are as follows:

[0091] S301, filter out objects whose current location is in the park and whose status is idle, and obtain the object as DX r And the working area is ZY u All service records and total number of statistics sum , map the operation tracks in these service records to the operation area ZY in turn u At each operation track, the position where the stay time is greater than t is taken as the operation point. Mark the operation track with at least one operation point in the confluence area, count the number of marked operation tracks l, obtain the weight coefficient of the confluence area where each operation point is located under each marked operation track, and substitute it into the formula to calculate the operation area ZY u With Object DX r The matching coefficient XSO between them is as follows:

[0092]

[0093] In the formula, y v is the number of operating points under the vth marked operating trajectory, c v is the number of operating points in the confluence area under the vth marked operating trajectory, It is the weight coefficient of the confluence area where the g-th operation point under the v-th marked operation trajectory is located.

[0094] The matching coefficient indicates the degree of harmony between the object and the operation area. When the service record of the object working in the operation area, the larger the proportion of the number of marked operation tracks, the larger the proportion of the number of operation points in the convergence area, and the larger the weight coefficient of the convergence area, the more the object meets the requirements of the operation area, and the larger the matching coefficient.

[0095] S302, set the coefficient threshold w and establish a pre-selected set for each work area, calculate the matching coefficient between each work area and each object, and put the objects with a matching coefficient greater than w into the corresponding pre-selected set. Determine whether each object exists in at least one pre-selected set. If the result is not, reduce the coefficient threshold w until each object exists in at least one pre-selected set; if the result is yes, take all objects in the pre-selected set as pre-selected objects for the corresponding work area.

[0096] S303, analyze the historical logs of all objects and classify these service records according to whether the operation area is the same, and calculate the average score of each type of service record as the basic score JCF of the corresponding operation area. The pre-selected object with the largest matching coefficient in each pre-selected set is used as the selected object of the corresponding operation area, and it is determined whether the selected objects of each operation area are different. If they are the same, mark the corresponding operation area and enter step S304, if they are not the same, enter step S305.

[0097] S304: Obtain the basic score of each marking operation area and the maximum matching coefficient XSO in the corresponding pre-selected set max and the second largest matching coefficient XSO sec , substitute into the formula to calculate the priority index of each marking operation area. The selected object is used as the matching object of the marking operation area with the highest priority index, and the matching objects are deleted from the pre-selected set of other marking operation areas and the pre-selected object with the largest matching coefficient is re-selected as its selected object, and the step S303 is entered again for re-judgment. The priority index calculation formula is as follows:

[0098]

[0099] In the formula, YZ is the priority index, JCF ave It is the average value of the basic scores for all operating areas.

[0100] If there is only one pre-selected object in the pre-selected set of the operation area, it will be directly used as the matching object, and the operation area will not be marked and will not participate in the priority index calculation and redistribution of other marked operation areas.

[0101] S305. Select an object as a matching object for the corresponding work area and generate a work task, dispatch the work task to the wearable device of the matching object, and display the specific locations of the work area and the matching object in the facility plan through a visual interface, as well as the area location and weight coefficient of each confluence area in the work area.

[0102] In S400, each matching object goes to the designated work area of ​​the work task to carry out work, and the wearable device records the work trajectory and work duration of this work in real time. After the work is completed, the manager or owner will evaluate and score it based on the completion quality, automatically generate a service record and upload it to the historical log through the Internet of Things.

[0103] See also Figure 2 The present invention provides a smart park service management system based on the Internet of Things, including a data acquisition module, a service management module, a job scheduling module and a data storage module.

[0104] The data collection module is used to collect the facility floor plan of the park, as well as the historical logs and status information of the objects.

[0105] The service management module divides the operation area according to the facility plan, selects sample records for each operation area in the historical log, maps the operation trajectory in the sample record to the operation area to divide the convergence area, and calculates the weight coefficient of each convergence area.

[0106] The job scheduling module selects service records for each object, maps the job track of each service record to each job area again, analyzes the intersection of the job track and the convergence area, and calculates the matching coefficient. According to the matching coefficient, a matching object is selected for each job area, and the job task is generated and dispatched to the wearable device of the matching object.

[0107] The data storage module is used to generate service records for each object and upload them to the history log.

[0108] The data collection module includes an object information collection unit, a history log collection unit and a map data collection unit.

[0109] The object information collection unit is used to collect the state information of the object. The object refers to the staff member, and the state information includes the location and state. The location refers to the real-time location of the object, and the state includes idle and busy.

[0110] The historical log collection unit is used to collect service records of each object at each work. Each service record includes the work area, work track, work duration and score. The work area refers to the area where the object carries out work, the work track refers to the movement track of the object when working in the work area, the work duration is the working time of the object in the work area, and the score refers to the evaluation score of this work, which is evaluated and scored by the management personnel or the owner.

[0111] The map data collection unit is used to collect the facility plan of the park. The facility plan is a plan drawn in proportion to show the layout of the facilities in the park.

[0112] The service management module includes a region division unit and a weight analysis unit.

[0113] The area division unit is used to divide the working area and the merging area.

[0114] First, each area in the facility plan that needs to be serviced is taken as an operation area, and the operation area ZY is selected from the historical log. u All service records of the operation area ZY are calculated, and the average score of these service records is used as the u Average score

[0115] Secondly, set the optimization coefficient e and filter out the scores greater than Service record as work area ZY u Map the operation track in each sample record to the operation area ZY in turn.u A duration threshold t is set, and the position where the stay time on each operation trajectory is greater than t is taken as the operation point.

[0116] Finally, set the distance threshold i and set the working area ZY u Connect the line segments between the operation points with a distance less than i under different operation trajectories, establish a circular area with the connecting line segments as the diameter, and combine the intersecting circular areas as the confluence area.

[0117] The weight analysis unit is used to calculate the weight coefficient. u The total number of operation points in all operation trajectories y sum , and the number of operating points in each confluence area y. Analyze the length of stay TL of each operating point n , and the operation duration SC of the sample record corresponding to the operation trajectory n and score pf n , according to the formula Calculate the weight coefficient QZ for each confluence zone.

[0118] The job scheduling module includes a matching analysis unit and a scheduling management unit.

[0119] The matching analysis unit is used to calculate the matching coefficient between the working area and the object.

[0120] First, filter out objects that are located in the park and are in the idle state, and obtain the object DX r All service records and total number of statistics sum , map the operation tracks in these service records to the operation area ZY in turn u At each operation track, the position where the stay time is greater than t is taken as the operation point; the operation track with at least one operation point in the confluence area is marked.

[0121] Secondly, the number of marked operation trajectories l is counted, and the weight coefficient of the confluence area of ​​each operation point under each marked operation trajectory is obtained. According to the formula Calculate the work area ZY u With Object DX r The matching coefficient between them is XSO, where y v is the number of operating points under the vth marked operating trajectory, c v is the number of operating points in the confluence area under the vth marked operating trajectory, It is the weight coefficient of the confluence area where the g-th operation point under the v-th marked operation trajectory is located.

[0122] Finally, set the coefficient threshold w and establish a pre-selected set for each work area, calculate the matching coefficient between each work area and each object, and put the objects with a matching coefficient greater than w into the corresponding pre-selected set; determine whether each object exists in at least one pre-selected set. If yes, reduce the coefficient threshold w until each object exists in at least one pre-selected set; if yes, take all objects in the pre-selected set as pre-selected objects for the corresponding work area.

[0123] The scheduling management unit is used to allocate and adjust objects.

[0124] First, the service records of all objects are classified according to whether the operation area is the same, and the average score of each type of service record is calculated as the basic score JCF of the corresponding operation area. The pre-selected object with the largest matching coefficient in each pre-selected set is selected as the selected object of the corresponding operation area.

[0125] Secondly, when different work areas have the same object as the selected object, these work areas are marked, and the basic score of each marked work area and the maximum matching coefficient XSO in the pre-selected set are obtained. max and the second largest matching coefficient XSO sec , according to the formula Calculate the priority index of each marked operation area separately.

[0126] The selected object is used as the matching object of the marking operation area with the highest priority index, and the matching object is deleted from the pre-selected set of other marking operation areas and the pre-selected object with the largest matching coefficient is re-selected as the selected object, and the judgment is repeated. ave It is the average value of the basic scores for all operating areas.

[0127] Finally, when the selected objects of all work areas are different, the selected objects are used as matching objects for the corresponding work areas and work tasks are generated. The work tasks are dispatched to the wearable devices of the matching objects, and the specific locations of the work areas and matching objects in the facility plan, as well as the area location and weight coefficient of each confluence area in the work area, are displayed through a visual interface.

[0128] The data storage module is used to record the operation trajectory and operation duration of each work of the object in real time, obtain the score of the manager or owner after the work is completed, automatically generate service records and upload them to the historical log through the Internet of Things.

[0129] Embodiment 1:

[0130] Assume that the two work areas A1 and A2 simultaneously select object B1 as the selected object, the basic score of A1 is 60, the maximum matching coefficient in the pre-selected set is 1.2, and the second largest matching coefficient is 0.8; the basic score of A2 is 53, the maximum matching coefficient in the pre-selected set is 1.1, and the second largest matching coefficient is 0.9; when the average basic score of all work areas is 50, substitute the formula to calculate the priority index of the two work areas A1 and A2 respectively:

[0131] A1 work area: A2 work area:

[0132] Then object B1 is used as the matching object of operation area A1, and operation area A2 resets the selected object.

[0133] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0134] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A smart park service management method based on the Internet of Things, characterized by: The method comprises the following steps: S100, collecting the facility plan of the park and the historical log of each object, collecting the status information of the objects within the park in real time through wearable devices, and mapping the status information to the facility plan; S200, analyzing the facility plan and dividing the operation area, selecting sample records for each operation area in the historical log, mapping the operation track in the sample record to the operation area to divide the merging area, and calculating the weight coefficient of each merging area; S300, filtering out service records for each object in the historical log, mapping the operation track of each service record to each operation area again, analyzing the intersection of the operation track and the convergence area and calculating the matching coefficient; selecting a matching object for each operation area according to the matching coefficient, generating an operation task and dispatching it to the wearable device of the matching object; S400. Each object goes to the designated work area to carry out work according to the work task. The wearable device records the relevant information of this work in real time. After the work is completed, a service record is generated and uploaded to the history log.

2. According to the method for managing smart park services based on the Internet of Things according to claim 1, it is characterized by: In S100, the facility plan refers to a plan drawn in proportion to display the layout of facilities in the park; the historical log refers to the service record of each time the object works, the object refers to the staff, and each service record includes the work area, work trajectory, work duration and score; the work area refers to the area where the object carries out work, the work trajectory refers to the movement trajectory of the object when working in the work area, the work duration is the working time of the object in the work area, and the score refers to the evaluation score of this work, which is evaluated and scored by the management personnel or the owner; the wearable device refers to the smart device worn by the staff, the wearable device integrates sensors, processors and communication functions, can monitor the movement status and real-time location of the staff, and exchange information with the data center background; the status information includes location and status, the location refers to the real-time location of the object, and the status includes idle and busy.

3. According to the method for managing smart park services based on the Internet of Things according to claim 2, it is characterized in that: In S200, the specific steps are as follows: S201, analyzing the areas that need to be served in the facility plan, taking each area that needs to be served as an operation area; obtaining the historical logs of all objects and filtering out the operation area ZY u All service records of the operation area are calculated based on the scores of these service records as the average value. u Average score Set the optimization coefficient e and filter out the items with a score greater than Service record as work area ZY u Sample records of S202, obtain the operation area ZY u All sample records of operation tracks and operation duration are mapped to the operation area ZY in the facility plan. u Set the duration threshold t, and analyze the operation duration to take the position on the corresponding operation track where the duration is greater than t as the operation point. There are different numbers of operation points on each operation track; analyze the operation area ZY u The distance between the working points of different working tracks is set as the distance threshold i, and the working points with a distance less than i are connected by line segments, and a circular area is established with the connecting line segments as the diameter, and the intersecting circular areas are combined as the confluence area; S203, Statistics Operation Area ZY u The total number of operation points in all operation trajectories y sum , and the number of operating points y in each confluence area; analyze the length of stay TL of each operating point n , and the operation duration SC of the sample record corresponding to the operation trajectory n and score pf n , substitute into the formula to calculate the weight coefficient of each confluence area: Where QZ is the weight coefficient.

4. According to the method for managing smart park services based on the Internet of Things according to claim 3, it is characterized in that: In S300, the specific steps are as follows: S301, filter out objects whose current location is in the park and whose status is idle, and obtain the object as DX r And the working area is ZY u All service records and total number of statistics sum , map the operation tracks in these service records to the operation area ZY in turn u At each operation track, the position where the stay time is greater than t is taken as the operation point; mark the operation track with at least one operation point in the confluence area, count the number of marked operation tracks l, obtain the weight coefficient of the confluence area where each operation point is located under each marked operation track, and substitute it into the formula to calculate the operation area ZY u With Object DX r The matching coefficient XSO between them is as follows: In the formula, y v is the number of operating points under the vth marked operating trajectory, c v is the number of operating points in the confluence area under the vth marked operating trajectory, is the weight coefficient of the confluence area where the hth operation point is located under the vth marked operation trajectory; S302, setting a coefficient threshold w and establishing a pre-selected set for each work area, respectively calculating the matching coefficient between each work area and each object, and placing objects with matching coefficients greater than w into the corresponding pre-selected set; Determine whether each object exists in at least one pre-selected set, and if yes, reduce the coefficient threshold w until each object exists in at least one pre-selected set; If the result is yes, all objects in the pre-selected set are taken as pre-selected objects in the corresponding operation area; S303, analyzing the historical logs of all objects and classifying these service records according to whether the operation areas are the same, respectively calculating the average score of each type of service records as the basic score JCF of the corresponding operation area; taking the pre-selected object with the largest matching coefficient in each pre-selected set as the selected object of the corresponding operation area, judging whether the selected objects of each operation area are different, if they are the same, marking the corresponding operation area and entering step S304, if they are not the same, entering step S305; S304: Obtain the basic score of each marking operation area and the maximum matching coefficient XSO in the corresponding pre-selected set max and the second largest matching coefficient XSO sec , substitute into the formula to calculate the priority index of each marking operation area; select the object as the matching object of the marking operation area with the highest priority index, delete the matching object from the pre-selected set of other marking operation areas and re-select the pre-selected object with the largest matching coefficient as its selected object, and enter step S303 again for re-judgment; wherein, the priority index calculation formula is as follows: In the formula, YZ is the priority index, JCF ave It is the average value of the basic scores of all operating areas; S305. Select an object as a matching object for the corresponding work area and generate a work task, dispatch the work task to the wearable device of the matching object, and display the specific locations of the work area and the matching object in the facility plan through a visual interface, as well as the area location and weight coefficient of each confluence area in the work area.

5. According to the method for managing smart park services based on the Internet of Things according to claim 4, it is characterized in that: In S400, each matching object goes to the designated work area of ​​the work task to carry out work, and the wearable device records the work trajectory and work duration of this work in real time. After the work is completed, the manager or owner evaluates and scores according to the completion quality, and automatically generates a service record and uploads it to the historical log.

6. A smart park service management system based on the Internet of Things, characterized by: The system includes a data acquisition module, a service management module, a job scheduling module and a data storage module; The data collection module is used to collect the facility floor plan of the park, as well as the historical logs and status information of the objects; the service management module divides the operation area according to the facility floor plan, selects sample records for each operation area in the historical log, maps the operation trajectory in the sample record to the operation area to divide the convergence area, and calculates the weight coefficient of each convergence area; The job scheduling module filters out service records for each object, maps the job trajectory of each service record to each work area again, analyzes the intersection of the job trajectory and the convergence area and calculates the matching coefficient; selects matching objects for each work area according to the matching coefficient, generates job tasks and dispatches them to the wearable devices of the matching objects; the data storage module is used to generate service records for each object and upload them to the historical log through the Internet of Things.

7. The smart park service management system based on the Internet of Things according to claim 6 is characterized by: The data collection module includes an object information collection unit, a history log collection unit and a map data collection unit; The object information collection unit is used to collect the state information of the object; the object refers to the staff, and the state information includes the location and state, the location refers to the real-time location of the object, and the state includes idle and busy; The historical log collection unit is used to collect service records of each object at each work; each service record includes the work area, work track, work duration and score; the work area refers to the area where the object carries out work, the work track refers to the movement track of the object when working in the work area, the work duration is the working time of the object in the work area, and the score refers to the evaluation score of this work, which is evaluated and scored by the management personnel or the owner; The map data collection unit is used to collect the facility plan of the park; the facility plan refers to a plan drawn in proportion to show the layout location of the facilities in the park.

8. The smart park service management system based on the Internet of Things according to claim 7 is characterized by: The service management module includes a region division unit and a weight analysis unit; The area division unit is used to divide the working area and the merging area; First, each area in the facility plan that needs to be serviced is taken as an operation area, and the operation area ZY is selected from the historical log. u All service records of the operation area ZY are calculated, and the average score of these service records is used as the u Average score Secondly, set the optimization coefficient e and filter out the scores greater than Service record as work area ZY u Sample records; map the operation track in each sample record to the operation area ZY in turn u At , set the duration threshold t, and take the position on each operation trajectory where the duration is greater than t as the operation point; Finally, set the distance threshold i and set the working area ZY u Connect the line segments between the operation points with a distance less than i under different operation trajectories, establish a circular area with the connecting line segments as the diameter, and combine the intersecting circular areas as the confluence area; The weight analysis unit is used to calculate the weight coefficient; statistical operation area ZY u The total number of operation points in all operation trajectories y sum , and the number of operating points y in each confluence area; analyze the length of stay TL of each operating point n , and the operation duration SC of the sample record corresponding to the operation trajectory n and score pf n , according to the formula Calculate the weight coefficient QZ for each confluence zone.

9. The smart park service management system based on the Internet of Things according to claim 8 is characterized by: The job scheduling module includes a matching analysis unit and a scheduling management unit; The matching analysis unit is used to calculate the matching coefficient between the working area and the object; First, filter out objects that are located in the park and are in the idle state, and obtain the object DX r All service records and total number of statistics sum , map the operation tracks in these service records to the operation area ZY in turn u At each operation track, the position where the stay time is greater than t is taken as the operation point; the operation track with at least one operation point in the confluence area is marked; Secondly, the number of marked operation trajectories l is counted, and the weight coefficient of the confluence area of ​​each operation point under each marked operation trajectory is obtained. According to the formula Calculate the work area ZY u With Object DX r The matching coefficient between them is XSO, where y v is the number of operating points under the vth marked operating trajectory, c v is the number of operating points in the confluence area under the vth marked operating trajectory, is the weight coefficient of the confluence area where the g-th operation point is located under the v-th marked operation trajectory; Finally, set the coefficient threshold w and establish a pre-selected set for each work area, calculate the matching coefficient between each work area and each object, and put the objects with matching coefficient greater than w into the corresponding pre-selected set; determine whether each object exists in at least one pre-selected set, if the result is yes, reduce the coefficient threshold w until each object exists in at least one pre-selected set; if the result is yes, take all objects in the pre-selected set as pre-selected objects for the corresponding work area; The scheduling management unit is used to allocate and adjust objects; First, the service records of all objects are classified according to whether the operation area is the same, and the average score of each type of service record is calculated as the basic score JCF of the corresponding operation area; the pre-selected object with the largest matching coefficient in each pre-selected set is selected as the selected object of the corresponding operation area; Secondly, when different work areas have the same object as the selected object, these work areas are marked, and the basic score of each marked work area and the maximum matching coefficient XSO in the pre-selected set are obtained. max and the second largest matching coefficient XSO sec , according to the formula Calculate the priority index of each marked operation area respectively; select the object as the matching object of the marked operation area with the highest priority index, delete the matching object from the pre-selected set of other marked operation areas and re-select the pre-selected object with the largest matching coefficient as its selected object, and re-judge; among them, JCF ave It is the average value of the basic scores of all operating areas; Finally, when the selected objects of all work areas are different, the selected objects are used as matching objects for the corresponding work areas and work tasks are generated. The work tasks are dispatched to the wearable devices of the matching objects, and the specific locations of the work areas and matching objects in the facility plan, as well as the area location and weight coefficient of each confluence area in the work area, are displayed through a visual interface.

10. The smart park service management system based on the Internet of Things according to claim 9, characterized in that: The data storage module is used to record the operation trajectory and operation duration of each work of the object in real time, obtain the score of the manager or owner after the work is completed, automatically generate service records and upload them to the historical log through the Internet of Things.

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