Title of invention: Elevator operation management system and operation management method
Technical field
[0001]
　The present invention relates to an elevator operation management system and an operation management method, and more particularly to an elevator operation management system and an operation management method having a function of predicting and outputting the number of people getting off in an elevator device.
Background technology
[0002]
　Conventionally, many proposals have been made regarding the operation management of elevator devices. Many of these proposals assume a situation where a user of an elevator device gets into a car and operates to a destination floor. The reality is that there are relatively few things.
[0003]
　Patent Document 1 and Patent Document 2 are cases in which improvements are proposed, assuming that the user gets out of the car.
[0004]
　For example, in Patent Document 1, a time limit required for a number of passengers expected to get off at each stop floor to get out of a car is set as a getting-off time limit, and at least one passenger gets in when the getting-off time period elapses. Is set as the boarding time, and the boarding time is updated and set anew each time the passenger gets in the car. is there.
[0005]
　Further, in the disembarking situation prediction presentation device of Patent Document 1, the image processing device 6 includes the in-car image information from the car-side user recognition camera 5 in the in-car situation information obtained from the image-processed image information. In addition to recognizing the number of users and the number of transportable vehicles, it is possible to determine which button has been operated by the car destination floor registration device 2 installed in the car 1 corresponding to each group grouped by processing each information. Recognizing the destination floor registration information, and using various information to calculate and predict the number of people getting off at which floor and how many people get off and the occupancy rate in the car 1 according to the number, and predicting the elevator The control device 7 displays on the hall display device 8 the result of determining whether or not the user can use the hall at each floor based on the result of the calculation.
Prior art documents
Patent literature
[0006]
Patent Document 1: Japanese Patent Laid-Open No. 2003-95562
Patent Document 2: Japanese Patent Laid-Open No. 2017-52578
Summary of the invention
Problems to be Solved by the Invention
[0007]
　In recent years, with the advanced use of the Internet and computer systems, processing of so-called big data, use of AI technology, and the like have been attempted in various fields.
[0008]
　From a perspective of an elevator control system in the near future from such a viewpoint, the elevator control system installed in a facility such as a building according to the example of the patent document described above controls individual elevators from various viewpoints, or a plurality of elevators are controlled. The elevators are controlled, but these are only operation management for users between the upper and lower floors of the building, and do not consider the relationship between the building and other facilities as a whole.
[0009]
　Especially when dividing these into facilities such as buildings and the outside, and comparing these, users who exit from the elevator car will then leave the facilities such as buildings, or vice versa, It is not supposed to grasp the elevator users who enter the facility such as a building from the outside in a macro and manage the operation of the elevator.
[0010]
　However, in the society of advanced utilization of the Internet and computer systems, the elevator control system in facilities such as buildings and other external systems are linked to predict the overall movement of people. It can be presumed that it will be possible to provide new services that did not exist.
Means for solving the problem
[0011]
　From the above, according to the present invention, "an elevator operation management system for controlling and managing a plurality of elevator devices in a facility, a receiving unit for obtaining the number of users of the elevator device and destination information of a car, and a receiving unit, The number of users and the car destination information obtained from the department are stored as past experience data, and the learning unit that learns and the floor that predicts the number of users getting off by each floor of the hall using the memory information of the learning unit Elevator operation management system characterized by having a separate number prediction unit and a request information output unit that outputs the estimated number of people getting off in the facility to a system other than the elevator operation management system". ..
[0012]
　Further, in the present invention, "an elevator operation management method by an elevator operation management system for controlling and managing a plurality of elevator devices in a facility, the number of users of the elevator device, destination information of the car as past experience data It is characterized by storing and predicting the number of users getting off by each floor of the hall using the stored past experience data, and outputting the predicted number of people getting off at the facility to a system other than the elevator operation management system. Elevator operation management method".
Effect of the invention
[0013]
　According to the present invention, an elevator control system in a facility such as a building and an external system other than that are connected to each other to predict a comprehensive movement of a person, thereby providing a new service that has not been available in the past. It will be possible.
Brief description of the drawings
[0014]
FIG. 1 is a diagram showing a schematic configuration of an elevator operation management system according to the present invention.
FIG. 2 is a diagram showing an example of a landing environment suitable for the present invention.
FIG. 3 is a diagram showing an example of a storage format of past experience data learned by a learning unit 31.
FIG. 4a is a diagram showing an example of a predicted passenger number table TB1 predicted by a floor-specific passenger number prediction unit 32.
FIG. 4b is a diagram showing an example of a predicted getting-off number table TB2 predicted by the floor-by-floor number prediction unit 32.
FIG. 5a is a diagram showing an example of a predicted passenger number table TB1 including actual data added by the accuracy verification unit 33.
FIG. 5b is a diagram showing an example of a predicted getting-off number table TB2 including the actual data added by the accuracy verification unit 33.
FIG. 6a is a diagram showing an output example (in increments of 1 minute) about the predicted number of people getting off in a time series.
FIG. 6b is a diagram showing an output example (in 5-minute increments) of a predicted number of people getting off in a time series.
FIG. 7 is a diagram showing an output example in which predicted values ​​of the number of people getting on and off for each floor are displayed and output.
FIG. 8 is a diagram showing an output example in which predicted values ​​and actual values ​​of the number of people getting on and off for each floor are displayed and output.
[Fig. 9] A diagram showing an example in which the number of people getting on and off is arranged vertically and horizontally, and displayed and output so that the current elevator usage status can be grasped.
FIG. 10 is a flowchart specifically exemplifying processing contents in the floor-by-floor number-of-people prediction unit 32 of FIG. 1.
MODE FOR CARRYING OUT THE INVENTION
[0015]
　Embodiments of the present invention will be described below with reference to the drawings.
Example 1
[0016]
　FIG. 1 shows a schematic configuration of an elevator operation management system according to the present invention. The facilities and systems in the facility such as the building 1 and the external system 2 are described here.
[0017]
　The facilities and systems in the facility such as the building 1 are generally an elevator operation management system 3, a hall elevator service requesting device 4 on each floor, a surveillance camera 5 on each floor, a building management system 6, and the like, and communication is performed between them. Data communication is mutually performed via the means 8. Further, a plurality of elevator control systems 7a... 7n are installed and controlled by the elevator operation management system 3. In implementing the present invention, the elevator operation management system 3 and the building management system 6 do not have to be equipment or systems in the facility such as the building 1. If mutual data communication is performed via the communication means 8, similar control and monitoring can be performed even if some or all of the functions are installed outside the facility such as the building 1.
[0018]
　In FIG. 1, a public institution management system is illustrated as an example of the external system 2, but a taxi dispatch system or the like may be used.
[0019]
　The elevator operation management system 3 according to the present invention obtains many inputs and settings and gives outputs. Among these inputs and outputs, between the elevator control system 7a...7n and the elevator operation management system 3, the elevator control system 7a...7n reports the operating state information S71 to the elevator operation management system 3 and the elevator control system 3 7a... 7n have their vehicle allocation units selected after the elevator button for each elevator has been pressed by the control command signal S72 from the elevator operation management system 3. What is characteristic here is that the elevator operation management system 3 operates and manages all the units in the building 1, and other matters are the same as normal elevator control, so the explanation here Omit.
[0020]
　In the present invention, as other inputs, the service request signal S4 from the hall elevator service request device 4 on each floor, the video signal S5 from the surveillance camera 5 on each floor, the building management system 6 to the building management information S6, and the public institution management system 2 Obtain public institution management information S2 and the like.
[0021]
　FIG. 2 is a diagram showing a landing environment example suitable for the present invention. At the elevator halls on each floor, surveillance cameras 5 (5-1, 5-2, 5-3, 5-4) for monitoring and photographing the space including the elevator doors, and a vertical button 4 as a hall elevator service request device 4 are provided. (4-1, 4-2, 4-3, 4-4) are installed. In FIG. 2, reference numeral 20 (20-1, 20-2, 20-3) is a lantern that indicates the current moving direction of the elevator car. FIG. 2 further includes an in-car camera 21 and a load sensor 22 in an elevator car 24.
[0022]
　As will be described below, the positioning of the service request signal S4 in the present invention is for confirming the ascending and descending directions of the elevator, and the up/down button 4 is illustrated in FIG. May be a destination floor registration device or the like.
[0023]
　The positioning of the video signal S5 in the present invention is for measuring the number of users, and can be replaced as long as the number of users can be estimated or confirmed directly or indirectly. In the example of FIG. 2, it is possible to obtain information on the number of users from the in-car camera 21 provided in the elevator car 24 and the load sensor 22 provided in the lower part of the elevator car 24.
[0024]
　In this way, it is possible to confirm from the service request signal S4 whether the destination floor of the user who uses the elevator is going up or down than the floor where the landing button is installed, and from the video signal S5. Indicates the number of users, the building management information S6 can confirm the action schedules such as conferences and events in the facility, and the public institution management information S2 can indicate the operation information (for example, train delay) of the public institution on the day. Can be grasped. It should be noted that some of these pieces of information include information that has been input to existing systems and used for some purpose, but the present invention is new in that it is used to estimate the predicted number of people getting off.
[0025]
　The reception unit 36 ​​in the elevator operation management system 3 of FIG. 1 obtains the service request signal S4, the video signal S5, the building management information S6, etc. via the communication means 8, and the operation state from the elevator control system 7a... 7n. Input the information S71. The driving state information S71 includes information on the position of the car. The overall evaluation unit 37 determines the user's request and the moving direction from these signals, and the allocation command unit 38 gives the control command signal S72 to the elevator control systems 7a... 7n of each unit and controls them. To do. This part is no different from the conventional elevator control, and will not be described further.
[0026]
　The service request signal S4, the video signal S5, the building management information S6 and the like obtained via the communication means 8 are recorded and used in the learning section 31. Furthermore, the number of users is also transmitted from the in-car camera 21 provided in the elevator car 24 and the load sensor 22 provided in the lower part of the elevator car 24 transmitted from the elevator control system 7a... 7n. Based on the information and the position of the elevator car, the number of passengers on each floor and the number of passengers getting off can be grasped. Here, the service request signal S4 and the video signal S5 are stored together with information on the time when these signals were generated, and are used as experience information in the past. As a result, a certain past scene (day of the week, season, etc.), a user's behavior at a certain time, and a mode are statistically grasped. For example, it is possible to grasp the outline of the movement situation of the user at the time of going to work, lunch, leaving time, and the like. Therefore, in the same future scene, it is possible to presume that although the same operation is not performed on an individual basis, the entire building shows a traffic flow similar to the past experience when viewed as a macro.
[0027]
　The information obtained by the receiving unit 36 ​​includes the destination information of the car. Destination information of the car, the destination direction of the information of the car or the destination floor, or the car position location is information. It should be noted that the car position location information may be the destination of the information by time-series grasp.
[0028]
　The service request signal S4 and the video signal S5 are used as the experience information in the past, whereas the building management information S6 from the building management system 6 is the action schedule such as meetings and events in the facility in the near future. (Holding place, attendees and their attending place) and the like are the information registered in the building management system 6, and according to this, for example, the movement of the user from each floor during a meeting from 3:00 today Can be predicted.
[0029]
　If the train delay and the degree thereof can be grasped from the public institution management information S2 as the operation information of the public institution on the day, especially the movement trend of the user at the time of going to work is different from the movement tendency in the normal time without delay. , Can be predicted to change. As is clear from this fact, the public institution management information S2 can be used as the past experience information or the correction information of the prediction determined from the schedule in the near future.
[0030]
　In this way, the learning unit 31 learns the number of people who normally use the elevator every day. The past experience data learned by the learning unit 31 is organized and stored as shown in FIG. 3, for example.
[0031]
　FIG. 3 illustrates, for example, a storage format of past record passengers, and stores the number of passengers on each floor and the boarding rate information for each ascending/descending floor by associating and storing it at each past date and time. There is. The memory format of the number of people who have descended in the past is also created in the same format. It is preferable that the storage format includes information that is stored by grasping the number of people for each day, for example, every 5 minutes, and accumulated for a long period in the past. The 5 minutes is a time width used for a scale used when planning the installation of the elevator, and is not limited to this. For example, it is possible to use a method that is determined for each case of the elevator every one hour or a method that specifies a fixed width other than 5 minutes. Further, the resolution may be calculated in increments of 1 minute, and may be appropriately processed for 5 minutes or 10 minutes. Further, the past experience data may include event information such as meetings and various events as accompanying information. The past experience data learned by the learning unit 31 is used as a past experience in the prediction process in the following process.
[0032]
　The floor-by-floor number-of-people prediction unit 32, based on past experience, the schedule of the meeting on the day, and the like, for example, the movement of the person in an arbitrary time width from the present time, or the movement of the person in the traffic flow of the building recognized by the learning unit. Estimate the number of people by floor. FIG. 4a shows an example of the predicted passenger number table TB1 predicted by the floor-by-floor passenger number prediction unit 32, and FIG. 4b shows an example of the predicted passenger number table TB2 by the floor-by-floor passenger number prediction unit 32.
[0033]
　The predicted passenger number table TB1 and predicted passenger number table TB2 are time data D1, D6, floor data D2, D7, predicted passenger data D3, D8, actual passenger data D4, D9, prediction accuracy data D5, D10 sequentially from the top. It is configured. The floor-by-floor number prediction unit 32 forms the data from the top to the third row in these tables using the past experience data in FIG.
[0034]
　For example, in the predicted passenger number table TB1, at 8 o'clock (which will be described later, for example, it represents 5 minutes from 8 o'clock), the number of passengers on each floor (here, from the first floor to the eighth floor) is 20, 9 respectively. , 7, 14, 13, 7, 8, and 5 are predicted. Further, for example, in the predicted descending number table TB2, at 8 o'clock time (which will be described later, for example, it represents 5 minutes from 8 o'clock), the number of descending persons on each floor (here, from the first floor to the eighth floor) is 20, It shows that it was predicted to be 5, 9, 15, 11, 15, 18, and 11.
[0035]
　As to the method of creating the predicted passenger number table TB1 and the predicted disembarkation number table TB2, the predicted passenger number table TB1 and the predicted passenger number table TB2 can be created in consideration of past experience and today's schedule. By making the correction, the accuracy can be increased and the value can be obtained.
[0036]
　The accuracy verification unit 33 adds the information of the lower two stages to the data of the upper three stages created by the floor-by-floor number prediction unit 32 based on actual experience. 5a shows an example of a predicted passenger number table TB1 including the actual data added by the accuracy verification unit 33, and FIG. 5b shows an example of a predicted passenger number table TB2 including the actual data added by the accuracy verification unit 33.
[0037]
　In this example, for example, in the predicted passenger number table TB1, at 8 o'clock time (which will be described later, for example, it represents 5 minutes from 8 o'clock), the number of passengers on each floor (here, from the first floor to the eighth floor), We predicted that the numbers would be 20, 9, 7, 14, 13, 7, 8, and 5, respectively, but in reality they were 18, 13, 10, 19, 14, 14, 10, and 9, and the accuracy of each was It can be seen that it was 82, 38, 60, 75, 92, 88, 95, 90%.
[0038]
　Further, in this example, for example, in the predicted number-of-descendants table TB2, at 8 o'clock time (which will be described later, for example, it represents 10 minutes from 8 o'clock), , Were predicted to be 20, 5, 9, 15, 11, 15, 18, 18, and 11, respectively, but in reality they were 17, 13, 15, 12, 12, 17, 17, 19, and the accuracy of each It can be seen that was 89, 69, 70, 74, 93, 50, 80, 56%.
[0039]
　These precisions are calculated for each certain time width. Here, the time width is set based on the scale used in the traffic calculation as described above, and is not limited to this. The calculated accuracy is stored in the learning unit 31, and in this embodiment, it is stored for each time zone and each floor. The saving format may be a traffic flow, a day of the week, or an event. As described above, the stored accuracy information is calculated from the daily prediction information and the actual measurement value, and is used when calculating the next predicted number of people. The method to be used is to calculate the weighted average of the past values ​​of the floor and the floor at the time concerned and to add the weight in the near future. Further, the method to be used is not limited to this, and may be a method in which the accuracy of the average value of 10 days before is used as it is, or a method of using the maximum value. It is desirable to use the statistical information calculated in the past by using a statistical method.
[0040]
　The request information output unit 34 appropriately processes the information on the predicted number of people getting off by the accuracy verification unit 33 according to the setting information from the output information setting unit 35, and outputs the information to the outside of the elevator operation management system 3. The external output destination is a building management system 6 or an external system 2, such as a public institution management system.
[0041]
　It should be noted that the output information setting unit 35 gives, for example, a time width and a designated time as setting contents.
[0042]
　The output format (display format) of the information on the predicted number of people getting off from the request information output unit 34 does not matter in many cases. In an extreme case, the raw information may be unprocessed, and the building management system 6 or the external system 2 on the user side interprets it appropriately according to the purpose of use, processes it, and uses it. .. Output examples and usage examples are explained below.
[0043]
　FIG. 6a and FIG. 6b are diagrams showing an output example of the predicted number of people in descending time series, and basically, regarding the predicted number of descending people table TB2, time data D6, predicted number of people data D8, actual number of people data D9, prediction The accuracy data D10 is summarized as time series data in 1 minute increments in FIG. 6a and 5 minute increments in FIG. 6b. It should be noted that the distinction in 1 minute increments, 5 minute increments, or the time in the 8 o'clock range is determined according to the time width setting and the time setting from the output information setting unit 35.
[0044]
　Information on the estimated number of people getting off in chronological order can be used, for example, at a taxi company that dispatches taxis to the entrance of a facility such as a building, and the number of people leaving the facility will be crowded, so the number of users is expected to increase. Efficient taxi dispatch can be realized by allocating vehicles in front.
[0045]
　In addition to the information transmitted to the outside of the building, there are cases where this information can be used inside the building. For example, it transmits time-series information about the predicted number of people getting off to tenants who belong to the building. If the tenant in the building is, for example, a restaurant, it is possible to accurately set the personnel schedule in advance. In addition, by utilizing this information for the schedule of the air conditioning system of the building, it is possible to provide a comfortable space by operating the air conditioning output according to the number of people on the floor where it is expected to get off a lot in advance.
[0046]
　FIG. 7 shows and outputs the predicted values ​​of the number of people getting on and off for each floor, and FIG. 8 further shows and outputs the actual values ​​(dotted lines) in a superimposed manner. This information is an easy-to-understand illustration of FIGS. 5a and 5b. For example, via the network 8, the elevator operation management system 3 is requested to obtain information for each hour of the past one day, and the predicted value and the actually measured value described above are output. This information is output to a building management room or a PC installed in the building management room or a Web content management screen for building management so that this information can be displayed to building managers for the day's user status. By visualizing the usage status in the building, the administrator can flexibly deal with the building security and the schedule of air conditioning equipment. The output method may not include the predicted value and may be only the actually measured value.
[0047]
　FIG. 9 is an example in which the numbers of people getting on and off are arranged vertically and horizontally, and displayed and output so that the current elevator usage status can be grasped. Depending on the area defined by the number of people getting on and off in the vertical and horizontal directions, normal use, lunch, uphill, downhill, etc. can be identified.
[0048]
　FIG. 10 is a flowchart specifically exemplifying the processing contents in the floor-by-floor number prediction unit 32 of FIG. 1. As a premise, the learning unit 31 processes the number of time-series users measured every day together with the boarding rate information for each floor and up/down direction to form the past experience data of FIG. Have been done. That is, it is assumed that the past experience data corresponding to the actual number data D4 and D9 are secured and stored in time series and for a corresponding number of days in the predicted passenger number table TB1 and the predicted disembarkation number table TB2. Also, it is assumed that the past days are stored including information on events and conferences held on that day.
[0049]
　The processing of FIG. 10 may be started at an appropriate timing, but if it is provided as information for one day on the following day, for example, it will be processed at an appropriate time on the previous day. Alternatively, if it is provided by a request from the outside, it may be started at the time of request.
[0050]
　In the first processing step S100 of the floor-by-floor number prediction unit 32, past experience data and the like are fetched. This includes actual number data D4, D9, time data D1, D6, building management information S6, and the like. In process step S101, setting information such as a time width and a designated time is fetched from the output information setting unit 35.
[0051]
　In the processing step S102, the output date (for example, tomorrow) is determined. It is determined whether the output date is a weekday, a holiday, or a part of the output date, and only the items having the corresponding conditions are extracted from the past experience data of FIG. In the processing step S103, for example, if the output day is a weekday, only the past experience data of the weekday is extracted, and if the output day is a holiday, only the past experience data of the holiday is extracted. If there are seasonal fluctuations in the users, it is better to take this point into consideration for extraction.
[0052]
　In the processing step S104, the use averages by time are calculated for the extracted time-series use records for a plurality of days, and are set as the predicted passenger number data D3 and D8 in the predicted passenger number table TB1 and the predicted passenger number table TB2. Since the above processing is performed for the number of users for each floor, floor data D2 and D7 are also obtained.
[0053]
　In processing step S105, the presence/absence of the building management information S6 is confirmed. For example, if a meeting is scheduled to be held from today at 15:00, in processing step S106, the movement of the user, the elevator The predicted number of passengers data D3 and D8 in the predicted number of passengers table TB1 and the predicted number of descending passengers table TB2 obtained in the processing step S104 are corrected to reflect the usage method. If the past experience data indicates that a conference to the same effect as this conference has been held in the past, the predicted passenger number table TB1 and the predicted number of passengers disembarked based on the user information at that time. It is preferable to correct the predicted number of people data D3 and D8 in the table TB2.
[0054]
　In processing step S108, the presence or absence of the public institution management information S2 is confirmed. For example, if it is obtained at 8 o'clock today that the train arriving at the nearest station of the building is late, then in processing step S108. , The predicted number of passengers data TB3 and D8 of the predicted number of passengers table TB1 and the predicted number of passengers descending table TB2 obtained in the processing steps S104 and S106 are reflected by reflecting the movement of the user and the way of using the elevator according to the degree of the delay. Fix it.
[0055]
　As described above, the past performance is corrected based on the action schedule and the information of the public institution, and the predicted passenger number data D3 and D8 of the predicted passenger number table TB1 and the predicted passenger number table TB2 are obtained.
[0056]
　The predicted number of people getting off in this way can be reflected to the operation of the system at the providing destination by being provided outside the elevator operation management system 3. Through this, it is possible to contribute to the realization of a more sophisticated society.
Industrial availability
[0057]
　In the highly-utilized society of the Internet and computer systems, it is possible to utilize the information of exits by building as a part of big data.
Explanation of symbols
[0058]
1: Facilities such as buildings, 2: External system (public institution management system), 3: Elevator operation management system, 4: Elevator service request device on each floor, 5: Surveillance camera on each floor, 6: Building management system, 7a ... 7n: elevator control system, 8: communication means, 31: learning unit, 32: number of people prediction unit by floor, 33: accuracy verification unit. 34: request information output unit, 35: output information setting unit, 36: reception unit, 37: comprehensive evaluation unit, 38: allocation command unit, S2: public institution management information, S4: service request signal, S5: video signal, S6 : Building management information, S72: Control command signal
The scope of the claims
[Claim 1]
　An elevator operation management system for controlling and managing a plurality of elevator devices in a facility, comprising a
　number of users of the elevator device, a receiving unit for obtaining destination information of a car, and a number of users obtained from the receiving unit. The destination information of the car is stored as past experience data, and a learning unit for learning, and a floor-specific number-of-floor number prediction unit for predicting the number of users getting off by floor of the hall using the memory information of the learning unit, An elevator operation management system comprising a request information output unit that outputs the predicted number of passengers getting off in the facility to a system other than the elevator operation management system.
[Claim 2]
　The elevator operation management system according to claim 1,
　wherein the event schedule information in the facility is obtained, and the number of users getting off by floor of the hall is predicted from the event schedule information and the past experience data. The featured elevator operation management system.
[Claim 3]
　The elevator operation management system according to claim 1 or 2
　, wherein the operation information in a public institution is obtained, and the number of users getting off by floor of a landing is predicted from the operation information and the past experience data. A featured elevator operation management system.
[Claim 4]
　The elevator operation management system according to any one of claims 1 to 3
　, wherein the predicted number of passengers getting off in the facility is output to a system other than the elevator operation management system, as a result. An elevator operation management system characterized by adding and outputting information on the number of people getting off and prediction accuracy.
[Claim 5]
　The elevator operation management system according to any one of claims 1 to 4
　, wherein the predicted number of passengers getting off in the facility, which is output to a system other than the elevator operation management system, is set in advance. The elevator operation management system, which is the number of people in a given time zone and is provided as time-series information.
[Claim 6]
　A elevator operation management system according to any one of claims 1 to 5,
　the destination information of the car is traveling direction information or destination floor or the car position of the car location is information Elevator operation management system characterized by that.
[Claim 7]
　An elevator operation management method by an elevator operation management system for controlling and managing a plurality of elevator devices in a facility, in which the
　number of users of elevator devices and car destination information are stored as past experience data and stored in the past. An elevator operation management method characterized by predicting the number of users getting off by each floor of a landing using experience data and outputting the predicted number of people getting off in the facility to a system other than the elevator operation management system. ..
[Claim 8]
　The elevator operation management method according to claim 7,
　wherein the event schedule information in the facility is obtained, and the number of users getting off by floor of the hall is predicted from the event schedule information and the past experience data. How to manage elevator operation.
[Claim 9]
　The elevator operation management method according to claim 7 or 8
　, wherein operation information in a public institution is obtained, and the number of passengers getting off by each floor of the landing is predicted from the operation information and the past experience data. Elevator operation management method characterized by.
[Claim 10]
　The elevator operation management method according to any one of claims 7 to 9
　, wherein the predicted number of disembarked passengers in the facility is output to a system other than the elevator operation management system as a result. An elevator operation management method characterized by adding and outputting information on the number of people getting off and prediction accuracy.
[Claim 11]
　The elevator operation management method according to any one of claims 7 to 10
　, wherein the estimated number of passengers getting off in the facility, which is output to a system other than the elevator operation management system, is set in advance. Elevator operation management method characterized in that it is the number of people in a given time zone and is provided as time-series information.
[Claim 12]
　A lift operation control method according to any one of claims 11 claim 7,
　destination information of the car is traveling direction information or destination floor or the car position of the car location is information Elevator operation management method characterized by the following.