Indoor people number measuring system and indoor people number measuring method

Abstract

The purpose of the present invention is to provide a system and a method for measuring the number of persons in a room, which can accurately correct the error between the number of persons entering and exiting a floor and can accurately calculate the number of persons in the room in the floor. The present invention is provided with: a difference calculation unit (25) for calculating the difference between the number of entering people and the number of leaving people in a floor of a building on the basis of elevator operation data, said difference being the difference between the total number of entering people and the total number of leaving people in the floor of the building; a correction processing data calculation unit (26) for time series data of the number of people entering / leaving the floor, the correction processing data for correcting at least one of the number of people entering the floor and the number of people leaving the floor within a given time period being obtained on the basis of the difference from the total number of people entering the floor and the number of people leaving the floor; and an online calculation unit (30) for calculating the number of people in the room on the floor by correcting the number of people who have calculated the correction processing data among the number of people entering the floor and the number of people leaving the floor on the basis of the operation data of the elevator.

Description

Technical Field

[0001] The present invention relates to a system and method for measuring the number of people in a room, and more particularly to a system and method for measuring the number of people in a room on each of a plurality of floors accessible by elevator. Background Art

[0002] In multi-story buildings like office buildings, diverse work styles permeate each floor, and the traditional practice of uniform equipment operation on each floor is increasingly inadequate. In other words, the demand is for equipment to be operated on a floor-by-floor basis, not uniformly. To achieve this, it is necessary to track the number of people in the room, or the number of occupants, on each floor.

[0003] Patent Document 1 discloses a device for estimating the number of people present, comprising: a boarding and alighting history information generating unit for generating boarding and alighting history information including the boarding and alighting floors and boarding and alighting dates and times of each elevator user based on the boarding and alighting status of an elevator car installed in a building. Furthermore, the device for estimating the number of people present on each floor comprises: a correction parameter calculating unit for calculating a correction parameter for use in calculating the number of people present on each floor based on the number of people entering and exiting the building during a given period and the boarding and alighting history information during the given period. Furthermore, the device for estimating the number of people present on each floor comprises: a device for estimating the number of people present on each floor, including those other than elevator users at the current time, by correcting the number of people present on each floor obtained from the boarding and alighting history information using the correction parameter. The boarding and alighting history information corresponds to elevator users who boarded and alighted the elevator car during the period for estimating the number of people present from a reference time point to the present time.

[0004] Patent Document 2 discloses an elevator dispatch planning system. This elevator dispatch planning system comprises: a motion prediction device that generates outbound status prediction data by statistically processing the power consumption patterns of each section on each floor of a residential building; a dispatch plan prediction device that formulates a dispatch plan for placing the elevator on standby at an appropriate floor based on the outbound status prediction data; and an elevator control device that performs dispatch control based on the dispatch plan. After placing the elevator on standby at the dispatch floor through dispatch control, the elevator control device collects boarding performance data that identifies the floor on which the user actually boarded the elevator. The dispatch plan prediction device corrects the current dispatch plan based on the boarding performance data, thereby formulating a new dispatch plan for placing the elevator on standby at a more appropriate floor, and then performs dispatch control based on the new dispatch plan.

[0005] Prior art literature

[0006] Patent Literature

[0007] Patent Document 1: Japanese Patent Application Laid-Open No. 2016-74525

[0008] Patent Document 2: International Publication No. 2017 / 175380 Summary of the Invention

[0009] -Problems to be solved by the invention-

[0010] By utilizing elevators in a building as so-called crowd flow sensors, it is possible to determine the number of people in each floor without installing new sensors, enabling efficient use of air conditioning / lighting equipment, cleaning / security, etc.

[0011] However, conventional methods do not adequately account for errors in the number of people entering and exiting. In particular, errors are significant for people who use the stairs instead of the elevator. Furthermore, it is difficult to calculate the number of people in a room on floors where elevator operation data is unavailable.

[0012] An object of the present invention is to provide a room occupancy measurement system and a room occupancy measurement method that can accurately correct errors in the number of people entering and leaving a floor and accurately calculate the number of people in the room on a floor.

[0013] -Methods for solving the problem-

[0014] To address the aforementioned issues, the present invention provides a room occupancy measurement system comprising: a headcount difference calculation unit for calculating the difference between the total number of people entering and exiting a building floor based on elevator operation data; a correction data calculation unit for calculating, based on the difference from the total number, correction data for correcting at least one of the number of people entering or exiting a floor within a given time period; and an occupancy calculation unit for calculating the number of people in the room on that floor by correcting the number of people entering and exiting the floor for which the correction data was calculated based on the elevator operation data. This system provides a room occupancy measurement system capable of accurately correcting errors in the number of people entering and exiting a floor and accurately calculating the number of people in the room on that floor.

[0015] Here, for example, the correction data calculation unit may set multiple movement models as models of a person's movement between floors, calculate model correction data as correction data for each movement model, and obtain correction data based on the model correction data. In this case, by using a movement model that matches a person's actual movement, more accurate correction data can be calculated.

[0016] Alternatively, for example, the correction data calculation unit may determine the ratios at which multiple movement models are applied, distribute the differences according to the determined ratios, calculate model correction data based on the distributed differences, and use the sum of the calculated model correction data as the correction data. In this case, the movement models can be assigned a ratio corresponding to actual human movement on each floor, allowing for the creation of more accurate correction data.

[0017] Furthermore, for example, the correction processing data calculation unit changes the ratio for each floor. In this case, it is possible to set a ratio corresponding to the actual movement of people on each floor.

[0018] Furthermore, for example, when calculating the correction data for correcting the total number of people exiting, the correction data calculation unit uses the following models as movement models: a model for using the elevator instead of the stairs; a model for using the elevator for going up and the stairs for going down; a model for using the stairs when the elevator is crowded and otherwise using the elevator; and a model for using the stairs instead of the elevator. The proportion of these movement models applied is varied for each floor. In this way, the movement models can be aligned with actual human movement.

[0019] Furthermore, for example, the correction processing data calculation unit increases the proportion of the model in which people use stairs less often than elevators on lower floors. In this case, it is possible to conform to the fact that people use stairs less often than elevators on lower floors.

[0020] Furthermore, for example, the correction data calculation unit calculates correction data for correcting the number of people leaving when the total number of people leaving is less than the total number of people entering, and calculates correction data for correcting the number of people entering when the total number of people entering is less than the total number of people leaving. In this case, the error in either the number of people entering or the number of people leaving can be corrected.

[0021] Furthermore, for example, the occupancy calculation unit may calculate the number of occupants on floors where elevator operation data cannot be collected using time-series data of physical quantities related to the number of occupants on that floor. In this case, the number of occupants can be calculated even on floors where elevator operation data cannot be collected.

[0022] Furthermore, for example, the correction-processed data calculation unit calculates the relationship between the number of people in a room and a physical quantity related to the number of people in the room on floors where elevator operation data can be collected. The occupant calculation unit then uses this relationship to calculate the number of people in the room on floors where elevator operation data cannot be collected. In this case, the number of people in the room can be calculated more accurately even on floors where elevator operation data cannot be collected.

[0023] Furthermore, for example, the occupant count calculation unit uses the more accurate method of calculating the number of occupants using calibration data or the method of calculating the number of occupants based on physical quantities. In this case, even if the accuracy of the method of calculating the number of occupants based on elevator operation data is not high, the occupant count can be calculated more accurately.

[0024] Furthermore, the present invention provides a method for measuring the number of people in a room, wherein a processor executes a program stored in a memory to calculate the difference between the total number of people entering and exiting a building floor based on elevator operation data. Based on the difference, correction data is calculated for correcting at least one of the number of people entering or exiting a floor within a given time period. Based on the elevator operation data, the number of people entering or exiting a floor for which the correction data was calculated is corrected to calculate the number of people in the room on that floor. In this case, a method for measuring the number of people in a room can be provided that accurately corrects errors in the number of people entering and exiting a floor and accurately calculates the number of people in the room on that floor.

[0025] -Effects of the Invention-

[0026] According to the present invention, an object is to provide a room occupancy measurement system and a room occupancy measurement method capable of accurately correcting errors in the number of people entering and leaving a floor and accurately calculating the number of people in the room on a floor. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 This is a block diagram showing the overall configuration of the building management system according to this embodiment.

[0028] Figure 2 This is a flowchart for explaining an outline of the operation of the building management system according to this embodiment.

[0029] Figure 3 This is a flowchart illustrating the processing of the offline processing unit in further detail.

[0030] Figure 4 This is a flowchart illustrating the processing of the online processing unit in further detail.

[0031] Figure 5 This is a diagram explaining a user's movement model.

[0032] Figure 6 It's the decision Figure 5 The processing shown in the flowchart is performed on the scale shown.

[0033] Figure 7This is a flowchart for explaining a process in which the offline processing unit calculates the difference between the total number of people entering (∑ number of people entering) and the total number of people leaving (∑ number of people leaving) on ​​each floor every day.

[0034] Figure 8 This is a flowchart for explaining processing in which the offline processing unit calculates an index of the use status of the elevator for a target floor based on the elevator operation data.

[0035] Figure 9 This is a flowchart for explaining the process of obtaining correction processing data for correcting the number of people leaving a floor by the offline processing unit.

[0036] Figure 10 Is used as correction processing data Figure 9 In this way, the calculation methods of the case where the correction term is obtained and the case where the correction coefficient is obtained are compared for each movement model.

[0037] Figure 11 (a) to (b) are graphs showing time series data of the number of people entering, leaving, and in-room occupancy before correction.

[0038] Figure 12 (a) to (c) are graphs showing the correction item for the number of people leaving, and the time series data of the number of people entering, leaving, and in-room after correction.

[0039] Figure 13 This is a diagram showing an example of measurement data related to a person's activity state.

[0040] Figure 14 This flowchart explains a method for calculating the number of people in a room based on measurement data related to human activity status when there is a large error in the method of calculating the number of people in a room by obtaining correction processing data from elevator operation data.

[0041] 1... Building management system, 10... Number of people entering / exiting calculating unit, 20... Offline processing unit, 21... Building floor information DB, 22... Building user inter-floor movement model DB, 23... Floor user movement model setting unit for each floor, 24... Elevator usage status index calculating unit, 25... Floor difference calculation unit for calculating the number of people entering and exiting a floor, 26... Correction data calculation unit for time-series data of number of people entering / exiting a floor, 27... Floor occupancy time-series data calculation unit, 28... Conversion coefficient calculation unit for converting measurement data related to human activity into occupancy, 30... Online processing unit, 31... Floor entry or exit correction processing unit, 32... Floor occupancy calculation unit, 33... Floor occupancy calculation unit based on measurement data related to human activity status. DETAILED DESCRIPTION

[0042] Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

[0043] <Overall Description of Building Management System 1>

[0044] Figure 1 It is a block diagram showing the overall configuration of the building management system 1 according to the present embodiment.

[0045] The building management system 1 of this embodiment is an example of a room occupancy counting system. This system calculates the number of people on each floor of a building based on elevator operation data. The building is not particularly limited as long as it has multiple floors and an elevator that transports people to each floor. Examples include office buildings and apartment buildings.

[0046] The building management system 1 is a computer device, such as a server computer. However, it is not limited to this and may be a PC (Personal Computer), a mobile computer, a smartphone, a tablet, etc. In addition, it may be a cloud server operating on the cloud.

[0047] The building management system 1 includes a processor such as a CPU (Central Processing Unit) as a computing unit and a main memory as a storage unit. The processor executes various software programs, such as the operating system (OS) and applications (application software). The main memory is a storage area that stores various software programs and the data used during their execution. Furthermore, the building management system 1 includes storage devices such as HDDs (Hard Disk Drives) and SSDs (Solid State Drives) as auxiliary storage devices, and a communication interface for external communication. Furthermore, input devices such as a mouse and keyboard, and output devices such as a display may also be included.

[0048] As shown in the figure, the building management system 1 includes an entry / exit number calculation unit 10 , an offline processing unit 20 , and an online processing unit 30 .

[0049] The entrance / exit number calculation unit 10 calculates the entrance number, which is the number of people who got off the elevator on each floor, based on the elevator operation data. Furthermore, the entrance / exit number calculation unit 10 calculates the exit number, which is the number of people who got on the elevator on each floor, based on the elevator operation data.

[0050] Although details will be described later, the offline processing unit 20 calculates the difference between the total number of people entering and the total number of people leaving the building's floors based on the elevator operation data, and based on the difference from the total, calculates correction processing data for correcting at least one of the number of people entering and the number of people leaving the floor within a given time.

[0051] Although described in detail later, the online processing unit 30 is an example of a room occupancy calculation unit. The online processing unit 30 calculates the number of occupants on a floor by correcting the number of people entering and exiting the floor for which correction processing data is calculated based on elevator operation data.

[0052] Hereinafter, the number of people entering / leaving calculating unit 10 , the offline processing unit 20 , and the online processing unit 30 will be described in further detail.

[0053] The entrance / exit calculation unit 10 includes: an elevator data input unit 11, an elevator data storage DB (database) 12, a measurement data input unit 13 related to the activity status of people on the floor, a measurement data storage DB (database) 14 related to the activity status of people, an identification unit 15 for data that can be used for the floor, and a floor entrance / exit calculation unit 16.

[0054] The elevator data input unit 11 inputs elevator data from an elevator system that manages elevator operations. The elevator data is, for example, elevator operation data. The elevator operation data includes, for example, the floor where the elevator stopped at a certain time and the weight of the elevator car.

[0055] The elevator data storage DB 12 stores the elevator operation data input to the elevator data input unit 11 .

[0056] The measurement data input unit 13 related to the activity status of people on a floor receives time-series data of physical quantities related to the number of people in the rooms on that floor. In this embodiment, the physical quantities related to the number of people in the rooms on that floor are measured data related to the activity status of people. Details will be described later, but examples of measurement data related to the activity status of people include electricity usage and bathroom usage. Measurement data related to the activity status of people can be input from, for example, a BEMS (Building Energy Management System), environmental sensors, bathroom sensors, and water supply and drainage sensors.

[0057] The measurement data storage DB 14 related to the human activity state stores the data input to the measurement data input unit 13 related to the human activity state on each floor.

[0058] The floor data identification unit 15 identifies floors for which elevator data can be used and floors for which elevator data cannot be used. Floors for which elevator data cannot be used include floors for which necessary data cannot be collected from elevators due to reasons such as old elevators or different elevator manufacturers.

[0059] The floor entry / exit calculation unit 16 calculates the number of people entering (t) and exiting (t) at a given time (t) based on the elevator data. They can be calculated based on the weight of the car included in the elevator data. That is, the weight of each person is determined in advance, and the number of people entering (t) and exiting (t) can be calculated based on the change in the weight of the car at the stopping floor and the car at the stopping floor that can be detected by the opening and closing of the car door. In this case, on floors close to the lobby floor, the number of people going down the stairs increases. Therefore, when observing the entire day, the relationship between the total number of people entering (∑ number of people entering) and the total number of people exiting (∑ number of people exiting) for one day is generally ∑ number of people entering > ∑ number of people exiting. This difference is the error in the number of people caused by using the stairs instead of the elevator. In this case, in order to accurately calculate the number of people in the room, it is necessary to correct the number of people exiting (t). On the other hand, for example, if the same tenant occupies multiple floors, there may be instances where ∑ number of people entering < ∑ number of people leaving due to the fact that they may travel between floors via stairs. In this case, in order to accurately calculate the number of people in the room, the number of people entering (t) needs to be corrected. Specifically, if the total number of people leaving is less than the total number of people entering, the number of people leaving (t) is corrected; if the total number of people entering is less than the total number of people leaving, the number of people entering (t) is corrected. Details will be described later, but the offline processing unit 20 calculates correction processing data for these corrections. The correction processing data is a correction term or correction coefficient used to correct these corrections.

[0060] The offline processing unit 20 includes a building floor information database (database) 21, a building user inter-floor movement model database (database) 22, a floor user movement model setting unit 23 for each floor, and an elevator usage status index calculation unit 24. Furthermore, the offline processing unit 20 includes a floor-by-floor user entry and exit difference calculation unit 25, a correction-processed data calculation unit 26 for the time-series data of the number of entry / exit passengers on each floor, a floor-by-floor user occupancy time-series data calculation unit 27, and a conversion coefficient calculation unit 28 for converting measured data related to human activity into the number of occupants.

[0061] The building's floor information DB21 stores the building's floor structure and the usage information for each floor. For example, each floor's usage information may include information about whether it is a lobby floor, a cafeteria floor, or a shared floor (resting floor). These floors experience more movement than typical floors. In other words, people tend to move around these floors. For example, it is likely that many people enter the building from the lobby floor in the morning, move to their work floors, and return to the lobby floor in the evening before leaving the building. Furthermore, it is likely that many people move from their work floors to the cafeteria floor and then back to their original floor during the day. The usage information for each floor can be used to determine which floors experience the most movement.

[0062] The building user inter-floor movement model DB 22 stores multiple movement models representing models of human movement between floors. Details will be described later, but in this embodiment, the following models are prepared as movement models: a) a model for using the elevator instead of stairs; b) a model for using the elevator for going up and the stairs for going down; c) a model for using the stairs when the elevator is crowded, but otherwise using the elevator; and d) a model for using the stairs instead of the elevator.

[0063] The floor-by-floor user movement model setting unit 23 changes and sets the proportion of these movement models for each floor. Specifically, the floor-by-floor user movement model setting unit 23 sets a larger proportion of models for people who use stairs instead of elevators, for example, as the floor becomes lower. This is because it is assumed that the lower the floor, the more people will use stairs to reach the lobby level instead of the elevator, or from the lobby level to their destination floor instead of the elevator. Therefore, this setting is tailored to the actual situation.

[0064] The elevator usage state index calculation unit 24 calculates time series data of the number of elevator users per floor and time series data of the average waiting time of elevators per floor as indices indicating the usage state of the elevators. These can be calculated based on the elevator data.

[0065] The floor entry / exit difference calculation unit 25 is an example of a headcount difference calculation unit. This floor entry / exit difference calculation unit 25 calculates the difference between the total number of people entering (∑ number of people entering) and the total number of people exiting (∑ number of people exiting) on ​​each floor of a building based on elevator operation data. The total number is, for example, the total number of people entering and exiting each day. Here, the difference = |∑ number of people entering - ∑ number of people exiting|.

[0066] The correction data calculation unit 26 for the time-series data of the number of people entering or exiting a floor is an example of a correction data calculation unit. This correction data calculation unit 26 calculates correction data for at least one of the number of people entering or exiting a floor within a given time period based on the difference from the total. Specifically, the correction data calculation unit 26 for the time-series data of the number of people entering or exiting a floor distributes the difference calculated by the difference calculation unit 25 between the number of people entering and exiting a floor to each mobility model in the ratio set by the floor user mobility model setting unit 23 for each floor. Furthermore, the correction data calculation unit 26 for the time-series data of the number of people entering or exiting a floor during a given time period (t) calculates correction data for correcting the number of people entering or exiting a floor. The actual processing will be described later.

[0067] The time series data calculation unit 27 for the number of people in a room on a floor calculates the number of people in a room on a given floor at a given time (t) by using the calculation unit 28 for converting the measured data related to human activities into the number of people in a room to obtain data necessary for the conversion coefficient.

[0068] The conversion coefficient calculation unit 28 for converting the measured data related to human activity into the number of people in the room calculates the conversion coefficient for converting the measured data related to human activity into the number of people in the room. For example, if the measured data related to human activity is the power usage (kWh) of OA equipment, the power usage per person (kWh / person) of the OA equipment can be calculated as the conversion coefficient based on the power usage of the OA equipment divided by the number of people in the room.

[0069] The floor for obtaining the number of occupants is preferably a floor for which elevator operation data can be obtained and which is close to a floor for which elevator operation data cannot be collected. In this case, the close condition means that the tenants are of the same type or shape.

[0070] The online processing unit 30 includes a correction processing unit 31 for the number of people entering or leaving a floor, a floor occupancy calculation unit 32, and a floor occupancy calculation unit 33 based on measurement data related to human activity status.

[0071] The floor entry / exit correction unit 31 corrects the floor entry / exit count based on the elevator operation data, calculating the corrected data for the floor entry / exit count. This corrected data is calculated by the correction data calculation unit 26 for the time-series data of the floor entry / exit count. Whether the corrected entry or exit count is corrected is determined by the correction results of the offline processing unit 20. Specifically, if the correction data calculation unit 26 for the time-series data of the floor entry / exit count calculates the corrected data for the total number of entry, the floor entry / exit correction unit 31 uses this corrected data to correct the entry count. Furthermore, if the correction data calculation unit 26 for the time-series data of the floor entry / exit count calculates the corrected data for the total number of exits, the floor entry / exit correction unit 31 uses this corrected data to correct the exit count.

[0072] The floor occupancy calculation unit 32 calculates the number of occupants on each floor for which the elevator data is available, based on the corrected number of people entering and exiting.

[0073] In the floor entry / exit correction processing unit 31, the number of occupants on each floor is obtained, for example, a newly obtained number of occupants, more specifically, the number of occupants at the current time. In this case, the floor entry / exit correction processing unit 31 corrects the number of occupants on each floor at the current time. Furthermore, the floor occupancy calculation unit 32 calculates the number of occupants on each floor at the current time (in real time) based on elevator data.

[0074] The floor occupancy calculation unit 33, based on measurement data related to human activity, calculates the number of occupants on floors where elevator operation data cannot be collected using time-series data of physical quantities related to the number of occupants on the floor. More specifically, the conversion coefficient calculation unit 28, which converts measurement data related to human activity into the number of occupants, determines the relationship between the number of occupants and the physical quantity related to the number of occupants on floors where elevator operation data can be collected. The floor occupancy calculation unit 33, based on measurement data related to human activity, uses this relationship to calculate the number of occupants on floors where elevator operation data cannot be collected. As described above, in this embodiment, measurement data related to human activity is used. Specifically, the floor occupancy calculation unit 33, based on measurement data related to human activity, converts the acquired measurement data related to human activity into the number of occupants using the conversion coefficient calculated by the floor occupancy time-series data calculation unit 27. The acquired measurement data related to human activity is, for example, newly acquired data, more specifically, data at the current time. In this case, the floor occupancy calculation unit 33 based on the measurement data related to the human activity status calculates the number of occupants on each floor at the current time point (real time) based on the measurement data related to human activity on the floors where the elevator operation data cannot be collected.

[0075] The number of people on each floor, calculated by the floor occupancy calculation unit 32 and the floor occupancy calculation unit 33 based on measurement data related to human activity, is output to the building management and operations department. The building management and operations department utilizes the calculated number of people on each floor as data for efficient operation of air conditioning and lighting equipment, cleaning, and security, for example.

[0076] <Description of Operations of Building Management System 1>

[0077] Figure 2 This is a flowchart for explaining an outline of the operation of the building management system 1 according to the present embodiment.

[0078] exist Figure 2 The schematic diagram of the processing by the offline processing unit 20 and the online processing unit 30 is shown in FIG. First, it is determined whether it is time to execute offline processing ( S201 ). For example, the execution time is determined by whether it is a predetermined time (e.g., 23:00) on the day before the processing by the online processing unit 30. Regarding the execution time, for example, a single time can be set for daily processing, or the day and time of processing can be changed to take into account changes in the day of the week or season.

[0079] As a result, if it is the execution time of the offline process (YES in S201 ), the offline processing unit 20 executes the loop process of S202 to S208 as the offline process for each floor of the target building.

[0080] On the other hand, when it is not the execution time of the offline process (No in S201), the process proceeds to S209.

[0081] In the loop process of S202 to S208, first, the offline processing unit 20 sets the target floor (S203).

[0082] Next, the offline processing unit 20 determines whether the elevator operation data can be used for the target floor (S204).

[0083] If the elevator operation data is found to be usable (YES in S204), the offline processing unit 20 calculates correction data for the number of people entering and exiting the elevator operation data (S205). Specifically, the correction data calculation unit 26 calculates correction data for the time-series data of the number of people entering and exiting on each floor, which corrects the number of people exiting on each floor at a given time (t).

[0084] Furthermore, the offline processing unit 20 calculates a conversion coefficient for converting the measured data related to the activity status of people on the floor into the number of people in the room (S206). Specifically, the calculation unit 28 for converting the measured data related to the activity status of people on the floor into the number of people in the room calculates a conversion coefficient for converting the measured data related to the activity status of people in the room into the number of people in the room.

[0085] After S206, the process proceeds to S207. In addition, if the elevator operation data cannot be used in S204 (No in S204), the process proceeds to S207.

[0086] In S207, the offline processing unit 20 determines whether all floors / areas to be managed have been processed.

[0087] As a result, when all floors / areas to be managed have been processed (Yes in S207 ), the loop processing of S202 to S208 is terminated and the process proceeds to S209 .

[0088] On the other hand, when all floors / areas targeted for management have not been processed (No in S207), the process returns to S203 to set other target floors.

[0089] In S209 , it is determined whether it is the day of control.

[0090] If it is the day of control (Yes in S209), the online processing unit 30 executes the loop processing of S210 to S216 for each floor of the target building as the online processing. On the other hand, if it is not the day of control (No in S209), the series of processing ends.

[0091] In the loop processing of S210 to S216, first, the online processing unit 30 sets the target floor (S211).

[0092] Next, the online processing unit 30 determines whether the elevator operation data can be used for the target floor (S212).

[0093] If the elevator operation data is available (YES in S212), the online processing unit 30 calculates the number of people entering, exiting, and occupants based on the elevator operation data (S213). Specifically, the floor-by-floor entrance / exit correction unit 31 corrects the number of people entering and exiting each floor for the number of people for which correction data has been calculated. Furthermore, the floor-by-floor occupancy calculation unit 32 calculates the number of people in the room on each floor based on the corrected number of people entering and exiting.

[0094] In contrast, if elevator operation data is unavailable (No in S212), the online processing unit 30 calculates the number of occupants based on the measurement data related to the activity status of people on each floor (S214). Specifically, the floor occupancy calculation unit 33, based on the measurement data related to the activity status of people, calculates the number of occupants using time-series data of physical quantities related to the number of occupants on each floor.

[0095] After S213 and S214, the process proceeds to S215. In S215, the online processing unit 30 determines whether all floors / areas to be managed have been processed.

[0096] As a result, when all floors / areas to be managed have been processed (Yes in S215 ), the loop processing of S210 to S216 is terminated.

[0097] On the other hand, when all floors / areas to be managed have not been processed (No in S215), the process returns to S211 to set other target floors.

[0098] Figure 3 1 is a flowchart illustrating the processing of the offline processing unit 20 in further detail.

[0099] Here, a state is shown where the offline processing unit 20 performs the loop processing of S301 to S313 on each floor of the target building.

[0100] In this loop process, first, the offline processing unit 20 sets a target floor ( S302 ).

[0101] The following steps S303 to S309 are described in detail. Figure 2 That is, in S303 to S309, the offline processing unit 20 calculates correction processing data of the number of people entering / exiting the elevator operation data.

[0102] The offline processing unit 20 determines whether the elevator operation data can be used for the target floor (S303).

[0103] As a result, if the elevator operation data can be used (YES in S303), the offline processing unit 20 sets the user movement model for the target floor based on the floor position information related to the target floor and the building user inter-floor movement model DB 22 (S304). This is the processing performed by the floor user movement model setting unit 23 for each floor described above.

[0104] Furthermore, the offline processing unit 20 calculates an elevator usage status indicator for the target floor based on the elevator operation data (S305). This is the processing performed by the elevator usage status indicator calculation unit 24 described above. The elevator usage status indicator includes time series data on the number of elevator users per floor and the average waiting time for elevators per floor.

[0105] Next, the offline processing unit 20 acquires the operation data (past) of the elevator for the target floor from the elevator data storage DB 12 ( S306 ).

[0106] Next, the offline processing unit 20 calculates the number of people entering and leaving the target floor (S307). Furthermore, the offline processing unit 20 calculates the difference between the total number of people entering (∑ number of people entering) and the total number of people leaving (∑ number of people leaving) on ​​each floor each day (S308). This is the process performed by the above-mentioned floor entry / exit difference calculation unit 25.

[0107] Furthermore, the offline processing unit 20 calculates correction data for the number of people entering or leaving the floor based on: 1) the user movement model; 2) the elevator usage status indicator; and 3) the difference between the total number of people entering and leaving the floor (S309). This is the processing performed by the correction data calculation unit 26 described above.

[0108] The following steps S310 to S311 are described in detail. Figure 2That is, in S310 to S311, the offline processing unit 20 calculates a conversion coefficient for converting the measurement data related to the activity state of people on the floor into the number of people in the room.

[0109] The offline processing unit 20 calculates the number of people in the room on the target floor based on the measurement data on the activity state of people on the floor ( S310 ).

[0110] Next, the offline processing unit 20 calculates a conversion coefficient for converting the measured data related to the activity status of people on the target floor into the number of people in the room. This calculation is performed using the formula: Conversion coefficient = number of people in the room / measured data value (S311). This processing is performed by the above-mentioned floor occupancy time series data calculation unit 27 and the conversion coefficient calculation unit 28 for converting the measured data related to human activity into the number of people in the room.

[0111] After S311, the process proceeds to S312. In addition, if the elevator operation data cannot be used in S303 (No in S303), the process proceeds to S312.

[0112] In S312, the offline processing unit 20 determines whether all floors / areas to be managed have been processed.

[0113] As a result, when all floors / areas to be managed have been processed (YES in S312 ), the loop processing of S301 to S313 is terminated.

[0114] On the other hand, when all floors / areas to be managed have not been processed (No in S312), the process returns to S302 to set other target floors.

[0115] Figure 4 1 is a flowchart illustrating the processing of the online processing unit 30 in further detail.

[0116] Here, a state is shown where the online processing unit 30 performs the loop processing of S401 to S413 on each floor of the target building.

[0117] In this loop process, first, the online processing unit 30 sets a target floor (S402).

[0118] Next, the online processing unit 30 determines whether the elevator operation data can be used for the target floor (S403).

[0119] As a result, when the elevator operation data can be used (Yes in S403), the online processing unit 30 inputs the elevator operation data for the target floor into the elevator data input unit 11 (S404).

[0120] Furthermore, the online processing unit 30 stores the elevator operation data in the elevator data storage DB 12 (S405).

[0121] Next, the floor entrance / exit number calculation unit 16 calculates the number of people entering and exiting the target floor using the latest operational data of the day ( S406 ).

[0122] Furthermore, the online processing unit 30 corrects the number of people entering or leaving (S407) based on the correction processing data calculated by the offline processing unit 20. This is the processing performed by the correction processing unit 31 for the number of people entering or leaving the floor.

[0123] Then, the online processing unit 30 calculates the number of people in the rooms on the target floor (S408). This is the processing performed by the aforementioned floor occupancy calculation unit 32. After S408, the process proceeds to S412.

[0124] Furthermore, if the elevator operation data cannot be used in S403 (No in S403), the online processing unit 30 inputs the measurement data related to the activity status of people on the target floor to the measurement data input unit 13 related to the activity status of people on the floor (S409).

[0125] Furthermore, the online processing unit 30 stores the measurement data related to the activity state of the person on the target floor in the measurement data storage DB 14 related to the activity state of the person ( S410 ).

[0126] Then, the online processing unit 30 uses a conversion coefficient that converts the measurement data related to the activity status of people on the target floor into the number of people in the room, and calculates the number of people in the room from the measurement data (S411). This is the processing performed by the floor occupancy calculation unit 33 based on the measurement data related to the activity status of people described above.

[0127] Furthermore, the online processing unit 30 determines whether all floors / areas to be managed have been processed ( S412 ).

[0128] As a result, when all floors / areas to be managed have been processed (Yes in S412 ), the loop processing of S401 to S413 is terminated.

[0129] On the other hand, when all floors / areas to be managed have not been processed (No in S412), the process returns to S402 to set other target floors.

[0130] Figure 5 This is a diagram explaining a user's movement model.

[0131] Figure 5 The user movement model is explained using a table that associates the movement model No., the movement model of the building user on each floor, the detection characteristics for the moving user, the detection method for the moving user, and the ratio of the number of people.

[0132] Here, as user movement models, the following are shown: a) a model in which the user uses the elevator instead of the stairs (No. 1); b) a model in which the user uses the elevator for going up and the stairs for going down (No. 2); c) a model in which the user uses the stairs when the elevator is crowded and uses the elevator otherwise (No. 3); and d) a model in which the user uses the stairs instead of the elevator (No. 4).

[0133] In the case of a) the model using the elevator instead of stairs (No. 1), the feature of detecting the moving user is that the user can be detected by the elevator operation data. In addition, the method of detecting the moving user is that the user can be detected by the elevator operation data.

[0134] In the case of model b) where users ascend by elevator and descend by stairs (No. 2), the feature for detecting mobile users is that movement on the stairs cannot be detected in the elevator data, so the difference between the number of people entering and exiting the venue calculated using the elevator operation data is displayed. Furthermore, a method for detecting mobile users is described, in which estimation is made based on the difference between the number of people entering and exiting the venue calculated using the elevator operation data.

[0135] In the case of model c) where the passenger uses the stairs when the elevator is crowded and otherwise uses the elevator (No. 3), the situation is the same as in the case of model b) where the passenger uses the elevator for going up and the stairs for going down (No. 2).

[0136] In the case of model d) using stairs instead of elevators (No. 4), the feature for detecting mobile users is that they cannot be detected in the elevator's operating data. Furthermore, the method for detecting mobile users is based on the assumption that a certain proportion of users, particularly on floors close to the lobby, move between floors.

[0137] The ratios are the percentages at which these mobility models are applied to each floor. Here, the ratios of 70%, 15%, 10%, and 5% are applied to each mobility model. Furthermore, these ratios vary by floor. The proportion of elevator users increases with higher floors, while the proportion of stair users increases with lower floors. This approach accommodates the fact that lower floors tend to use stairs more often than elevators.

[0138] In this embodiment, the difference between the total number of people entering (∑entering people) and the total number of people leaving (∑exiting people) on each floor is distributed according to this ratio for each movement model, thereby correcting the number of people entering and leaving. This allows for a more accurate estimation of the origin of the difference as an error, and more accurate correction data can be calculated.

[0139] Figure 6 It's the decision Figure 5 The processing shown in the flowchart is performed on the scale shown.

[0140] Here, a state is shown where the offline processing unit 20 performs the loop processing of S601 to S611 on each floor of the target building.

[0141] In this loop process, first, the offline processing unit 20 sets a target floor (S602).

[0142] Next, the offline processing unit 20 determines whether the elevator operation data can be used for the target floor (S603).

[0143] If the elevator operation data is found to be usable (Yes in S603), the offline processing unit 2 acquires floor information of the target floor (S604). This information includes, for example, the position information of the target floor and the positional relationship between the target floor and the lobby floor or cafeteria floor.

[0144] Next, the offline processing unit 20 determines whether the difference between the total number of people entering (∑ number of people entering) and the total number of people leaving (∑ number of people leaving) on ​​the target floor is equal to or greater than a given value ( S605 ).

[0145] As a result, when the value is equal to or greater than a given value (Yes in S605 ), the offline processing unit 20 sets a) the ratio of the model that uses the elevator instead of the stairs based on the floor information ( S606 ).

[0146] Furthermore, the offline processing unit 20 sets b) the scale of the model for going up by elevator and going down by stairs based on the floor information ( S607 ).

[0147] Furthermore, the offline processing unit 20 sets the ratio of the model that uses the stairs when the elevator is crowded and otherwise uses the elevator based on the floor information (c) (S608).

[0148] Furthermore, the offline processing unit 20 sets d) the scale of the model that uses stairs instead of the elevator based on the floor information ( S609 ).

[0149] After S609, the process proceeds to S610. In addition, if the elevator operation data cannot be used in S603 (No in S603), the process proceeds to S610.

[0150] In S610 , the offline processing unit 20 determines whether all floors / areas to be managed have been processed.

[0151] As a result, when all floors / areas to be managed have been processed (Yes in S610 ), the loop processing of S601 to S611 is terminated.

[0152] On the other hand, when all floors / areas to be managed have not been processed (No in S610), the process returns to S602 to set other target floors.

[0153] Figure 7 This is a flowchart for explaining a process in which the offline processing unit 20 calculates the difference between the total number of people entering (∑ number of people entering) and the total number of people leaving (∑ number of people leaving) on ​​each floor every day.

[0154] This further details Figure 3 Processing of S306 to S308.

[0155] First, past elevator operation data is input to the offline processing unit 20 (S701).

[0156] Next, the offline processing unit 20 calculates time series data of the number of people entering and exiting each floor based on past elevator operation data ( S702 ).

[0157] Furthermore, the offline processing unit 20 calculates the total value of the number of people entering (per day) and the total value of the number of people leaving (per day) for each floor ( S703 ).

[0158] The offline processing unit 20 then calculates the difference between the total number of people entering the venue (per day) and the total number of people leaving the venue (per day) for each floor. Furthermore, the offline processing unit 20 stores, for each day, whichever is greater, the total number of people entering or leaving the venue, and the calculated difference.

[0159] Figure 8 This is a flowchart for explaining a process in which the offline processing unit 20 calculates an index of the use state of the elevator for a target floor based on the operation data of the elevator.

[0160] This further details Figure 3 The processing of S305.

[0161] First, past elevator operation data is input to the offline processing unit 20 (S801).

[0162] Next, the offline processing unit 20 calculates the number of elevator users and the average waiting time for each floor, each time, and each direction (ascending direction, descending direction) based on past elevator operation data (S802).

[0163] Furthermore, the offline processing unit 20 outputs the result calculated in S802 to the correction processing data calculation unit 26 for the time series data of the number of people entering / exiting the floor ( S803 ).

[0164] Figure 9 This is a flowchart for explaining the process of obtaining correction processing data for correcting the number of people leaving a floor by the offline processing unit 20.

[0165] This further details Figure 3 The processing of S309. Figure 9 In the following, a case where a correction term is obtained as correction processing data is described.

[0166] Here, a state is shown where the offline processing unit 20 performs the loop processing of S901 to S909 on each floor of the target building.

[0167] In this loop process, first, the offline processing unit 20 sets a target floor (S902).

[0168] Next, the offline processing unit 20 determines whether the elevator operation data can be used for the target floor (S903).

[0169] As a result, if the elevator operation data can be used (Yes in S903), the offline processing unit 20 inputs information indicating which of the total number of people entering and the total number of people leaving the target floor is larger (S904).

[0170] Next, the offline processing unit 20 calculates a correction term for the model b) using the elevator for going up and the stairs for going down (S905). Specifically, the correction term is calculated by assigning the difference value to the smaller time series data of the total number of people entering and the total number of people leaving, based on the above ratio. For example, if the total number of people leaving is smaller, the correction term (t) for the number of people leaving at time (t) in the model is calculated using the number of people leaving before correction (t) at time (t), the total number of people leaving, and the ratio, using the following mathematical formula (1):

[0171] Correction term for the number of people leaving (t)

[0172] =(Difference × (number of exits before correction (t) / total number of exits)) × ratio…(1)

[0173] Next, the offline processing unit 20 calculates a correction term for the model (S906) for the case where the elevator is used in addition to the stairs when the elevator is crowded. Specifically, the correction term (t) for the number of people exiting at time (t) in this model is calculated using the total number of people using the elevator at time (t) and the ratio of the number of people using the elevator at time (t) using the following mathematical formula (1).

[0174] Correction term for the number of people leaving (t)

[0175] =(Difference × (Number of elevator users (t) / Total number of elevator users)) × Ratio…(2)

[0176] Furthermore, the offline processing unit 20 calculates a correction term for the model (d) in which stairs are used instead of elevators (S907). Specifically, as shown in the following mathematical formulas (3) and (4), the number of people entering (t) and exiting (t) before correction are used, and these are multiplied by a ratio to calculate the correction term (t) for the number of people entering (t) and the correction term (t) for the number of people exiting (t) at time (t) in the model.

[0177] Correction term for the number of people attending (t) = number of people attending before correction (t) × proportion… (3)

[0178] Correction term for the number of people leaving (t) = number of people leaving before correction (t) × proportion… (4)

[0179] After S907, the process proceeds to S908. In addition, if the elevator operation data cannot be used in S903 (No in S903), the process also proceeds to S908.

[0180] In S908, the offline processing unit 20 determines whether all floors / areas to be managed have been processed.

[0181] As a result, when all floors / areas to be managed have been processed (Yes in S908 ), the loop processing of S901 to S909 is terminated.

[0182] On the other hand, when all floors / areas to be managed have not been processed (No in S908), the process returns to S902 to set other target floors.

[0183] Figure 10 Is used as correction processing data Figure 9 In this way, the calculation methods of the case where the correction term is obtained and the case where the correction coefficient is obtained are compared for each movement model.

[0184] For the model a) using an elevator instead of stairs (No. 1), there is no correction term or correction coefficient.

[0185] In the model (No. 2) where the vehicle goes up by elevator and down by stairs, the correction term can be calculated using the above-mentioned equation (1). Furthermore, the correction coefficient at time (t) of this model is obtained using the following equation (5).

[0186] Correction coefficient for the number of exits (t) = (difference / total number of exits) × ratio…(5)

[0187] In the model (No. 3) where the elevator is used in addition to the stairs when the elevator is crowded, the correction term can be calculated using the above-mentioned equation (2). In addition, the correction coefficient at time (t) of this model is obtained using the following equation (6).

[0188] Correction coefficient for number of people leaving (t) = (difference / total number of people using the elevator) × ratio…(6)

[0189] In the model (No. 4) where stairs are used instead of elevators, the correction term is calculated using the above-mentioned equations (3) and (4). Furthermore, the correction coefficient at time (t) in this model is calculated using the following equations (7) and (8).

[0190] Correction coefficient for number of attendees (t) = ratio…(7)

[0191] Correction coefficient for number of exits (t) = ratio…(8)

[0192] The correction processing data used in the online processing unit 30 to correct the number of people entering and exiting is the sum of the correction processing data calculated for each movement model (hereinafter sometimes referred to as "model correction processing data"). When the correction term is used as the correction processing data, the correction term (t) for the number of people exiting is the correction term (t) for the number of people exiting in equation (1) + the correction term (t) for the number of people exiting in equation (2) + the correction term (t) for the number of people exiting in equation (4). Furthermore, when the correction coefficient is used as the correction processing data, the correction coefficient (t) for the number of people exiting is the correction coefficient (t) for the number of people exiting in equation (5) + the correction coefficient (t) for the number of people exiting in equation (6) + the correction coefficient (t) for the number of people exiting in equation (8).

[0193] It can also be said that the offline processing unit 20 sets a plurality of movement models, calculates model correction processing data as correction processing data for each movement model, and obtains correction processing data based on the model correction processing data.

[0194] Alternatively, it can be said that the offline processing unit 20 determines the ratio of applying a plurality of movement models, distributes the differences according to the determined ratio, calculates model correction processing data based on the distributed differences, and sets the sum of the calculated model correction processing data as correction processing data.

[0195] Figure 11 (a) to (b) are graphs showing time series data of the number of people entering, leaving, and in-room before correction. Here, the horizontal axis represents time, and the vertical axis represents the number of people.

[0196] This is time series data showing the changes in the number of people entering, leaving, and in the number of people in the room every hour between 0:00 and 24:00 of a day.

[0197] in, Figure 11 (a) is a graph showing time series data of the number of people entering and leaving a certain floor before correction. Figure 11 (b) shows the Figure 11 A graph showing the number of people in a room calculated based on the time series data in (a).

[0198] In this case, the number of people in the room should be zero during the late-night hours. However, since the total number of people entering (∑entering) > the total number of people leaving (∑exiting), the number of people in the room does not reach zero even during the late-night hours. The difference between the total number of people entering and the total number of people leaving is counted as the number of people in the room. Furthermore, on floors with night shifts, the number of people in the room may not necessarily reach zero even during the late-night hours. In this case, this difference is corrected to account for the number of people on the night shift and applied to the above-mentioned mobility model.

[0199] Figure 12 (a) to (c) are graphs showing the correction term for the number of people leaving, the number of people entering after correction, the number of people leaving, and the time series data of the number of people in the room. Here, the horizontal axis represents time, and the vertical axis represents the number of people.

[0200] This is time series data showing the changes in the correction factor for the number of people leaving the venue, the number of people entering the venue, the number of people leaving the venue, and the number of people in the room every hour between 0:00 and 24:00 of the day.

[0201] in, Figure 12 (a) shows the distribution of the number of people leaving the venue. Figure 11 Here, the correction term for the model b) using the elevator for going up and the stairs for going down is shown. Here, the correction term is generated for 12:00 and 18:00. That is, Figure 12(a) shows the correction term (t) generated for the number of people leaving the venue when the time (t) is 12:00 and 18:00.

[0202] Figure 12 (b) is a graph showing the time series data of the number of people entering and leaving when the number of people leaving is corrected by the correction term. Figure 11 Compared with the case (a), the number of people leaving at 12:00 and 18:00 increases through this correction. Figure 12 (b) shows the correction of the number of people leaving the venue when the time (t) is 12:00 and 18:00.

[0203] Figure 12 (c) shows the Figure 12 (b) shows the number of people in the room calculated based on the corrected number of people entering and leaving the room. In this case, it shows that during the late night time, Figure 11 The difference shown in (b) is corrected and disappears, and the number of people in the room becomes 0.

[0204] Figure 13 This is a diagram showing an example of measurement data related to a person's activity state.

[0205] Here, for the measurement data related to the activity state of a person shown in No. 1 to No. 7, the relationship between the unit of the measurement data and the number of people in the room is shown in the figure.

[0206] Examples of measurement data related to human activity include: power usage data for outlets connected to individual OA equipment on the target floor ("OA outlet" power usage data) (No. 1); bathroom usage data on the target floor (such as bathroom water usage and the number of times each bathroom room is used) (No. 2); entry and exit data for the entry and exit management system on the target floor (No. 3); CO2 concentration measurement data on the target floor (No. 4); water usage data for water and sewage systems on the target floor (No. 5); noise measurement data on the target floor (No. 6); and waste volume measurement data on the target floor (No. 7). Since these data increase with the number of people in the room, there is a correlation between these measurement data and the number of people in the room. Therefore, the number of people in the room can be calculated based on these measurement data.

[0207] The online processing unit 30 can also use the more accurate method of calculating the number of occupants using calibration data or the method of calculating the number of occupants based on measurement data related to human activity. For example, if the method of calculating the number of occupants by calculating calibration data based on elevator operation data results in a significant error, the method of calculating the number of occupants based on measurement data related to human activity can be used.

[0208] Figure 14 This is a flowchart illustrating this situation.

[0209] Here, a state is shown where the online processing unit 30 performs the loop processing of S1401 to S1408 on each floor of the target building.

[0210] In this loop process, first, the online processing unit 30 sets a target floor (S1402).

[0211] Next, the online processing unit 30 determines whether the elevator operation data can be used for the target floor (S1403).

[0212] As a result, if the elevator operation data can be used (Yes in S1403), it is determined whether the difference between the total number of people entering (per day) and the total number of people leaving (per day) for the target floor is greater than a given value (S1404).

[0213] If the difference is greater than the given value (YES in S1404), the online processing unit 30 determines that the calculation of the number of people in the room based on the elevator operation data has a large error and calculates the number of people in the room using the measurement data related to the activity status of people on the target floor (S1405). The process then proceeds to S1407.

[0214] If the difference is smaller than the given value (No in S1404 ), the process proceeds to S1406 .

[0215] On the other hand, if the elevator operation data cannot be used in S1403 (No in S1403), execute Figure 4 The calculation process of the number of people in the room using the elevator operation data described in the flowchart (S1406) is then performed.

[0216] In S1407, the online processing unit 30 determines whether all floors / areas to be managed have been processed.

[0217] As a result, when all floors / areas to be managed have been processed (Yes in S1407 ), the loop processing of S1401 to S1408 is terminated.

[0218] On the other hand, when all floors / areas to be managed have not been processed (No in S1407), the process returns to S1402 to set other target floors.

[0219] <Explanation of the effect>

[0220] According to the building management system 1 described in detail above, the offline processing unit 20 calculates, based on past elevator operation data, the difference between, for example, the total number of daily entrances (∑entrances) and the total number of daily exits (∑exit). Furthermore, the offline processing unit 20 uses this difference to calculate correction data for correcting any errors in at least one of the number of entrances and exits. The correction data includes the aforementioned correction terms and correction coefficients used to correct the parameters for the number of entrances and exits on a floor at a given time (t). This allows for more accurate correction data to be calculated. Furthermore, the offline processing unit 20 sets multiple movement models as models of human movement between floors, calculates model correction data for each movement model, and calculates correction data based on the model correction data. In this case, more accurate correction data can be calculated by using movement models that match actual human movement and applying them at an appropriate scale.

[0221] The online processing unit 30 then uses this corrected data to, for example, calculate the number of people in a room in real time. In this case, correction is performed not on the number of people in the room, but on the number of people entering and leaving the room. This allows for highly accurate correction of errors in the number of people entering and leaving a floor, and for highly accurate calculation of the number of people in the room on that floor.

[0222] Furthermore, the number of people moving between floors and their movement patterns vary by weekday. For example, in buildings such as office buildings, the number of people entering and leaving the building on weekdays and weekends often differs significantly. Therefore, to calculate the number of people in a room by the online processing unit 30, it is preferable to use past elevator operation data from the same week as input by the offline processing unit 20. Similarly, past elevator operation data can be selected to take into account seasonal fluctuations such as holidays, Golden Week, and the year-end holiday.

[0223] <Explanation of the method for measuring the number of people in a room>

[0224] The processing performed by the building management system 1 is achieved through the cooperation of software and hardware resources.

[0225] Therefore, the processing performed by the above-mentioned building management system 1 can be understood as the following method for measuring the number of people in a room: a processor executes a program recorded in a memory, and based on the operation data of the elevator, the difference between the total number of people entering and the total number of people leaving the building on each floor is calculated; based on the difference with the total, correction processing data for correcting at least one of the number of people entering and the number of people leaving the floor within a given time is calculated; based on the operation data of the elevator, the number of people entering and leaving the floor for which the correction processing data is calculated is corrected, thereby calculating the number of people in the room on the floor.

[0226] In addition, the program running in the building management system 1 can be understood as a program for causing a computer to implement the following functions: a function of calculating the difference between the total number of people entering and the total number of people leaving the building on a floor based on the operation data of the elevator, and calculating correction processing data for correcting at least one of the number of people entering and the number of people leaving the floor within a given time based on the difference from the total; and a function of calculating the number of people in the room on a floor by correcting the number of people entering and leaving the floor for which the correction processing data is calculated based on the operation data of the elevator.

[0227] Furthermore, the program for realizing the present embodiment can of course be provided via communication means, or can be provided by being stored in a recording medium such as a CD-ROM.

[0228] While the present embodiment has been described above, the technical scope of the present invention is not limited to the scope described in the above embodiment. Various modifications or improvements to the above embodiment are included in the technical scope of the present invention, as is clear from the description of the claims.

Claims

1. A system for measuring the number of people in a room, characterized in that: have: The number difference calculation unit calculates the difference between the total number of people entering and the total number of people leaving the building on a floor based on the elevator operation data. a correction processing data calculation unit that obtains correction processing data for correcting at least one of the number of people entering and the number of people leaving a floor within a given time period based on a difference from the total; and The occupancy calculation unit calculates the number of occupants on the floor by correcting the number of people entering and exiting the floor for which the correction data is calculated, based on the elevator operation data.

2. The system for measuring the number of people in a room according to claim 1, wherein: The correction processing data calculation unit sets a plurality of movement models as models of human movement between floors, calculates model correction processing data as correction processing data for each of the movement models, and obtains the correction processing data based on the model correction processing data.

3. The system for measuring the number of people in a room according to claim 2, wherein: The correction processing data calculation unit determines a ratio for applying the plurality of movement models, distributes the differences according to the determined ratio, calculates the model correction processing data based on the distributed differences, and sets a sum of the calculated model correction processing data as the correction processing data.

4. The system for measuring the number of people in a room according to claim 3, wherein: The correction processing data calculation unit changes the ratio for each floor.

5. The system for measuring the number of people in a room according to claim 4, wherein: The correction processing data calculation unit uses the following models as the movement models when calculating the correction processing data for correcting the total number of people exiting: a model in which people use the elevator instead of the stairs; a model in which people use the elevator for going up and the stairs for going down; a model in which people use the stairs when the elevator is crowded and the elevator otherwise; and a model in which people use the stairs instead of the elevator. Apply the scale of these mobile models per floor change.

6. The system for measuring the number of people in a room according to claim 5, wherein: The correction processing data calculation unit increases the ratio of the model in which stairs are used rather than elevators, as the floors are lower.

7. The system for measuring the number of people in a room according to claim 1, wherein: The correction processing data calculation unit calculates correction processing data for correcting the number of people leaving when the total number of people leaving is less than the total number of people entering, and calculates correction processing data for correcting the number of people entering when the total number of people entering is less than the total number of people leaving.

8. The system for measuring the number of people in a room according to claim 1, wherein: The occupancy calculation unit calculates the number of occupants in a floor where elevator operation data cannot be collected, using time-series data of a physical quantity related to the number of occupants in the floor.

9. The system for measuring the number of people in a room according to claim 8, wherein: The correction processing data calculation unit obtains the relationship between the number of people in a room and a physical quantity related to the number of people in the room on a floor where the operation data of the elevator can be collected. The occupant count calculation unit calculates the number of occupants on a floor where elevator operation data cannot be collected using this relationship.

10. The system for measuring the number of people in a room according to claim 8, wherein: The occupant count calculation unit adopts a method that is more accurate between a method of calculating the number of occupants using the calibration data and a method of calculating the number of occupants based on the physical quantity.

11. A method for measuring the number of people in a room, characterized in that: The processor executes the program recorded in the memory, Based on the elevator operation data, the difference between the total number of people entering and the total number of people leaving the building is calculated. Based on the difference from the total, correction processing data for correcting at least one of the number of people entering and the number of people leaving the floor within a given time period is obtained, The number of people entering and exiting a floor for which the correction data is calculated is corrected based on the elevator operation data, thereby calculating the number of people in the floor.

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