Facility management device and facility management method

Abstract

To more accurately estimate the number of people in each area of ​​the facility. [Solution] The facility management device includes a first acquisition unit that acquires power data of outlet-using devices, which are electronic devices that use outlets in the facility area; a second acquisition unit that acquires equipment operation status data indicating the operating status of equipment in the area; an unoccupied state time estimation unit that estimates the time the target area is unoccupied based on the equipment operation status data; an occupancy-dependent component output unit that outputs a power component of the power data of outlet-using devices that depends on the number of people in the room based on the time the area is unoccupied; and an occupancy index output unit that calculates an occupancy index related to the number of people in the target area from the power component that depends on the number of people in the room.

Description

Technical Field

[0001] The present invention relates to a facility management device and a facility management method, and is particularly suitable for application to a facility management device related to a technology for estimating the number of people present in an area or floor (hereinafter referred to as "floor or the like") of a facility.

Background Art

[0002] Buildings are characterized in that the activity states of users vary greatly on each floor or the like. Specifically, the number of people present on each floor or the like varies greatly over time. Especially after the COVID-19 pandemic, due to the establishment of various office forms and work styles, the diversification of office forms and the like has further expanded. Examples of such office forms include ABW (Activity-Based Working) type offices, shared offices, or satellite offices.

[0003] As technologies for estimating the number of people present on a floor, there are technologies described in Patent Document 1 and Patent Document 2. In the technology described in Patent Document 1, it is utilized that the power consumption of outlets per predetermined time is in a proportional relationship with the number of people present in the same time period, and the power consumption of outlets is used instead of the number of people present. In the technology described in Patent Document 2, the number of residents is estimated from the number of electrical devices whose power supplies are turned on, but the number of residents is estimated from the number of electrical devices being used.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Patent Document 2

Summary of the Invention

Problems to be Solved by the Invention

[0005] However, the technology described in Patent Document 1 may not accurately determine the number of people in each room on each floor, etc., based solely on the power consumption of electrical outlets. On the other hand, the technology described in Patent Document 2 may not accurately estimate the number of residents based solely on the number of electrical appliances being used.

[0006] This invention was made in consideration of the above points, and aims to propose a facility management device and facility management method that can more accurately estimate the number of people in a facility area. [Means for solving the problem]

[0007] To solve these problems, the present invention includes: a first acquisition unit that acquires power data of outlet-using devices, which are electronic devices that use outlets in the area of ​​a facility; a second acquisition unit that acquires equipment operation status data indicating the operating status of equipment in the area; an unoccupied state time estimation unit that estimates the time the target area is unoccupied based on the equipment operation status data; an occupancy-dependent component output unit that outputs a power component of the power data of the outlet-using devices that depends on the number of people in the room based on the time the area is unoccupied; and an occupancy index output unit that calculates an occupancy index relating to the number of people in the target area from the power component that depends on the number of people in the room.

[0008] Furthermore, in the present invention, the first acquisition unit has a first acquisition step of acquiring power data of outlet-using devices, which are electronic devices that use outlets in the area of ​​the facility; the second acquisition unit has a second acquisition step of acquiring equipment operation status data that indicates the operating status of the equipment in the area; the unoccupied state time estimation unit has an unoccupied state time estimation step of estimating the unoccupied state time of the target area based on the equipment operation status data; the occupant-dependent component output unit has an occupant-dependent component output step of outputting a power component of the power data of the outlet-using devices that depends on the number of occupants based on the unoccupied state time; and the occupant-index output unit has an occupant-index output step of calculating an occupant-index related to the number of occupants in the target area from the power component that depends on the number of occupants. [Effects of the Invention]

[0009] According to the present invention, the number of people in a facility area can be estimated more accurately. [Brief explanation of the drawing]

[0010] [Figure 1] This is a system configuration diagram showing an example of the hardware configuration of a building management system equipped with a facility management device according to the first embodiment. [Figure 2] This is a system configuration diagram showing a functional configuration example of a building management system including a facility management device according to the first embodiment. [Figure 3] Figure 1 is a flowchart illustrating an example of the procedure for estimating the number of occupants as an example of a facility management method for the facility management device shown. [Figure 4A] Figure 3 shows an example of the basic concept of estimating the number of people in the room in step S6. [Figure 4B] Figure 3 shows an example of the basic concept of estimating the number of people in the room in step S6. [Figure 4C] Figure 3 shows an example of the basic concept of estimating the number of people in the room in step S6. [Figure 5]It is a diagram showing an example of the characteristics regarding the power data of a lighting device. [Figure 6] It is a diagram showing an example of the characteristics regarding the power data of an outlet-connected device. [Figure 7] It is a diagram showing an example of the power data to be collected. [Figure 8] It is a diagram showing an example of the power data to be collected. [Figure 9] It is a diagram showing an example of information for estimating an unoccupied state of a floor or the like and its estimation method or the like. [Figure 10] It is a flowchart showing an example of the procedure of the unoccupied state time estimation process shown in FIG. 3. [Figure 11] It is a diagram showing an example of the result of the clustering process regarding the power data of a lighting device. [Figure 12] It is a diagram showing an example of the result of the clustering process regarding the power data of a lighting device. [Figure 13] It is a flowchart showing an example of the procedure of the average value calculation process step S4 by time on weekdays shown in FIG. 2. [Figure 14A] It is a diagram showing an example of the result of the average value calculation process shown in FIG. 13. [Figure 14B] It is a diagram showing an example of the result of the average value calculation process shown in FIG. 13. [Figure 15] It is a flowchart showing an example of the procedure of the power component calculation process. [Figure 16] It is a flowchart showing an example of the procedure of the power component calculation process shown in FIG. 3. [Figure 17A] It is a diagram showing an example of the result of the power component calculation process shown in FIG. 16. [Figure 17B] It is a diagram showing an example of the result of the power component calculation process shown in FIG. 16. [Figure 17C] It is a diagram showing an example of the result of the power component calculation process shown in FIG. 16. [Figure 18] It is a flowchart showing an example of the procedure of the in-room number index calculation process shown in FIG. 3. [Figure 19] It is a diagram showing an example of the in-room index data. [Figure 20] Figure 2 shows an example of the data managed in the conversion coefficient database. [Figure 21] This is a system configuration diagram showing a functional configuration example of a building management system including a facility management device according to the second embodiment. [Figure 22] This is a system configuration diagram showing a functional configuration example of a building management system including a facility management device according to the third embodiment. [Figure 23A] This figure shows an example of the average daily power consumption of electrical devices using electrical outlets on a weekday, averaged over multiple days. [Figure 23B] This figure shows an example of the average daily power consumption of electrical devices using electrical outlets on a holiday, averaged over multiple days. [Figure 23C] Figure 23A shows an example of the power component that depends on the number of people in a room, obtained by subtracting the constantly used power component from the power consumption of devices using electrical outlets on a typical weekday. [Modes for carrying out the invention]

[0011] An embodiment of the present invention will be described in detail below with reference to the drawings. (1) First Embodiment Figure 1 is a system configuration diagram showing an example of the hardware configuration of a building management system 100 equipped with a facility management device 1 according to the first embodiment. Note that the arrows in the figure show an example of the flow of data and commands, and are not limited to the example shown.

[0012] This embodiment provides a method for estimating the number of occupants (an index) from power data (particularly outlet power data). By removing the power components of continuously used equipment from the power data, the power components dependent on the number of occupants are extracted to estimate the number of occupants. Here, in order to estimate the power components of continuously used equipment, it is necessary to identify the time when the room is unoccupied. To estimate the time when the room is unoccupied, clustering is performed on power data from lighting equipment, access control data, etc., to identify unoccupied periods. As a result, the power components of continuously used equipment can be calculated, the power components dependent on the number of occupants can be calculated to obtain an occupancy index, and further, a specific number of occupants can be calculated using a conversion coefficient.

[0013] In this embodiment, by understanding the time-dependent changes in the number of people in each floor or area (hereinafter also collectively referred to as "floor, etc."), it is possible to understand not only daily changes but also the time-dependent changes in the average number of people in the room or staying there (hereinafter collectively referred to as "number of people in the room") on a weekly, monthly, quarterly, or yearly basis.

[0014] In this embodiment, an occupancy index is estimated as an indicator related to the number of people in each area (or section) or floor of a building. Based on this estimated occupancy index, equipment such as air conditioning and lighting in the target area can be appropriately controlled based on the number of people in the area, and the cleaning and security schedules for the floor or area can be appropriately managed. Each area may be a part of a floor, or it may span multiple floors of a building.

[0015] Figure 2 is a system configuration diagram showing a functional configuration example of a building management system 100 including a facility management device 1 according to the first embodiment. The building management system 100 comprises a facility management device 1, a building energy management system 2, outlet power supply equipment 3, lighting equipment 4, access control system 5, sensor equipment 6, air conditioning equipment 7, and elevator equipment 8. A building has, for example, multiple floors. Each floor has an area that is part of it. Therefore, one floor may contain multiple areas. The arrows in the figure indicate the direction of data and commands. The illustrated example is merely conceptual and may not be an exact representation.

[0016] The building energy management system 2 is connected to the facility management device 1, the power outlet equipment 3, the lighting equipment 4, the access control system 5, the sensor device 6, the air conditioning equipment 7, and the elevator equipment 8 via a network (not shown). The arrows shown in the diagram illustrate an example of the flow of data and commands, and are not limited to the examples shown.

[0017] The outlet power supply equipment 3 is installed, for example, on each floor or in each area. The outlet power supply equipment 3 is a power supply equipment that includes outlets that supply power to electronic devices such as computers used by users working on the floor or in the area. The outlet power supply equipment 3 outputs power data regarding the devices used by users who utilize the outlet power supply equipment 3 to the building energy management system 2. Therefore, the outlet power supply equipment 3 provides power data regarding the devices used by users who utilize the outlet power supply equipment 3 to the facility management device 1 via the building energy management system 2.

[0018] Lighting equipment 4 is, for example, lighting equipment installed on the ceiling of each floor or area. Lighting equipment 4 is, for example, equipment that illuminates the floor or area from above. Lighting equipment 4 outputs power data and operational data related to the lighting equipment to the building energy management system 2. Therefore, lighting equipment 4 outputs power data and operational data related to the lighting equipment via the building energy management system 2.

[0019] The access control system 5 is, for example, a system for recording the time of entry and exit when a user enters or leaves each floor or area.

[0020] Sensor device 6 is, for example, a sensor that measures illuminance, CO2 concentration, etc., on each floor or in each area.

[0021] Air conditioning equipment 7 is, for example, air conditioning equipment installed on each floor or in each area. Air conditioning equipment 7 is set to operate, for example, from the start time on weekdays until the end time. Elevator equipment 8 refers to elevator equipment that moves between floors, stopping at each floor.

[0022] On the other hand, the facility management device 1 includes a first acquisition unit 10, a second acquisition unit 20, an unoccupied state time estimation unit 30, an occupancy-dependent component output unit 40, an occupancy index output unit 50, an average value calculation unit 60, a constantly used equipment power component calculation unit 70, a conversion coefficient database 80, and a calendar information database 90.

[0023] The first acquisition unit 10 has the function of acquiring power data from electronic devices that use electrical outlets in the facility area. The power data referred to here is not limited to information indicating the amount of electricity.

[0024] The second acquisition unit 20 has the function of acquiring equipment operating status data that shows the operating status of equipment such as lighting fixtures in the area. This equipment operating status data also includes power data. In order to identify the time when the area is unoccupied, the second acquisition unit 20 acquires data from one or a combination of the following: power data from lighting fixtures, operating status data from lighting fixtures, entry and exit information data from access control devices, operating status data from water supply equipment, operating status data from toilet equipment, illuminance measurement data from illuminance sensors, noise measurement data from noise sensors, and CO2 concentration measurement data from CO2 (carbon dioxide) concentration sensors. This data is then separated into groups of unoccupied states and other groups through clustering (grouping).

[0025] The unmanned state time estimation unit 30 has the function of estimating the unmanned state time of the target area based on the equipment operating status data described above.

[0026] The occupancy-dependent component output unit 40 has the function of calculating and outputting a power component that depends on the number of people in the room from the power data of the devices using the outlets, based on the specified unoccupied time. The occupancy-dependent component output unit 40 can, for example, employ two types of calculation methods based on the unoccupied time. In the first calculation method, the occupancy-dependent component output unit 40 calculates the power component of the devices that are always in use and calculates the occupancy-dependent component based on this. In the second calculation method, the occupancy-dependent component output unit 40 calculates the occupancy-dependent component so as to correct the value of the power data of the devices using the outlets during the unoccupied time to zero.

[0027] The occupancy index output unit 50 has the function of calculating an occupancy index for the number of people in the target area from the power component which depends on the number of people in the room.

[0028] The average value calculation unit 60 has the function of calculating, for example, the average value for each time of day on weekdays, based on the power data acquired by the first acquisition unit 10.

[0029] The power component calculation unit 70 for continuously used equipment has the function of calculating the power component of equipment that is continuously used on a floor or in an area.

[0030] The conversion coefficient database 80 is a database referenced when converting power data, such as electricity consumption, with the number of people in an area.

[0031] The calendar information database 90 manages information related to calendars (hereinafter referred to as "calendar information"), such as information related to weekdays, weekends, and holidays.

[0032] The occupancy index output unit 50 described above outputs a command to control at least one of the facilities and equipment (e.g., air conditioning, lighting, cleaning robot) on the floor or area based on the occupancy index.

[0033] The occupancy index output unit 50 outputs commands to manage the time required for at least one of the area's cleaning and security activities, based on the occupancy index. The occupancy index output unit 50 may also output the occupancy index itself to a display device. This enables facility managers to manage the facility according to the number of occupants.

[0034] The unoccupied state time estimation unit 30 estimates the unoccupied state time by grouping power data or equipment operating status data of lighting equipment 4 as an example of equipment.

[0035] The unoccupied state time estimation unit 30 estimates the unoccupied state time based on the entry and exit data for the area collected from the entry and exit control device, from the time of the last person to leave until the time of the first person to enter the next day.

[0036] The unoccupied state time estimation unit 30 groups (clusters) at least one time series data from a floor or area, such as access control information data from an access control device, operating status data from water supply equipment, operating status data from toilet equipment, illuminance measurement data from an illuminance sensor, noise measurement data from a noise sensor, and CO2 concentration measurement data from a CO2 concentration sensor, and estimates the unoccupied state time based on the time series data belonging to the unoccupied state group, which is an example of the group with the lowest value.

[0037] However, when power data is from devices using electrical outlets, disadvantages include, for example, large fluctuations in power consumption depending on the device, and a tendency for errors to occur due to the small size and fluctuations of the power consumption values. As a result, it can be difficult to determine the duration of unoccupied periods using only outlet power data. Therefore, as in the embodiment described above, clustering is performed on power data from lighting equipment or access control data to identify unoccupied periods, making it possible to determine the duration of unoccupied periods more accurately.

[0038] The unoccupied state time estimation unit 30 estimates that the system is unoccupied during holiday hours if the calendar information corresponds to a holiday, based on calendar information (e.g., date attribute information) that corresponds to the date of the power data of the equipment using the outlet. This identification method uses date information, for example, and does not use time-series data of operating status.

[0039] The unoccupied state time estimation unit 30 estimates that a specific time period is unoccupied if that time period, based on the time information of the power data of the equipment using the outlet, falls within that specific time period. This determination method, for example, does not use time-series data of the equipment's operating status, but rather utilizes time information.

[0040] Here, we will explain an example of controlling equipment and devices on a floor, etc., using the unoccupied state information or unoccupied state time information from the unoccupied state time estimation unit 30. For example, 24-hour operating copiers, office automation equipment, and sensors will switch to standby mode if they are not used for a predetermined period of time (e.g., 5 minutes). Such equipment monitors for operation by energizing sensors, microcontrollers, logic circuits, etc., so that they can be activated immediately when a button is pressed. However, if it is determined that the room is unoccupied, these devices can also be put into standby mode. Specifically, the unoccupied state time estimation unit 30 transmits signals of unoccupied state information or unoccupied state time information to these devices, including, for example, the occupancy index output unit 50.

[0041] The occupancy index output unit 50 outputs, for example, an order to control at least one of the area's facilities and equipment, or an order to manage the time spent performing at least one of the area's cleaning and security, based on information about the unoccupied state or information about the duration of the unoccupied state.

[0042] This allows for further energy savings by minimizing power consumption during the standby state of equipment. Given the large number of devices and the long operating hours, especially considering nighttime and holiday periods, the aforementioned power reductions are expected to result in overall energy savings for the entire building.

[0043] Furthermore, by using the unoccupied state information or unoccupied state time information from the unoccupied state time estimation unit 30 to activate the cleaning robot for the target floor, etc., it can be operated without affecting the walking or working environment of users on the floor, etc. This cleaning robot may also be a patrol-type cleaning robot within the building. This allows the robot to be operated in common areas such as corridors and restrooms on the floor, etc., without affecting users on the floor, etc.

[0044] Furthermore, by using the unmanned state time estimation unit 30's information on unmanned states or the time of unmanned states to instruct patrolling security robots within the building to patrol the unmanned floors or areas, crimes targeting unmanned periods can be suppressed, thereby strengthening security.

[0045] Furthermore, by using the unoccupied state information or unoccupied state time information from the unoccupied state time estimation unit 30 to send information to the elevator control device and elevator group management device indicating that there is no possibility of the elevator stopping for landing calls or other reasons on the target floor, the elevator's operational efficiency can be improved. For example, since there is no need to keep the elevator waiting on an unoccupied floor, the elevator can be made to wait only on the remaining occupied floors, thereby reducing waiting times and improving operational efficiency. Information that the floor is unoccupied or that waiting is unnecessary may also be sent to the elevator control device and elevator group management device.

[0046] As described above, by using the unmanned state information or unmanned state time information from the unmanned state time estimation unit 30 to control equipment and facilities on floors and areas, as well as patrolling robots and elevators within the building, efficient control utilizing unmanned state information becomes possible.

[0047] The occupancy-dependent component output unit 40 calculates the power component consumed by continuously operating equipment during unoccupied periods based on the unoccupied periods, and subtracts the power component consumed by continuously operating equipment from the power data of the equipment using the outlets to calculate a component that depends on the number of people in the floor or area.

[0048] The occupancy-dependent component output unit 40 calculates and outputs the power component consumed by continuously operating equipment based on the average power data of equipment using outlets during the unoccupied period.

[0049] The occupancy-dependent component output unit 40 corrects the value of the power component that depends on the number of people in the room during the unoccupied period to zero.

[0050] The occupancy index output unit 50 described above sets the occupancy index as a value obtained by multiplying the power component, which depends on the number of occupants, by a conversion coefficient set to a value based on the average amount of power used per person for devices using the outlets. The occupancy index output unit 50 sets the occupancy index as a value obtained by multiplying the power component, which depends on the number of occupants, by a conversion coefficient set to the reciprocal of the average power usage value per person for devices using the outlets.

[0051] Figure 3 is a flowchart showing an example of the procedure for estimating the number of occupants as an example of a facility management method for the facility management device 1 shown in Figure 1. First, an overview of the facility management method will be explained. The facility management method includes: a first acquisition step in which a first acquisition unit 10 acquires power data of outlet-using devices, which are electronic devices that use outlets in the facility area; a second acquisition step in which a second acquisition unit 20 acquires equipment operation status data that indicates the operating status of equipment in the area; an unoccupied state time estimation step in which an unoccupied state time estimation unit 30 estimates the unoccupied state time of the target area based on the equipment operation status data; an occupant-dependent component output step in which an occupant-dependent component output unit 40 calculates and outputs the power component of the power data of outlet-using devices that depends on the number of occupants based on the unoccupied state time; and an occupant-count index output step in which an occupant-count index output unit 50 calculates an occupant-count index related to the number of occupants in the target area from the power component that depends on the number of occupants.

[0052] In step S1, data collection takes place. In this embodiment, two main types of data are collected. First, the first acquisition unit 10 acquires power data from devices using outlets on each floor of the building. Meanwhile, the second acquisition unit 20 acquires operating status data from equipment such as lighting fixtures 4. These power data and operating status data are, for example, time-series data for each hour.

[0053] In step S1, the access control system 5 collects access control data representing the time when a user enters or leaves a floor, etc., and provides it to the facility management device 1 via the building energy management system 2. In step S1, the sensor device 6 measures the illuminance of the floor, etc., using an illuminance sensor (not shown), and provides this illuminance sensor data to the facility management device 1 via the building energy management system 2.

[0054] In step S1, the sensor device 6 measures noise on the floor, etc., using a noise sensor (not shown), and provides this noise sensor data to the facility management device 1 via the building energy management system 2. In step S1, the sensor device 6 may also measure the condition of the floor, etc., using other sensors (not shown), and provide this condition sensor data to the facility management device 1 via the building energy management system 2. The second acquisition unit 20 collects equipment operation status data indicating the operating status of equipment such as lighting fixtures 4 in the area. In addition, the second acquisition unit 20 may also collect equipment operation status data indicating the operating status of other equipment as described above.

[0055] In step S2, the unoccupied state time estimation unit 30 first identifies the unoccupied state. Specifically, the unoccupied state time estimation unit 30 applies, for example, a clustering method to group each target floor, etc., into groups of unoccupied states and groups of occupied states. The unoccupied state time estimation unit 30 acquires time information for the unoccupied state.

[0056] In step S2, the unmanned state time estimation unit 30 clusters the operating status data of the lighting equipment and divides it into groups of unmanned states and other groups, i.e., groups of occupied states, identifies the unmanned groups, and estimates the time information for the unmanned groups.

[0057] In step S3, the continuously used equipment power component calculation unit 70 calculates the average value of the power data of the devices using the outlets in the unoccupied state based on the time information for the unoccupied group, and calculates the power component of the continuously used equipment in the power data of the devices using the outlets.

[0058] In step S4, the average value calculation unit 60 calculates the power component dependent on the number of people in the room. The average value calculation unit 60 extracts power data for devices using outlets from the calendar information database 90, based on the calendar information, for weekdays, and calculates an average value for each time period, for example, an average value for each time period over multiple days.

[0059] In step S5, the occupancy-dependent component output unit 40 subtracts the constantly used power component from the calculated average weekday time-specific data to calculate and output the power component that depends on the number of occupants in the power data of the devices using the outlets. Furthermore, the occupancy-dependent component output unit 40 performs a correction process to adjust the value of the power component that depends on the number of occupants to, for example, zero for the unoccupied time specified as described above.

[0060] In step S6, the occupancy-dependent component output unit 40 calculates the occupancy index. The occupancy-dependent component output unit 40 calculates the occupancy index based on the power component that depends on the number of people in the room. Specifically, the occupancy-dependent component output unit 40 subtracts the constantly used power component from the calculated average power data for each hour on weekdays to calculate and output the power component that depends on the number of people in the room in the power data of the devices using the outlets. Furthermore, the occupancy-dependent component output unit 40 performs a process to correct the value of the power component that depends on the number of people in the room to zero for the specified unoccupied period.

[0061] In step S6, the occupancy-dependent component output unit 40 estimates the number of occupants. The occupancy-dependent component output unit 40 uses the reciprocal of the average amount of power used per person at the electrical outlet as a conversion coefficient, and calculates the occupancy index by calculating: Occupancy = Occupancy-dependent power component × Conversion coefficient. The basic concepts of the conversion coefficient and the estimation of the number of occupants will be described later.

[0062] In step S7, the occupancy-dependent component output unit 40 outputs the calculated occupancy index to the building energy management system 2.

[0063] In step S8, the building energy management system 2 controls the air conditioning equipment, lighting equipment, and elevators within the building management system. Based on the occupancy index data for each floor / area, the building energy management system 2 controls the air conditioning equipment, lighting equipment, elevators, and other equipment according to the time-dependent changes in the occupancy index for each floor, etc.

[0064] Figures 4A to 4C are diagrams illustrating examples of the basic concepts of estimating the number of occupants in step S6 shown in Figure 3. Figure 4A shows an example of the state before removing the constantly used power component for power consumption as a power component dependent on the number of occupants, Figure 4B shows an example of the state after excluding the constantly used power component, and Figure 4C shows an example where the power component dependent on the number of occupants is taken as input information and plotted on the horizontal axis.

[0065] The power component dependent on the number of occupants, shown in Figure 4A, changes upwards from the constant power component 40B in the power consumption amount, which is shown on the vertical axis as a power component dependent on the number of occupants, to the right. The constant power component 40B corresponds to the value of the constant power component 40C.

[0066] When the occupancy-dependent component output unit 40 removes the value of the constantly used power component 40C from the power component that depends on the number of occupants shown in Figure 4A, the power component that depends on the number of occupants is transformed so that it rises from the origin to the upper right on the power consumption shown on the vertical axis, as shown in Figure 4B.

[0067] Furthermore, the occupancy-dependent component output unit 40 can estimate a specific number of occupants 40F for a given number of occupants, based on the characteristics of a preset number of occupants, as shown by the arrows in Figure 4C, regarding the amount of electricity used as an occupancy-dependent power component shown in Figure 4B.

[0068] Here, we will explain an example of the characteristics of power data for building facilities. When power data is power data from devices using outlets, advantages include, for example, a strong correlation with the number of occupants and the ability to measure on a floor-by-floor basis. Disadvantages include, for example, large fluctuations in power consumption depending on the device and a high likelihood of errors due to the small fluctuations in power consumption values. The disadvantages can be avoided by combining the data with an occupancy index based on lighting power consumption data or by averaging the data over multiple days.

[0069] Figure 5 shows an example of the characteristics of the power data of lighting equipment 4. Figure 6 shows an example of the characteristics of the power data of equipment using an electrical outlet. In Figures 5 and 6, the left side shows an example of the distribution of power consumption on floors etc. by the number of people in the room, and the right side shows an example of the distribution of uniform power consumption on floors etc. without considering the number of people in the room.

[0070] In the distribution example shown on the left side of Figure 5, the power data for occupied rooms (group G1) and the power data for unoccupied rooms (group G2) are distributed in a way that allows them to be distinguished according to the distribution of the number of people in the room. The power data for unoccupied rooms (group G2) includes, for example, the power of lighting equipment 4 such as a night light, and is characterized by small fluctuations in power consumption.

[0071] In the distribution example shown on the right side of Figure 5, the power consumption data for occupied rooms (group G1) and the power consumption data for unoccupied rooms (group G2) are distributed separately in terms of power consumption on the vertical axis, even without considering the distribution of the number of people in the room, and are therefore distinguishable from each other.

[0072] In the distribution example shown on the left side of Figure 6, the power data for occupied rooms (group G1) and the power data for unoccupied rooms (group G2) are distributed in a way that allows them to be distinguished according to the distribution of the number of people in the room. The power data for unoccupied rooms (group G2) includes, for example, the power of continuously operating equipment and is characterized by large fluctuations in power consumption.

[0073] In the distribution example shown on the right side of Figure 6, the power consumption data for occupied rooms (group G1) and the power consumption data for unoccupied rooms (group G2) are partially mixed together in the power consumption data on the vertical axis, even without considering the distribution of the number of people in the room. As a result, they are distributed in a way that makes it difficult to clearly distinguish between them.

[0074] Figure 7 shows an example of the collected power data. This power data manages the date, time, floor, and power data collected by the building energy management system 2. Note that this electronic data may also manage areas instead of floors, or in conjunction with floors.

[0075] The power data collected by the building energy management system 2 includes, for example, outlet power consumption [kWh] as an example of power data for devices using outlets, lighting power consumption [kWh] as an example of operational data for lighting equipment, and air conditioning power consumption [kWh] as an example of operational data for air conditioning.

[0076] Figure 8 shows an example of the collected power data. This power data manages the date, time, floor, and power data collected by the building energy management system 2. Note that this electronic data may also manage areas instead of floors, or in conjunction with floors.

[0077] The power data collected by the building energy management system 2 includes, for example, the number of lighting fixtures in operation, access control information for each floor from the access control system 5, the operating status of water supply facilities, the operating status of toilet facilities, and the illuminance measurement value [lx (lux)] from the illuminance sensor.

[0078] Figure 9 shows an example of information used to estimate whether a floor or other area is unoccupied, a method for estimating an unoccupied state, and points to note. The information used to estimate the unoccupied state of a floor or other area includes classifications and items. In the example shown, classifications based on time characteristics and classifications based on power data characteristics are managed.

[0079] Figure 10 is a flowchart showing an example of the procedure for estimating the unoccupied state time shown in Figure 3. In the unoccupied state time estimation process, the unoccupied state time estimation unit 30 estimates the unoccupied time for each floor, etc. The details will be explained below.

[0080] In step S21, the unoccupied time estimation unit 30 performs clustering based on the input values ​​for power consumption or operating status of lighting equipment 4 on each floor, etc. The unoccupied time estimation unit 30 uses clustering methods such as clustering into two or more groups or the k-means method.

[0081] In step S22, the unattended state time estimation unit 30 selects a group of unattended states according to the results of the clustering process. For example, the unattended state time estimation unit 30 selects the group in which at least one of the power value and operating status values ​​is smallest as the unattended state group.

[0082] In step S23, the unattended state time estimation unit 30 estimates the unattended state time based on the group of unattended states.

[0083] In this embodiment, the unmanned state time estimation unit 30 groups the data as follows. If the number of clusters, i.e., the number of groups to be formed, is 2 as a result of the clustering process shown in Figure 10, the unmanned state time estimation unit 30 groups the data into unmanned state and manned state. If the number of clusters is 3, the unmanned state time estimation unit 30 groups the data into group G2 for unmanned state, group G3 for manned state or transient state to unmanned state, and group G1 for steady state of manned state.

[0084] Figures 11 and 12 show examples of clustering results for power data of lighting equipment 4. Figure 11 shows an example where there are 2 clusters. Figure 12 shows an example where there are 3 clusters.

[0085] The illustrated example shows an example of hourly electricity consumption [kWh] on weekdays. This is calculated by the average value calculation unit 60. The average value calculation unit 60 extracts weekday information from the calendar information database 90 and calculates the hourly average of the power data of outlet-connected devices for weekdays.

[0086] The unmanned state time estimation unit 30 determines in Figure 11 that 0:00 to 6:00 is group G2 (unmanned state), 6:00 to 21:00 is group G1 (manned state), and 21:00 to 24:00 is group G2 (unmanned state).

[0087] The unmanned state time estimation unit 30 determines in Figure 12 that 0:00 to 6:00 is group G2 of the unmanned state, 6:00 to 8:00 is group G3 of the transitional state to the manned state, 8:00 to 19:00 is group G1 of the manned state, 19:00 to 21:00 is group G1 of the transitional state to the unmanned state, and 21:00 to 24:00 is group G2 of the unmanned state.

[0088] Figure 13 is a flowchart showing an example of the procedure for step S4 of the process for calculating the average value by time of day on weekdays, as shown in Figure 2. The average value calculation process is performed by the average value calculation unit 60.

[0089] In step S41, the average value calculation unit 60 extracts weekday information from the calendar information. Here, weekday information refers to information about days from Monday to Friday that are not holidays. In step S42, the average value calculation unit 60 obtains power data for outlet-using equipment on each floor, etc., from the building energy management system 2, and also obtains the above weekday information. In step S42, the average value calculation unit 60 extracts power data for outlet-using equipment on weekdays.

[0090] In step S43, the average value calculation unit 60 calculates the time-based average of power data for devices using outlets on weekdays. The average value calculation unit 60 calculates the average value for multiple days, time-based.

[0091] In Figure 13, the average value calculation unit 60 performs an averaging process on the power data (energy consumption) of the devices using the outlet, and calculates, for example, the following average values. Example of the amount of electricity used by an electrical outlet on a typical weekday. • Example of average daily electricity consumption from electrical outlets over multiple days. Here, the average value calculation unit 60 may perform the averaging process by excluding days when the amount of power consumed by devices using the outlets during unoccupied periods is higher than on other days. This allows the average value calculation unit 60 to perform averaging that excludes, for example, cases where devices using the outlets were in operation during unoccupied periods, thereby enabling more accurate averaging.

[0092] Figures 14A and 14B show an example of the results of the average value calculation process shown in Figure 13. This average value calculation process calculates the power components related to equipment that is always in use.

[0093] Figure 14A shows an example of the results of extracting power data from devices using outlets during periods when the room is unoccupied. Figure 14B shows an example of the results of calculating the overall average value of power data from devices using outlets during periods when the room is unoccupied.

[0094] Figure 15 is a flowchart showing an example of the procedure for calculating power components. In the power component calculation process, the power component calculation unit 70 for continuously used equipment calculates power components that depend on the number of people in the room.

[0095] In step S51, the continuously used equipment power component calculation unit 70 acquires power data related to equipment using outlets on each floor, etc. The power data is time-series data. In step S51, the continuously used equipment power component calculation unit 70 acquires power data for each floor, etc., when it is unoccupied.

[0096] In step S51, the continuously used equipment power component calculation unit 70 extracts power data related to the equipment using the outlets for the time the room is unoccupied. In step S52, the continuously used equipment power component calculation unit 70 calculates the total average value of the power data of the equipment using the outlets for the time the room is unoccupied.

[0097] The power component calculation unit 70 for continuously used equipment calculates the total average value for the target power data as follows: • Subtract the power consumption component of continuously used equipment from the average value for each time of day on weekdays, and calculate the power consumption component that depends on the number of people in the room. - Correct the time value for unoccupied periods to zero.

[0098] Figure 16 is a flowchart showing an example of the procedure for calculating power components as shown in Figure 3. In the power component calculation process, the occupancy-dependent component output unit 40 calculates and outputs power components that depend on the number of occupants in the room.

[0099] In step S51, the occupancy-dependent component output unit 40 acquires data on unoccupied time information for each floor, etc., and extracts the time information for unoccupied times on weekdays for each floor, etc.

[0100] In step S52, the occupancy-dependent component output unit 40 obtains the average power data for devices using the outlets at different times on weekdays, and the power value component data for devices that are always in use, and calculates the power value component that depends on the number of people in the room for the devices using the outlets. The occupancy-dependent component output unit 40 calculates the average power data for different times on weekdays minus the power value component for devices that are always in use (data value for each time).

[0101] In step S53, the occupancy-dependent component output unit 40 corrects the time of unoccupied state for the power value component that depends on the number of occupants, which was calculated above. The occupancy-dependent component output unit 40 corrects the value of the time of unoccupied state to zero and obtains power value component data that depends on the number of occupants. This is the power value component for each floor, etc., at each time.

[0102] Figures 17A to 17C show examples of the results of the power component calculation process shown in Figure 16. In this power component calculation process, the occupancy-dependent component output unit 40 corrects the power component for the time when the room is unoccupied, and calculates the occupancy index by multiplying the power component that depends on the number of occupants by a conversion coefficient.

[0103] Figure 17A shows an example of power data for devices using outlets that depend on the number of people in the room, Figure 17B shows an example of the amount of power of lighting equipment 4 as a power component that depends on the number of people in the room, and Figure 17C shows an example of a power component that depends on the number of people in the room, reflecting the time MZ when the room is unoccupied.

[0104] In Figure 17A, for example, the power consumption of devices using the outlets changes from time to time between 7:00 and 23:00, and for example, the power consumption of devices used continuously varies from time to time between 0:00 and 7:00 and between 23:00 and 24:00. The occupancy-dependent component output unit 40 considers these time periods between 0:00 and 7:00 and between 23:00 and 24:00 as unoccupied periods and corrects the power consumption [kWh] of the lighting equipment 4 to zero, as shown in Figure 17B.

[0105] The occupancy-dependent component output unit 40 also considers the power consumption of devices using outlets shown in Figure 17A as well, treating the time periods 0:00-7:00 and 23:00-24:00 as unoccupied time MZ, as shown in Figure 17C, and corrects the power consumption [kWh] of devices using outlets to zero during unoccupied time, as shown in Figure 17B.

[0106] Figure 18 is a flowchart showing an example of the procedure for calculating the occupancy index shown in Figure 3. The occupancy index calculation process is performed by the occupancy index output unit 50.

[0107] In step S61, the occupancy index output unit 50 obtains a power value component that depends on the number of occupants and a conversion coefficient for calculating the occupancy index. In step S62, the occupancy index output unit 50 obtains the occupancy index by calculating, for example, the power value component that depends on the number of occupants multiplied by the conversion coefficient, and outputs the occupancy index data. This occupancy index data is, for example, time-based data for each floor.

[0108] Figure 19 shows an example of occupancy index data. The example of occupancy index data includes each floor, time, and occupancy index [people]. For example, on the 5th floor, there are 0 people occupying at 6:00, 3 people occupying at 7:00, 24 people occupying at 8:00, and 132 people occupying at 9:00.

[0109] Figure 20 shows an example of the data managed in the conversion coefficient database 80 shown in Figure 2. The conversion coefficient database 80 manages floor type, tenant attributes as an example of floor / area, average power consumption per person [W / person] for devices using outlets, and conversion coefficient [person / W]. The conversion coefficient is the reciprocal of the average power consumption per person for devices using outlets.

[0110] According to the above embodiment, the number of people in a facility area can be estimated more accurately.

[0111] (2) Second embodiment The building management system equipped with the facility management device according to the second embodiment has substantially the same configuration and operation as the building management system 100 equipped with the facility management device 1 according to the first embodiment. Therefore, the explanation of the similar configuration and operation will be omitted, and the following explanation will focus on the differences.

[0112] Figure 21 is a system configuration diagram showing a functional configuration example of a building management system including the facility management device 1A according to the second embodiment. The arrows in the figure show an example of the flow of data and commands and are not limited to the example shown. In the facility management device 1A according to the second embodiment, a power component calculation unit 70 for continuously used equipment, an average value calculation unit 60, and an occupancy-dependent component output unit 40 are provided on the outlet-using equipment side and the equipment side, respectively.

[0113] In the second embodiment, the method for calculating the occupancy index utilizes not only power data from devices using electrical outlets, as in the first embodiment, but also power data from equipment such as lighting fixtures 4. That is, in the second embodiment, the method for calculating the occupancy index is divided into equipment side, such as lighting fixtures 4, and outlet-using device side, and the power components dependent on the number of occupants on each floor are calculated separately. The outlet-using device side is the same as in the first embodiment, so the explanation is omitted below.

[0114] On the equipment side, the continuously used equipment power component calculation unit 70 calculates the continuously used power component based on the power data for lighting equipment 4 on each floor etc. from the second acquisition unit 20 and the unoccupied state time estimation unit 30. This continuously used power component corresponds to the continuously used power component 40B described above. The method for identifying the unoccupied state in the second embodiment is the same as in the first embodiment.

[0115] The occupancy-dependent component output unit 40, in addition to the calculation method of the first embodiment, also considers the constantly used power component and outputs the power component dependent on the number of occupants to the occupancy index output unit 50. The occupancy index output unit 50 calculates the occupancy index for the target floor, etc., based not only on the power component dependent on the number of occupants on the outlet-using equipment side, as in the first embodiment, but also on the power component dependent on the number of occupants on the equipment side as described above.

[0116] In other words, the facility management device 1A according to the second embodiment includes, in addition to the configuration of the facility management device 1 according to the first embodiment, another occupancy-dependent component output unit 40 that calculates and outputs a power component of the equipment's power data that depends on the number of occupants, based on the unoccupied time specified as in the first embodiment. The occupancy index output unit 50 calculates an occupancy index from the power components that depend on the number of occupants, calculated by the occupancy-dependent component output unit 40 in the first embodiment and the other occupancy-dependent component output unit 40.

[0117] According to the embodiments described above, in addition to the effects of the first embodiment, the power component dependent on the number of occupants calculated by the other occupant-dependent component output unit 40 is also utilized, making it possible to calculate the occupant index more accurately.

[0118] (3) Third Embodiment The building management system equipped with the facility management device according to the third embodiment has substantially the same configuration and operation as the building management system 100 equipped with the facility management device 1 according to the first embodiment. Therefore, the explanation of the similar configuration and operation will be omitted, and the following explanation will focus on the differences.

[0119] Figure 22 is a system configuration diagram showing a functional configuration example of a building management system including the facility management device 1B according to the third embodiment. The arrows shown in the figure illustrate an example of the flow of data and commands, and are not limited to the example shown.

[0120] In the first embodiment, a second acquisition unit 20 was provided, but in the third embodiment, instead, an unmanned state management database 99 is provided. In the unmanned state management database 99, information regarding the time when each floor, etc., can be identified as being unmanned (hereinafter referred to as "unmanned state time information") is managed in advance.

[0121] In the first embodiment, the unoccupied state time estimation unit 30 acquires power data related to equipment such as lighting fixtures 4 on each floor from the second acquisition unit 20 and estimates the unoccupied state time based on the power data related to the equipment. In contrast, in the third embodiment, the unoccupied state time estimation unit 30 acquires unoccupied state time information from the unoccupied state management database 99 and estimates the unoccupied state time based on the unoccupied state time information.

[0122] Figure 23A shows an example of the average daily power consumption of devices using electrical outlets on weekdays, averaged over multiple days. Figure 23B shows an example of the average daily power consumption of devices using electrical outlets on weekends, averaged over multiple days.

[0123] Figure 23C shows an example of the power consumption component, which depends on the number of people in the room, obtained by subtracting the constantly used power consumption component shown in Figure 23B from the power consumption of devices using outlets on a weekday per day, as shown in Figure 23A. This constantly used power consumption component corresponds to the power consumption of devices using outlets on a holiday per day, as shown in Figure 23B. In Figures 23A to 23C, the vertical axis represents power consumption, and the horizontal axis represents time.

[0124] The power consumption of devices using electrical outlets per day on holidays, as shown in Figure 23B, represents the power consumption during holidays. Therefore, the occupancy index output unit 50 described above considers the power consumption of devices using electrical outlets per day on holidays to be the power consumption during the unoccupied period on the target floor, etc.

[0125] The occupancy index output unit 50 calculates and outputs the power component that depends on the number of occupants, as shown in Figure 23C, by subtracting the constantly used power component, which is the power component that is always in use, as shown in Figure 23B, from the amount of power used by devices using outlets on a weekday per day, as shown in Figure 23A.

[0126] According to this embodiment, even without power data for each floor, the amount of power consumed during unoccupied periods on each floor can be determined, and the same effects as in the first embodiment can be achieved.

[0127] The facility management device 1 according to the above embodiment includes: a first acquisition unit 10 that acquires power data of outlet-using devices, which are electronic devices that use outlets in the facility area; a second acquisition unit 20 that acquires equipment operation status data indicating the operating status of equipment on the floor or in the area; an unoccupied state time estimation unit 30 that estimates the time the target area is unoccupied based on the equipment operation status data; an occupancy-dependent component output unit 40 that calculates and outputs the power component of the power data of outlet-using devices that depends on the number of people in the room based on the time the area is unoccupied; and an occupancy index output unit 50 that calculates an occupancy index related to the number of people in the target area from the power component that depends on the number of people in the room.

[0128] The facility management method according to the above embodiment includes: a first acquisition step in which a first acquisition unit 10 acquires power data of outlet-using devices, which are electronic devices that use outlets in the facility area; a second acquisition step in which a second acquisition unit 20 acquires equipment operation status data indicating the operating status of equipment in the area; an unoccupied state time estimation step in which an unoccupied state time estimation unit 30 estimates the unoccupied state time of the target area based on the equipment operation status data; an occupancy-dependent component calculation step in which an occupancy-dependent component output unit 40 calculates and outputs the power component of the power data of outlet-using devices that depends on the number of occupants based on the unoccupied state time; and an occupancy-level index calculation step in which an occupancy-level index output unit 50 calculates an occupancy-level index related to the number of occupants in the target area from the power component that depends on the number of occupants.

[0129] In this way, even without using the elevator's operating status, it is possible to more accurately estimate the number of people in each area of ​​the facility based on the time-dependent changes in the number of people in each floor.

[0130] In this embodiment, the occupancy index output unit 50 outputs a command to control at least one of the facilities and equipment (e.g., air conditioning, lighting, cleaning robot) of a floor or area based on the occupancy index. In this way, the number of occupants on each floor can be estimated based on the time trend of the number of occupants on each floor, and facilities and equipment such as lighting on each floor can be controlled according to the number of occupants on each floor. At the same time, waste can be reduced and efficiency can be improved. Such control may also be used for elevator operation control, cleaning, security operation, etc.

[0131] In this embodiment, the occupancy index output unit 50 outputs a command to manage the time required for at least one of area cleaning and security based on the occupancy index. In this way, non-control devices such as elevator operation control, cleaning, and security will operate appropriately according to the number of occupants on each floor in response to the command.

[0132] In this embodiment, the unoccupied state time estimation unit 30 transmits a signal indicating unoccupied state information or unoccupied state time information. The occupancy index output unit 50 outputs, for example, a command to control at least one of the area's equipment and devices, or a command to manage the implementation time of at least one of the area's cleaning and security, based on the unoccupied state information or unoccupied state time information. In this way, further energy savings can be achieved by keeping the standby state of the equipment in a state that uses the minimum necessary power. Given the large number of devices and the long duration when considering nighttime and holidays as a whole, the above power reduction can be expected to have an energy-saving effect on the entire building.

[0133] In this embodiment, the unoccupied time estimation unit 30 estimates the unoccupied time by grouping power data or equipment operating status data of lighting equipment 4, which is an example of equipment. By estimating the unoccupied time in this grouped manner, the number of people in the area can be estimated more accurately.

[0134] In this embodiment, the unoccupied time estimation unit 30 groups (clusters) at least one time-series data from a floor or area, such as entry / exit information data from an access control device, operating status data from water supply equipment, operating status data from toilet equipment, illuminance measurement data from an illuminance sensor, noise measurement data from a noise sensor, and CO2 concentration measurement data from a CO2 concentration sensor, and estimates the unoccupied time based on the time-series data belonging to the unoccupied state group, which is an example of the group with the lowest value. By estimating the unoccupied time in this way, the number of people in an area of ​​the facility can be estimated more accurately.

[0135] In this embodiment, the unoccupied time estimation unit 30 estimates the unoccupied time based on entry and exit data for the area collected from the entry and exit management device, from the time of the last person to leave until the time of the first person to enter the next day. This method allows for a simpler and more accurate estimation of the number of people in a facility area by using entry and exit data.

[0136] In this embodiment, the unoccupied state time estimation unit 30 determines that the facility is unoccupied during holiday hours based on calendar information (e.g., date attribute information) corresponding to the date of power data of devices using outlets, if the calendar information indicates a holiday. This method does not use time-series data of operating status, but uses date information. By identifying unoccupied states in this way, the number of people in the facility area can be estimated more accurately.

[0137] In this embodiment, the unoccupied state time estimation unit 30 identifies a specific time period as unoccupied when a predetermined time period based on the time information of the power data of the devices using the outlets falls within that specific time period. Note that this method does not use time-series data of operating status, but uses time information. By identifying unoccupied states in this way, the number of people in the facility area can be estimated more accurately.

[0138] In this embodiment, the occupancy-dependent component output unit 40 outputs the power component consumed by continuously operating equipment during unoccupied periods based on the unoccupied period, and subtracts the power component consumed by continuously operating equipment from the power data of the equipment using the outlets to output a component that depends on the number of occupants in the floor or area. Because the component that depends on the number of occupants in the floor or area is calculated in this way, the number of occupants in the facility area can be estimated more accurately.

[0139] In this embodiment, the occupancy-dependent component output unit 40 calculates and outputs the power component consumed by continuously operating equipment based on the average power data of equipment using outlets during the unoccupied period. This allows for a more accurate estimation of the number of occupants in the facility area by calculating the power component consumed by continuously operating equipment.

[0140] In this embodiment, the occupancy-dependent component output unit 40 corrects the value of the power component that depends on the number of occupants during the unoccupied period to zero. By making this correction, the number of occupants in the facility area can be estimated more accurately.

[0141] In this embodiment, the occupancy index output unit 50 sets the occupancy index as a value obtained by multiplying the power component, which depends on the number of occupants, by a conversion coefficient set to a value based on the average amount of power used per person for devices using outlets. By using such an occupancy index, the number of occupants in the area can be estimated more accurately.

[0142] In this embodiment, the occupancy index output unit 50 sets the occupancy index as a value obtained by multiplying the power component, which depends on the number of occupants, by a conversion coefficient set to the reciprocal of the average power consumption per person for devices using outlets. By using such an occupancy index, the number of occupants in the facility area can be estimated more accurately.

[0143] In other words, the facility management device 1A according to the second embodiment includes, in addition to the configuration of the facility management device 1 according to the first embodiment, another occupancy-dependent component output unit 40 that calculates and outputs a power component of the equipment's power data that depends on the number of occupants, based on the unoccupied time specified as in the first embodiment. The occupancy index output unit 50 calculates an occupancy index from the power component that depends on the number of occupants, calculated by the occupancy-dependent component output unit 40 and the other occupancy-dependent component output unit 40. In this way, since the power component that depends on the number of occupants calculated by the other occupancy-dependent component output unit 40 is also utilized, the occupancy index can be calculated more accurately.

[0144] It should be noted that the present invention is not limited to the embodiments described above, but includes various modifications and equivalent configurations within the spirit of the attached claims. For example, the embodiments described above are described in detail for the purpose of clearly illustrating the present invention, and the present invention is not necessarily limited to having all the configurations described. Also, each element described in parallel in this embodiment may be configured such that at least one of the elements is connected in series with respect to the other elements. [Industrial applicability]

[0145] This invention can be applied to a facility management device that estimates the number of people in a room, such as a floor of a building. [Explanation of symbols]

[0146] 100... Building management system, 1, 1A, 1B... Facility management system

Claims

1. A first acquisition unit acquires power data of electronic devices that use electrical outlets within the facility area, and A second acquisition unit acquires equipment operating status data indicating the operating status of the equipment in the aforementioned area, An unmanned state time estimation unit estimates the amount of time the target area is unmanned based on the aforementioned equipment operating status data, An occupancy-dependent component output unit outputs a power component from the power data of the devices using the outlet that depends on the number of people in the room, based on the time the room is unoccupied. An occupancy index output unit calculates an occupancy index for the number of people in the target area from the power component which depends on the number of people in the room, A facility management device characterized by being equipped with the following features.

2. The aforementioned occupancy index output unit is: Based on the aforementioned occupancy index, a command is output to control at least one of the facilities and equipment in the area. The facility management device according to feature 1.

3. The aforementioned occupancy index output unit is: Based on the aforementioned occupancy index, an order is issued to manage the time required for at least one of the cleaning and security activities in the area. The facility management device according to feature 1.

4. The aforementioned occupancy index output unit is: Based on the aforementioned unmanned period, the system outputs commands to control at least one of the facilities and equipment in the area, or commands to manage the time spent on at least one of the cleaning and security activities in the area. The facility management device according to claim 2 or 3.

5. The aforementioned unattended state time estimation unit is: The power data or operating status data of the equipment is grouped together to estimate the time of the unattended state. The facility management device according to feature 1.

6. The aforementioned unattended state time estimation unit is: The time of the unoccupied state is estimated based on the time series data belonging to the group with the lowest value, which includes at least one time series data from the access control system's access information data, the water supply equipment's operating status data, the toilet equipment's operating status data, the illuminance measurement data from the illuminance sensor, the noise measurement data from the noise sensor, and the CO2 concentration measurement data from the CO2 concentration sensor. The facility management device according to feature 4.

7. The aforementioned unattended state time estimation unit is: Based on the entry and exit data for the area collected from the access control system, the time period from the departure time of the last person to the entry time of the first person entering the next day is estimated to be the time the area is unoccupied. The facility management device according to feature 1.

8. The aforementioned unattended state time estimation unit is: Based on the calendar information corresponding to the date of the power data of the device using the outlet, if the calendar information indicates a holiday, the system identifies that the holiday period is unoccupied. The facility management device according to feature 1.

9. The aforementioned unattended state time estimation unit is: If a predetermined time period based on the time information of the power data of the aforementioned outlet-using device is a specific time period, then the specific time period is identified as the unoccupied state. The facility management device according to feature 1.

10. The aforementioned room occupancy-dependent component output unit is: Based on the aforementioned unoccupied time, the power component consumed by continuously operating equipment during the unoccupied time is output, and by subtracting the power component consumed by the continuously operating equipment from the power data of the equipment using the outlets, a component dependent on the number of people in the floor or area is output. The facility management device according to feature 1.

11. The aforementioned room occupancy-dependent component output unit is: Based on the aforementioned unoccupied period, the power component consumed by the continuously operating equipment is output from the average power data of the devices using the outlets during the unoccupied period. The facility management device according to feature 10.

12. The aforementioned room occupancy-dependent component output unit is: The power component value, which depends on the number of people in the room during the unoccupied period, is corrected to zero. The facility management device according to feature 11.

13. The aforementioned occupancy index output unit is: The occupancy index is set by multiplying the power component, which depends on the number of occupants, by a conversion coefficient that is set to a value based on the average amount of power used per person for the devices using the outlets. The facility management device according to feature 1.

14. The aforementioned occupancy index output unit is: The occupancy index is set by multiplying the power component, which depends on the number of occupants, by a conversion coefficient set to the reciprocal of the average power consumption per person for the devices using the outlets. The facility management device according to feature 12.

15. The facility includes another occupancy-dependent component output unit that outputs a power component of the power data of the facility that depends on the number of people in the room, based on the time the room is unoccupied. The aforementioned occupancy index output unit is: The occupancy index is output from the power components dependent on the number of occupants, which are output by the occupancy-dependent component output unit and the other occupancy-dependent component output unit. The facility management device according to feature 1.

16. The first acquisition unit performs a first acquisition step of acquiring power data of outlet-using devices, which are electronic devices that use outlets in the facility area, The second acquisition unit performs a second acquisition step of acquiring equipment operating status data indicating the operating status of the equipment in the area, The unmanned state time estimation unit estimates the unmanned state time of the target area based on the equipment operating status data in an unmanned state time estimation step, The occupancy-dependent component output unit outputs an occupancy-dependent component that depends on the number of people in the room, based on the time the room is unoccupied. The occupancy index output unit outputs an occupancy index related to the number of people in the target area from the power component which depends on the number of people in the room, in an occupancy index output step, A facility management method characterized by having the following features.

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