Building operation system

Abstract

To provide a building operation device capable of coping with the daily increase / decrease of the number of staying persons in a building.SOLUTION: The building operation apparatus includes an air conditioning control unit that controls an air conditioning apparatus that performs air conditioning inside the building, a database in which a date and time, weather, and the number of staying people inside the building are recorded in association with each other, a weather prediction information acquisition unit that acquires weather prediction information regarding prediction of weather at a specific date and time, and a staying person number prediction unit that predicts the number of staying people at the specific date and time based on the weather prediction information acquired by the weather prediction information acquisition unit and the date and time, the weather, and the number of staying people recorded in the database in association with each other. The air-conditioning control unit controls the air-conditioning apparatus based on the number of staying people on the specific date and time predicted by the number-of-staying people prediction unit so that the inside of the building on the specific date and time is in a predetermined state.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a building operation device. [Background technology]

[0002] Due to the spread of COVID-19, the number of people working both in the office and at home is increasing, and working styles in which the number of people in the office varies greatly from day to day are on the rise. Existing offices are designed to operate with a fixed number of people. As a result, this may not reflect the actual situation of office work after COVID-19. Therefore, it is important to control air conditioning systems in accordance with actual usage.

[0003] Patent Document 1 discloses a technique for periodically measuring the relationship between the change in the amount of electricity used in a space to be air-conditioned after a predetermined time and time. The technique in Patent Document 1 determines whether the measured amount of electricity matches a pattern of change in the amount of electricity generated in advance.

[0004] As a result, the technology in Patent Document 1 determines the final exit time and controls the air conditioning device so that power consumption is lower than normal after the final exit time.The technology in Patent Document 1 makes it possible to control air conditioning with the aim of reducing power consumption without compromising comfort, even in companies where exit times are not strictly adhered to or where exit times vary from person to person. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Patent No. 5523359 Summary of the Invention [Problem to be solved by the invention]

[0006] However, the technology described in Patent Document 1 only considers the difference in the time of arrival and departure from work. Therefore, the technology described in Patent Document 1 may not be able to deal with the increase or decrease in the number of people coming to work each day, i.e., the increase or decrease in the number of people staying in a building each day.

[0007] An object of the present invention is to provide a building operation device that can better respond to changes in the number of people staying in a building each day. [Means for solving the problem]

[0008] In order to solve the above problem, the building operation device of the present invention comprises an air conditioning control unit that controls an air conditioning unit that conditions the air inside the building, a database in which the date and time, weather, and the number of people inside the building are recorded in association with each other, a weather forecast information acquisition unit that acquires weather forecast information regarding the forecast weather for a specific date and time, and a visitor number prediction unit that predicts the number of people staying on a specific date and time based on the weather forecast information acquired by the weather forecast information acquisition unit and the date and time, weather, and number of people staying recorded in association with the database, and the air conditioning control unit controls the air conditioning unit so that the inside of the building on a specific date and time is in a predetermined state based on the number of people staying on a specific date and time predicted by the visitor number prediction unit. [Effects of the Invention]

[0009] According to the present invention, it is possible to better respond to changes in the number of people staying in a building each day. Further features related to the present invention will become apparent from the description of the present specification and the accompanying drawings. In addition, the problems, configurations, and effects other than those described above will become apparent from the following description of the embodiments. [Brief explanation of the drawings]

[0010] [Figure 1] FIG. 2 is a functional block diagram of the building operation device according to the first embodiment. [Figure 2] Table showing an example of data recorded in the database of Figure 1. [Figure 3]4 is a flowchart showing the operation of the building operation device of the first embodiment. [Figure 4] 1A is a graph showing changes in the set temperature in the first embodiment and the comparative example, and FIG. 1B is a graph showing cumulative energy consumption in the first embodiment and the comparative example. [Figure 5] FIG. 10 is a functional block diagram of a building operation device according to a second embodiment. [Figure 6] 10 is a flowchart showing the operation of the building operation device according to the second embodiment. [Figure 7] 10A and 10B are diagrams showing examples of displaying recommended seats in an elevator hall and inside an elevator. [Figure 8] FIG. 10 is a diagram showing an example of a display of recommended seats at the entrance of a room. [Figure 9] FIG. 10 is a diagram showing an example of an email message presenting recommended seats. [Figure 10] FIG. 11 is a functional block diagram of a building operation device according to a third embodiment. [Figure 11] 10 is a flowchart showing the operation of the building operation device according to the third embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0011] Hereinafter, the present embodiment will be described with reference to the accompanying drawings. In the accompanying drawings, functionally identical elements are designated by the same numerals. Note that the accompanying drawings show embodiments and implementation examples according to the principles of the present disclosure, but these are for understanding the present disclosure and are not to be used to interpret the present disclosure in a limiting manner. The descriptions in this specification are merely typical examples and are not intended to limit the scope or application of the present disclosure in any way.

[0012] (First embodiment) The first embodiment will be described below. Fig. 1 is a functional block diagram of a building operation device 100A according to the first embodiment. The building operation device 100A is configured as a computer that controls equipment such as air conditioners 21 and 22 and lighting fixtures 31 and 32 of a building 200 such as an office building. The building operation device 100A performs the operations of the functional blocks shown in Fig. 1 by having a computing device such as a CPU (Central Processing Unit) of the building operation device 100A execute computer programs stored in a ROM (Read Only Memory) and a RAM (Random Access Memory) of the building operation device 100A. The building operation device 100A further includes recording media such as a hard disk drive (HDD) and a solid state drive (SSD).

[0013] 1 , building operation device 100A includes a visitor counting unit 1, a weather forecast information acquiring unit 2, a database 3, a visitor count predicting unit 4, a building equipment control unit 5, an air conditioning control unit 6, and a lighting control unit 7. The visitor counting unit 1 counts the number of people inside building 200.

[0014] The visitor counting unit 1 is connected to the elevators, the entrance / exit card reader, the human presence sensor, etc. of the building 200. The visitor counting unit 1 counts the number of people inside the building 200 from elevator usage information, the data from the entrance / exit card reader, the value of the human presence sensor, etc. The date and time when the visitor counting unit 1 measured the number of people, the weather at the date and time when the visitor counting unit 1 measured the number of people, and the number of people measured by the visitor counting unit 1 are recorded in association with each other.

[0015] The term "date and time" refers to a date, expressed as a year, month, day, and day of the week, as well as the time on that date. Weather refers to various phenomena that occur in the atmosphere. Weather includes, for example, weather such as sunny, cloudy, rainy, and snowy, temperature, humidity, amount of precipitation (amount of snowfall), and wind speed.

[0016] The weather forecast information acquisition unit 2 acquires weather forecast information relating to the forecast of weather at a specific date and time. The weather forecast information can be acquired, for example, from a public weather forecasting organization or a private weather forecasting organization. The weather forecast information acquisition unit 2 also acquires meteorological information relating to the weather at that time at a specific date and time. For example, the weather at the date and time when the number of visitors is measured by the visitor counting unit 1 is the weather indicated by the meteorological information acquired by the weather forecast information acquisition unit 2 at the date and time when the number of visitors is measured by the visitor counting unit 1.

[0017] The database 3 is physically composed of an HDD, an SSD, etc. The database 3 may be installed on a server external to the building operation device 100A. By installing the database 3 on a server, the database 3 can be accessed from various locations and devices via a network line, improving convenience. The database 3 records the date and time, weather, and the number of people inside the building 200 in association with each other.

[0018] FIG. 2 is a table showing an example of data recorded in database 3 of FIG. 1. As shown in FIG. 2, database 3 stores information related to the date and time, weather, and number of visitors related to Building A as building 200 operated by building operation device 100A. The date and time includes information related to the year, month, day, day of the week, and time. The weather includes information related to weather such as sunny, cloudy, rainy, and snowy, temperature, humidity, amount of precipitation, and wind speed. The number of visitors may include the number of visitors in each area of ​​building 200 in addition to the total number of visitors inside building 200.

[0019] Information about Building A as building 200 includes location (latitude and longitude) and size (floor area). Location may include information such as the address and the nearest train station. Size may include information such as the number of floors. Information about Building A as building 200 may also include information about facilities inside building 200, such as whether or not there are rest areas and cafeterias within Building A, and information about facilities outside building 200, such as whether or not there are restaurants within a radius of several hundred meters outside Building A.

[0020] Furthermore, the information about Building A as building 200 includes the maximum number of people who stayed inside Building A, the age distribution (average age), the gender ratio (in the example of FIG. 2, the number of men / total number of people), and the ratio of the number of commuters by train to the number of commuters by car (in the example of FIG. 2, the number of commuters by train / total number of people). The age distribution may include information about the ratio of people by age group, such as those in their 20s and 30s. Furthermore, the information about Building A as building 200 may include the industry of the people who stayed inside Building A.

[0021] Database 3 records, as the number of people staying inside building 200, the number of people staying inside other buildings whose difference in size or location with building 200 is equal to or less than a threshold. Database 3 also records, as the number of people staying inside building 200, the number of people staying inside other buildings whose difference in any of the number of people staying inside building 200, age composition, gender ratio, and ratio of the number of commuters by rail and the number of commuters by car is equal to or less than a threshold. The number of people staying inside other buildings is recorded in association with the date, time, and weather.

[0022] For example, in the example of FIG. 2, the above information regarding Building B, which is located close to Building A operated by the building operation device 100A, is recorded as another building. In other words, database 3 records information about other buildings similar to building 200 operated by building operation device 100A. There may be multiple other buildings similar to building 200. The above threshold value is an acceptable degree of similarity and can be arbitrarily set within a range that allows for the collection of a sufficient amount of information about other buildings. Furthermore, database 3 may record each of the above information in association with information such as whether or not there are any company events, such as meetings.

[0023] The visitor count prediction unit 4 shown in Fig. 1 predicts the number of visitors at a specific date and time based on the weather forecast information acquired by the weather forecast information acquisition unit 2 and the date and time, weather, and number of visitors recorded in association with each other in the database 3. By configuring the visitor count prediction unit 4 as a computing device installed on a server, the visitor count prediction unit 4 can be accessed from various locations and devices via a network line, improving convenience. The prediction of the number of visitors by the visitor count prediction unit 4 will be described in detail below.

[0024] The building equipment control unit 5 controls the air conditioning control unit 6 and the lighting control unit 7 based on the number of visitors inside the building 200 predicted by the visitor number prediction unit 4. The air conditioning control unit 6 controls the air conditioners 21 and 22 that condition the air inside the building 200. The air conditioning control unit 6 controls the air conditioners 21 and 22 so that the inside of the building 200 on a specific date and time is in a predetermined state, based on the number of visitors on a specific date and time predicted by the visitor number prediction unit 4. Information on the number of visitors predicted by the visitor number prediction unit 4 is transmitted to the air conditioning control unit 6 via the building equipment control unit 5. The predetermined state means, for example, temperature, humidity, air cleanliness, etc. that meet standards set by public organizations for air conditioning equipment.

[0025] The lighting control unit 7 controls the lighting of the lights 31 and 32 based on the number of visitors at a specific date and time predicted by the visitor number prediction unit 4.

[0026] Fig. 3 is a flowchart showing the operation of the building operation device 100A of Embodiment 1. As shown in Fig. 3, the visitor count prediction unit 4 refers to the database 3 and determines whether there is data on the building 200 that matches the specific date and time and the weather at the specific date and time indicated by the weather forecast information acquired by the weather forecast information acquisition unit 2 (S101).

[0027] In this case, the number-of-visitors prediction unit 4 extracts the date and time in the past year that corresponds to the specific date and time from the dates and times for the building 200 recorded in the database 3. For example, if the specific date and time is month A, day B, day C, hour D, minute E, and day B is day C of the week in the Fth week of month A, the corresponding date and time in the past X year is day C of the week in the Fth week of month A of year X.

[0028] When the weather recorded in association with the date and time of the past year for the building 200 is similar to the weather indicated by the weather forecast information acquired by the weather forecast information acquisition unit 2, the visitor count prediction unit 4 predicts the number of visitors recorded in association with the date and time of the past year for the building 200 as the number of visitors at a specific date and time. For example, the weather is considered to be similar when the weather conditions, such as sunny and rainy, match. Furthermore, the temperature, humidity, precipitation, and wind speed are determined based on whether the difference between the temperature, etc. indicated by the weather forecast information and the temperature, etc. in the information in the database 3 is equal to or less than a predetermined threshold.

[0029] Below is an example of predicting the number of people staying in building 200 at 9:30 AM on the following day, Monday, April 15, 2024, on Sunday, April 14, 2024. The weather forecast information acquired by the weather forecast information acquisition unit 2 predicts that the weather at 9:30 AM on April 15, 2024 will be sunny, with a temperature of 20°C, humidity of 44%, precipitation of 0 mm / h, and wind speed of 3 m / s.

[0030] Monday, April 15, 2024 is the Monday of the third week of April 2024. Database 3 records information about Building A, which is building 200, at 9:30 AM on Monday, April 17, 2023, which is the Monday of the third week of April 2023. The weather at 9:30 AM on April 17, 2023 nearly matches the weather forecast information for 9:30 AM on April 15, 2024. Therefore, the number-of-guests prediction unit 4 determines that the weather recorded in association with the date and time of the past year for building 200 is similar to the weather indicated by the weather forecast information acquired by weather forecast information acquisition unit 2.

[0031] The visitor count prediction unit 4 determines that there is data for building 200 (S101) and applies the data on the number of visitors in Building A at 9:30 AM on April 17, 2023 (S102). As shown in FIG. 2, the number of visitors in Building A is 90, so the visitor count prediction unit 4 predicts that the number of visitors at 9:30 AM on April 15, 2024 will be 90.

[0032] On the other hand, for example, if the weather forecast information acquired by the weather forecast information acquisition unit 2 predicts bad weather at 9:30 AM on April 15, 2024, with rain, a temperature of 25°C, humidity of 88%, precipitation of 11 mm / h, and a wind speed of 9 m / s, and this differs from the data recorded in the database 3 for building A, the visitor count prediction unit 4 determines that the weather recorded in association with the date and time of past years for building 200 is not similar to the weather indicated by the weather forecast information acquired by the weather forecast information acquisition unit 2. The visitor count prediction unit 4 determines that there is no data for building 200 (S101) and executes the process of S103.

[0033] The visitor count prediction unit 4 refers to the database 3 and determines whether there is data on other buildings that matches the specific date and time and the weather at the specific date and time indicated by the weather forecast information acquired by the weather forecast information acquisition unit 2 (S103). In this case, the visitor count prediction unit 4 extracts the date and time of the past year that corresponds to the specific date and time from the date and time for other buildings recorded in the database 3. Furthermore, if the weather recorded in association with the date and time of the past year for other buildings is similar to the weather indicated by the weather forecast information acquired by the weather forecast information acquisition unit 2, the visitor count prediction unit 4 predicts the number of visitors recorded in association with the date and time of the past year for other buildings as the number of visitors at the specific date and time.

[0034] Database 3 records information about Building B, another building similar to Building A, at 9:30 AM on Monday, April 17, 2023, which is the Monday of the third week of April 2023. The weather at 9:30 AM on April 17, 2023 closely matches the weather forecast information for 9:30 AM on April 15, 2024. Therefore, the number-of-visitors prediction unit 4 determines that the weather recorded in association with the date and time of the past year for the other building is similar to the weather indicated by the weather forecast information acquired by the weather forecast information acquisition unit 2.

[0035] The visitor count prediction unit 4 determines that there is data for other buildings (S103) and applies the data on the number of visitors in Building B at 9:30 AM on April 17, 2023 (S104). As shown in FIG. 2, the number of visitors in Building B is 60, so the visitor count prediction unit 4 predicts that the number of visitors at 9:30 AM on April 15, 2024 will be 60.

[0036] On the other hand, for example, if the weather forecast information acquired by the weather forecast information acquisition unit 2 predicts that the weather at 9:30 a.m. on April 15, 2024 will be sunny, with a temperature of 33°C, humidity of 90%, precipitation of 0 mm / h, and a wind speed of 1 m / s, resulting in extreme heat, and this differs from the data recorded in database 3 for building B, the number of visitors prediction unit 4 determines that there is no data for other buildings (S103) and executes processing of S105.

[0037] The visitor count prediction unit 4 predicts the number of visitors by applying average data (S105). The average data may be, for example, the number of visitors at a date and time corresponding to 9:30 AM on April 15, 2024 up to several years ago, regardless of the weather, in Building A as building 200 or another building such as Building B similar to Building A.

[0038] For example, for a newly constructed building 200, the visitor count prediction unit 4 can predict the number of visitors for the first year using data from other buildings or average data. From the following year, for example, the visitor count prediction unit 4 can predict the number of visitors using the date and time when the number of visitors was measured by the visitor count measurement unit 1, which is recorded in association with the database 3, the weather at the date and time when the number of visitors was measured by the visitor count measurement unit 1, and the number of visitors measured by the visitor count measurement unit 1. Since the tendency of the number of visitors differs in each office, the number of visitors can be predicted with high accuracy by reflecting the tendency of the number of visitors in each office.

[0039] The visitor number prediction unit 4 may predict the number of visitors by referring to company events such as meetings recorded in the database 3. The visitor number prediction unit 4 may also predict the number of visitors by referring to conference room reservations and plans such as business trips and vacations of each person registered in the scheduler.

[0040] Based on the number of visitors predicted by the visitor number prediction unit 4, the air conditioning control unit 6 controls the air conditioners 21 and 22, and the lighting control unit 7 controls the lighting 31 and 32. FIG. 4(A) is a graph showing changes in the set temperature in the first embodiment and the comparative example, and FIG. 4(B) is a graph showing cumulative energy consumption in the first embodiment and the comparative example. FIGS. 4(A) and 4(B) show an example of an office in a building 200 where working hours are 8:45 to 17:15 and the lunch break is 12:00 to 13:00. As shown in FIG. 4(A), in the comparative example, the set temperature is only raised by 1°C to match the temperature after noon, when the temperature is predicted to rise.

[0041] On the other hand, in the first embodiment, since it is predicted that people will start coming to work around 8:00 AM and the number of people staying there will increase, the air conditioning operation starts at 7:30 AM and the set temperature is gradually lowered until 9:30 AM. Since it is predicted that fewer people will be staying there during the lunch break as people go out, the set temperature is raised and then returned to its original setting at 12:30 PM before the end of the lunch break. The set temperature could be returned to its original setting at 1:00 PM when the lunch break ends, but by returning the set temperature a little earlier, it is possible to work at a comfortable temperature immediately after the lunch break. The set temperature is gradually raised from 5:30 PM, which is the end of the workday. The air conditioning set temperature is raised at 8:00 PM when almost no one is staying in the offices of building 200.

[0042] In the first embodiment, the air conditioning control unit 6 changes the set temperatures of the air conditioners 21, 22 depending on the number of people staying. By setting the set temperatures in stages at the start of work, sudden rotation of the compressors of the air conditioners 21, 22 can be suppressed. Therefore, as shown in FIG. 4(B), the first embodiment can reduce cumulative energy consumption by approximately 10% compared to the comparative example. Furthermore, since the room is at the optimum temperature at the start of work, people can start work in a comfortable temperature environment.

[0043] In addition to rooms, conference rooms separated by walls can also be pre-cooled or pre-heated by predicting the number of people using the conference room's reservation information or each person's scheduler. By operating the air conditioner in advance, sudden changes in the compressor can be suppressed, reducing the air conditioner's power consumption. Also, by controlling the temperature so that it is just right at the start of a meeting, the meeting can begin at the right temperature, improving comfort.

[0044] Regarding the lights 31 and 32, if it is predicted that the number of people staying is small, the lighting control unit 7 can reduce power consumption by turning off some of the lights 31 and 32 or by driving the lights 31 and 32 at reduced output. The lighting control unit 7 may also use a motion sensor to turn on the lights 31 and 32 only in places where people are present. Note that, since complete darkness would hinder movement inside the building 200, it is better for the lighting control unit 7 to drive the lights 31 and 32 at reduced output. Furthermore, if it is predicted that the number of people staying is smaller than a predetermined number and the building has multiple elevators, the number of elevators in operation may be reduced.

[0045] According to this embodiment, the visitor number prediction unit 4 can predict the number of visitors at a specific date and time based on the weather forecast information acquired by the weather forecast information acquisition unit 2 and the date, time, weather, and number of visitors recorded in association with the database 3.

[0046] Furthermore, the visitor count prediction unit 4 extracts a date and time in a past year that corresponds to the specific date and time from the date and time for the building 200 recorded in the database 3. When the weather recorded in association with the date and time in a past year for the building 200 is similar to the weather indicated by the weather forecast information acquired by the weather forecast information acquisition unit 2, the visitor count prediction unit 4 predicts the number of visitors recorded in association with the date and time in a past year for the building 200 as the number of visitors at the specific date and time. This makes it possible to predict the number of visitors.

[0047] Furthermore, the air conditioning control unit 6 controls the air conditioners 21, 22 so that the inside of the building 200 is in a predetermined state on a specific date and time based on the number of visitors on that specific date and time predicted by the visitor number prediction unit 4, and is therefore able to appropriately pre-cool and heat the inside of the building 200. Therefore, even in air conditioning that has a poor response of the temperature inside the building 200 to the set temperature, appropriate pre-cooling and heating can improve the comfort inside the building 200 and reduce the energy consumption of the building 200. Therefore, in this embodiment, it is possible to better respond to daily increases and decreases in the number of visitors in the building 200.

[0048] Furthermore, according to this embodiment, when the weather recorded in association with a date and time in a past year for building 200 is not similar to the weather indicated by the weather forecast information acquired by weather forecast information acquisition unit 2, visitor count prediction unit 4 extracts a date and time in a past year that corresponds to the specific date and time from the dates and times for other buildings recorded in database 3. When the weather recorded in association with a date and time in a past year for other buildings is similar to the weather indicated by the weather forecast information acquired by weather forecast information acquisition unit 2, visitor count prediction unit 4 predicts the number of visitors recorded in association with a date and time in a past year for other buildings as the number of visitors at the specific date and time. Therefore, even if data for building 200 operated by building operation device 100A is not stored in database 3, the number of visitors in building 200 can be predicted.

[0049] Moreover, according to this embodiment, over time, the database 3 stores the date and time when the visitor count was measured by the visitor counting unit 1, the weather indicated by the weather information at the date and time when the visitor count was measured by the visitor counting unit 1, and the number of visitors measured by the visitor counting unit 1, in association with each other. Therefore, over time, data about the building 200 is accumulated in the database 3, and the accuracy of the visitor count prediction by the visitor count prediction unit 4 improves.

[0050] (Second embodiment) The second embodiment will be described below. Fig. 5 is a functional block diagram of a building operation device 100B of the second embodiment. In this embodiment, in addition to the first embodiment, recommended seats are presented as seats recommended for sitting, thereby reducing the energy consumption of the building 200. As shown in Fig. 5, the building operation device 100B further includes a recommended seat determination unit 8 and a recommended seat presentation unit 9 in addition to the components of the building operation device 100A of the first embodiment.

[0051] The recommended seat determination unit 8 is connected to the visitor number prediction unit 4. The recommended seat determination unit 8 determines recommended seats inside the building 200 on a specific date and time based on the number of visitors on the specific date and time predicted by the visitor number prediction unit 4. The recommended seat presentation unit 9 presents the recommended seats determined by the recommended seat determination unit 8 to visitors inside the building 200. As will be described below, when the number of visitors on the specific date and time predicted by the visitor number prediction unit 4 is equal to or less than a threshold, the recommended seat determination unit 8 determines one or more recommended seats gathered in a specific area inside the building 200. The air conditioning control unit 6 controls the air conditioners 21, 22 so that the specific area is in a predetermined state.

[0052] The recommended seat presentation unit 9 is connected to display devices such as displays installed in the elevator hall, inside the elevator, and at the entrances to rooms inside the building 200. The recommended seat presentation unit 9 is also connected to an email distribution device that distributes emails to company portable electronic terminals and the like carried by people staying inside the building 200. The recommended seat presentation unit 9 presents recommended seats by displaying them in any of the elevator hall, inside the elevator, and at the entrances to rooms inside the building 200. In addition to the elevator hall, the recommended seat presentation unit 9 may also display recommended seats in places that are visible when people arrive at the building 200, such as near the entry / exit ID check unit. The recommended seat presentation unit 9 also presents recommended seats by distributing the recommended seats by email.

[0053] FIG. 6 is a flowchart showing the operation of the building operation device 100B of the second embodiment. As shown in FIG. 6, the recommended seat determination unit 8 determines whether the number of visitors predicted by the visitor number prediction unit 4 is equal to or less than a threshold (S201). The threshold for the number of visitors can be set, for example, according to the capacity of each room inside the building 200. For example, if there are three rooms inside the building 200 and each room has a capacity of 43 people, the threshold for the number of visitors can be set to 43 people and 86 people, which are integer multiples of the capacity of each room. Furthermore, if the air conditioners 21 and 22 in each room can be operated in divided areas within each room, the threshold for the number of visitors can be set to the capacity of the divided areas.

[0054] If it is determined that the number of visitors is equal to or less than the threshold (S201), the recommended seat determination unit 8 determines one or more recommended seats gathered in a specific area (S202). For example, if the specific area is three rooms inside the building 200 as described above, and the predicted number of visitors is 43 or less, the recommended seat determination unit 8 determines seats in one of the three rooms as recommended seats. If the predicted number of visitors is 86 or less, the recommended seat determination unit 8 determines seats in two of the three rooms as recommended seats. Furthermore, as described above, if the predicted number of visitors is equal to or less than the capacity of the divided areas of each room, the recommended seat determination unit 8 determines seats in the divided areas from one side of the room as recommended seats.

[0055] The recommended seat presentation unit 9 distributes the recommended seats by email (S203). The email can be distributed, for example, the day before the predicted number of visitors or before the start of work on that day. Furthermore, if the number of visitors on the predicted number of visitors changes significantly, the email can be distributed at any time on that day. The recommended seat presentation unit 9 displays the recommended seats on a display device such as a display installed in the elevator hall, inside the elevator, or at the entrance to the room inside the building 200 (S204). The display of the recommended seats can be, for example, from before the start of work on the predicted number of visitors until the morning. Furthermore, if the number of visitors on the predicted number of visitors changes significantly, the recommended seats can be displayed at any time on that day.

[0056] The air conditioning control unit 6 controls the air conditioners 21, 22 so that the recommended seat areas are in a predetermined state (S205). The lighting control unit 7 turns on the lights 31, 32 in the recommended seat areas. The lighting control unit 7 turns off the lights 31, 32 in areas other than the recommended seat areas, or reduces the output of the lights 31, 32. On the other hand, if it is determined that the number of people staying exceeds the threshold (S201), the recommended seat determination unit 8 does not determine a recommended seat.

[0057] Fig. 7 is a diagram showing an example of the display of recommended seats in the elevator hall and inside the elevator. As shown in Fig. 7, above the destination floor buttons 41 in the elevator hall and inside the elevator, a display device 44 such as a display connected to the recommended seat presentation unit 9 is disposed. When the destination floor button 41 is pressed, the recommended seat determined by the recommended seat determination unit 8 is displayed on the display device 44.

[0058] FIG. 8 is a diagram showing an example of a recommended seat display at the entrance to a room. As shown in FIG. 8, display devices 44, 45, such as displays connected to the recommended seat presentation unit 9, are arranged above the room entrance 42. The recommended seats are displayed in text on the display device 44. The recommended seats are displayed in plan views on the display device 45. FIG. 9 is a diagram showing an example of an email message presenting recommended seats. As shown in FIG. 9, the recommended seats are displayed in email message 43 of the email delivered by the recommended seat presentation unit 9.

[0059] In this embodiment, the recommended seat determination unit 8 determines recommended seats inside the building 200 based on the number of visitors predicted by the visitor number prediction unit 4. The recommended seat presentation unit 9 presents the recommended seats determined by the recommended seat determination unit 8 to visitors inside the building 200. When the predicted number of visitors is equal to or less than a threshold, the recommended seat determination unit 8 determines one or more recommended seats gathered in a specific area inside the building 200. The air conditioning control unit 6 controls the air conditioners 21, 22 so that the specific area is in a predetermined state.

[0060] For this reason, for example, based on the predicted number of people staying, it is possible to suggest that people should sit in a specific room or one side of a room so that seats are filled. By having people sit in a certain amount of groups, it is possible to stop the air conditioners 21, 22 in places where no one is sitting and turn off or reduce the output of the lights 31, 32, thereby reducing the energy consumption of the building 200.

[0061] The recommended seats may be presented as recommended seats or as fixed seats. Presenting the recommended seats as recommended seats allows visitors to act spontaneously, which increases worker comfort. If reducing energy consumption is a priority, presenting the recommended seats as fixed seats allows visitors to sit as determined by the recommended seat determination unit 8, thereby reducing energy consumption.

[0062] (Third embodiment) The third embodiment will be described below. FIG. 10 is a functional block diagram of a building operation device 100C of the third embodiment. In addition to the components of the building operation device 100B of the second embodiment, the building operation device 100C further includes a seating detection unit 10 and a seating recording unit 11. The seating detection unit 10 detects seating at each of a plurality of seats inside the building 200. The seating detection unit 10 identifies the person occupying each of the plurality of seats inside the building 200, and detects seating and leaving at each of the plurality of seats. The seating detection unit 10 is connected to, for example, a human presence sensor installed above each seat in the building 200. This allows the seating detection unit 10 to detect seating at each seat.

[0063] The seating detection unit 10 is also connected to, for example, a personal computer installed at each seat in the building 200. The seating detection unit 10 can detect the seating of each seat and identify the occupant of each seat based on an ID or the like input when the personal computer at each seat is started up. The seating detection unit 10 is also connected to, for example, a camera installed near each seat in the building 200. By performing a pattern matching process on the video captured by the camera, the seating detection unit 10 can detect the seating of each seat and identify the occupant of each seat.

[0064] The seating recording unit 11 records the seating at each of the plurality of seats based on the seating at each of the plurality of seats detected by the seating detection unit 10. The seating recording unit 11 records the time when the seated person identified by the seating detection unit 10 sat down and the time when the person left the seat. The seating recording unit 11 is connected to the seating detection unit 10 and the recommended seat determination unit 8.

[0065] The recommended seat determination unit 8 prioritizes seats with a high number of occupants as recommended seats based on the seating at each of the multiple seats recorded in the seating recording unit 11. Furthermore, when the time an occupant leaves their seat recorded in the seating recording unit 11 is later than a predetermined threshold such as the end of work, the recommended seat determination unit 8 determines one or more recommended seats gathered in a specific area within the building 200 for the occupant. The recommended seat presentation unit 9 presents the recommended seats determined by the recommended seat determination unit 8 to the occupant who left their seat later. The air conditioning control unit 6 controls the air conditioners 21, 22 so that the area of ​​the recommended seats determined for the occupant who left their seat later is in a predetermined state.

[0066] 11 is a flowchart showing the operation of the building operation device 100C of the third embodiment. As shown in FIG. 11, similar to the second embodiment, the recommended seat determination unit 8 determines whether the number of visitors predicted by the visitor count prediction unit 4 is equal to or less than a threshold (S301). If it is determined that the number of visitors is equal to or less than the threshold (S301), the recommended seat determination unit 8 refers to the seating recording unit 11 and determines whether the seat occupant left their seat later than a threshold such as the end of work (S302).

[0067] The determination of whether the seat leaving time is late is made, for example, when the seating recording unit 11 records a predetermined number of consecutive times of leaving the seat later than the end of work time, etc. If the seat leaving time of the seated person recorded in the seating recording unit 11 is later than the threshold (S302), the recommended seat determination unit 8 determines one or more recommended seats gathered in a specific area inside the building 200 for the seated person (S303), as in the second embodiment. If the seat leaving time of the seated person recorded in the seating recording unit 11 is not later than the threshold (S302), the recommended seat determination unit 8 executes the process of S304.

[0068] The recommended seat determination unit 8 refers to the seating recording unit 11 and determines whether the seated person is a person who tends to sit in a seat away from seats occupied by other seated people (S304). The determination of whether the seated person is a person who tends to sit in a seat away from other seated people is made, for example, if the seating recording unit 11 records that the person has sat in a seat away from other seated people a predetermined number of times in a row. If the seated person is a person who tends to sit in a seat away from other seats occupied by other seated people and other recommended seats, the recommended seat determination unit 8 determines a seat away from other seats occupied by other seated people and other recommended seats as a recommended seat for the person in question (S305).

[0069] When priority is given to the comfort of the visitor, the recommended seat determination unit 8 determines a seat that is spaced at least two seats apart from other seats occupied by the visitor and other recommended seats as the recommended seat. On the other hand, when priority is given to reducing energy consumption, the recommended seat determination unit 8 determines a seat that is spaced at a distance of approximately one seat apart from other seats occupied by the visitor and other recommended seats as the recommended seat. When it is determined that the visitor is not a person who tends to sit in seats far apart (S304), the recommended seat determination unit 8 executes the process of S306.

[0070] The recommended seat determination unit 8 determines a seat with a higher number of occupants as a recommended seat based on the seating at each of the plurality of seats recorded in the seating recording unit 11 (S306). When determining a seat with a higher number of occupants as a recommended seat based on the seating at each of the plurality of seats recorded in the seating recording unit 11, the recommended seats can be determined in descending order of the amount of time that an occupant spends at each of the plurality of seats, for example.

[0071] The recommended seat presentation unit 9 distributes the recommended seat by email (S307). When the recommended seat determination unit 8 has determined a recommended seat for a specific seated occupant in S303 or S305, the recommended seat presentation unit 9 distributes the recommended seat determined by the recommended seat determination unit 8 to the seated occupant by email. As in the second embodiment, the recommended seat presentation unit 9 displays the recommended seat on display devices 44, 45, such as displays installed in an elevator hall, inside an elevator, and at the entrance to a room inside the building 200 (S204). When the recommended seat determination unit 8 has determined a recommended seat for a specific seated occupant in S303 or S305, the recommended seat presentation unit 9 does not necessarily have to display the recommended seat determined by the recommended seat determination unit 8 to the seated occupant.

[0072] The air conditioning control unit 6 controls the air conditioners 21, 22 so that the recommended seat areas are in a predetermined state (S309). The lighting control unit 7 turns on the lights 31, 32 in the recommended seat areas. The lighting control unit 7 turns off the lights 31, 32 in areas other than the recommended seat areas, or reduces the output of the lights 31, 32. On the other hand, if it is determined that the number of people staying exceeds the threshold (S301), the recommended seat determination unit 8 does not determine a recommended seat.

[0073] In this embodiment, the recommended seat determination unit 8 prioritizes seats with many occupants as recommended seats based on the seating at each of the multiple seats recorded in the seating recording unit 11. By recording seating occupancy, it is possible to identify popular seats where many people sit and unpopular seats where no one sits. Furthermore, by recording seats where people usually sit, it is possible to identify who is sitting in which seat. By presenting popular seats where many people sit as recommended seats, it is possible to work comfortably.

[0074] In this embodiment, for a person who often sits away from other seats where other people are seated, a seat that allows them to sit away from other seats where other people are seated can be presented, allowing them to work comfortably.

[0075] In this embodiment, when the time at which the seated person leaves their seat, as recorded in the seating recording unit 11, is later than a threshold value, the recommended seat determination unit 8 determines a recommended seat in a specific area within the building 200 for the seated person. The recommended seat presentation unit 9 presents the recommended seat determined by the recommended seat determination unit 8 to the seated person. The air conditioning control unit 6 controls the air conditioners 21, 22 so that the area of ​​the recommended seat is in a predetermined state.

[0076] That is, in the case of people who often work overtime and stay late into the night inside the building 200, the recommended seat presentation unit 9 presents recommended seats so that people who stay late into the night are seated close to each other. This makes it possible to bias the seating positions during overtime work, and after regular working hours, it is possible to stop the air conditioners 21, 22 in areas where no one is sitting and turn off the lights 31, 32, or operate the air conditioners 21, 22 and the lights 31, 32 at low output. This makes it possible to reduce the energy consumption of the building 200.

[0077] In addition, since the number of guests may increase more than predicted due to unexpected factors, in order to achieve both comfort and reduced energy consumption, the air conditioners 21, 22 and the lights 31, 32 may be operated at low output. This makes it possible to respond to the increased number of guests in a short period of time, even if the number of guests increases more than predicted due to unexpected factors.

[0078] The present invention is not limited to the above-described embodiments and includes various modifications. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and are not necessarily limited to those including all of the described configurations. Furthermore, it is possible to replace part of the configuration of one embodiment with the configuration of another embodiment, or to add the configuration of another embodiment to the configuration of one embodiment. Furthermore, it is possible to add, delete, or replace part of the configuration of each embodiment with other configurations. Furthermore, the above-described configurations, functions, processing units, processing means, etc. may be implemented in part or in whole in hardware, for example, by designing an integrated circuit, or entirely in software. [Explanation of symbols]

[0079] 1. Visitor Count Department 2. Weather forecast information acquisition unit 3 Database 4. Number of visitors forecast section 5 Building Facilities Control Department 6 Air conditioning control unit 7 Lighting control unit 8. Recommended Seat Determination Department 9. Recommended seating information section 10. Seated detection unit 11 Seating Record Section 21,22 Air conditioning equipment 31,32 Lighting 41 Destination Floor Button 42 Room Entrance 43 Email text 44,45 Display device 100A,100B,100C Building operation equipment 200 Buildings

Claims

1. an air conditioning control unit that controls an air conditioning device that conditions the air inside the building; a database in which the date and time, the weather, and the number of people staying inside the building are recorded in association with each other; a weather forecast information acquisition unit that acquires weather forecast information regarding a forecast of the weather at the specific date and time; a visitor number prediction unit that predicts the number of visitors at a specific date and time based on the weather forecast information acquired by the weather forecast information acquisition unit and the date and time, the weather, and the number of visitors that are associated and recorded in the database; Equipped with the air conditioning control unit controls the air conditioning device so that the inside of the building at the specific date and time is in a predetermined state, based on the number of visitors at the specific date and time predicted by the visitor number prediction unit. A building operation device characterized by:

2. The number-of-visitors prediction unit extracting the date and time of a past year corresponding to a specific date and time from the date and time for the building recorded in the database; When the weather recorded in association with the date and time of the past year for the building is similar to the weather indicated by the weather forecast information acquired by the weather forecast information acquisition unit, The number of visitors recorded in association with the date and time in the past year for the building is predicted as the number of visitors at the specific date and time. The building operation device according to claim 1 .

3. The database includes: As the number of people staying inside the building, the location of the building, the size of the building, the number of people staying inside the building, the age composition of the people staying inside the building, the male / female ratio of the people staying inside the building, and the number of people staying inside other buildings whose difference from any of the ratios of the number of people staying inside the building who commute by rail and the number of people who commute by car is equal to or less than a threshold are recorded; The number of people staying inside the other building is recorded in association with the date and time and the weather, The number-of-visitors prediction unit When the weather recorded in association with the date and time of the past year for the building is not similar to the weather indicated by the weather forecast information acquired by the weather forecast information acquisition unit, extracting the date and time in the past year corresponding to the specific date and time from the date and time for the other building recorded in the database; and, if the weather recorded in association with the date and time in the past year for the other building is similar to the weather indicated by the weather forecast information acquired by the weather forecast information acquisition unit, predicting the number of visitors recorded in association with the date and time in the past year for the other building as the number of visitors at the specific date and time. The building operation device according to claim 2 .

4. Further, a visitor number measuring unit that measures the number of people staying inside the building, the weather forecast information acquisition unit acquires meteorological information regarding the weather at the specific date and time, The building operation device of claim 1, characterized in that the database records the date and time when the number of visitors was measured by the visitor counting unit, the weather indicated by the weather information at the date and time when the number of visitors was measured by the visitor counting unit, and the number of visitors measured by the visitor counting unit, in association with each other.

5. a recommended seat determination unit that determines a recommended seat inside the building on the specific date and time based on the number of visitors on the specific date and time predicted by the visitor number prediction unit; a recommended seat presentation unit that presents the recommended seats determined by the recommended seat determination unit; The building operation device according to claim 1, further comprising:

6. When the number of visitors at the specific date and time predicted by the visitor number prediction unit is equal to or less than a threshold value, the recommended seat determination unit determines the recommended seat in a specific area inside the building; The air conditioning control unit controls the air conditioning device so that the area is in a predetermined state. The building operation device according to claim 5 .

7. a seating detection unit that detects seating at each of a plurality of seats inside the building; a seating recording unit that records seating at each of the plurality of seats based on seating at each of the plurality of seats detected by the seating detection unit; Furthermore, The building management device described in claim 5, characterized in that the recommended seat determination unit prioritizes the seat with the most occupancy as the recommended seat based on the seating at each of the multiple seats recorded in the seating recording unit.

8. The recommended seat presentation unit presenting the recommended seats by either displaying the recommended seats in an elevator hall, inside an elevator, or at a room entrance within the building, or by distributing the recommended seats by email; The building operation device according to claim 5 .

9. the seating detection unit detects seating and leaving of each of the plurality of seats while identifying an occupant at each of the plurality of seats inside the building; the seating recording unit records the time at which the seated person identified by the seating detection unit leaves the seat, the recommended seat determination unit determines the recommended seat in a specific area inside the building for the seated person when the time at which the seated person left the seat recorded in the seating recording unit is later than a threshold value; the recommended seat presentation unit presents the recommended seat determined by the recommended seat determination unit to the seated person; The air conditioning control unit controls the air conditioning device so that the area is in a predetermined state. The building operation device according to claim 7 .

Images