JP2015197242A - energy saving related information generating system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an energy saving related information generating system for generating information concerning a temperature distribution in another area in order to perform a relative evaluation of information concerning a temperature distribution in a certain space so as to generate information concerning a temperature distribution in an appropriate space in view of performing a comparing operation.SOLUTION: An energy saving related information generating system 100 comprises: a memory part 34; an input part 32; a similar space extracting part 35a; and a generating part 35b. The memory part 34 stores man-time series data concerning a position of human and temperature-time series data concerning the temperature distribution in each of many spaces to be air conditioned. The input part 32 receives a request for generating energy saving related information for the first space included in many spaces to be air conditioned. The similar space extracting part 35a extracts a similar space having a pattern showing a utilization situation similar to the first space from many spaces to be air conditioned. The generating part 35b generates information concerning a temperature distribution in the similar space on the basis of the temperature time series data in the similar space.

Description

  The present invention relates to an energy saving related information generation system that generates information related to a temperature distribution in another space in order to relatively evaluate information related to the temperature distribution in a certain space.

  In buildings such as office buildings, commercial buildings, and residences, it is required to optimally maintain the thermal environment of the space (indoors) and realize human comfort. On the other hand, for example, Patent Document 1 (Japanese Patent Laid-Open No. 2000-251189) discloses that a plurality of temperature sensors are arranged in a space and the air conditioner is controlled using the obtained temperature distribution. Yes.

  By the way, in recent years, in addition to optimally maintaining the indoor thermal environment, it is also required to achieve a desired thermal environment while efficiently using energy. In order to realize such high energy efficiency, it is first necessary to appropriately evaluate the current energy usage.

  For example, as in Patent Document 1 (Japanese Patent Laid-Open No. 2000-251189), if the temperature distribution in the space is quantitatively grasped, information such as whether there is an excessively air-conditioned area in the space can be obtained. It is possible to assess whether energy is being wasted.

  In addition, in order to appropriately evaluate the energy usage status, not only quantitatively grasp the temperature distribution in the space, but also relatively compare the difference in energy usage status with other spaces (other rooms). Will also be important.

  Evaluation of relative energy usage is relatively easy if, for example, the temperature of a certain space is compared with the temperature of another randomly selected space. However, in reality, the temperature distribution can change depending on how each user uses the space, so the compared space may not be appropriate for comparison. .

  An object of the present invention is an energy-saving related information generation system that generates information related to the temperature distribution in another space in order to relatively evaluate information related to the temperature distribution in a certain space, and considers the use status of the space by the user. Thus, an object of the present invention is to provide an energy saving related information generation system that generates information related to temperature distribution in an appropriate space for comparison.

  The energy-saving related information generation system according to the first aspect of the present invention includes a storage unit, a reception unit, a similar space extraction unit, and a generation unit. The storage unit accumulates and stores human time-series data relating to the position of the person in each air-conditioning target space and temperature time-series data relating to the temperature distribution in each air-conditioning target space for a number of air-conditioning target spaces. A reception part receives the production | generation request | requirement of the energy saving related information for 1st spaces contained in many space for air conditioning. The similar space extraction unit extracts a similar space having a usage pattern similar to the first space from a large number of air-conditioning target spaces based on the human time-series data of the first space. A generation part produces | generates the information regarding the temperature distribution of the similar space based on the temperature time series data of the similar space as the energy saving related information for the first space.

  Here, based on the time-series data related to the human position, a similar space having a similar usage pattern to that of the first space to be evaluated is extracted, and energy saving related information for the first space is related to the temperature distribution of the similar space. Information is generated. Therefore, it is possible to appropriately perform the relative evaluation of the first space based on the generated energy saving related information.

  An energy-saving related information generation system according to a second aspect of the present invention is an energy-saving related information generation system according to the first aspect, wherein the similar space extraction unit is based on human time-series data in a large number of air-conditioning target spaces. A second space in which the obtained enrollment state variation pattern is similar to the enrollment state variation pattern obtained from the human time-series data in the first space is extracted as a similar space.

  Here, since the space where the variation pattern of the enrollment state is similar to the first space is extracted as the similar space, the relative evaluation of the first space is performed based on the information regarding the temperature distribution of the similar space generated as the energy saving related information. Can be performed appropriately.

  An energy saving related information generation system according to a third aspect of the present invention is an energy saving related information generation system according to the first aspect or the second aspect, and the generation unit includes information on temperature distribution in a similar space as energy saving related information. Further, comparison information with the information regarding the temperature distribution of the first space corresponding to the information regarding the temperature distribution of the similar space is further generated.

  Here, since comparative information that compares information related to the temperature distribution of the first space and the similar space of the first space is generated as energy saving related information, the energy usage status of the target space is relatively evaluated using the energy saving related information. Easy to do.

  An energy-saving related information generation system according to a fourth aspect of the present invention is an energy-saving related information generation system according to any one of the first to third aspects, wherein the storage unit is a device used in each air conditioning target space. Further accumulate and store information on energy consumption. The generation unit further generates, as energy saving related information, comparison information between information related to the energy consumption of the device used in the first space and information related to the energy consumption of the device used in the similar space.

  Here, the comparison information comparing the information on the energy consumption of the device used in the first space and the information on the energy consumption of the device used in the similar space of the first space is generated as the energy saving related information. Therefore, it is easy to relatively evaluate the energy usage status of the target space using the energy saving related information.

  An energy saving related information generation system according to a fifth aspect of the present invention is the energy saving related information generation system according to the fourth aspect, and further includes a presentation unit for presenting energy saving related information. The storage unit further stores at least one of information related to the specifications of each air-conditioning target space, information related to the specifications of devices used in each air-conditioning target space, and information related to contract power in each air-conditioning target space. The presenting unit stores information on specifications of each air-conditioning target space, information on specifications of equipment used in each air-conditioning target space, and each air-conditioning target stored in the storage unit for at least one of the first space and the similar space At least one piece of information regarding the contracted power of the space is further presented.

  Here, the specifications of the air-conditioning target space, the specifications of the equipment used in the air-conditioning target space, information on the contracted power of the air-conditioning target space, etc. are presented, and various specifications of the first space and similar spaces of the first space It is easy to examine measures to promote energy saving by utilizing the difference in power and contract power.

  An energy saving related information generating system according to a sixth aspect of the present invention is an energy saving related information generating system according to any of the first to fifth aspects, wherein the temperature time-series data is stored in an air-conditioning target space. It is time series data of the distribution of the steady temperature of the air-conditioning target space from which the influence is removed.

  Here, the temperature time-series data used when generating the information on the temperature distribution as the energy-saving related information is the time-series data of the steady temperature distribution of the air-conditioning target space from which the human influence is removed. It is easy to perform relative evaluation of space appropriately.

  In the energy-saving related information generation system according to the first aspect of the present invention, a similar space having a similar usage pattern to the first space to be evaluated is extracted based on time-series data relating to the position of a person. Information related to the temperature distribution of the similar space is generated as the energy saving related information. Therefore, it is possible to appropriately perform the relative evaluation of the first space based on the generated energy saving related information.

  In the energy saving related information generation system according to the second aspect of the present invention, the relative evaluation of the first space can be appropriately performed based on the information related to the temperature distribution of the similar space generated as the energy saving related information.

  In the energy saving related information generation system according to the third and fourth aspects of the present invention, the comparison information between the information on the first space and the information on the similar space in the first space is generated as the energy saving related information. It is easy to relatively evaluate the energy usage status of the target space using related information.

  In the energy saving related information generation system according to the fifth aspect of the present invention, it is easy to examine a policy for promoting energy saving.

  In the energy-saving related information generation system according to the sixth aspect of the present invention, it is easy to appropriately perform the relative evaluation of the first space.

It is a schematic diagram of the energy-saving related information generation system concerning one embodiment of the present invention. It is an example of the air-conditioning object space where the infrared sensor unit of the energy-saving related information generation system of FIG. 1 is arranged. FIG. 2 is a schematic plan view of the air conditioning target space as viewed from above. In FIG. 2, the position of the person in the air conditioning target space is drawn with a circle. In FIG. 2, the infrared sensor unit and the air conditioning indoor unit attached to the ceiling of the target space are drawn with a two-dot chain line. It is a block diagram of the energy-saving related information generation system of FIG. It is a block diagram of the infrared sensor unit of the energy-saving related information generation system of FIG. It is a flowchart of operation | movement of the infrared sensor unit of FIG. It is an example of the thermal image data acquired by the sensor part of the infrared sensor unit of FIG. It is a figure for demonstrating the time peak exclusion thermal image data generation process in the flowchart of FIG. In the spatial peak exclusion thermal image data generation process in the flowchart of FIG. 5, temporal peak exclusion thermal image data composed of 16 columns × 16 columns (256 pixels) is converted into 4 columns × 4 columns (16 pixels). The section divided into is shown. It is a figure for demonstrating the space peak exclusion thermal image data generation process in the flowchart of FIG. It is an example of the temperature distribution data (spatial peak exclusion thermal image data) extracted from thermal image data by the infrared sensor unit of FIG. It is an example of the human distribution data extracted from thermal image data by the infrared sensor unit of FIG. It is an example of the flowchart of the energy-saving related information generation process (a similar space extraction process is also included) by the energy-saving related information generation system which concerns on FIG. It is an example of the flowchart of the calculation process of the ratio of the enrolled area in the comfortable temperature area in the flowchart of FIG. It is a block diagram of an energy-saving related information generation system concerning modification H.

  An energy saving related information generation system 100 according to an embodiment of the present invention will be described below. The following embodiments are specific examples of the present invention and do not limit the technical scope of the present invention. The following embodiments can be modified as appropriate without departing from the spirit of the present invention.

(1) Overall Configuration The energy saving related information generation system 100 accumulates and stores temperature time series data and human time series data of a large number (N) of air conditioning target spaces R1, R2,. The temperature time series data is time series temperature distribution data of each of the air-conditioning target spaces R1, R2,. The human time series data is time series human distribution data of each of the air conditioning target spaces R1, R2,. For example, the number of air conditioning target spaces R1, R2,... RN is 100 or more.

  The energy saving related information generation system 100 is configured to save energy related information for the air conditioning target space Rm for one air conditioning target space Rm (m = 1 to N) included in a large number of air conditioning target spaces R1, R2,. The request for generating is accepted. When the energy saving related information generation system 100 receives the generation request of the energy saving related information for the air conditioning target space Rm, the temperature time series data and human time series of the accumulated many air conditioning target spaces R1, R2,. Energy saving related information for the air conditioning target space Rm is generated using the data. The energy-saving related information for the air conditioning target space Rm includes information related to the temperature distribution of the similar space of the air conditioning target space Rm based on the temperature time series data of the similar space of the air conditioning target space Rm. The similar space of the air conditioning target space Rm is a space having a usage pattern similar to the air conditioning target space Rm in the air conditioning target spaces R1, R2,. It should be noted that which of the air-conditioning target spaces R1, R2,... RN is a similar space to the air-conditioning target space Rm is determined based on human time-series data for a predetermined period of the air-conditioning target space Rm. .

  The air-conditioning target spaces R1, R2,... RN here are all spaces used as offices, for example. However, the present invention is not limited to this, and the air conditioning target spaces R1, R2,... RN may include spaces used as commercial facilities, schools, hotels, residences, and the like. Further, the air-conditioning target spaces R1, R2,... RN need not include spaces used as offices.

  FIG. 2 is a schematic view of an air-conditioning target space Rk as an example of the air-conditioning target spaces R1, R2,. The air conditioning target space Rk is a square room of 5 m × 5 m in plan view. In FIG. 2, the infrared sensor unit 20 and the air conditioning indoor unit 90 attached to the ceiling of the air conditioning target space Rk are drawn with a two-dot chain line. The infrared sensor unit 20 will be described later.

  Near the center of the ceiling of the air conditioning target space Rk, a ceiling cassette type air conditioning indoor unit 90 is installed (see FIG. 2). The air conditioning indoor unit 90 is connected to an air conditioning outdoor unit (not shown) by a refrigerant pipe, and functions as an air conditioner together with the air conditioning outdoor unit. The air conditioning indoor unit 90 has air outlets (not shown) in all directions, and can blow out air-conditioned air in all directions. Each air outlet of the air conditioning indoor unit 90 is provided with a flap (not shown) for adjusting the air direction. Each flap is configured to be controllable independently of the other flaps. Further, a ventilation duct (not shown) is provided in the air conditioning target space Rk. The ventilation duct is provided with a ventilation fan (not shown). The air-conditioning target space Rk is configured to be ventilated by a ventilation duct by operating a ventilation fan. In the air conditioning target space Rk used as an office, a plurality of people usually work. In FIG. 2, a person is drawn with a circle.

  2 is an example of the air conditioning target spaces R1, R2,... RN. The size and shape of the air-conditioning target spaces R1, R2,... RN, the type, number, arrangement, etc. of the devices installed in the air-conditioning target spaces R1, R2,... RN are not limited to those shown in FIG. . The arrangement and the number of the infrared sensor units 20 are also examples, and are not limited thereto. The infrared sensor unit 20 should just be arrange | positioned in an appropriate position in order to achieve the objective mentioned later. Usually, the size and shape of the air-conditioning target spaces R1, R2,... RN, the type, number and arrangement of the air-conditioning target spaces R1, R2,. It differs for each air conditioning target space R1, R2,.

  The energy-saving related information generation system 100 is disposed in each of a large number of air-conditioning target spaces R1, R2,... RN and each of the infrared sensor units 20 disposed in a large number of air-conditioning target spaces R1, R2,. The computer 50 and the main computer 30 are mainly included (see FIG. 1).

  One or more infrared sensor units 20 are installed in each of the air conditioning target spaces R1, R2,. The main computer 30 is installed in a place different from the air conditioning target spaces R1, R2,. The main computer 30 is communicably connected to the infrared sensor unit 20 and the computer 50 via the communication network 10 (see FIG. 1). The communication network 10 is a WAN (Wide Area Network) such as the Internet, for example.

  The infrared sensor unit 20 measures the temperature distribution of the air conditioning target spaces R1, R2,... RN, and acquires thermal image data composed of a plurality of pixels. In addition, the infrared sensor unit 20 removes the human influence existing in the air conditioning target spaces R1, R2,... RN from the acquired thermal image data, and the steady temperature of the air conditioning target spaces R1, R2,. Temperature distribution data indicating the distribution is extracted. In addition, the infrared sensor unit 20 extracts human distribution data indicating a human distribution existing in the air conditioning target spaces R1, R2,... RN from the acquired thermal image data. The infrared sensor unit 20 transmits the extracted temperature distribution data and human distribution data to the main computer 30 via the communication network 10.

  The main computer 30 receives temperature distribution data and human distribution data transmitted by a large number of infrared sensor units 20. Note that the main computer 30 receives the received temperature distribution data and human distribution data from which infrared sensor unit 20 (from which infrared sensor unit 20 disposed in which air conditioning target space R1, R2,... RN). ) It is configured to be able to recognize whether it is transmitted information. The main computer 30 stores the received temperature distribution data and human distribution data as temperature time-series data and human time-series data for each of the air-conditioning target spaces R1, R2,. ). The temperature time-series data is time-series temperature distribution data of the air-conditioning target spaces R1, R2,. The human time series data is time series human distribution data of each of the air conditioning target spaces R1, R2,.

  An input unit 32 (see FIG. 3), which will be described later, of the main computer 30 receives a request for generating energy saving related information for the air conditioning target space Rm. Moreover, in the main computer 30, the communication part 31 (refer FIG. 3) mentioned later transmits the energy saving related information for air-conditioning object space Rm transmitted from the computer 50 arrange | positioned in air-conditioning object space R1, R2, ... RN. The request for generating is accepted. When the input unit 32 or the communication unit 31 receives a generation request for energy saving related information for the air conditioning target space Rm, the processing unit 35 (see FIG. 3) of the main computer 30 is based on the temperature time-series data and the human time-series data. Thus, energy saving related information for the air conditioning target space Rm is generated. The energy-saving related information for the air conditioning target space Rm generated by the main computer 30 includes information related to the temperature distribution of the similar space of the air conditioning target space Rm. When the energy saving related information for the air conditioning target space Rm is generated, the main computer 30 transmits the energy saving related information generation request for the air conditioning target space Rm to the computer 50 that has transmitted the generation request for the energy saving related information via the communication unit 31. Send. Further, when the energy saving related information for the air conditioning target space Rm is generated, the main computer 30 presents the energy saving related information for the air conditioning target space Rm to the output unit 33 (see FIG. 3) described later.

  Each computer 50 is connected to the main computer 30 via the communication network 10 and is configured to be communicable with the main computer 30. The computer 50 is, for example, a desktop computer, and mainly includes a CPU, a memory such as a ROM and a RAM, an auxiliary storage device such as an HDD, and an input / output device.

  A request for generating energy-saving related information for the air-conditioning target space Rm is input to an input unit 51 (see FIG. 3) of the computer 50 such as a keyboard and a mouse by a user of the air-conditioning target space Rm. The computer 50 transmits the input generation request for energy saving related information for the air-conditioning target space Rm to the main computer 30 via the communication network 10. In addition, the computer 50 receives the energy saving related information for the air conditioning target space Rm transmitted from the main computer 30. The computer 50 presents the received energy-saving related information for the air-conditioning target space Rm to the output unit 52 (see FIG. 3) including a display or the like. The output unit 52 is an example of a presentation unit.

  Here, the computer 50 is a desktop computer, but is not limited thereto, and may be a laptop computer or a tablet computer, for example. Moreover, it replaces with the computer 50 and a smart phone etc. may be used instead. Moreover, the computer 50 does not need to be installed in the air conditioning target spaces R1, R2,. The computer 50 only needs to be configured to be able to transmit a request for generating energy-saving related information for the air-conditioning target space Rm to the main computer 30 and to be able to receive the generated energy-saving related information for the air-conditioning target space Rm.

(2) Detailed Configuration The infrared sensor unit 20 and the main computer 30 will be described below.

(2-1) Infrared sensor unit One or more infrared sensor units 20 are installed in each of the air conditioning target spaces R1, R2,. Each infrared sensor unit 20 measures the temperature distribution of the whole or part of each air conditioning target space R1, R2,..., RN, and acquires thermal image data composed of a plurality of pixels. In addition, each infrared sensor unit 20 has temperature distribution data indicating the steady temperature distribution of the whole or a part of each air conditioning target space R1, R2,... RN from the acquired thermal image data, and each air conditioning target space R1. , R2,..., RN, and human distribution data indicating human distribution existing in the whole or a part thereof are extracted.

  Each infrared sensor unit 20 mainly includes a sensor unit 21 and a unit processing device 22 (see FIG. 4).

  In the following, in particular, in the air conditioning target space Rk shown in FIG. 2, the thermal image data of the air conditioning target space Rk is acquired by one infrared sensor unit 20, and the temperature distribution data and human distribution data of the air conditioning target space Rk are extracted. For example, the sensor unit 21 and the unit processing device 22 of the infrared sensor unit 20 will be described in detail.

(2-1-1) Sensor part The sensor part 21 is an example of an acquisition part. The sensor unit 21 measures the temperature distribution of the entire air-conditioning target space Rk and acquires thermal image data composed of a plurality of pixels at a plurality of points in time. Specifically, the sensor unit 21 measures the temperature distribution of the air conditioning target space Rk and acquires thermal image data composed of 256 pixels every 3 seconds.

  The sensor unit 21 has a thermopile type infrared sensor array. Specifically, the sensor unit 21 includes 16 rows × 16 rows (256 pieces) of infrared detection elements 21a (thermopiles) (see FIG. 4). Each detection element 21a detects infrared rays collected by a lens (not shown) of the sensor unit 21, and outputs a voltage corresponding to the detected amount of infrared rays. The infrared sensor unit 20 is attached to the ceiling so that a lens (not shown) of the sensor unit 21 faces downward. The sensor unit 21 uses the detection elements 21a of 16 rows × 16 rows to apply a voltage corresponding to the amount of detected infrared rays for each region obtained by dividing the 5 m × 5 m air-conditioning target space Rk vertically and horizontally in a plan view. get.

  The sensor unit 21 includes a conversion unit 21b that converts analog voltage data output from the detection element 21a into digital temperature data (see FIG. 4). The conversion unit 21b mainly includes a CPU (Central Processing Unit) and a memory such as a ROM (Read Only Memory) and a RAM (Random Access Memory). In the conversion unit 21b, the CPU executes a program stored in the memory, thereby performing a process of converting the voltage output from each detection element 21a into a temperature. For the conversion, conversion information stored in the memory, for example, a conversion formula for converting a voltage into a temperature, a conversion table in which a voltage and a temperature are related, or the like is used. The conversion unit 21b converts the voltage value output from the 256 detection elements 21a into a temperature, so that the sensor unit 21 is configured by 16 columns × 16 columns of pixels (configured by 256 pixels). Get image data. Each pixel of the thermal image data has a temperature value as information.

(2-1-2) Unit Processing Device The unit processing device 22 is a device that extracts temperature distribution data and human distribution data from the thermal image data acquired by the sensor unit 21. In other words, the unit processing device 22 is a device that generates temperature distribution data and human distribution data from the thermal image data acquired by the sensor unit 21. The temperature distribution data and human distribution data extracted from the thermal image data are transmitted to the main computer 30.

  The unit processing device 22 mainly includes a CPU and a memory such as a ROM or a RAM. In the unit processing device 22, the CPU executes various processes by executing programs stored in the memory. The unit processing device 22 is accommodated in the same housing (not shown) as the sensor unit 21.

  The unit processing device 22 mainly includes a unit communication unit 23, a unit storage unit 24, and a unit processing unit 25 as functional units (see FIG. 4).

(2-1-2-1) Unit Communication Unit The unit communication unit 23 enables connection between the unit processing device 22 and the communication network 10. The unit processing device 22 communicates with the main computer 30 via the unit communication unit 23.

(2-1-2-2) Unit Storage Unit The unit storage unit 24 stores a program to be executed by the unit processing unit 25. The unit storage unit 24 stores thermal image data acquired by the sensor unit 21 that is used by the unit processing unit 25 to be described later to generate temperature distribution data and human distribution data.

(2-1-2-3) Unit Processing Unit The unit processing unit 25 controls each unit of the infrared sensor unit 20 by executing a program stored in the unit storage unit 24.

  In addition, the unit processing unit 25 executes the program stored in the unit storage unit 24 to remove the influence of human beings present in the air-conditioning target space Rk from the thermal image data acquired by the sensor unit 21. Temperature distribution data indicating the distribution of the steady temperature of the air conditioning target space Rk is extracted. In other words, the unit processing unit 25 obtains temperature distribution data indicating the steady temperature distribution of the air-conditioning target space Rk, from which the human influence existing in the air-conditioning target space Rk is removed from the thermal image data acquired by the sensor unit 21. Generate.

  In addition, the unit processing unit 25 executes a program stored in the unit storage unit 24, thereby, based on the thermal image data acquired by the sensor unit 21, a human distribution (human position) existing in the air conditioning target space Rk. ) Is extracted. In other words, the unit processing unit 25 generates human distribution data indicating a human distribution (human position) existing in the air conditioning target space Rk from the thermal image data acquired by the sensor unit 21.

  The unit processing unit 25 mainly includes a temperature distribution data extraction unit 25a and a human distribution data extraction unit 25b as sub-function units related to extraction of temperature distribution data and human distribution data (see FIG. 4).

(2-1-2-3-1) Temperature distribution data extraction unit The temperature distribution data extraction unit 25a mainly executes processing for extracting temperature distribution data from the thermal image data stored in the unit storage unit 24. . The temperature distribution data extraction unit 25a determines that the pixel indicating the temperature peak included in the thermal image data is a pixel indicating human influence, and removes the value of the pixel indicating human influence, thereby removing the human influence. .

  Here, the pixel indicating the temperature peak included in the thermal image data includes both a pixel indicating a temporal temperature peak and a pixel indicating a spatial temperature peak.

  A pixel indicating a temporal temperature peak is when a temperature value of a pixel representing the same position (region) in the air-conditioning target space Rk is observed over time for a plurality of thermal image data acquired at a plurality of time points. Means a pixel whose temperature is temporarily increased.

  A pixel showing a spatial temperature peak means a pixel whose temperature value is locally increased in one thermal image data as compared to surrounding pixels.

  The process of extracting temperature distribution data from the thermal image data performed by the temperature distribution data extraction unit 25a will be described later.

(2-1-2-3-2) Human Distribution Data Extraction Unit The human distribution data extraction unit 25b mainly executes human distribution data extraction processing from the thermal image data stored in the unit storage unit 24. .

  The human distribution data extraction unit 25b uses the fact that the human temperature appears relatively higher than the temperature of the air in the air-conditioning target space Rk, and uses the fact that the human distribution exists in the air-conditioning target space Rk. The human distribution data indicating is extracted. For example, specifically, by using the method described in Patent Document 2 (Japanese Patent Laid-Open No. 6-160507), the position of a person is grasped from thermal image data, and human distribution data is extracted (human distribution data). Can be generated). However, the method for extracting the human distribution data from the thermal image data is not limited to the method described in Patent Document 1 (Japanese Patent Laid-Open No. 6-160507), and other methods may be used.

(2-2) Main Computer The main computer 30 distinguishes temperature distribution data and human distribution data generated by a certain infrared sensor unit 20 from temperature distribution data and human distribution data generated by other infrared sensor units 20. Receive. The main computer 30 uses the received temperature distribution data and human distribution data as temperature time-series data and human time-series data for each air conditioning target space R1, R2,. Memorize). The temperature time series data is time series temperature distribution data of each of the air-conditioning target spaces R1, R2,. The human time series data is time series human distribution data of each of the air conditioning target spaces R1, R2,.

  When a plurality of infrared sensor units 20 are installed in a certain air conditioning target space R1, R2,..., RN, all infrared rays installed in the air conditioning target spaces R1, R2,. The temperature distribution data and human distribution data extracted by the sensor unit 20 are connected (synthesized) to obtain temperature distribution data and human distribution data of the entire air-conditioning target spaces R1, R2,. It is done.

  When the main computer 30 receives a request for generating energy-saving related information for a certain air conditioning target space Rm, the main computer 30 stores the temperature time-series data of a large number of air conditioning target spaces R1, R2,. Energy saving related information for the air conditioning target space Rm is generated using the human time series data. In the main computer 30, a communication unit 31 (see FIG. 3) described later receives a request for generating energy-saving related information for the air conditioning target space Rm from the computer 50. Moreover, in the main computer 30, the input part 32 (refer FIG. 3) mentioned later receives the production | generation request | requirement of the energy saving related information for air-conditioning object space Rm. The main computer 30 transmits the generated energy saving related information for the air conditioning target space Rm to the computer 50 that has transmitted the generation request of the energy saving related space Rm for the air conditioning target space Rm to the communication unit 31. The output unit 52 (see FIG. 3) of the computer 50 presents energy saving related information for the air conditioning target space Rm. Moreover, the main computer 30 presents the generated energy saving related information for the air conditioning target space Rm to the output unit 33 (see FIG. 3) described later.

  The main computer 30 mainly includes a CPU, a memory such as a ROM and a RAM, an auxiliary storage device such as an HDD (Hard Disc Drive), and an input / output device.

  The main computer 30 mainly includes a communication unit 31, an input unit 32, an output unit 33, a storage unit 34, and a processing unit 35 as functional units (see FIG. 3).

(2-2-1) Communication Unit The communication unit 31 enables connection between the main computer 30 and the communication network 10. The main computer 30 communicates with a number of infrared sensor units 20 and a number of computers 50 via the communication unit 31.

  The communication unit 31 is an example of a reception unit. The communication unit 31 receives a request for generating energy-saving related information for the air conditioning target space Rm transmitted by the computer 50 via the communication network 10.

(2-2-2) Input unit The input unit 32 mainly includes a keyboard, a mouse, and the like. The input unit 32 receives various commands and various information from a user of the energy saving related information generation system 100 or the like.

  The input unit 32 is an example of a reception unit. The input unit 32 accepts a generation request for energy saving related information. The input unit 32 receives the generation request for energy saving related information together with the designation of the air conditioning target space Rm that is the target of generation of the energy saving related information.

(2-2-3) Output unit The output unit 33 mainly includes a display. The output unit 33 is an example of a presentation unit. The output unit 33 presents energy saving related information of the air conditioning target space Rm generated by the processing unit 35.

(2-2-4) Storage Unit The storage unit 34 includes a memory such as a ROM and a RAM, and an auxiliary storage device such as an HDD.

  The storage unit 34 stores a program to be executed by the processing unit 35.

  The storage unit 34 stores various types of information. The storage unit 34 includes a temperature time-series data storage area 34a, a human time-series data storage area 34b, a spatial information storage area 34c, and an energy saving related information storage area 34d as areas for storing information.

(2-2-4-1) Temperature time-series data storage area In the temperature time-series data storage area 34a, the air-conditioning target spaces R1, R2,. , RN, the temperature time series data relating to the temperature distribution is accumulated and stored.

  Specifically, when only one infrared sensor unit 20 is installed in a certain air conditioning target space R1, R2,..., RN, the temperature time-series data storage area 34a is installed in that space. The temperature distribution data periodically transmitted from the infrared sensor unit 20 (here, every minute) is accumulated and stored as temperature time-series data.

  On the other hand, when a plurality of infrared sensor units 20 are installed in a certain air conditioning target space R1, R2,..., RN, the temperature time-series data storage area 34a has a plurality of units installed in the space. The temperature distribution data periodically transmitted from the infrared sensor unit 20 (here, every minute) are connected (synthesized) to represent the temperature distribution of the entire space and accumulated as temperature time series data. And memorized.

(2-2-4-2) Human time-series data storage area The human time-series data storage area 34b includes air-conditioning target spaces R1, R2,. , Human time series data relating to the position of the person in the RN is accumulated and stored.

  Specifically, when only one infrared sensor unit 20 is installed in a certain air conditioning target space R1, R2,..., RN, the human time series data storage area 34b is installed in that space. The human distribution data periodically transmitted from the infrared sensor unit 20 (here, every minute) is accumulated and stored as human time-series data.

  On the other hand, when a plurality of infrared sensor units 20 are installed in a certain air conditioning target space R1, R2,..., RN, the human time-series data storage area 34b includes a plurality of units installed in the space. Human distribution data periodically transmitted from the infrared sensor unit 20 (here, every minute) are connected (synthesized) to represent the position of the person in the entire space, and as human time series data Accumulated and stored.

(2-2-4-3) Spatial information storage area The spatial information storage area 34c stores various types of information related to the air conditioning target spaces R1, R2,.

  In the spatial information storage area 34c, for example, various types of information regarding the air-conditioning target spaces R1, R2,..., RN input via the input unit 32 when the energy saving related information generation system 100 is introduced are stored. Further, for example, various information regarding the air-conditioning target spaces R1, R2,..., RN transmitted from the computer 50 are stored as appropriate in the space information storage area 34c.

  The various information related to the air conditioning target spaces R1, R2,..., RN stored in the spatial information storage area 34c includes, for example, information related to the specifications of the air conditioning target spaces R1, R2,. Information on the specifications of the air-conditioning target spaces R1, R2,..., RN includes information on the location, construction year, building structure, etc. of the air-conditioning target spaces R1, R2,. It includes information such as the areas and uses of the spaces R1, R2,. Moreover, the information regarding the specifications of the air conditioning target spaces R1, R2,..., RN includes a plan view of the air conditioning target spaces R1, R2,.

  In addition, various information related to the air-conditioning target spaces R1, R2,..., RN stored in the spatial information storage area 34c includes, for example, specifications of the devices used in the air-conditioning target spaces R1, R2,. Contains information about. Here, the equipment used in the air conditioning target spaces R1, R2,..., RN means the equipment used for the air conditioning target spaces R1, R2,. R1, R2,..., RN need not be devices installed in RN. The equipment used in the air conditioning target spaces R1, R2,... RN includes, for example, an air conditioner that performs heating and cooling in the air conditioning target spaces R1, R2,. The specifications of the devices used in the air conditioning target spaces R1, R2,..., RN include information such as the capacity (capacity) and model of the air conditioner, for example.

  In addition, various information related to the air conditioning target spaces R1, R2,..., RN stored in the space information storage area 34c includes, for example, the capacity of the air conditioning target spaces R1, R2,. , R2,..., RN).

  In addition, the information regarding the air conditioning target spaces R1, R2,..., RN shown here is an example, and the present invention is not limited to this. For example, information other than the above may be stored in the spatial information storage area 34c, and a part of the above information may not be stored.

(2-2-4-4) Energy saving related information storage area The energy saving related information storage area 34d stores energy saving related information generated by the generation unit 35b described later.

(2-2-5) Processing Unit The processing unit 35 executes various types of information by executing programs stored in the storage unit 34.

  In particular, when the communication unit 31 receives a request for generating energy-saving related information for the air-conditioning target space Rm transmitted from the computer 50, or the input unit 32 receives the energy-saving related information for the air-conditioning target space Rm. When the generation request is received, energy saving related information for the air conditioning target space Rm is generated.

  The processing unit 35 includes a similar space extraction unit 35a and a generation unit 35b as sub-function units related to generation of energy saving related information.

(2-2-5-1) Similar Space Extraction Unit When the communication unit 31 or the input unit 32 receives a generation request for energy saving related information for the air conditioning target space Rm, the similar space extraction unit 35a A process of extracting a similar space is performed. Based on the human time-series data of the air conditioning target space Rm, the similar space extraction unit 35a has a space having a usage pattern similar to that of the air conditioning target space Rm, from a large number of air conditioning target spaces R1, R2,. Extracted as a similar space to the air conditioning target space Rm.

  Specifically, the similar space extraction unit 35a determines the air conditioning target from a plurality of air conditioning target spaces R1, R2,... RN based on human time-series data for a predetermined period (here, one day) of the air conditioning target space Rm. A space having a usage pattern similar to the space Rm is extracted as a similar space of the air-conditioning target space Rm.

  The usage status pattern is, for example, a change pattern of enrollment status obtained from human time-series data. The enrollment state variation pattern is, for example, a daily enrollment rate variation pattern. The enrollment rate is the number of persons actually enrolled in the air conditioning target spaces R1, R2,... RN, the capacity of the air conditioning target spaces R1, R2,. Indicates the ratio to (set value). The enrollment rate variation pattern is a pattern of how the enrollment rate varies in one day.

  The enrollment rate variation patterns are classified into, for example, a single mountain type, a double mountain type, and a 24-hour type. The outline of each feature of the single mountain type, the double mountain type, and the 24-hour type will be described.

  In the single mountain type, there are no humans (the enrollment rate is 0) in the early morning and late at night. In the Ichiyama type, the enrollment rate starts to rise in the morning, the enrollment rate reaches its maximum at a certain time, and the enrollment rate is maintained until the evening. Then, the enrollment rate starts to drop in the evening, and the enrollment rate becomes 0 at midnight.

  Even in the two-mountain type, there are no humans (the enrollment rate is 0) in the early morning and late at night. In the Futayama type, after the enrollment rate rises to the maximum in the morning, the enrollment rate decreases once during the day. Then, after the enrollment rate rises again in the evening, the enrollment rate begins to decrease over the night, and the enrollment rate becomes zero at midnight.

  In the 24-hour type, the enrollment rate hardly fluctuates for 24 hours.

  In addition, the kind of enrollment rate fluctuation pattern is not limited to these. The enrollment rate variation pattern may be classified into more types according to the characteristics.

  The extraction process of the similar space of the air-conditioning target space Rm by the similar space extraction unit 35a will be described later.

(2-2-5-2) Generation Unit When the communication unit 31 or the input unit 32 receives a generation request for energy-saving related information for the air conditioning target space Rm, the generation unit 35b generates the temperature time-series data storage area 34a and the person. Based on the temperature time series data and the human time series data stored in the time series data storage area 34b, energy saving related information for the air conditioning target space Rm is generated.

  In particular, the generation unit 35b uses the information on the temperature time series data and the human time series data of the air conditioning target space Rm and the similar space of the air conditioning target space Rm extracted by the similar space extraction unit 35a, to use the air conditioning target space Rm. Generate energy-saving information for use.

  The energy-saving related information for the air conditioning target space Rm generated by the generation unit 35b includes information regarding the temperature distribution of the similar space of the air conditioning target space Rm. The generation unit 35b generates information related to the temperature distribution of the similar space of the air-conditioning target space Rm based on the temperature time series data of the similar space of the air-conditioning target space Rm.

  The energy-saving related information for the air conditioning target space Rm generated by the generation unit 35b includes information on the temperature distribution of the similar space of the air conditioning target space Rm and the temperature distribution for the air conditioning target space Rm corresponding to this information. Contains comparison information.

  The generation process of the energy saving related information for the air conditioning target space Rm by the generation unit 35b will be described later.

(3) Operation of Infrared Sensor Unit The operation of the infrared sensor unit 20 will be described.

  The sensor unit 21 of the infrared sensor unit 20 acquires thermal image data at a plurality of times (here, every 3 seconds). The unit processing unit 25 of the unit processing device 22 of the infrared sensor unit 20 extracts temperature distribution data from a plurality of thermal image data (generates temperature distribution data) at predetermined time intervals (here, every minute). . Further, the unit processing unit 25 extracts human distribution data from the thermal image data (generates human distribution data) every predetermined time (here, every minute). The infrared sensor unit 20 transmits temperature distribution data and human distribution data to the main computer 30 via the unit communication unit 23 at predetermined time intervals (here, every minute).

  When the main computer 30 receives the temperature distribution data and the human distribution data every minute, the temperature time series data and the human time are stored in the temperature time series data storage area 34a and the human time series data storage area 34b of the storage unit 34. These are accumulated and stored as series data.

  In addition, the acquisition frequency of the thermal image data of the sensor unit 21 shown here, the generation frequency of the temperature distribution data of the unit processing unit 25, and the transmission frequency of the temperature distribution data and the human distribution data of the infrared sensor unit 20 are examples. Yes, it is not limited to this.

  A specific operation of the infrared sensor unit 20 will be described with reference to the flowchart of FIG. Here, the specific operation of the infrared sensor unit 20 will be described by taking the infrared sensor unit 20 installed in the air conditioning target space Rk shown in FIG. 2 as an example.

  In the control of the operation of the infrared sensor unit 20, as will be described later, whether or not to execute a predetermined operation is determined depending on whether or not the two time counters T1 and T2 have counted a predetermined time. When the infrared sensor unit 20 is turned on, the time counters T1 and T2 that have been reset to 0 are started to be counted in step S0.

  In step S1, the sensor unit 21 acquires thermal image data. The thermal image data acquired by the sensor unit 21 is stored in the unit storage unit 24 of the unit processing device 22 together with the acquisition time of the thermal image data.

  FIG. 6 is an example of thermal image data acquired by the sensor unit 21. 6 is thermal image data obtained by measuring the temperature distribution of the air-conditioning target space Rk shown in FIG. 2 (the air-conditioning target space Rk at the position where a person is drawn with a circle in FIG. 2). FIG. 6 is an example of thermal image data obtained by measuring the temperature distribution of the air-conditioning target space Rk during heating.

  FIG. 6 is a diagram for showing that pixels having different temperatures exist in the thermal image data obtained for the air-conditioning target space Rk. Here, a relative temperature distribution is drawn according to the type of hatching. ing. Actually, each pixel of the thermal image data has a temperature value as information. In FIG. 6, pixels with relatively high temperatures are drawn with dots. Here, the higher the dot density, the higher the temperature of the pixel. In FIG. 6, pixels with relatively low temperatures are drawn with diagonal lines. Here, a pixel having a narrower interval between diagonal lines means that the temperature of the pixel is relatively low. Pixels that are neither dotted nor shaded mean a relatively intermediate temperature. In FIG. 6, a dot indicating that the temperature is relatively high is attached to a pixel corresponding to a position where a person is present and a pixel adjacent to the pixel. Also, the pixel on the lower left side in FIG. 6 is hatched indicating that the temperature is relatively low.

  In step S2, it is determined whether or not the value of the time counter T2 is 1 minute. That is, in step S2, it is determined whether 1 minute has elapsed since the time counter T2 reset to 0 started counting. If it is determined in step S2 that the value of the time counter T2 is 1 minute, the process proceeds to step S5 and step S6. On the other hand, if it is determined in step S2 that the value of the time counter T2 is not 1 minute (has not reached 1 minute), the process proceeds to step S3.

  In step S3, it is determined whether or not the value of the time counter T1 is 3 seconds. That is, in step S3, it is determined whether or not 3 seconds have elapsed since the time counter T1 reset to 0 has started counting. Step S3 is repeatedly executed until it is determined that the value of the time counter T1 is 3 seconds. If it is determined in step S3 that the value of the time counter T1 is 3 seconds, the process proceeds to step S4.

  In step S4, the value of the time counter T1 is reset to 0 and starts counting again. Then, it returns to step S1.

  In step S5, the values of the time counters T1 and T2 are reset to 0, and counting is started again. Then, it returns to step S1.

  In step S6, the thermal image data stored in the unit storage unit 24 is read out for generating temperature distribution data and human distribution data. Specifically, thermal image data for one minute is read in order from the oldest information among the thermal image data stored in the unit storage unit 24. As described above, since the sensor unit 21 acquires thermal image data every 3 seconds, 20 pieces of thermal image data (at a plurality of times) are read from the unit storage unit 24 in step S6.

  In addition, the process of step S6 and the process of step S7-step S11 mentioned later are performed independently of the process of step S1-step S4. That is, the thermal image data is acquired by the sensor unit 21 while the processes of Step S6 to Step S11 are being performed.

  After step S6 ends, the process proceeds to step S7 and step S9. Steps S7 and S8 and step S9 are executed in parallel.

  In step S7 and step S8, the process of extracting temperature distribution data indicating the distribution of the steady temperature of the air-conditioning target space Rk is performed from the thermal image data by removing the human influence existing in the air-conditioning target space Rk.

  First, in step S7, the temperature distribution data extraction unit 25a determines that a pixel indicating a temporal temperature peak included in the thermal image data read from the unit storage unit 24 in step S6 is a pixel indicating human influence. Then, the human influence is removed by eliminating the pixel value indicating the human influence. Specifically, in step S7, the temperature distribution data extraction unit 25a executes time peak exclusion thermal image data generation processing.

  The time peak exclusion thermal image data generation process executed by the temperature distribution data extraction unit 25a will be specifically described.

  The temperature distribution data extraction unit 25a reads the value of each pixel (the pixel value) of the thermal image data read from the unit storage unit 24 and acquired at a plurality of time points (every 3 seconds) during a predetermined period (in 1 minute). Temporal peak exclusion thermal image data is generated in which the time-series minimum value of the temperature value of each pixel is a value representing the temperature of each pixel in a predetermined period.

  With reference to FIG. 7, the generation processing of time peak exclusion thermal image data will be specifically described. Note that each thermal image data is image data of 256 pixels as described above, but in FIG. 7, only one pixel is focused on.

  The temperature distribution data extraction unit 25a reads the temperature of the pixels indicating the same position (region) in the air conditioning target space Rk of all (20) thermal image data read from the unit storage unit 24 in step S6. Know the value. For example, as shown in the upper part of FIG. 7, the temperature distribution data extraction unit 25a includes 20 temperature values (25.1, 25.1, 28.1, 25) of pixels indicating the same position in the air conditioning target space Rk. .0, ... 25.0). Then, the temperature distribution data extraction unit 25a compares the 20 temperature values and grasps the minimum value (25.0 here) as shown in the lower part of FIG. The temperature distribution data extraction unit 25a performs such processing for all 256 pixels, thereby grasping the minimum value of each pixel and generating one thermal image data having the minimum value as the temperature value of each pixel. . The thermal image data generated in this way is referred to as time peak excluded thermal image data.

  When a person moves in the air conditioning target space Rk, a temperature value is temporarily stored in a pixel corresponding to a position on the path through which the person passes among the plurality of thermal image data acquired by the sensor unit 21 every 3 seconds. In some cases, a pixel having a high temperature (indicating a temperature peak in time) is included. Here, the temperature distribution data extraction unit 25a performs the generation processing of the time peak exclusion thermal image data, so that the temporary temperature peak (for example, in FIG. (Temporary rise in temperature of 28.1 ° C.) seen in FIG. For this reason, the temperature distribution data extraction unit 25a removes the human influence by performing the generation processing of the time peak exclusion thermal image data, more specifically, the influence of the human moving in the air conditioning target space Rk. It is possible to extract the removed temperature distribution data.

  After time peak exclusion thermal image data is generated in step S7, the process proceeds to step S8.

  In step S8, the temperature distribution data extraction unit 25a determines that the pixel indicating the spatial temperature peak included in the thermal image data is a pixel indicating human influence, and excludes the value of the pixel indicating human influence. So, remove the human influence. Specifically, in step S8, the temperature distribution data extraction unit 25a determines that a pixel indicating a spatial temperature peak included in the temporal peak exclusion thermal image data generated in step S7 is a pixel indicating human influence. Then, the human influence is removed by eliminating the pixel value indicating the human influence. More specifically, in step S8, the temperature distribution data extraction unit 25a executes a spatial peak exclusion thermal image data generation process.

  The spatial peak elimination thermal image data generation process executed by the temperature distribution data extraction unit 25a will be specifically described.

  First, the temperature distribution data extraction unit 25a extracts 16 columns × 16 columns (256 pixels) constituting the temporal peak exclusion thermal image data generated based on the thermal image data in step S7 from a plurality of adjacent pixels. The process of dividing into sections is performed. For example, the temperature distribution data extraction unit 25a includes 16 columns × 16 columns of pixels of the temporal peak exclusion thermal image data acquired in step S7, and 16 pixels of 4 columns × 4 columns are defined as 16 sections. Divide into sections. (See FIG. 8).

  Next, the temperature distribution data extraction unit 25a obtains spatial peak-excluded thermal image data in which the minimum value of the pixel value (temperature value) included in each section is set to a value indicating the temperature of the pixel included in each section. Generate.

  The generation process of spatial peak exclusion thermal image data will be specifically described with reference to FIG. The time peak exclusion thermal image data is divided into 16 sections as shown in FIG. 8 by the temperature distribution data extraction unit 25a, but in FIG. 9, only one of the sections is focused.

  The temperature distribution data extraction unit 25a grasps the temperature value of 16 pixels included in one section of the time peak exclusion thermal image data. For example, the temperature distribution data extraction unit 25a, as shown in the upper part of FIG. 28.1, 26.2, ...). Then, the temperature distribution data extraction unit 25a compares the 16 temperature values and, as shown in the lower part of FIG. 9, the minimum value (here 25.0) is included in the temperature value of this section (included in this section). As a pixel temperature value). The temperature distribution data extraction unit 25a performs such processing for all the sections (16 sections). And the temperature distribution data extraction part 25a grasps | ascertains the temperature of all the divisions, and produces | generates one spatial peak exclusion thermal image data comprised by the division of 4 rows x 4 rows. This spatial peak exclusion thermal image data is temperature distribution data extracted from the thermal image data.

  When a human is staying at a certain position (a position corresponding to a pixel having thermal image data) in the air-conditioning target space Rk for a predetermined time (here 1 minute), for example, when a human is sitting on a chair and working think of. In this case, the temporal peak-excluded thermal image data includes a pixel whose temperature corresponds to a human position (in some cases, a pixel closer to that pixel) and a locally large temperature value (space). A pixel showing a typical temperature peak appears. Here, the temperature distribution data extraction unit 25a performs generation processing of the spatial peak exclusion thermal image data, so that the spatial temperature peak (e.g., 28. A locally large value) can be eliminated with respect to a surrounding temperature of 1 ° C. Therefore, the temperature distribution data extraction unit 25a performs the generation processing of the spatial peak exclusion thermal image data to remove the human influence, more specifically, particularly at the same position in the air-conditioning target space Rk for a predetermined time ( In this case, temperature distribution data from which the influence of a stationary human being is removed can be extracted.

  FIG. 10 is an example of spatial peak exclusion thermal image data (temperature distribution data extracted by the temperature distribution data extraction unit 25a) generated by the temperature distribution data extraction unit 25a. In the temperature distribution data, each section has a temperature value as information. Since the human influence is removed from the temperature distribution data, the temperature distribution data does not include a section having a relatively high temperature representing the presence of the human (see FIG. 10).

  In step S9, the human distribution data extraction unit 25b executes human distribution data extraction processing for each of the 20 thermal image data read from the unit storage unit 24 in step S6. Specifically, the human distribution data extraction unit 25b uses the fact that the human temperature appears relatively higher than the temperature of the air in the air-conditioning target space Rk, and uses the thermal image data to enter the air-conditioning target space Rk. The position of an existing person is specified, and human distribution data indicating the human distribution is extracted. As a result, the human distribution data extraction unit 25b generates 20 human distribution data (every 3 seconds).

  FIG. 11 is an example of human distribution data generated by the human distribution data extraction unit 25b. FIG. 11 shows human distribution data in the air-conditioning target space Rk shown in FIG. 2 (when the human is in a position drawn with a circle in FIG. 2). Pixels with diagonal lines are pixels indicating the presence of a human being. The human distribution data does not include temperature information.

  In step S10, the unit processing unit 25 uses the unit communication unit 23 as the main computer 30 as the temperature distribution data indicating the distribution of the steady temperature of the air conditioning target space Rk, using the spatial peak exclusion thermal image data extracted in step S8. Send to. The temperature distribution data transmitted to the main computer 30 is information associated with the acquisition time of the temperature distribution data. In other words, the temperature distribution data transmitted to the main computer 30 is data including information on the acquisition time of the temperature distribution data. Note that the acquisition time of the temperature distribution data is determined, for example, as the acquisition time of the thermal image data acquired first among the plurality of thermal image data used for extracting the temperature distribution data. The main computer 30 stores the temperature distribution data received by the main computer 30 in the temperature time-series data storage area 34a of the storage unit 34 as time-series temperature distribution data (temperature time-series data).

  In step S <b> 10, the unit processing unit 25 transmits the plurality of (20) human distribution data extracted in step S <b> 9 to the main computer 30 via the unit communication unit 23. Each human distribution data transmitted to the main computer 30 is information associated with the acquisition time of the human distribution data. In other words, the human distribution data transmitted to the main computer 30 is data including information on the acquisition time of the human distribution data. The acquisition time of the human distribution data is determined, for example, as the acquisition time of the thermal image data used for extracting each human distribution data. The main computer 30 stores the plurality of human distribution data received by the main computer 30 in the human time series data storage area 34b of the storage unit 34 as time series human distribution data (human time series data).

  The temperature distribution data and the human distribution data transmitted from the unit processing device 22 and stored in the storage unit 34 are data-compressed. Data compression reduces the data transmission time from the unit processing device 22 to the main computer 30. Further, the storage capacity of the storage unit 34 in which data is stored can be suppressed.

  Thereafter, in step S <b> 11, the thermal image data for which the temperature distribution data and the human distribution data have been extracted is deleted from the unit storage unit 24.

  Steps S6 to S11 are executed when it is determined again in step S2 that the time counter T2 has reached 1 minute.

  In addition, operation | movement of the infrared sensor unit demonstrated here is an example, Comprising: It is not limited to this.

  For example, although step S7 and step S8 and step S9 are performed in parallel here, it is not limited to this, and step S9 may be performed after execution of step S7 and step S8. .

  Further, for example, step S9 need not be executed after one minute has elapsed, and human distribution data may be generated each time the sensor unit 21 acquires thermal image data. Further, in this case, the human distribution data may be transmitted to the main computer 30 every time human distribution data is generated, instead of being collectively transmitted to the main computer 30 in step S10. .

  Further, for example, the thermal image data in the unit storage unit 24 may not be deleted in step S11, and the amount of thermal image data stored in the unit storage unit 24 exceeds the storage capacity of the unit storage unit 24. Alternatively, the first thermal image data may be deleted in order.

(4) Energy Saving Related Information Generation Processing The energy saving related information generation processing for the air conditioning target space Rm (including extraction processing of a similar space of the air conditioning target space Rm) by the processing unit 35 of the main computer 30 is shown in the flowchart of FIG. Will be described.

  The generation process of energy saving related information is executed when the communication unit 31 or the input unit 32 receives a generation request of energy saving related information for the air conditioning target space Rm.

  First, in step S31, the similar space extraction unit 35a reads the human time series data of the air conditioning target space Rm for the most recent day from the human time series data storage area 34b.

  Next, in step S32, the similar space extraction unit 35a calculates the number of persons enrolled in the air conditioning target space Rm by time based on the person time-series data read in step S31. Then, the similar space extraction unit 35a divides the calculated number of persons enrolled in the air conditioning target space Rm by time by the capacity of the air conditioning target space Rm stored in the spatial information storage area 34c. The enrollment rate of the air conditioning target space Rm is calculated according to time. Then, the similar space extraction unit 35a is configured such that the enrollment rate of the air-conditioning target space Rm according to time is any of the enrollment rate variation pattern types (for example, one mountain type, two mountain type, and 24 hour type) prepared in advance. Judge whether it is close to the kind.

  For example, the similar space extraction unit 35a determines that the enrollment rate variation pattern of the air-conditioning target space Rm is a 24-hour type when the enrollment rate is 0 for less than a predetermined time in 24 hours. In addition, for example, the similar space extraction unit 35a derives a polynomial that approximates the enrollment rate of the calculated air-conditioning target space Rm by hour, for example, using the least square method, and the curve represented by the polynomial is a 24-hour medium. Whether the variation pattern of the enrollment rate of the air-conditioning target space Rm is a single mountain type or a double mountain type is determined based on how many local maximum values there are. However, the determination method of the variation pattern of the enrollment rate in the air-conditioning target space Rm by the similar space extraction unit 35a is an example, and is not limited to this.

  Next, in step S33, the similar space extraction unit 35a obtains human time series data for the most recent day in other target spaces (air conditioning target spaces R1, R2,... RN other than the air conditioning target space Rm). Read from the human time-series data storage area 34b.

  Next, in step S34, the similar space extraction unit 35a determines the type of variation pattern of the enrollment rate for the air conditioning target spaces R1, R2,... RN other than the air conditioning target space Rm. The determination method of the variation pattern type of the enrollment rate of the air-conditioning target spaces R1, R2,... RN other than the air-conditioning target space Rm by the similar space extraction unit 35a is the enrollment rate of the air-conditioning target space Rm described in step S32. Since the method is the same as the method for determining the type of variation pattern, the description is omitted here.

  Next, in step S35, the similar space extraction unit 35a has the enrollment rate variation pattern of the enrollment rate of the air conditioning target space Rm in the air conditioning target spaces R1, R2, ... RN other than the air conditioning target space Rm. A space that is the same as the type of variation pattern is extracted as a similar space to the air-conditioning target space Rm.

  Next, in step S36, the generation unit 35b reads the temperature time-series data for the most recent day for the air-conditioning target space Rm from the temperature time-series data storage area 34a. Moreover, the production | generation part 35b reads the human time series data for the latest one day from the human time series data storage area 34b about the air-conditioning target space Rm.

  Next, the generation unit 35b proceeds to step S100, step S120, and step S140, and uses the information read out in step S36 to set 3 for the air-conditioning target space Rm as in the following (a) to (c). Calculate one value.

(A) Ratio of enrolled area in comfortable temperature area In step S100, the generation unit 35b calculates the ratio of enrolled area in the comfortable temperature area for the air conditioning target space Rm. Specifically, the generation unit 35b calculates the ratio of the enrollment area in the comfortable temperature area for the time zone in which a person is enrolled in the air conditioning target space Rm. The comfortable temperature area means a section determined from the temperature time series data to be in a temperature range (set value) that a person feels comfortable. The enrollment area means a section where a human is present in each section of the temperature time-series data. The ratio of the enrolled area in the comfortable temperature area means the ratio of the number of sections in the comfortable temperature area and enrolled area to the total number of sections in the comfortable temperature area. The ratio of the enrolled area in the comfortable temperature area of the air conditioning target space Rm is an example of information regarding the temperature distribution of the air conditioning target space Rm.

  Specifically, the generation unit 35b calculates the ratio of the enrolled area in the comfortable temperature area, for example, as in the flowchart of FIG.

  First, in step S101, the generation unit 35b determines the time during which a person is present in the air-conditioning target space Rm based on the human time-series data read in step S36.

  Next, in step S102, the generation unit 35b determines one temperature time-series data to be used for calculation processing in step S104 next time.

  Specifically, the generation unit 35b is temperature time-series data of the time determined that a person is present in the air conditioning target space Rm in step S101, and has not been used yet in the process of step S104 described later. Among the temperature time series data, the temperature time series data of the earliest time is determined as the temperature time series data used for the calculation process. When the process of step S102 is performed for the first time after step S101 is performed, the earliest temperature time-series data of the time determined that a person is enrolled in the air conditioning target space Rm in step S101. The temperature time series data of the time is determined as the temperature time series data used for the calculation process.

  Next, in step S103, the generation unit 35b determines human time-series data used for calculation processing in step S104 next time.

  Specifically, in step S103, the generation unit 35b determines, from the human time series data read in step S36, human time series data having the same acquisition time as the one temperature time series data determined in step S102. . Here, as described above, the infrared sensor unit 20 generates one piece of temperature distribution data per minute, whereas 20 pieces of human distribution data are generated per minute. Therefore, here, the value in seconds of the acquisition time of the human time series data is ignored, and the temperature time series data determined in step S102 and the 20 human time series data whose acquisition times match up to the minute unit. In step S104, it is determined as the human time series data used for the calculation process.

  Next, in step S104, the generation unit 35b uses the temperature time-series data determined in step S102 and the human time-series data determined in step S103 to calculate the temperature time-series data of the comfortable temperature area and the enrollment area. The ratio of the number of partitions to the total number of partitions in the comfortable temperature area is calculated.

  Specifically, the generation unit 35b first converts each of the 20 human time series data determined in step S103 (for example, the human time series data as shown in FIG. 11) into the temperature time series data ( For example, the number of compartments of the temperature time series data that is the comfortable temperature area and the enrollment area is acquired for each person time series data. Here, the number of sections of the temperature time-series data that is the comfortable temperature area and the enrollment area is obtained by the number of human time-series data determined in step S103 (that is, 20).

  Moreover, the production | generation part 35b acquires the total number of divisions of a comfortable temperature area using the temperature time series data determined by step S102.

  And the production | generation part 35b calculates the ratio which occupies for the total number of divisions of the comfortable temperature area of the number of the divisions of the temperature time series data of a comfortable temperature area and an enrollment area. Specifically, the generation unit 35b uses the acquired number of compartments of the temperature time-series data of the 20 comfortable temperature areas and enrollment areas to obtain the number of compartments of the temperature time-series data of the comfort temperature areas and enrollment areas. The average value of the ratio to the total number of sections in the comfortable temperature area is calculated.

  Next, in step S105, it is determined whether or not all the temperature time-series data of the time determined as the time in which the person is present in the air-conditioning target space Rm in step S101 has been used for the processing in step S104. .

  If it is determined that part of the temperature time-series data at the time when it is determined in step S101 that a person is present in the air-conditioning target space Rm is not used in the process of step S104, the process returns to step S102. In the processing from step S102 to step S104, it is determined in step S105 that all the temperature time-series data of the time determined that a person is present in the air conditioning target space Rm in step S101 has been used for the processing in step S104. Repeat until

  If it is determined in step S105 that all the temperature time-series data of the time determined that a person is present in the air-conditioning target space Rm in step S101 has been used for the processing in step S104, the process proceeds to step S106.

  In step S106, the generation unit 35b performs a process of calculating an average of the ratio of the number of sections that are the comfortable temperature area and the enrollment area that is repeatedly calculated in step S104 to the total number of sections in the comfortable temperature area. Thus, the value calculated in step S106 is the ratio of the enrolled area in the comfortable temperature area of the air conditioning target space Rm.

(B) Spatial average temperature during unmanned operation In step S120, the generation unit 35b calculates a spatial average temperature during unmanned operation for the air conditioning target space Rm. The unmanned time is a time when it is determined from the human time-series data that no person exists in the air-conditioning target space Rm. The space average temperature is the average temperature of the entire air conditioning target space Rm.

  In step S120, specifically, the generation unit 35b determines a time during which no person is present in the air-conditioning target space Rm based on the person time-series data read in step S36. Next, the generation unit 35b determines temperature time-series data of the time (no-at-home time) determined that no person is present in the air conditioning target space Rm among the temperature time-series data read in step S36. And the production | generation part 35b calculates the average temperature of air-conditioning object space Rm in the acquisition time of each temperature time series data using the temperature information of each division about each determined temperature time series data. Furthermore, the generation unit 35b calculates the average temperature of the air-conditioning target space Rm in the entire unmanned period using the average temperature of the air-conditioning target space Rm at the acquisition time of each temperature time series data.

(C) Low enrollment rate time In step S140, the generation unit 35b causes the enrollment rate to be a value within a predetermined low enrollment rate range (for example, greater than 0% and less than 10%) for the air conditioning target space Rm. Is calculated as the low enrollment rate time. The enrollment rate is as shown in the description of the similar space extraction unit 35a.

  Specifically, the generation unit 35b grasps the number of persons enrolled in the air-conditioning target space Rm for each person time series data based on the person time series data read in step S36. And the production | generation part 35b divides the number of persons grasped | ascertained according to human time series data by the number of capacity | capacitances of the air-conditioning object space Rm memorize | stored in the spatial information storage area 34c, and thereby the enrollment rate according to human time series data calculate. The generation unit 35b grasps the number of human time-series data whose calculated enrollment rate falls within the low enrollment rate range, and obtains the human time-series data acquisition interval, in other words, the human distribution data acquisition interval (here, 3 seconds). ) To calculate the low enrollment time of the air conditioning target space Rm.

  The calculation results of step S100, step S120, and step S140 are stored in the energy saving related information storage area 34d of the storage unit 34.

  When step S100, step S120, and step S140 are completed, the process proceeds to step S37.

  In step S37, the generation unit 35b reads the temperature time-series data for the most recent day from the temperature time-series data storage area 34a for the similar space of the air-conditioning target space Rm. Moreover, the production | generation part 35b reads the human time series data for the latest one day from the human time series data storage area 34b about the similar space of the air-conditioning target space Rm.

  Next, it progresses to step S200, step S220, and step S240, and the production | generation part 35b uses the information read by step S37, respectively, the ratio of the enrollment area which occupies for each comfortable temperature area according to space, and the space average temperature at the time of unattended , And low enrollment time.

Steps S200, S220, and S240 are:
1) The calculation target space is not the air conditioning target space Rm, but is a similar space to the air conditioning target space Rm. 2) Normally, not a single space, but a plurality of spaces, each of the enrolled area in the comfortable temperature area. It differs from the processing of Step S100, Step S120, and Step S140 in that the ratio, the space average temperature during unattended, and the low enrollment rate time are calculated, but for other points, Step S100, Step S120, and Since it is the same as the process of step S140, description is abbreviate | omitted.

  The calculation results of step S200, step S220, and step S240 are stored in the energy saving related information storage area 34d of the storage unit 34.

  In addition, the ratio of the enrolled area in the comfortable temperature area in the similar space of the air conditioning target space Rm and the air conditioning target space Rm calculated in step S100, step S120, step S140, step S200, step S220, and step S240, unmanned The time space average temperature and the low enrollment rate time are examples of energy saving related information of the air conditioning target space Rm.

  In particular, the ratio of the enrolled area in the comfortable temperature area of the similar space of the air-conditioning target space Rm is an example of information regarding the temperature distribution of the similar space of the air-conditioning target space Rm. Further, the ratio of the enrolled area in the comfortable temperature area of the air-conditioning target space Rm is information corresponding to the ratio of the enrolled area in the comfortable temperature area of the similar space of the air-conditioned target space Rm.

  When step S200, step S220, and step S240 are completed, the process proceeds to step S38.

  In step S38, the generation unit 35b uses the information (calculated value) about the air conditioning target space Rm obtained in steps S100, S120, and S140 and the similar space of the air conditioning target space Rm obtained in steps S200, S220, and S240. Information (calculated value) and comparison information are generated.

  Specifically, the generation unit 35b ranks the air-conditioning target space Rm and the air-conditioning target space Rm similar spaces with respect to the ratio of the enrolled area in the comfortable temperature area, the space average temperature during unattended, and the low enrollment rate time, respectively. Is generated.

  For example, the ratio of the enrolled area in the comfortable temperature area means that the smaller the value is, the more air conditioning is performed in a space where there is no human being. Therefore, the generation unit 35b generates a ranking for the air conditioning target space Rm and the similar space of the air conditioning target space Rm so that the higher the ratio of the enrolled area in the comfortable temperature area, the higher the ranking.

  Further, for example, the space average temperature during unattended means that the lower the temperature during heating and the higher the temperature during cooling, the less wasteful energy input. Therefore, the generation unit 35b generates rankings for the air-conditioning target space Rm and the similar space of the air-conditioning target space Rm so that the ranking becomes higher as the useless energy is input.

  Further, for example, if the enrollment time is low, it means that the shorter the time, the less the amount of energy used per person. Therefore, the generation unit 35b generates a ranking for the air conditioning target space Rm and the similar space of the air conditioning target space Rm so that the ranking is higher as the low enrollment rate time is shorter.

(5) Energy saving related information presentation process The energy saving related information for the air conditioning target space Rm generated by the generation unit 35b and stored in the energy saving related information storage area 34d is a request for generating energy saving related information for the air conditioning target space Rm. The output is presented to the output unit 52 of the computer 50 and the output unit 33 of the main computer 30. On the other hand, when a generation request for energy saving related information for the air conditioning target space Rm is input to the input unit 32, the energy saving for the air conditioning target space Rm generated by the generation unit 35b and stored in the energy saving related information storage area 34d. The related information is presented to the output unit 33.

  Specifically, the output unit 52 and the output unit 33 present energy saving related information in the following format.

  For example, the ratio of the enrollment area in the comfortable temperature area, the spatial average temperature when there is no person, and the low enrollment rate time are presented as a histogram representing the frequency distribution. At this time, the output unit 52 and the output unit 33 are presented so as to be able to determine in which class of the histogram the air-conditioning target space Rm is located. For example, in the output unit 52 and the output unit 33, only the histogram including the air-conditioning target space Rm is presented in different colors, so that it can be determined that the air-conditioning target space Rm belongs to the class. In addition, the output unit 52 and the output unit 33 include the ratio of the enrolled area in the comfortable temperature area of the energy saving related information in the air-conditioning target space Rm and the similar space of the air-conditioning target space Rm, the space average temperature during unattended, and low Ranking (comparison information) about enrollment rate time is displayed.

  The output unit 52 and the output unit 33 receive various instructions from the input unit 51 of the computer 50 and the input unit 32 of the main computer 30, so that various types of information stored in the spatial information storage area 34 c are stored. It is configured to be displayable. For example, the output unit 52 and the output unit 33 include information regarding the specifications of the air conditioning target space Rm and the similar space of the air conditioning target space Rm, for example, a similar space of the air conditioning target space Rm and the air conditioning target space Rm. The building construction year, the air-conditioning target space Rm, the usage of the space similar to the air-conditioning target space Rm, etc. are displayed. Further, for example, the output unit 52 and the output unit 33 display information about the specifications of the air-conditioning target space Rm and the equipment installed in the air-conditioning target space Rm, for example, the capacity (capacity) of the air conditioner, the model, and the like. Is done.

(6) Features (6-1)
The energy-saving related information generation system 100 according to the present embodiment includes a storage unit 34, a communication unit 31 and an input unit 32 as examples of a reception unit, a similar space extraction unit 35a, and a generation unit 35b. The storage unit 34 includes, for a large number of air-conditioning target spaces R1, R2,..., RN, human time-series data relating to human positions in the air-conditioning target spaces R1, R2,. R1, R2,..., Temperature time series data related to the temperature distribution in RN are accumulated and stored. The communication part 31 and the input part 32 receive the production | generation request | requirement of the energy saving related information for air-conditioning object space Rm contained in many air-conditioning object space R1, R2, ..., RN. The similar space extraction unit 35a is based on the human time-series data of the air-conditioning target space Rm, and has a usage pattern similar to the air-conditioning target space Rm from the multiple air-conditioning target spaces R1, R2,. To extract. The generation unit 35b generates information related to the temperature distribution of the similar space based on the temperature time series data of the similar space (the ratio of the enrolled area in the comfortable temperature area) as the energy saving related information for the air conditioning target space Rm.

  Here, based on the time-series data regarding the human position, a similar space having a similar usage pattern to the air conditioning target space Rm to be evaluated is extracted, and the temperature of the similar space is used as energy saving related information for the air conditioning target space Rm. Information about the distribution is generated. Therefore, it is possible to appropriately perform the relative evaluation of the air conditioning target space Rm based on the generated energy saving related information.

(6-2)
In the energy-saving related information generation system 100 according to the present embodiment, the similar space extraction unit 35a changes the enrollment state obtained from the person time-series data in a large number of air-conditioning target spaces R1, R2,. A space whose pattern is similar to the change pattern of the enrollment state obtained from the human time-series data in the air conditioning target space Rm is extracted as a similar space.

  Here, since the space where the change pattern of the enrollment state is similar to the air-conditioning target space Rm is extracted as a similar space, based on the information on the temperature distribution of the similar space generated as the energy saving related information, the air-conditioning target space Rm Relative evaluation can be performed appropriately.

(6-3)
In the energy-saving related information generation system 100 according to the present embodiment, the generation unit 35b includes, as energy-saving related information, information related to the temperature distribution in the similar space (ratio of enrolled area in the comfortable temperature area) and information related to the temperature distribution in the similar space. The ranking is generated as comparison information with the information about the temperature distribution (the ratio of the enrolled area in the comfortable temperature area) about the air-conditioning target space Rm corresponding to.

  Here, a ranking that compares information about the temperature distribution of the air conditioning target space Rm and the similar space of the air conditioning target space Rm (the ratio of the enrolled area in the comfortable temperature area) is generated as energy saving related information for the air conditioning target space Rm. Therefore, it is easy to relatively evaluate the energy usage status of the air conditioning target space Rm using the energy saving related information.

(6-4)
The energy saving related information generation system 100 according to the present embodiment includes an output unit 33 of the main computer 30 and an output unit 52 of the computer 50 as examples of a presentation unit that presents energy saving related information. The storage unit 34 stores information on the specifications of the air-conditioning target spaces R1, R2,..., RN, and information on the specifications of the devices (air conditioners) used in the air-conditioning target spaces R1, R2,. Remember further. The output unit 33 and the output unit 52 include information on the specifications of the air-conditioning target spaces R1, R2,..., RN, which are stored in the storage unit 34, for the similar spaces of the air-conditioning target space Rm and the air-conditioning target space Rm. , Information regarding the specifications of the equipment used in each air conditioning target space R1, R2,.

  Here, the specifications of the air-conditioning target spaces R1, R2,..., RN and the equipment used in the air-conditioning target spaces R1, R2,. Specifications can be presented, and the difference between various specifications of the air conditioning target space Rm and the similar space of the air conditioning target space Rm can be grasped. Easy.

(6-5)
In the energy-saving related information generation system 100 according to the present embodiment, the temperature time-series data is the air-conditioning target spaces R1, R2,..., From which the human influence existing in the air-conditioning target spaces R1, R2,. ..Time series data of RN steady temperature distribution.

  Here, the temperature time-series data used when generating information related to the temperature distribution as the energy-saving related information is the distribution of the steady temperature of the air-conditioning target spaces R1, R2,. Since it is time-series data, it is easy to appropriately perform relative evaluation of the air-conditioning target space Rm.

(7) Modifications Modifications of the above embodiment are shown below. The following modifications may be used in combination with some or all of the other modifications as long as they do not contradict each other.

(7-1) Modification A
In the above embodiment, the temperature distribution data and the human distribution data are acquired by the infrared sensor unit 20, but the present invention is not limited to this.

  The energy-saving related information generation system 100 can capture, for example, a large number of temperature sensors arranged in the air conditioning target spaces R1, R2,..., RN and the entire range of the air conditioning target spaces R1, R2,. One or a plurality of omnidirectional cameras may be provided. The energy saving related information generation system 100 may be configured to be able to acquire information similar to the above temperature distribution data using a temperature sensor and information similar to the above human distribution data using an omnidirectional camera. However, as in the above embodiment, it is possible to reduce the number of devices constituting the energy saving related information generation system 100 by acquiring the temperature time series data and the human time series data from the thermal image data obtained from the infrared sensor unit 20. It is economical.

  For example, the energy-saving related information generation system 100 may not include a device that acquires temperature distribution data and human distribution data as a configuration. For example, the energy saving related information generation system 100 is connected to an external database storing information similar to temperature time series data and human time series data via the communication network 10 instead of having the infrared sensor unit 20. May be. The processing unit 35 of the main computer 30 may extract a similar space of the air conditioning target space Rm by using an external database as a storage unit, and generate energy saving related information for the air conditioning target space Rm.

(7-2) Modification B
In the above embodiment, the unit processing unit 25 of the unit processing device 22 included in the infrared sensor unit 20 extracts the temperature distribution data and the human distribution data, but the present invention is not limited to this. For example, the main computer 30 may receive the thermal image data acquired by the sensor unit 21, and the processing unit 35 of the main computer 30 may perform a process of extracting temperature distribution data and human distribution data from the thermal image data.

(7-3) Modification C
In the above-described embodiment, the influence of humans existing in the air-conditioning target spaces R1, R2,... RN is removed from the temperature time-series data, but the present invention is not limited to this. From the temperature time series data, the human influence existing in the air-conditioning target spaces R1, R2,. However, when the human influence existing in the air conditioning target spaces R1, R2,... RN is not removed from the temperature time series data, the temperature distribution of the air conditioning target spaces R1, R2,. Since there is a possibility of erroneously grasping, it is preferable that the influence of human beings present in the air-conditioning target spaces R1, R2,.

(7-4) Modification D
In the above embodiment, the energy saving related information for the air conditioning target space Rm is presented to the output unit 33, but the present invention is not limited to this, and the energy saving related information may not be presented to the output unit 33. Moreover, in the said embodiment, although the input part 32 receives the production | generation request | requirement of the energy saving related information for air-conditioning object space Rm, it is not limited to this, The input part 32 is the energy saving related information for air conditioning object space Rm. The generation request may not be accepted.

(7-5) Modification E
In the said embodiment, it is comprised from the computer 50 to the communication part 31 of the main computer 30 so that the energy saving related information for air-conditioning object space Rm can be transmitted. Moreover, in the said embodiment, the output part 52 of the computer 50 is comprised so that the energy saving related information for air-conditioning object space Rm can be shown. However, the present invention is not limited to this, and the energy saving related information generation system 100 may not include the computer 50 as a configuration.

  In this case, for example, the input unit 32 receives a request for generating energy saving related information for the air conditioning target space Rm, and the output unit 33 presents the energy saving related information for the air conditioning target space Rm.

(7-6) Modification F
In the said embodiment, the similar space extraction part 35a makes air-conditioning object space R1, R2, ... RN with the same kind of enrollment rate fluctuation pattern the same air-conditioning object space Rm as the similar space of air-conditioning object space Rm. Although it extracts, it is not limited to this.

  For example, the similar space extraction unit 35a extracts air-conditioning target spaces R1, R2,... RN having the same type of enrollment rate variation pattern as the air-conditioning target space Rm as similar spaces of the air-conditioning target space Rm. Also good. For example, the type of enrollment rate variation pattern for one week is a weekly holiday 1 day type, a weekly holiday 2 day type, a weekend business type, or the like.

  In addition, the similar space extraction unit 35a has the same type of enrollment rate fluctuation pattern as the air-conditioning target space Rm and the same type of enrollment rate change pattern for one week as the air-conditioning target space Rm. , R2,... RN may be extracted as a similar space to the air conditioning target space Rm.

  Further, the similar space extraction unit 35a may provide information other than the enrollment rate variation pattern, for example, the area of the air conditioning target spaces R1, R2,... RN stored in the spatial information storage area 34c, or the air conditioning target spaces R1, R2. ,..., RN usage information and the like may be used together to extract a similar space of the air-conditioning target space Rm.

(7-7) Modification G
In the above embodiment, the generation unit 35b generates, as the energy saving related information, the ratio of the enrolled area occupying the comfortable temperature area, the spatial average temperature during unattended, and the low enrollment rate time, but the energy saving related information generated by the generating unit 35b The information is not limited to this. For example, the generation unit 35b may calculate the ratio of the comfortable temperature area in the enrolled area with respect to the time when the person is enrolled in the air conditioning target space Rm. The ratio of the comfortable temperature area to the enrolled area means the ratio of the number of temperature time series data sections in the enrolled area and the comfortable temperature area to the number of temperature time series data sections in the enrolled area. Here, the ratio of the dissatisfied person regarding the thermal environment can be predicted by calculating the ratio of the comfortable temperature area in the enrolled area. And based on the ratio of the dissatisfied person estimated, the air conditioning target space Rm and the similar space of the air conditioning target space Rm can be relatively compared.

(7-8) Modification H
In the above embodiment, only the storage unit 34 of the main computer 30 functions as a storage unit, but the present invention is not limited to this. For example, the energy saving related information generation system 100 may include an external database 34 ′ as a storage unit in addition to the storage unit 34 of the main computer 30 (see FIG. 14). The external database 34 ′ is configured to be able to communicate with the main computer 30 via the communication network 10.

  In the external database 34 ′, for example, information related to the power consumption of the air conditioner used for air conditioning of the air conditioning target spaces R1, R2,. Then, when the similar space extraction unit 35a extracts the similar space of the air conditioning target space Rm, the generation unit 35b extracts the power consumption of the air conditioner between the air conditioning target space Rm and the similar space of the air conditioning target space Rm from the external database 34 ′. You may acquire the information about. And the production | generation part 35b is the information regarding the power consumption of the air conditioning apparatus used for the air conditioning of the air conditioning object space Rm, the information regarding the power consumption of the air conditioning apparatus used in the similar space of the air conditioning object space Rm, The comparison information may be generated as energy saving related information.

  For example, in the external database 34 ′, the power consumption of the air conditioners R1, R2,... RN is divided by the area of the air conditioners R1, R2,. The energy consumption basic unit per unit floor area may be stored for each air conditioning target space R1, R2,. The generation unit 35b may generate the ranking of the air conditioning target space Rm and the similar space of the air conditioning target space Rm based on this information. For example, the generation unit 35b has a similar space between the air conditioning target space Rm and the air conditioning target space Rm so that the lower the value of the energy consumption basic unit, the higher the ranking of the energy consumption basic unit per unit floor area of the air conditioner. May be generated.

  Further, in the external database 34 ′, the power consumption of the air conditioners in the air conditioning target spaces R1, R2,... RN is calculated from the human time series data of the air conditioning target spaces R1, R2,. The energy consumption basic unit of the air conditioner per unit number divided by the average number of enrolled persons in the air conditioning target spaces R1, R2,... RN is stored for each air conditioning target space R1, R2,. May be. The generation unit 35b may generate the ranking of the air conditioning target space Rm and the similar space of the air conditioning target space Rm based on this information.

  When the air conditioner uses energy other than electricity (for example, gas or the like), the external database 34 ′ stores, for example, information on the consumption amount of energy other than electricity of the air conditioner. Also good.

  By being configured as described above, it is easy to relatively evaluate the energy usage status of the air conditioning target space Rm using the energy saving related information.

  In addition, although the information regarding the power consumption of the air conditioner of air-conditioning object space R1, R2, ... RN was stored in the external database 34 'here, it is not limited to this. For example, the main computer 30 and a power meter (not shown) installed in the air conditioning target spaces R1, R2,... RN are configured to be communicable, and the air conditioning target spaces R1, R2 are stored in the storage unit 34 of the main computer 30. ,... May be configured to store information related to the power consumption of the RN air conditioner.

  Further, here, the external database 34 ′ stores information on the power consumption of the air conditioners in the air conditioning target spaces R 1, R 2,... RN, but is not limited thereto. For example, the external database 34 ′ may store information related to power consumption of lighting devices and OA devices used in the air conditioning target spaces R 1, R 2,. Similarly to the above, the generation unit 35b may generate, as energy saving related information, comparison information on information regarding power consumption between the air-conditioning target space Rm and a similar space of the air-conditioning target space Rm for these devices. .

(7-9) Modification I
In the external database 34 ′ of the modified example G, in addition to the information regarding the power consumption of the air conditioners in the air conditioning target spaces R1, R2,. Instead of the information on the power consumption of the air conditioner, information on the contract power of the air conditioning target spaces R1, R2,..., RN may be stored. When an instruction is given from the input unit 51 of the computer 50 or the input unit 32 of the main computer 30, the output unit 52 of the computer 50 and the output unit 33 of the main computer 30 are stored in the external database 34 ′. The contracted power of the air conditioning target space Rm and the similar space of the air conditioning target space Rm may be displayed.

  Here, the difference in contract power between the air-conditioning target space Rm and the similar space of the air-conditioning target space Rm can be grasped, so it is easy to examine measures for promoting energy saving using this. is there.

  Here, the external database 34 ′ stores information on the contract power of the air conditioning target spaces R 1, R 2,..., RN, but is not limited to this. For example, information regarding the contracted power of the air conditioning target spaces R1, R2,..., RN input from the input unit 51 of the computer 50 is transmitted to the main computer 30, and the air conditioning target spaces R1, R2,. .., RN contract power may be stored.

(7-10) Modification J
In the above embodiment, the storage unit 34 of the main computer 30 includes the temperature time series data storage area 34a, the human time series data storage area 34b, the spatial information storage area 34c, and the energy saving related information storage area 34d. Is not to be done.

  For example, the external database 34 ′ of Modification G may be provided with part or all of a temperature time-series data storage area, a human time-series data storage area, a spatial information storage area, and an energy saving related information storage area. The illustration is omitted.

  The energy-saving related information generation system according to the present invention takes into account the use status of a space by a user when generating information about the temperature distribution of another space in order to relatively evaluate the information about the temperature distribution of a certain space. It is useful as an energy saving related information generation system for generating information related to temperature distribution in an appropriate space for comparison.

31 Communication Department (Reception Department)
32 Input part (reception part)
33 Output unit (presentation unit)
34 storage unit 35a similar space extraction unit 35b generation unit 52 output unit (presentation unit)
100 Energy saving related information generation system R1, R2, ... RN Air conditioning target space Rm 1st space

JP 2000-251189 A JP-A-6-160507

Claims (6)

For a large number of air-conditioning target spaces (R1, R2,... RN), human time-series data relating to human positions in each air-conditioning target space, and temperature time-series data relating to temperature distribution in each air-conditioning target space; A storage unit (34) for accumulating and storing
Receiving units (31, 32) that receive generation requests for energy-saving related information for the first space (Rm) included in a large number of air-conditioning target spaces;
A similar space extraction unit (35a) for extracting a similar space having a usage pattern similar to that of the first space from a number of the air-conditioning target spaces based on the human time-series data of the first space;
A generator (35b) that generates information on the temperature distribution of the similar space based on the temperature time-series data of the similar space as the energy-saving related information for the first space;
An energy saving related information generation system (100) comprising: In the similar space extraction unit, the enrollment state variation pattern obtained from the person time-series data in a large number of the air-conditioning target spaces has the enrollment state variation obtained from the person time-series data in the first space. A second space similar to the pattern is extracted as the similar space;
The energy saving related information generation system according to claim 1. The generation unit further includes, as the energy saving related information, comparison information between information on the temperature distribution of the similar space and information on the temperature distribution of the first space corresponding to the information on the temperature distribution of the similar space, Generate,
The energy saving related information generation system according to claim 1 or 2. The storage unit further accumulates and stores information on energy consumption of devices used in each of the air-conditioning target spaces,
The generation unit compares the information on the energy consumption of the device used in the first space with the information on the energy consumption of the device used in the similar space as the energy saving related information. Generate more information,
The energy-saving related information generation system according to any one of claims 1 to 3. A presentation unit (33, 52) for presenting the energy-saving related information;
Further comprising
The storage unit further stores at least one of information on specifications of the air-conditioning target spaces, information on specifications of the devices used in the air-conditioning target spaces, and information on contract power of the air-conditioning target spaces. ,
The presenting unit stores information on the specifications of the air-conditioning target spaces stored in the storage unit and specifications of the devices used in the air-conditioning target spaces, at least one of the first space and the similar space. And at least one of information on contract electric power of each air-conditioning target space is further presented.
The energy saving related information generation system according to claim 4. The temperature time-series data is time-series data of the distribution of the steady temperature of the air-conditioning target space, which removes the human influence existing in the air-conditioning target space.
The energy-saving related information generation system according to any one of claims 1 to 5.

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