JP6038677B2 - Data processing system and program - Google Patents

Description

  Embodiments described herein relate generally to a data processing system and program that can be used for building performance evaluation and the like.

  In recent years, attention has been focused on energy saving of buildings. In Japan, there is known a building performance evaluation system called CASBEE (Comprehensive Assessment System for Built Environment Efficiency). Against this background, attention is being focused on BEMS (Building Energy Management System).

  In the next-generation BEMS, sensors for grasping the current situation play an important role. For example, it is considered to control lighting and air conditioning based on the result of sensing a person with an image sensor. In order to ensure the comfort and productivity of workers in an energy-saving environment, the role of the sensor for grasping the situation is great.

  By the way, it is difficult to verify in advance in the design stage the energy saving and comfort of a building (hereinafter collectively referred to as an evaluation index). At present, the evaluation index is verified afterwards from the power consumption measured since the lighting and air conditioning of the completed building started operation, and questionnaires to the occupants. Although there are attempts to evaluate comfort by evaluating the seating rate, it is difficult to say that such a rough verification represents an accurate actual situation.

  Therefore, it has been proposed to use simulation so that the evaluation index can be verified in advance. If the evaluation index after completion can be accurately simulated, the installation position, number, and required specifications of lighting and air conditioning can be selected accurately from the beginning of the design.

JP 2009-96612 A JP 2010-200823 A

  In general, this type of simulator is input with data reflecting human positions or population distribution in a building (hereinafter referred to as population distribution data). Of course, the success or failure of the simulation depends greatly on the superiority or inferiority of the input data. In other words, if population distribution data that correctly represents the actual situation cannot be prepared, a correct evaluation index cannot be obtained even if simulation is executed. As the scale of a building increases, the gap between the predictions made by simulation and the actual situation will increase.

  From the background as described above, it is desired that population distribution data can be created in advance. In particular, it is hoped that a wide variety of population distribution data based on various situations can be easily created, edited, or visualized using a user-friendly interface, but such a tool is still desired. unknown.

  An object is to provide a data processing system and program capable of easily processing population distribution data.

  According to the embodiment, the data processing system includes a creation unit, a storage unit, and an output unit. The creation unit creates population distribution data that reflects changes over time in the position of the person based on information indicating the location of the person in the target space. The storage unit stores population distribution data. The output unit outputs the stored population distribution data.

FIG. 1 is a functional block diagram illustrating an example of a data processing apparatus according to the embodiment. FIG. 2 is a diagram illustrating an example of a screen displayed on the display 2. FIG. 3 is a diagram illustrating an example of a screen displayed on the display 2. FIG. 4 is a diagram illustrating an example of data that can be acquired by the image sensor. FIG. 5 is a diagram illustrating an example of the relationship between the arrangement of the image sensor and the detection area. FIG. 6 is a diagram illustrating an example of population distribution data created based on sensing data. FIG. 7 is a diagram illustrating an example of a screen displayed on the display 2. FIG. 8 is a diagram illustrating an example of the distribution of the number of people for each area. FIG. 9 is a diagram illustrating an example of the attribute data 4b. FIG. 10 is a diagram illustrating an example of population distribution data associated with attribute data. FIG. 11 is a diagram illustrating an example of gate arrangement and seat arrangement. FIG. 12 is a diagram illustrating an example of entry / exit information. FIG. 13 is a diagram illustrating another example of population distribution data. FIG. 14 is a diagram illustrating another example of visualized population distribution data. FIG. 15 is a diagram illustrating an example of personal work information. FIG. 16 is a diagram illustrating another example of population distribution data. FIG. 17 is a diagram illustrating another example of visualized population distribution data. FIG. 18 is a diagram showing another example of work information (work place table). FIG. 19 is a diagram showing an example of a schedule table in which the schedule of each individual is recorded. FIG. 20 is a diagram illustrating an example of editing population distribution data. FIG. 21 is a diagram for explaining an example of an operation for editing population distribution data. FIG. 22 is a diagram illustrating an example of the description of the population distribution data in units of groups. FIG. 23 is a diagram illustrating another example of expression of population distribution data. FIG. 24 is a diagram illustrating an example of an attendance scene. FIG. 25 is a diagram illustrating an example of color coding that can be used for the indoor layout displayed on the display 2. FIG. 26 is a diagram illustrating another example of a display mode of population distribution data.

  Hereinafter, a data processing system according to an embodiment will be described with reference to the drawings. As shown in FIG. 1, the data processing apparatus according to the embodiment includes an operation unit 1, a display 2, an interface unit 3, a storage unit 4, a program memory 5, and a CPU (Central Processing Unit) 6. That is, the data processing device (shown with reference numeral 100) is a computer that functions when the CPU 6 executes a program stored in the program memory 5.

  The operation unit 1 is a human machine interface including a keyboard and a mouse. The display 2 forms a GUI (Graphical User Interface) environment, accepts information input and data editing operations by the user using the operation unit 1, and provides information to the user. The interface unit 3 includes a slot for connecting to an external recording medium or a communication network, and mediates exchange of data with the outside. For example, CAD (Computer Aided Design) data or the like can be read into the data processing apparatus 100 by USB (registered trademark).

The storage unit 4 stores population distribution data 4a, attribute data 4b, sensing data 4c, and template data 4d as data according to the embodiment.
The population distribution data 4a is data that reflects changes over time in the position of a person in an office building, for example. That is, the population distribution data 4a is data reflecting the population distribution in the target space. In addition, human presence / absence can also be expressed by the population distribution data 4a. It is possible to represent the movement trajectory of humans by capturing time-series fluctuations in the population distribution. Moreover, if the instantaneous value of the population distribution is captured, it is possible to represent the position of the person at that time.

The attribute data 4b is data indicating individual attributes that can be distinguished, and can be associated with the population distribution data 4a. In addition to the person ID (IDentification), name, affiliation, job title, etc., it is possible to capture the preference of air conditioning (hot, cold, etc.) or the preference of lighting as attributes.
The attribute data 4b can be defined for each group including a plurality of persons. In addition, items such as time, place, title, preference, behavior pattern (whether smoking is available, break time, etc.), forgetting to erase rate, sensor detection performance can be defined as attribute data 4b for a person or group. It is. Furthermore, the attribute data 4b can set a distribution within the group.

  The sensing data 4c is data acquired by a sensor that detects a person existing in a target space (such as a building floor) in a building and its position. For example, measurement information of an image sensor provided in the next generation BEMS or the like corresponds to the sensing data 4c. Since the sensing data 4c reflects the population distribution in the target space, the population distribution data 4a can be created based on the sensing data 4c.

In particular, if personal authentication is possible using an image sensor, the attribute data 4b can be created with reference to a database in which personal information is registered. Visitor data may be assigned to a person without registration information.
The template data 4d is a template of population distribution data corresponding to a typical scene. That is, in the embodiment, population distribution data corresponding to a scene such as absence, attendance, or full room is stored in the storage unit 4 in advance as a template.

  The program memory 5 stores a data creation program 5a, an editing program 5b, a display control program 5c, and an output control program 5d as programs including instructions necessary for processing functions according to this embodiment. These programs can be recorded on a removable medium (recording medium) such as a CD-ROM, or can be downloaded via a communication line such as an IP network.

The CPU 6 reads each program from the program memory 5 and performs arithmetic processing by hardware, and includes a data creation unit 6a, an editing unit 6b, a display control unit 6c, and an output control unit 6d as its processing functions.
The data creation unit 6a creates population distribution data 4a based on information indicating the location of a person in a target space (such as a room or a floor). For example, the sensing data 4c is one piece of information indicating the location of a person, and the data creation unit 6a creates population distribution data 4a based on the sensing data 4c, for example. In addition, the data creation unit 6a creates population distribution data 4a that reflects a temporal change in position for each group including a plurality of people based on the sensing data 4c. The created population distribution data 4 a is stored in the storage unit 4.

  The editing unit 6b edits the population distribution data 4a based on an editing operation by the user. The editing operation includes operations such as selection of a person icon using a GUI and copy / paste using a shortcut key.

  The display control unit 6 c reads the population distribution data 4 a corresponding to the designated floor, time zone, etc., and visually displays the population distribution data 4 a on the display 2. That is, for example, as shown in FIG. 2, the display control unit 6 c displays a person icon reflecting the population distribution data 4 a so as to overlap the indoor layout of the target space. That is, the person icon is arranged at a position that reflects the position of the person in the indoor layout.

  In FIG. 3, for example, the population distribution at 14: 00-15: 00 and the population distribution at 15: 00-16: 00 one hour later are displayed side by side. As a result, the hourly change in population distribution is shown in an easy-to-understand manner. In the case of reproducing the population distribution, it is possible to specify reproduction, fast forward, rewind, and the like.

  The indoor layout schematically shows, for example, the arrangement of desks and seats, and may be, for example, any one of a bird's-eye view, a bird's-eye view, a side view, and a three-dimensional view in which the target space is looked down two-dimensionally. In this way, by superimposing and displaying human icons on the indoor layout, it is possible to visualize the flow of people per unit time (a concept that represents changes in population distribution over time), and how the seating status changes every moment. It becomes possible to see.

  The output control unit 6d outputs the population distribution data 4a to a file in various storage formats such as .csv, .txt, or .xml. In addition, it is also possible to output a file format corresponding to an application (such as a simulator) for reading the population distribution data 4a or a moving image showing a change in the population distribution in a format such as .mpeg.

  Here, a method of creating population distribution data 4a by processing data sensed by an image sensor or the like with software will be described.

  Recent image sensors can divide the field of view into a plurality of areas and associate each with an indoor area. If this type of image sensor is used, for example, sensing data indicating the presence / absence of a person can be obtained for each detection area. As shown in FIG. 4, the obtained sensing data can be managed by distinguishing the image sensor ID and the detection area for each image sensor.

  The data creation unit 6a creates population distribution data 4a by data analysis based on sensing data as shown in FIG. 4 and, for example, image sensor arrangement information as shown in FIG. FIG. 5 shows a plurality of image sensors (ID = 1 to 6) and seat IDs in respective fields of view. Sensing data from the image sensor may indicate a periodic status (for example, presence / absence every minute), or may indicate a change in an event (present / absent, absent → present).

  FIG. 6 shows an example of the created population distribution data, which is stored in the storage unit 4, and for each seat, the ID of a person who is present is divided into a database by dividing the time zone, and the population distribution data 4a is a display control. The content as shown in FIG. 7 is displayed on the display 2 by the unit 6c.

  6 and 7, a database is created for each seat. As shown in FIG. 8, for example, the population distribution can be expressed by the number of people (population) for each area (group) in which a plurality of desks are combined. You can also.

  In this way, it is possible to create the population distribution data 4a based on the sensing data acquired by the image sensor. By performing a control simulation such as lighting and air conditioning based on the population distribution data 4a, energy saving and The comfort can be verified.

  Further, by performing person authentication with the image sensor, it is possible to associate the attribute data 4b with the population distribution data 4a.

  The attribute data 4b is data indicating attributes for each individual, and includes a person ID (IDentification), name, affiliation, job title, etc., as well as preference for air conditioning (hot, cold, etc.) or lighting preference.

The attribute data 4b is a database in which values for each person are registered for each of a plurality of items such as name, affiliation, and post as shown in FIG. 9, for example. Each person is distinguished by a person ID (for example, 1, 2,...).
The preference of air conditioning may be expressed by an index indicating comfort, such as PMV (Predicted Mean Vote), in addition to the stage setting such as hot, normal, and cold. The preference for lighting may be a value indicating brightness such as illuminance or a feeling of brightness, in addition to a step setting such as bright, normal, or dark.

  The absence rate is an index expressed by, for example, (seating time) / (total time), and indicates that the user leaves the seat for (numerator) time during (denominator) time. With this index, it is possible to manage the absence of seats due to toilets, smoking, and meetings at the other party. In addition, it is possible to add away seats such as A toilet, B smoking room, and C seat as data.

  The forgetting to turn off rate indicates the probability of forgetting to turn off the screen of personal PC (personal computer) or lighting (when sensor control is not performed). The detection rate of the sensor is an index indicating a person that is easily detected by the sensor and a person that is difficult to detect. The detection rate of an ideal sensor is 100%, but undetected occurs in an actual sensor due to performance variations. Such elements can also be managed in the attribute data 4b.

  The attribute data in FIG. 9 can be edited via the GUI by the editing unit 6b. If random setting or automatic setting is specified, the value for each item is set randomly within a predetermined range. It is also possible to do. The range designation in the random setting can also be given through the GUI. For example, the detection rate of the sensor can be specified as 90% to 100%. In the automatic setting, the value for each item can be made completely random, or the distribution within a predetermined range can be set. For example, the preference for air conditioning can be set as 80% normal, 10% hot, 10% cold.

  Such attribute data can be associated with an occupant as shown in FIG. 10 by specifying an individual by face authentication, for example.

  As a result, it is possible to verify energy saving and comfort by performing a control simulation of lighting, air conditioning, etc. in consideration of personal preferences.

  Note that the personal authentication by the image sensor is not limited to face authentication, but may be anything that can identify an individual such as authentication by a name plate.

  Next, a method of creating the population distribution data 4a based on person entry / exit information managed by the entry / exit management system will be described.

  In the entrance / exit management system, the entrance / exit information can be created by registering the ID of the person who has passed for each gate provided in the building site or in the building. For example, as shown in FIG. 11, a gate is provided at the entrance of each room, and the entry / exit information is created. FIG. 12 is an example of entry / exit information in a certain period.

  The data creation unit 6a creates the population distribution data 4a based on these pieces of information (entrance / exit information, seats, gate arrangement, etc.). FIG. 13 shows an example of the created population distribution data 4a, and FIG. 14 shows an example of a display visualizing the population distribution data 4a.

  When the population distribution data 4a is created based on the entrance / exit information, it can be assumed that the person is seated on the seat ID as shown in FIG. 13 by adding seat information as attribute information of the person. In addition, when there is no seat information in the gate that has passed, for example, when the gate to the conference room is passed, the seating position in the conference room may be random.

  In this way, it is possible to create the population distribution data 4a based on the entrance / exit information acquired by the entrance / exit management system, and by performing a control simulation such as lighting and air conditioning based on the population distribution data 4a. It becomes possible to verify energy saving and comfort.

  Furthermore, it is also possible to create the population distribution data 4a using the work information of each individual as shown in FIG. The work information is information that can be managed by an office work management system or the like. Based on the work information and the seat information added to the attribute information of the person, the data creation unit 6a can create the population distribution data 4a by assuming that the person who has not gone out is seated in his / her seat. Is possible. FIG. 16 shows an example of the created population distribution data 4a, and FIG. 17 shows an example of a display visualizing the population distribution data 4a.

  As work information, detailed work information such as man-hour management and information for managing time may be used. For the work for which the work place is determined, a table indicating the work place as shown in FIG. 18 may be created and used. Thereby, it is possible to create the population distribution data 4a considering the case of working outside the seat.

  Furthermore, population distribution data can also be created using a schedule table in which the location of an individual for each hour as shown in FIG. 19 is used. In the schedule table shown in FIG. 19, the location of each individual date and time is shown. The data creation unit 6a creates the population distribution data 4a based on such a schedule.

  In this way, it is possible to create the population distribution data 4a based on work information and a schedule, and by performing a control simulation such as lighting and air conditioning based on this population distribution data 4a, energy saving and comfort can be achieved. Verification can be performed.

  The population distribution data 4a can be edited, and the editing unit 6b edits the population distribution data 4a based on an editing operation by the user.

FIG. 20 shows population distribution data 4a indicating the location of each person for each hour. For example, a person (ID = 1) is in the seat 1 of the 3rd floor-1A block from 9:00 to 10:00, and It is set that it was in the same place for 1 hour and moved to the cafeteria from 12:00 to 1:00. Note that the time zone break (unit time) is not limited to one hour, but may be set in any manner such as every 30 minutes, every 2 hours, or every minute.
The population distribution data 4a can be edited by drag and drop using a GUI as shown in FIG. 21, for example. For example, in the case of a Windows (registered trademark) -based computer, the population distribution data 4a can be rewritten by operating a person icon by copy / paste (Ctrl + c, Ctrl + v).

  In addition, the population distribution data 4a can be described in units of groups as shown in FIG. For example, a plurality of persons can be managed as a group, and each group can be managed by being distinguished by an ID. FIG. 22A shows that a person (ID = 1) belongs to the group (ID = 1) and the number of persons is 7. As shown in FIG. 22B, it is also possible to set the number of persons existing in the group and the number of persons within a predetermined range at random. Thus, the movement of a person can be expressed not only by movement of each individual but also by movement in units of groups.

  The population distribution data 4a can also be expressed by the form shown in FIG. In FIG. 20, the population distribution data is represented by representing the location of each individual distinguished by ID for each time. Instead, as shown in FIG. 23, it is possible to express population distribution data by representing a person present for each time zone for each seat distinguished by ID. Of course, the population distribution data expressed in this way can also be edited by the editing unit 6b, and the unit time in the horizontal column can also be set arbitrarily.

  The population distribution data 4a can be pre-templated and stored in the storage unit 4. For example, as an example of a typical scene in a building, an attendance scene as shown in FIG. 24 can be made into a template. According to the visualized image shown in FIG. 24, it is shown that a person existing in the elevator hall on the first floor moves to each floor as time passes and is seated. Population distribution data corresponding to this scene is stored in advance in the storage unit 4 as template data 4d.

If the user reads the template data 4d when editing the population distribution data 4a and modifies the template, the user can be remarkably reduced in labor compared to creating the population distribution data 4a from nothing. In addition to the attendance scenes, the following scenes can also be templated and stored in advance as template data 4d.
(Working scene): A person moves from each floor to the first floor.
(Lunch Scene): In the first half of the lunch time, people move from each floor to the cafeteria floor, and in the second half, people move from the cafeteria floor to each floor.
(Holiday scene): The attendance rate is low overall.

  Thus, it is possible to create the population distribution data 4a also by editing, and verifying energy saving and comfort by performing a control simulation such as lighting and air conditioning based on the population distribution data 4a. It becomes possible.

  Furthermore, the indoor layout displayed on the display 2 can be displayed in different colors as shown in FIG. 25, for example. The display control unit 6c acquires drawing data of the target space with a file (CAD data shown in FIG. 1) in a format such as CAD, 3DCAD, or bitmap, calculates the indoor layout, and displays it on the display 2. At that time, for example, as shown in FIG. 25, it is possible to distinguish and display by an object (wall, window, etc.) color index, or to input additional information such as magnification (10 cm per pixel) at the same time.

  The data processing apparatus 100 can have a drawing function (drawing application) to draw an indoor layout. Note that the data for creating the indoor layout is not limited to the CAD format, and any data can be used as long as it can represent drawing data or a design drawing.

  Furthermore, the population distribution data 4a is not limited to the top view or the overhead view for each floor as described above, but can be displayed using a three-dimensional diagram as shown in FIG. At that time, it is preferable to use a more realistic model for the icon indicating the desk or person.

  As described above, in this embodiment, the population distribution data 4a reflecting the temporal change of the human position can be created from sensing data or the like, and the population distribution data 4a is generated based on the editing operation by the GUI of the computer. Enabled to edit. Furthermore, the attribute data of each individual can be displayed together, and this attribute data can also be edited via the GUI. Therefore, population distribution data for simulating energy saving and comfort can be easily created and visualized. Therefore, it is possible not only to verify the performance of the building in advance, but also to improve the accuracy of the simulation.

  In recent image sensors, information such as the presence / absence of individual persons and the distribution of the number of persons can be acquired, and it is planned to utilize such information for the control of lighting and air conditioning. However, with existing technology, for example, the energy-saving effect can be verified only by the attendance rate, so it cannot be denied that it lacks persuasive power.

On the other hand, according to the embodiment, it becomes possible to easily edit and visualize the population distribution data that becomes the data under the simulation, and it is possible to create accurate population distribution data over various scenes, and thus the accuracy of the simulation. Will also improve. By improving the accuracy of the simulation, for example, it becomes possible to quantitatively evaluate the energy saving effect due to the introduction of the image sensor. This becomes an appeal point for explaining the advantages of the image sensor to customers such as a building owner.
Therefore, it is possible to provide a data processing system and program that can easily process population distribution data.

  The present invention is not limited to the above embodiment. For example, in the embodiment, software is installed in a stand-alone computer to realize each function. Alternatively, it is also possible to edit, process, and create population distribution data by installing software on a server computer and accessing the server computer from a client terminal. For example, those skilled in the art will readily understand that this kind of environment can be realized by storing population distribution data in a server computer and applying CGI (Common Gateway Interface) technology.

  Although an embodiment of the present invention has been described, this embodiment is presented as an example and is not intended to limit the scope of the invention. The novel embodiment can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the scope of the invention. This embodiment and its modifications are included in the scope and gist of the invention, and are included in the invention described in the claims and the equivalents thereof.

  DESCRIPTION OF SYMBOLS 100 ... Data processing apparatus, 1 ... Operation part, 2 ... Display, 3 ... Interface part, 4 ... Memory | storage part, 5 ... Program memory, 6 ... CPU, 4a ... Population distribution data, 4b ... Attribute data, 4c ... Sensing data, 4d ... template data, 5a ... data creation program, 5b ... editing program, 5c ... display control program, 5d ... output control program, 6a ... data creation unit, 6b ... editing unit, 6c ... display control unit, 6d ... output control unit

Claims (20)

Population distribution data reflecting the time-dependent change of the human position is processed by processing sensing data indicating a human location for each of a plurality of detection areas in the target space, which is obtained by an image sensor capable of dividing the field of view into a plurality of areas. A creation section to create,
A storage unit for storing the population distribution data;
A data processing system comprising: an output unit for outputting the stored population distribution data. The data processing system according to claim 1, wherein the creation unit creates the population distribution data based on a population distribution in the target space detected by the image sensor .   The creation unit creates the population distribution data based on at least one of entry / exit information of each individual, work information of each individual, and a schedule that records the schedule of each individual. The data processing system described.   The data processing system according to claim 1, further comprising an editing unit that edits the stored population distribution data based on a user editing operation. The storage unit stores a template of population distribution data corresponding to a representative scene,
The data processing system according to claim 4 , wherein the editing unit reads the template of the scene designated in the editing operation from the storage unit.   The data processing system according to claim 1, wherein the storage unit stores the population distribution data and attribute data indicating attributes for each individual in association with each other.   The data processing system according to claim 1, wherein the storage unit stores the population distribution data and attribute data indicating attributes for each group including the plurality of persons in association with each other. The data processing system according to claim 1, wherein the creation unit creates population distribution data that reflects a temporal change in position for each group including the plurality of humans based on the sensing data . The data processing system according to claim 4 , wherein the editing unit edits the population distribution data based on an editing operation using a GUI (Graphical User Interface).   The data processing system according to claim 1, further comprising: a display control unit configured to display an indoor layout and population distribution data based on the drawing data of the target space. A program executed by a computer, wherein the program
Population distribution data reflecting the time-dependent change of the human position is processed by processing sensing data indicating a human location for each of a plurality of detection areas in the target space, which is obtained by an image sensor capable of dividing the field of view into a plurality of areas. A creation section to create,
A storage unit for storing the population distribution data;
A program that functions as an output unit that outputs the stored population distribution data. The program according to claim 11, wherein the creating unit creates the population distribution data based on a population distribution in the target space detected by the image sensor .   The creation unit creates the population distribution data based on at least one of entry / exit information of each individual, work information of each individual, and a schedule table recording the schedule of each individual. The program described.   The program according to claim 11, further comprising an editing unit that edits the stored population distribution data based on a user's editing operation. The storage unit stores a template of population distribution data corresponding to a representative scene,
The program according to claim 14 , wherein the editing unit reads out the template of the scene specified in the editing operation from the storage unit.   The program according to claim 11, wherein the storage unit stores the population distribution data and attribute data indicating attributes for each individual in association with each other.   The said storage part is a program of Claim 11 which matches and memorize | stores the said population distribution data and the attribute data which show the attribute for every group containing the said some human. The program according to claim 11, wherein the creation unit creates population distribution data that reflects a temporal change in position for each group including the plurality of humans based on the sensing data . The program according to claim 14 , wherein the editing unit edits the population distribution data based on an editing operation using a GUI (Graphical User Interface).   The program according to claim 11, further comprising: a display control unit configured to display an indoor layout and population distribution data based on the drawing data of the target space.

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