Spatial proposal system, spatial proposal method, and program

Abstract

We provide a space proposal system that can suggest more appropriate spaces. [Solution] The spatial proposal system 10 comprises a model construction unit 16 that constructs a model showing the relationship between spatial usage information regarding which of several areas included in the space (different spaces) multiple users used, spatial usage effect information showing the evaluation of the multiple users' use of the space, and characteristic information showing the characteristics of each of the multiple users; an acquisition unit 14 that acquires target characteristic information showing the characteristics of users who use a target space (space 70) different from the space; a generation unit 15 that generates spatial design information related to the spatial design of the target space from the acquired target characteristic information by inference using the constructed model; and an output unit 18 that outputs the generated spatial design information.

Description

Technical Field

[0001] The present invention relates to a space proposal system, a space proposal method, and a program.

Background Art

[0002] Patent Document 1 discloses an office layout generation device related to a space proposal system that can determine the optimal office furniture and equipment and information equipment and perform an optimal layout based on the characteristics of the work performed in the office.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] The present invention provides a space proposal system and the like that can propose a more appropriate space.

Means for Solving the Problems

[0005] A space proposal system according to an aspect of the present invention includes a model construction unit that constructs a model showing the relationship between space utilization information regarding which area among a plurality of areas included in the space is used by a plurality of users who use the space, space utilization effect information indicating an evaluation regarding the utilization of the space by the plurality of users, and characteristic information indicating the characteristics of each of the plurality of users, an acquisition unit that acquires target characteristic information indicating the characteristics of a user who uses a target space different from the space in the target space, a generation unit that generates space design information regarding the space design of the target space from the acquired target characteristic information by inference using the constructed model, and an output unit that outputs the generated space design information.

[0006] A spatial proposal method according to one aspect of the present invention is a spatial proposal method performed by a computer, comprising the steps of: constructing a model showing the relationship between spatial utilization information relating to which of a plurality of areas included in the space a plurality of users used; spatial utilization effect information showing the evaluation of the plurality of users' use of the space; and characteristic information showing the characteristics of each of the plurality of users; acquiring target characteristic information showing the characteristics of users of a target space different from the space; generating spatial design information relating to the spatial design of the target space from the acquired target characteristic information by inference using the constructed model; and outputting the generated spatial design information.

[0007] A program according to one aspect of the present invention is a program for causing the computer to execute the spatial proposal method. [Effects of the Invention]

[0008] The spatial proposal system of the present invention can propose a more appropriate space. [Brief explanation of the drawing]

[0009] [Figure 1] Figure 1 is a block diagram showing the functional configuration of the spatial proposal system according to the embodiment. [Figure 2] Figure 2 shows an example of a space in which multiple workers according to the embodiment operate. [Figure 3] Figure 3 shows an example of a feature quantity related to the use of space according to the embodiment. [Figure 4] Figure 4 shows an example of the screen of each worker's mobile terminal according to the embodiment. [Figure 5] Figure 5 is a flowchart showing specific examples of the construction operation and proposal operation of the spatial proposal system according to the embodiment. [Figure 6] Figure 6 is a flowchart showing the clustering operation for model construction according to the embodiment. [Figure 7] Figure 7 illustrates the calculation of the common behavior of the model according to the embodiment. [Modes for carrying out the invention]

[0010] The embodiments will be described in detail below with reference to the drawings. Note that the embodiments described below are all comprehensive or specific examples. The numerical values, shapes, materials, components, arrangement positions and connection configurations of components, steps, and the order of steps shown in the following embodiments are examples only and are not intended to limit the present invention. Furthermore, components in the following embodiments that are not described in an independent claim will be described as optional components.

[0011] Please note that each figure is a schematic diagram and not necessarily a strictly accurate representation. Furthermore, in each figure, substantially identical components are denoted by the same reference numerals, and redundant explanations may be omitted or simplified.

[0012] In the following explanation, an office is used as an example of a space and target space, but the space and target space are not limited to offices; any space such as public facilities and homes can be envisioned. Furthermore, in the example where the space and target space are offices, the users of the space and target space are the workers who work in that space and target space.

[0013] (Embodiment) [composition] First, the configuration of the spatial proposal system according to the embodiment will be described. Figure 1 is a block diagram showing the functional configuration of the spatial proposal system according to the embodiment.

[0014] The spatial proposal system 10 is a system that can make suggestions such as changing the number of seats in a target space where multiple workers work. The target space here is, for example, an office space (indoor space) where multiple workers work on a free-address basis. Figure 2 is a diagram showing an example of a space where multiple workers work.

[0015] The target space (space 70) shown in FIG. 2 includes, for example, a solo area where an individual can concentrate on work, a collaboration area for multiple people to work together, a discussion area for discussions such as web conferences and open meetings, a meeting area for holding topic-specific meetings in small partitioned meeting rooms, and a rest area, a total of five areas. Note that the space 70 may include other areas or may not include any of the illustrated areas. Any areas may be included in the space 70. Also, for the above areas, areas subdivided according to the use such as a web conference area and an open meeting area may be included.

[0016] The space proposal system 10 is realized by, for example, one or more server devices (cloud servers). Specifically, the space proposal system 10 includes a communication unit 11, an information processing unit 12, and a storage unit 13.

[0017] The communication unit 11 is a communication module (communication circuit) for the space proposal system 10 to communicate with a plurality of mobile terminals 20, information terminals 40, etc. via a wide area communication network such as the Internet. The communication performed by the communication unit 11 is, for example, wired communication, but may also be wireless communication. The communication standard used for communication is not particularly limited either.

[0018] The information processing unit 12 performs information processing for making a proposal regarding the target space by generating and outputting space design information including at least one of the area ratio, seat number ratio, and arrangement position of each of a plurality of areas arranged in the target space, the control conditions for controlling the environment of the target space, the necessary number of space control devices for controlling the environment, and the space design effects obtained when following the space design information. The information processing unit 12 is realized by, for example, a microcomputer, but may also be realized by a processor. The information processing unit 12 includes, as functional components, an acquisition unit 14, a generation unit 15, a model construction unit 16, a model inference unit 17, and an output unit 18. The functions of the acquisition unit 14, the generation unit 15, the model construction unit 16, the model inference unit 17, and the output unit 18 are realized, for example, by a microcomputer or a processor constituting the information processing unit 12 executing a computer program stored in the storage unit 13.

[0019] The storage unit 13 is a storage device that stores information necessary for the above information processing and computer programs executed by the information processing unit 12. The storage unit 13 is realized by, for example, a HDD (Hard Disk Drive), but may also be realized by a semiconductor memory or the like.

[0020] Here, in FIG. 1, in addition to the space proposal system 10, a plurality of mobile terminals 20, a positioning system 30, and an information terminal 40 are also shown. These terminals and systems will be described below.

[0021] The mobile terminal 20 is an information terminal carried (owned) by a worker located in a space different from the target space (hereinafter also simply referred to as a different space). The mobile terminal 20 measures the position (coordinates) of the worker who owns the mobile terminal 20 in the workplace and transmits position information indicating the measured position to the space proposal system 10. The mobile terminal 20 is, for example, a smartphone, but may also be a tablet terminal or a communication terminal dedicated for positioning.

[0022] The positioning system 30 is a system composed of multiple communication terminals 31 installed in different spaces. Each of the multiple communication terminals 31 functions as a beacon transmitter. That is, each of the multiple communication terminals 31 emits a beacon signal containing the identification information of the communication terminal 31. Alternatively, each worker may carry a communication terminal 31 that functions as a beacon transmitter instead of a mobile terminal 20, and the position of the communication terminal 31 may be measured by multiple beacon receivers (not shown) installed in different spaces. In other words, the position of the worker in the workplace can be measured in the same way even if the relationship between transmission and reception is reversed. In this way, any method can be used to measure the position as long as the position of the worker in the workplace can be measured.

[0023] The information terminal 40 is used by a user who wishes to receive proposals regarding a target space from the spatial proposal system 10. The user may be, for example, the administrator of the target space (such as a human resources manager), but may also be a spatial designer (in other words, a planner). The information terminal 40 may be, for example, a personal computer, but may also be a smartphone or tablet device.

[0024] [Information acquisition operation] The spatial proposal system 10 acquires location information and evaluation information from mobile terminals 20 held by workers located in different spaces. The operation of acquiring location information and evaluation information will be described below.

[0025] The different space is a space set up for the purpose of acquiring information for model construction, specifically the relationship between worker characteristic information and satisfaction levels, prior to outputting information about the target space. In this embodiment, the space proposal system 10 makes it possible to acquire only characteristic information from users of the target space and make proposals regarding the target space by performing inference using a model constructed based on information obtained in the different space. In other words, the different space can be said to be a space for the provider of proposals regarding the target space to conduct experiments for data collection in advance.

[0026] Multiple communication terminals 31 (beacon transmitters) are distributed across different spaces. Each of the multiple workers has a mobile terminal 20 that receives beacon signals from each of the multiple communication terminals 31 and generates location information indicating the current location (coordinates) of the mobile terminal 20 based on the received beacon signals.

[0027] Specifically, the mobile terminal 20 measures the received signal strength of the received beacon signal and calculates the distance between the mobile terminal 20 and each of the multiple communication terminals 31 based on the measured received signal strength. Based on the distance between the mobile terminal 20 and each of the multiple communication terminals 31 and the installation location information of each of the multiple communication terminals 31 that is pre-stored (registered) in the mobile terminal 20, the mobile terminal 20 can generate location information indicating the current location of the mobile terminal 20 (the worker possessing the mobile terminal 20) by three-point positioning. The mobile terminal 20 may also generate location information for the mobile terminal 20 by one-point positioning based on the distance to one communication terminal 31 and the installation location information of that one communication terminal 31. The location information includes a worker ID to distinguish between the multiple workers.

[0028] The mobile terminal 20 transmits the generated location information to the spatial suggestion system 10. The communication unit 11 of the spatial suggestion system 10 receives the location information, and the information processing unit 12 stores the received location information in the storage unit 13.

[0029] The above process is repeated at predetermined time intervals. As a result, the storage unit 13 of the spatial proposal system 10 stores time-series data of the location information of each of the multiple mobile terminals 20. In other words, the storage unit 13 stores time-series data of the location information of multiple workers. The time-series data of location information can be rephrased as movement path information or movement trajectory. The spatial proposal system 10 can obtain feature quantities related to the use of different spaces, as shown in Figure 3, by transforming the time-series data of location information.

[0030] Figure 3 shows an example of features related to spatial utilization. In Figure 3, features related to the use of different spaces by a single worker are summarized. As shown in Figure 3, multiple types of features are obtained from the time-series data of the worker's location information, and one or more features are included for each type. Furthermore, by combining at least some of these features, it is possible to calculate further features such as the utilization rate of different spaces for each worker (not shown). In addition, as further features, it is also possible to calculate the utilization rate of each of the multiple areas set in each different space (areas corresponding to the five areas shown in Figure 2), and the time spent in each of the multiple areas (neither of which are shown). In this embodiment, these features are used as spatial utilization information for each worker to construct the model described later. Note that in addition to the features for each worker, features related to two or more workers may also be obtained as features. Such features related to two or more workers may include, for example, proximity information and discrete information between workers obtained from the relationship of the location information of the two or more workers.

[0031] Returning to Figure 1, each of the multiple workers inputs their evaluation of a different space into their mobile terminal 20 at the end of the day. In other words, the evaluations of the use of different spaces by multiple workers are entered into multiple mobile terminals 20 carried by the multiple workers. The evaluation here is, in other words, the level of satisfaction with the use of the different spaces on that day. For example, as shown in Figure 4, a questionnaire is displayed on the screen of each worker's mobile terminal 20, and when a worker answers this questionnaire, this satisfaction information is automatically sent to the space proposal system 10 as space utilization effectiveness information. The evaluation is done on an 11-point scale, for example, from 0 to 10. As mentioned above, there are cases where multiple workers carry communication terminals 31. In that case, instead of inputting evaluations of different spaces into the mobile terminal 20, each worker can input their evaluation using an input device provided in the different space (such as a general-purpose PC or dedicated terminal used by each worker).

[0032] Furthermore, satisfaction information may include satisfaction levels for each area used among multiple areas set up in different spaces, as well as subjective satisfaction levels regarding the progress of tasks performed in conjunction with the use of different spaces, in addition to overall satisfaction levels when using different spaces. In this case, the questionnaires displayed should be appropriately configured to obtain the desired level of satisfaction. Also, instead of satisfaction levels, task-related results may be used as an evaluation of the use of different spaces as described above. In other words, a similar space proposal system can be constructed by replacing "satisfaction levels" with "results" as described below.

[0033] Task outcomes specifically include the progress or results of tasks performed using different spaces, or the quality of the approach to the tasks. Specifically, task outcomes include well-being, motivation (more precisely, the degree of motivational outcomes), performance, productivity, engagement, creativity, work speed, and work quality. Well-being, engagement, and motivation can be collected through questionnaires, and can be obtained in the same way as satisfaction using questionnaires designed to elicit such outcomes. On the other hand, performance, work speed, work quality, and productivity can be subjective measures obtained through questionnaires as described above, or objective measures measured from the actual amount of work completed by the workers. Regarding work speed and work quality, for workers performing only simple tasks, both can be considered synonymous with performance. However, depending on the type of task, work speed and work quality may not be synonymous with performance, for example, in research positions where work speed and work quality do not directly lead to concrete results. In such cases, it may be preferable to use performance separately from work speed and work quality.

[0034] The mobile terminal 20 receives the input of the evaluation and transmits evaluation information (score) to the spatial proposal system 10. As a result, the storage unit 13 of the spatial proposal system 10 stores spatial utilization effect information for each of the multiple workers. The spatial utilization effect information includes the worker ID. The worker ID is used to distinguish between multiple workers and to link the spatial utilization information and spatial utilization effect information for each worker.

[0035] Furthermore, the acquisition unit 14 acquires characteristic information, including at least one of the environmental preferences, personality traits, job characteristics, and organizational characteristics of each worker in different spaces. Such characteristic information is acquired by conducting questionnaires (for example, one or more questionnaires, including one at the start of use of a different space) when workers use different spaces. The questionnaires here may be acquired by the space proposal system 10 via the mobile terminal 20, or an administrator who has acquired the questionnaires on paper may input them via the information terminal 40 for the space proposal system 10 to acquire. Note that at least one of the environmental preferences, personality traits, job characteristics, and organizational characteristics of each worker may be acquired separately from the characteristic information. The characteristic information also includes a worker ID. Therefore, the worker ID can be used to distinguish between multiple workers and to link the space usage information, space usage effect information, and characteristic information for each worker.

[0036] According to the information acquisition operation of the spatial proposal system 10 as described above, the storage unit 13 of the spatial proposal system 10 stores spatial utilization information obtained from the time-series data of the location information of each of the multiple workers, spatial utilization effect information for each of the multiple workers, and characteristic information for each of the multiple workers.

[0037] The model construction unit 16 pre-constructs a model showing the relationship between spatial utilization information, spatial utilization effect information, and characteristic information obtained in different spaces. This allows the model to acquire characteristic information from workers in the target space and perform inference using that characteristic information. In this inference, the model inference unit 17 uses the pre-constructed model to generate and output (propose) spatial layout information for the target space that is likely to improve worker satisfaction in the target space. The following describes specific examples of the construction operation related to such model construction and the proposal operation including model inference.

[0038] [Examples of construction and proposal operations] Figure 5 is a flowchart illustrating specific examples of the construction and proposal operations of the spatial proposal system 10. As shown in Figure 5, the storage unit 13 of the spatial proposal system 10 stores layout information indicating the layout (floor plan) of different spaces, and the layout information defines the coordinate range of each of the multiple areas included in the different spaces. The information processing unit 12 of the spatial proposal system 10 can obtain information on the usage status of multiple areas, i.e., spatial usage information, by comparing time-series data of the position information of multiple workers in different spaces with the coordinate ranges of the multiple areas. Furthermore, as described above, the acquisition unit 14 acquires spatial usage effect information and characteristic information before and after the use of different spaces. In this way, the spatial proposal system 10 acquires the model construction data (spatial usage information, spatial usage effect information, and characteristic information) necessary for model construction (S101).

[0039] The model building unit 16 uses the acquired model building data to construct a model that shows the relationship between spatial utilization information, spatial utilization effect information, and characteristic information (S102). Here, the model building data is prone to noise due to subjective evaluations such as satisfaction levels and variations in how workers utilize the space (e.g., using it only every other day, or showing only specific trends dependent on meeting schedules). Furthermore, there are constraints that make it difficult to obtain a large amount of data, as it is difficult to secure a sufficient number of people who can continuously acquire subjective evaluations in a limited environment where a positioning system exists. Therefore, considering the use case where a model is built in advance and then used to make inferences about the target space that is the subject of the proposal, it is necessary to construct a model that is resistant to noise even with a small amount of data and has high explainability (which can also be called convincingness) of the inference.

[0040] Therefore, when building a model, for example, several conditions are set, such as whether or not there are responses regarding characteristic information, whether the number of responses for satisfaction data is above a certain number, and whether the attendance rate or stay rate at the office meets certain conditions, in order to filter the data to leave only data that is significant for analysis.

[0041] Then, after the screening process described above, the model building and evaluation are repeated, as shown in the flowchart in Figure 6, to extract data showing the same trend even from small amounts of data and build multiple models. This allows the built models, which are tailored to the trends indicated by the characteristic information of the workers in the target space, to be used for inference. Figure 6 is a flowchart showing the clustering operation for model building.

[0042] First, from the model building data remaining after the above screening (for example, assuming that data from 50 individuals remains, the following explanation will be given), data with different trends (data from 24 individuals under certain conditions) are excluded. Data with different trends can be extracted using existing data comparison techniques such as basic statistics, ordinal statistics, correlation coefficients, and machine learning. Next, as shown in Figure 6, a machine learning model showing the relationship between spatial utilization information and spatial utilization effect information is constructed using a gradient boosting method (e.g., XGBoost) for the remaining 26 individuals' model building data. Then, the accuracy of the machine learning model is evaluated on the model building data using leave-one-out cross-validation (LOOCV) (S11). Step S11 is repeated for all patterns so that all 26 individuals' model building data are used for validation, and the accuracy of the machine learning model is evaluated for all patterns. Then, the model building data corresponding to individuals with low accuracy under predetermined conditions is excluded (S12). Under certain conditions, the model building data for 5 individuals was excluded due to low accuracy.

[0043] Next, for the machine learning models corresponding to the remaining 21 model-building data from the machine learning models constructed in step S11, the common behavior of each machine learning model, namely the trend of the influence of spatial utilization information on spatial utilization effect information, is calculated (S13). Model explanation methods such as SHAP (SHapley Additive exPlanations) can be used for the calculation in step S13. For example, Figure 7 is an example of the calculation of the common behavior of machine learning models. In Figure 7, the results of calculating the trend of influence using SHAP for a certain machine learning model are shown, with each item on the vertical axis representing each feature of spatial utilization information, and the horizontal axis showing the influence of that feature on satisfaction. Specifically, the closer the value on the horizontal axis is to -1.00, the greater the influence on decreasing satisfaction, and the closer it is to 1.00, the greater the influence on increasing satisfaction. For simplicity, the values ​​of each feature are shown in three stages with a legend. By performing the same calculation for all machine learning models corresponding to the model-building data of the 21 individuals, 21 calculation results similar to Figure 7 can be obtained.

[0044] Next, machine learning models are extracted when the trend of the influence of spatial utilization information on spatial utilization effect information is the same (S14). Here, out of 21 calculation results, 10 calculation results showed the same trend based on threshold judgments, so these 10 models were extracted as comparable machine learning models. Subsequently, data with similar SHAP ratios are clustered in the spatial utilization information of the 10 individuals corresponding to the comparable machine learning models (S15). In other words, in these models, the features of spatial utilization information that are likely to contribute to improving satisfaction are grouped into the same group according to their type. Furthermore, spatial utilization information with a large SHAP calculation value in the clustered data is defined as an important function.

[0045] Furthermore, among the 10 individuals corresponding to comparable machine learning models, those with similar types of important work styles are clustered (S16).

[0046] Then, in step S16, the commonality of the characteristic information of the clustered individuals is calculated (S17). In calculating commonality, for example, the characteristic information is extracted from the characteristic information that is common to a predetermined number of people or more.

[0047] By examining the relationship between the common characteristic information of people belonging to such a cluster and the types of feature quantities in spatial utilization information, it is possible to construct a model that shows how to improve satisfaction by combining characteristic information with spatial utilization information features.

[0048] Afterward, the model building data for the group that has been formed (10 people in this case) is excluded (S18), and the process returns to step S11. The same process is repeated for the remaining people (40 people) until it is no longer possible to group them.

[0049] As described above, it is possible to extract data showing the same trend even from a small amount of data and construct multiple models. As in this embodiment, it is possible to apply this to situations where a model is constructed in advance and then used to perform inference on a different target space. In this example, the gradient boosting method was used to construct a machine learning model, but other machine learning methods such as random forests, SVMs (support-vector machines), and neural networks may also be used to construct machine learning models. In addition, an example of using one-out cross-validation when the number of people in the data is small was described, but k-Fold cross-validation may be used depending on the amount of data.

[0050] Returning to Figure 5, after constructing the model, inference data is obtained by conducting a questionnaire with users of the target space in the same way as with users of different spaces (S103). The inference data includes characteristic information of users of the target space. This information is grouped so that users with similar satisfaction trends are grouped together, corresponding to a model that shows the relationships between groups, and then used in the next processing.

[0051] The generation unit 15 generates spatial design information (S105) by having the model inference unit 17 perform inference (S104) using the grouped inference data with a pre-constructed model. The output unit 18 then outputs the generated spatial design information (S106). The spatial design information includes at least one of the following, calculated based on the number of workers and spatial utilization information to improve their satisfaction: the area ratio, seating ratio and placement location of each of the multiple areas to be placed in the target space, control conditions for controlling the environment of the target space and the required number of spatial control devices for controlling the environment, and the spatial design effect obtained when following the spatial design information (for example, the degree to which satisfaction improves in each area). Note that the control conditions and the required number of control devices can be calculated by including environmental orientation and personality characteristics in the characteristic information.

[0052] [Effects, etc.] The following describes examples of inventions that can be obtained from the disclosures in this specification, and explains the effects and other benefits that can be obtained from these examples.

[0053] Invention 1 is a spatial proposal system 10 comprising: a model construction unit 16 that constructs a model showing the relationship between spatial utilization information regarding which of multiple areas contained in a space (different spaces) multiple users used, spatial utilization effect information showing an evaluation of the multiple users' use of the space, and characteristic information showing the characteristics of each of the multiple users; an acquisition unit 14 that acquires target characteristic information showing the characteristics of users who use a target space (space 70) different from the space; a generation unit 15 that generates spatial design information regarding the spatial design of the target space from the acquired target characteristic information through inference using the constructed model; and an output unit 18 that outputs the generated spatial design information.

[0054] This spatial proposal system 10, by using a model constructed from model construction data acquired in advance by users of a space different from the target space, can output (propose) spatial design information that is likely to be suitable for users of the target space, even if only the target characteristic information is acquired by the user of the target space. Therefore, it becomes possible to propose a more appropriate space.

[0055] Invention 2 is a spatial proposal system 10 as described in Invention 1, wherein the model building unit 16 groups multiple users such that users who have the same tendency for satisfaction based on spatial utilization effect information relative to feature quantities based on spatial utilization information are divided into the same group, and builds a model that associates predetermined groups with characteristic information of the users divided into said predetermined groups.

[0056] This spatial proposal system 10 groups multiple users so that users with similar satisfaction trends based on spatial utilization effect information are placed in the same group, and outputs spatial design information that is likely to be suitable for the users of the target space by creating a model that associates predetermined groups with the characteristic information of the users divided into those predetermined groups. In other words, since it can model the relationship between groups of users with similar satisfaction trends and the characteristic information of those groups, it has the advantage that the model is easier to build and easier to train even with a small amount of model building data.

[0057] Invention 3 is a spatial proposal system 10 described in Invention 2, wherein, in reasoning using a model, the spatial proposal system 10 groups users of the target space in such a way that users with similar satisfaction tendencies are grouped together, based on the target characteristic information of the users of the target space.

[0058] This spatial proposal system 10 can model the relationship between groups of users with similar satisfaction trends and characteristic information within those groups, and can then perform inferences by grouping users of the target space so that users with similar satisfaction trends are divided into the same groups.

[0059] Invention 4 is a spatial proposal system 10 described in any one of Inventions 1 to 3, wherein the spatial utilization information includes at least one of the following: the utilization rate of the space, the utilization rate of each of the multiple areas, and the time spent in each of the multiple areas.

[0060] Such a spatial proposal system 10 can use at least one of the following as spatial utilization information for model construction data: the spatial utilization rate, the utilization rate of each of the multiple areas, and the duration of stay in each of the multiple areas.

[0061] Invention 5 is a spatial proposal system 10 described in any one of Inventions 1 to 4, wherein the spatial utilization effect information includes at least one of the following: the overall satisfaction level of each of the multiple users when using the space, the satisfaction level of the area used among the multiple areas, the satisfaction level of the tasks performed in connection with the use of the space, and the results related to the tasks.

[0062] Such a spatial proposal system 10 can use at least one of the following as spatial utilization effect information for model construction data: the overall satisfaction level of each of the multiple users when using the space, the satisfaction level of the area used among multiple areas, the satisfaction level of the tasks performed in conjunction with the use of the space, and the results related to the tasks.

[0063] Invention 6 is a spatial suggestion system 10 described in any one of Inventions 1 to 5, wherein the characteristic information includes at least one of the following for each user: environmental preferences, personality traits, job traits, and organizational traits.

[0064] Such a spatial proposal system 10 can use at least one of the following as characteristic information for model construction data: each user's environmental preferences, personality traits, job traits, and organizational traits.

[0065] Invention 7 is a spatial suggestion system 10 described in any one of Inventions 1 to 6, wherein the acquisition unit 14 further acquires at least one of the following information: subjective evaluation information relating to the individuality of each user of the target space, biometric information, basic attribute information including at least one of age and gender, and occupational attribute information including at least one of job title and occupation.

[0066] Such a spatial proposal system 10 can use, in its model-based inference, at least one of the following pieces of information: subjective evaluation information about the individuality of each user of the target space, biometric information, basic attribute information including at least one of age and gender, and occupational attribute information including at least one of job title and occupation.

[0067] Invention 8 is a spatial proposal system 10 described in any one of Inventions 1 to 7, wherein the spatial design information includes at least one of the following: the area ratio, seating ratio and placement location of each of a plurality of areas to be placed in the target space, control conditions for controlling the environment of the target space and the required number of spatial control devices for controlling the environment, and the spatial design effect obtained when following the spatial design information.

[0068] Such a spatial proposal system 10 can output spatial design information that includes the area ratio, seating ratio and placement location of each of several areas to be placed in the target space, control conditions for controlling the environment of the target space and the required number of spatial control devices for controlling the environment, and at least one of the spatial design effects that can be obtained by following the spatial design information.

[0069] Invention 9 is a spatial proposal method performed by a computer, comprising the steps of: constructing a model that shows the relationship between spatial utilization information regarding which of several areas included in a space were used by multiple users of a space (different spaces) (step S102); spatial utilization effect information showing an evaluation of the multiple users' use of the space; and characteristic information showing the characteristics of each of the multiple users; acquiring target characteristic information showing the characteristics of users of a target space (space 70) different from the space (step S103); generating spatial design information relating to the spatial design of the target space from the acquired target characteristic information by inference using the constructed model (step S105); and outputting the generated spatial design information (step S106).

[0070] This method of proposing spatial arrangements can achieve the same effects as the spatial arrangement system 10 described above.

[0071] Invention 10 is a program for causing a computer to execute the spatial proposal method of Invention 9.

[0072] Such a program can be used to achieve the same effects as the spatial proposal system 10 described above using a computer.

[0073] (Other embodiments) Although embodiments have been described above, the present invention is not limited to the embodiments described above.

[0074] For example, in the above embodiment, the space was an office space, but the space proposal system may propose the required number of seats in multiple areas included in spaces other than office spaces.

[0075] Furthermore, in the above embodiment, it was explained that the spatial proposal system may be implemented by a single server device or by multiple server devices. Thus, the term "system" in this specification may consist of a single device or multiple devices. When a system consists of multiple devices, the components of the system (in particular, the functional components) may be distributed among the multiple devices in any way.

[0076] Furthermore, the communication method between devices in the above embodiment is not particularly limited. In addition, relay devices (such as broadband routers) not shown may be involved in the communication between devices.

[0077] Furthermore, in the above embodiment, a process executed by a specific processing unit may be executed by another processing unit. Also, the order of multiple processes may be changed, or multiple processes may be executed in parallel.

[0078] Furthermore, in the above embodiment, each component may be realized by executing a software program suitable for each component. Each component may also be realized by a program execution unit such as a CPU or processor reading and executing a software program recorded on a recording medium such as a hard disk or semiconductor memory.

[0079] Furthermore, each component may be implemented by hardware. For example, each component may be a circuit (or integrated circuit). These circuits may form a single circuit as a whole, or they may be separate circuits. Also, each of these circuits may be a general-purpose circuit or a dedicated circuit.

[0080] Furthermore, general or specific embodiments of the present invention may be implemented as a system, apparatus, method, integrated circuit, computer program, or recording medium such as a computer-readable CD-ROM. Alternatively, they may be implemented as any combination of a system, apparatus, method, integrated circuit, computer program, and recording medium.

[0081] For example, the present invention may be implemented as a spatial proposal method executed by a computer, such as the spatial proposal system of the above embodiment, or as a program (computer program product) that causes a computer to execute a spatial proposal method. Furthermore, the present invention may be implemented as a computer-readable non-temporary recording medium on which such a program is recorded.

[0082] Furthermore, the present invention also includes forms obtained by applying various modifications to each embodiment that a person skilled in the art could conceive, or forms realized by arbitrarily combining the components and functions of each embodiment without departing from the spirit of the present invention. [Explanation of symbols]

[0083] 10. Spatial Proposal System 11 Communications Department 12 Information Processing Section 13 Storage section 14 Acquisition Department 15 Generation part 16 Model Building Department 17. Model Inference Unit 18 Output section 20 Mobile devices 30 Positioning Systems 31 Communication terminals 40 Information terminals 70 space

Claims

1. A model building unit constructs a model that shows the relationship between spatial usage information, which of the multiple areas included in the space was used by multiple users of the space; spatial usage effect information, which shows the evaluation of the multiple users' use of the space; and characteristic information, which shows the characteristics of each of the multiple users. An acquisition unit that acquires target characteristic information indicating the characteristics of users utilizing a target space different from the aforementioned space, A generation unit generates spatial design information relating to the spatial design of the target space from the acquired target characteristic information by inference using the constructed model, It comprises an output unit that outputs the generated spatial design information. A spatial design system.

2. The aforementioned model building unit, The users are grouped into the same group such that users who have the same trend in satisfaction based on the spatial utilization effect information relative to the feature quantities based on the spatial utilization information are divided into the same group. Construct the model that associates a predetermined group with the characteristic information of users divided into that predetermined group. The spatial proposal system according to claim 1.

3. In the inference using the aforementioned model, users of the target space are grouped together based on the target characteristic information of the users of the target space, such that users with similar satisfaction tendencies are grouped together. The spatial proposal system according to claim 2.

4. The aforementioned space utilization information includes at least one of the following: the utilization rate of the space, the utilization rate of each of the multiple areas, and the duration of stay in each of the multiple areas. The spatial proposal system according to claim 1.

5. The aforementioned space utilization effectiveness information includes at least one of the following: the overall satisfaction level of each of the multiple users when using the space, the satisfaction level of the area used among the multiple areas, the satisfaction level of the tasks performed in conjunction with the use of the space, and the results related to the tasks. The spatial proposal system according to claim 1.

6. The aforementioned characteristic information includes at least one of the following for each user: environmental preferences, personality traits, job characteristics, and organizational characteristics. The spatial proposal system according to claim 1.

7. The acquisition unit further acquires at least one of the following: subjective evaluation information relating to the individuality of each user in the target space, biometric information, basic attribute information including at least one of age and gender, and occupational attribute information including at least one of job title and occupation. The spatial proposal system according to claim 1.

8. The spatial design information includes at least one of the following: the area ratio, seating ratio, and placement location of each of the multiple areas to be placed within the target space; control conditions for controlling the environment of the target space; the required number of spatial control devices for controlling the environment; and the spatial design effect obtained when following the spatial design information. A spatial proposal system according to any one of claims 1 to 7.

9. A spatial proposal method performed by a computer, Steps include constructing a model that shows the relationship between spatial usage information, which of the multiple areas included in the space was used by multiple users of the space; spatial usage effect information, which shows the evaluation of the multiple users' use of the space; and characteristic information, which shows the characteristics of each of the multiple users. A step of acquiring target characteristic information that indicates the characteristics of users who use a target space different from the aforementioned space, The steps include generating spatial design information relating to the spatial design of the target space from the acquired target characteristic information by inference using the constructed model, The step of outputting the generated spatial design information includes Space proposal method.

10. To cause the computer to execute the spatial proposal method described in claim 9. program.

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