JP7798134B2 - Information processing system and information processing method - Google Patents

Description

The present invention relates to an information processing system and an information processing method.

In recent years, devices have been developed that can identify the source of odors within a specific space. For example, Patent Document 1 describes an odor identification device that uses coke odors and tar odors collected from potential odor sources in steel plants as reference odors and identifies the source and cause of unknown odors in steel plants and other facilities.

JP 2006-017467 A

The smell in a restroom space is important for users to realize the cleanliness of the space and to use it comfortably. The smell in a restroom space can constantly change depending on the frequency of use, cleaning frequency, the smell of the air flowing in from outside the space, and the air flow within the space. The smell in a restroom space is caused by changes in the relative and/or absolute intensity of various known smells.

One aspect of the present invention is to provide an information processing system and information processing method that accurately determine the cause of changes in odors in a toilet space.

An information processing system according to one aspect of the present invention comprises: an odor measurement device that measures odors within a toilet space and outputs a measurement signal; an estimation unit that inputs the measurement signal output from the odor measurement device into a trained model obtained by machine learning using training data including explanatory variables including the measurement signal output from the odor measurement device during a sample period and a target variable including event information indicating an event actually identified as the cause of a change in odor within the toilet space corresponding to the measurement signal during the sample period, and outputs an estimation result that estimates the causative event of the change in odor within the toilet space; and a determination unit that determines the causative event of the change in odor within the toilet space based on the multiple estimation results output from the estimation unit. The odor measurement device comprises multiple odor sensor elements that are capable of measuring different odor substances, and the measurement signal is output from each of the multiple odor sensor elements.

An information processing method according to one aspect of the present invention includes an estimation step of inputting the measurement signals output from an odor measurement device that measures odors within a toilet space into a trained model obtained by machine learning using training data including explanatory variables including measurement signals output from the odor measurement device during a sample period from the odor measurement device, and objective variables including event information indicating events actually identified as the cause of changes in odor within the toilet space corresponding to the measurement signals during the sample period, and outputting an estimation result that estimates the event causing the changes in odor within the toilet space; and a determination step of determining the event causing the changes in odor within the toilet space based on multiple estimation results output from the estimation unit during a target period.

One aspect of the present invention provides an information processing system and information processing method that accurately determine the cause of changes in odor in a toilet space.

1 is a schematic diagram illustrating an example of a configuration of an information processing system according to an embodiment of the present invention. 1 is a functional block diagram showing an example of an information processing system including an odor measurement device according to an embodiment of the present invention. FIG. 2 is a top view showing an example of the configuration of an odor sensor element. 1 is a functional block diagram showing an example of a configuration of an information processing system according to an embodiment of the present invention. 10 is a flowchart showing an example of a processing flow in which an information processing system according to an embodiment of the present invention determines an odor in a toilet space. 1 is a schematic diagram illustrating an example of a configuration of an information processing system according to an embodiment of the present invention. 1 is a schematic diagram illustrating an example of a configuration of an information processing system according to an embodiment of the present invention. 1 is a functional block diagram showing an example of a configuration of an information processing system according to an embodiment of the present invention. 1 is a functional block diagram showing an example of a configuration of an information processing system according to an embodiment of the present invention. 1 is a functional block diagram showing an example of a configuration of an information processing system according to an embodiment of the present invention.

One embodiment of the present invention is described below, but the present invention is not limited to this. Furthermore, unless otherwise specified in this specification, the numerical range "A to B" means "greater than or equal to A and less than or equal to B."

In this specification, a "toilet space" refers to a space in which one or more toilet bowls are installed, and is also referred to as a toilet, toilet room, restroom, or washroom. A toilet space may be a space in which only one toilet bowl is installed (for example, a private room), or a space in which multiple toilet bowls are installed.

[Embodiment 1]
(Information processing system 100)
First, an overview of an information processing system 100 according to an embodiment of the present invention will be described using Fig. 1. Fig. 1 is a schematic diagram showing an example of the configuration of an information processing system 100 according to an embodiment of the present invention.

As shown in FIG. 1, the information processing system 100 includes an odor measurement device 30 capable of outputting a detection signal based on an odorous substance corresponding to the odor in the toilet space, and a determination device 10 capable of determining the cause of a change in odor in the toilet space based on the detection signal. As shown in FIG. 1, the information processing system 100 may include an odor measurement device 30 and a determination device 10 connected via a wide-area communication network 40.

The information processing system 100 is useful as a method for determining the cause of a change in odor within a restroom space. For example, the restroom space manager can dispatch cleaning staff at the appropriate time based on the determined cause. The information processing system 100 can also digitize the status of multiple restroom spaces to support efficient restroom space management.

The number of odor measuring devices 30 provided in the information processing system 100 according to one embodiment of the present invention is not particularly limited, and may be one or more, three or more, five or more, or ten or more. Furthermore, the odor measuring devices 30 may be installed in toilet spaces located in different locations, or some or all of them may be installed in toilet spaces located in the same location. In one embodiment, the odor measuring device 30 may be installed so that the height of the air intake facing the floor surface is 50 cm or less from the floor. Because odors typically rise from the floor, the above configuration allows for more accurate odor detection.

The wide-area communication network 40 is not particularly limited and may be the Internet, a telephone line network, a mobile communication network, a CATV communication network, a satellite communication network, etc., and more specifically may be Bluetooth (registered trademark), Bluetooth (registered trademark) Low Energy (BLE), Wi-Fi (registered trademark), Thread, ZigBee (registered trademark), cellular low-power wide-area (LPWA) (e.g., narrowband (NB)-IoT, LTE-M), non-cellular LPWA (e.g., Sigfox (registered trademark), LoRaWAN), etc. The wide-area communication network 40 may also be connected to a cloud server that stores the detection signal output by the odor measuring device 30 and the determination result output by the determination device 10. Furthermore, if the wide-area communication network 40 is connected to a cloud server, the determination device 10 may be implemented as the cloud server.

Furthermore, the determination device 10 may transmit the determination result of the causative event of the change in odor within the toilet space to a manager terminal 50 owned by the manager of the toilet space. In this specification, the manager of the toilet space may be, for example, the owner of the building in which the toilet space is located, or a manager entrusted with managing the toilet space. This allows the manager of the toilet space to obtain information regarding the causative event of the change in odor within the toilet space and to take appropriate action, such as dispatching a cleaning staff member, to the toilet space. Examples of the manager terminal 50 include a laptop computer, smartphone, tablet terminal, etc. The determination device 10 may also display the determination result on a web page accessible by the manager terminal.

In the information processing system 100, the odor measurement device 30 is equipped with multiple sensor elements that can measure different odor substances. The measurement signal is output from each of the multiple odor sensor elements. The sensor elements will be described below. After that, details of the odor measurement device 30 that uses the odor sensor element 31, and the information processing system 100 that includes the odor measurement device 30 and the determination device 10 will be described.

(Odor measuring device 30)
The outline and effects of an odor measurement device 30 employing an odor sensor element 31 will be described below with reference to Fig. 2. Fig. 2 is a functional block diagram showing an example of the configuration of an information processing system 100 equipped with an odor measurement device 30 employing an odor sensor element 31. The odor measurement device 30 includes an odor sensor element 31 that detects odor substances, a power source 32 (power supply), a clock 33 (timer), a control unit 34, and a communication unit 35. As described above, the odor measurement device 30 may be connected to a wide area communication network 40.

The power supply 32 is a power source for supplying power to the odor sensor element 31. The power supply 32 may be a constant voltage power supply, a constant current power supply, or an AC power supply. If the power supply 32 is a constant voltage power supply, it supplies a current (e.g., a direct current of 1 μA to 10 mA) to the odor sensor element 31 via lead wires. The voltage value supplied by the power supply 32 is, for example, 0.01 V to 10 V, and more specifically, 2.5 V or 5.0 V.

The clock 33 measures the time. The clock 33 transmits the measured time to the control unit 34. The clock 33 may be a clock whose time is set by the user, or may be a radio-controlled clock.

The control unit 34 controls all parts of the odor measuring device 30. The control unit 34 also outputs the odor detected by the odor sensor element 31 as a measurement signal. The control unit 34 may output the odor measurement signal according to the time measured by the clock 33.

The communication unit 35 transmits the measurement signal output by the control unit 34. The communication unit 35 transmits the measurement signal to the wide area communication network 40, and the transmitted measurement signal is acquired by the determination device 10.

The odor measuring device 30 may further include a housing, although this is not a required component. The housing is a container capable of containing air containing odorous substances. If a housing is included, the odor sensor element 31 is installed within the housing.

The odor measuring device 30 outputs a measurement signal that indicates the change over time in the electrical conductivity of the odor sensor element 31 before and after an odor substance is adsorbed to the odor sensor element 31. This makes it possible to detect and identify various odor substances.
stomach.

<Odor sensor element 31>
3 is a top view showing an example of the configuration of an odor sensor element 31. The odor sensor element 31 includes an odorant receiving layer 315 containing the above-described resin composition, a first metal wiring 313A, and a second metal wiring 313B. In the following, when there is no need to distinguish between the first metal wiring 313A and the second metal wiring 313B, they may be referred to as metal wiring 313.

The first metal wiring 313A and the second metal wiring 313B are each metal wirings that function as electrodes for measuring changes in the electrical conductivity of the odorant receiving layer 315 (i.e., the resin composition). That is, the first metal wiring 313A and the second metal wiring 313B are spaced apart from each other, and the odorant receiving layer 315 is in contact with at least a portion of the first metal wiring and at least a portion of the second metal wiring. In one example, the first metal wiring 313A and the second metal wiring 313B are metal wirings that are not in direct contact with each other, and may be metal wirings that are approximately parallel to each other, as shown in Figure 2.

As shown in FIG. 3, metal wiring 313, including first metal wiring 313A and second metal wiring 313B, may be disposed on substrate 311. Substrate 311 may be a substrate such as glass epoxy commonly used in electronic circuits. Metal wiring 313 may be metal wiring such as copper or gold. The thickness of each of first metal wiring 313A and second metal wiring 313B when viewed perpendicular to the surface of the substrate may be, for example, 10 μm to 2 mm.

The odorant receiving layer 315 may be in contact with at least a portion of the first metal wiring 313A and at least a portion of the second metal wiring 313B. The odorant receiving layer 315 may be arranged to fill the area between the first metal wiring 313A and the second metal wiring 313B, as shown in Figures 2 and 3, for example.

If the electrical conductivity of the odorant receiving layer 315 (i.e., the electrical conductivity of the odor sensor element 31) is low, it is desirable that the distance between the first metal wiring 313A and the second metal wiring 313B be a predetermined distance (e.g., 500 μm) or less.

The odorant receiving layer may contain a resin composition. The resin composition may contain a resin and may further contain one or more types selected from a surfactant and a filler (e.g., a conductive carbon material). In this specification, "odorant receiving layer" refers to a layer that adsorbs the odorant to be identified. The odorant receiving layer 315 is formed from the resin composition described above. The odorant receiving layer 315 may be provided as part of the odor sensor element 31. The electrical resistance of this odorant receiving layer 315 changes in response to odorant adsorption, etc. In other words, the odor sensor element 31 is an odor detection device equipped with such an odorant receiving layer 315, and the odor measurement method of the odor sensor element 31 may be a chemiresistor type. Furthermore, the odor sensor element 31 is not limited to the chemiresistor type odor sensor element described above, but may also include one or more types of odor sensor elements used in known gas sensors, ammonia sensors, odor sensors, VOC sensors (volatile organic compound sensors), etc. The detection results from sensor elements used in these known sensors may be used as reference values when analyzing odors.

The information processing system 100 may include a known sensor different from the odor sensor element 31. There are no particular limitations on the known sensor, and any sensor that can be used as a known sensor can be used. Examples of known sensors include gas sensors, thermo-hygrometers, volatile organic compound (VOC) sensors, alcohol sensors, optical sensors, human presence sensors, and door opening/closing sensors. Using a known sensor in conjunction with the odor measuring device 30 may more accurately identify the cause of the odor in the toilet space. Note that in the information processing system 100, the odor measuring device 30 may be configured to include the odor sensor element 31 and a sensor element that is the same as these known sensors.

For example, a gas sensor is suitable for detecting odors caused by gas leaks. Optical sensors are also suitable for detecting odors caused by smoke. If the vomit contains alcohol, an alcohol sensor can detect it more accurately. A thermo-hygrometer can be used to correct the values detected by odor sensors, VOC sensors, gas sensors, etc., and to estimate the lifespan of sensor probes based on the environment in which the sensors are installed. Note that if the results of the odor sensor differ from those of other sensors, the results of the odor sensor may take priority.

When the odor sensor element 31 is a chemiresistor type containing a resin composition, the change in electrical conductivity over time differs between when odorant A is adsorbed and when odorant B, which is different from odorant A, is adsorbed, making it possible to detect and distinguish various odorants. The odor measurement device 30 described below includes multiple odor sensor elements 31 each having a substrate 311 with a structure for detecting odorants (metal wiring 313 and odorant receiving layer 315). Each substrate 311 is provided with multiple sets of odorant receiving layers 315, each of which can measure different odorants. Each of the multiple odor sensor elements 31 may be equipped with a constant-voltage power supply and a voltmeter. In the odor measurement device 30, each substrate 311 may be provided with one structure for detecting odorants (metal wiring 313 and odorant receiving layer 315). Alternatively, in the odor measurement device 30, multiple sets of structures for detecting odorants (metal wiring 313 and odorant receiving layer 315) may be provided on a single substrate 311. In the latter case, a constant voltage power supply and a voltmeter are connected to each set provided on the substrate 311.

The resin compositions contained in the odorant receiving layers 315 of the multiple odor sensor elements 31 included in the odor measuring device 30 may be the same or different. If the odorant receiving layers 315 included in the multiple odor sensor elements 31 have the same composition, each of the multiple odorant receiving layers 315 will be able to detect the same odorant. Furthermore, if the multiple odor sensor elements 30 each include odorant receiving layers 315 with different compositions, each of the multiple odorant receiving layers 315 will respond differently to the odorant. In this way, by providing multiple sets of configurations for detecting odorants, the accuracy of odorant identification in the odor measuring device 30 can be improved.

The odor measuring device 30 described above can output the change in electrical conductivity of the odor sensor element 31 over time for each odor substance when various odor substances are adsorbed onto the odor sensor element 31. By applying this odor measuring device 30, it is possible to compare the change in electrical conductivity of the odor sensor element 31 over time when odor substance A is adsorbed onto the odor sensor element 31 with the change in electrical conductivity of the odor sensor element 31 over time when odor substance B is adsorbed onto the odor sensor element 31. Based on the results of this comparison, it is possible to realize a determination device 10 that can determine the cause of odor changes in the toilet space, as described below, from the odor substances adsorbed onto the odor sensor element 31.

(Determination device 10)
Below, we will explain the overview and effects of the determination device 10. The determination device 10 is a device that determines the cause of a change in odor in a toilet space from the measurement signal output by the above-mentioned odor measurement device 30. The determination device 10 uses a trained model obtained by machine learning, so it can determine odor substances with high accuracy.

Figure 4 is a functional block diagram showing an example configuration of the determination device 10. The determination device 10 includes a control unit 1 that controls all of the components of the determination device 10, and a memory unit 2 that stores various data used by the determination device 10, but is not limited to this configuration. For example, the memory unit 2 may be an external device attached to the determination device 10. Furthermore, the determination device 10 may be connected to the wide area communication network 40, as described above.

<Control Unit 1>
First, the control unit 1 will be described. The control unit 1 includes a measurement signal acquisition unit 11, an estimation unit 12, a determination unit 13, a communication unit 14, and an output control unit 15. Furthermore, the functions of some of the blocks included in the control unit 1 may be provided to another device that can communicate with the determination device 10, and the relevant blocks may be omitted from the control unit 1. For example, the function of the output control unit 15 may be provided to another device. In this case, the determination device 10 may output the result determined by the determination unit 13 from the other device.

The measurement signal acquisition unit 11 acquires the measurement signal output from the odor measurement device 30 via the wide area communication network 40. The measurement signal acquisition unit 11 may be configured to acquire the measurement signal output from the odor measurement device 30 in real time, or may be configured to acquire the measurement signal stored on the wide area communication network 40 at regular intervals. The measurement signal acquisition unit 11 preferably acquires the measurement signal every first hour. The measurement signal acquisition unit stores the acquired measurement signal data in the memory unit 2.

The first time period may be, for example, 1 minute, 5 minutes, 10 minutes, 30 minutes, 1 hour, 2 hours, 4 hours, 6 hours, 8 hours, 10 hours, or more, but is not particularly limited.

The estimation unit 12 inputs the measurement signal data into the trained model 22 to estimate the causative event of the change in odor in the toilet space. The measurement signal may be measurement signal data 21 stored in the memory unit 2. From the viewpoint of improving the accuracy of the estimation, it is preferable that the estimation unit 12 inputs multiple measurement signals into the trained model 22. The estimation unit may estimate an event including at least one of fecal contamination of the toilet space, urine contamination, and vomit contamination as the causative event of the change in odor in the toilet space. The estimation unit 12 may estimate the type of the causative event, for example, by class classification. The estimation unit 12 may also estimate the intensity of the causal analysis, in which case the intensity estimation may be performed by regression analysis. The estimation unit 12 may output the estimation result every second time. The second time may be shorter than, the same as, or longer than the first time. From the viewpoint of improving the accuracy of the estimation result of the estimation unit, it is preferable that the second time be longer than the first time. The estimation unit 12 stores the output estimation results in the memory unit 2.

The event may be an event caused by a user of the toilet space other than contamination by feces, urine, or vomit. In this specification, "an event caused by a user of the toilet space" refers to an event in which the odor in the toilet space changes due to an odor emitted by the user themselves. In other words, "an event caused by a user of the toilet space" can be considered an odor that is unrelated to contamination of the toilet space itself. Specific examples include odors such as perfume, tobacco, body odor, fabric softener on the user's clothes, and detergent for the user's clothes that are caused by the user. By being able to infer an event caused by a user of the toilet space as the causal event, it becomes possible to detect changes in the odor of the toilet space that are due to factors other than contamination of the toilet space, allowing for more accurate estimation.

The determination unit 13 determines the causal event of the change in odor in the toilet space based on the multiple estimation results output from the estimation unit 12. The multiple estimation results may be stored in the memory unit 2 as estimation result data 23. The determination unit 13 estimates the causal event based on the multiple estimation results. The determination unit 13 may determine the causal event by, for example, identifying the causal event that is most frequently estimated as the causal event in the estimation results obtained from the most recent N estimations. Because the determination unit 13 determines the causal event based on the multiple estimation results, it is possible to accurately determine the causal event. The determination unit 13 may determine the causal event as an event including at least one of contamination of the toilet space by feces, contamination by urine, and contamination by vomit, as the causal event. The determination unit 13 may further output information regarding the magnitude of the impact of the causal event on the odor in the toilet space and/or information regarding the elimination of the causal event, as necessary.

Examples of information relating to the impact of odors in the toilet space include the intensity of the odor, the duration of the odor, the type of odor, and the unpleasantness of the odor. Furthermore, examples of information relating to resolving the causative event include dispatching a cleaning service, giving instructions to cleaning staff, etc.

The output control unit 15 outputs the determination result by the determination unit 13 to the communication unit 16. When the determination result by the determination unit 13 is sent to the administrator terminal 50, the output control unit 15 may identify the administrator terminal 50 to which the determination result is to be sent, based on the administrator terminal data 24.

The communication unit 14 transmits the determination result output by the output control unit 15 to the administrator terminal 50 via the wide area communication network 40 based on the administrator terminal data 24. The communication unit 14 may transmit the determination result directly to the administrator terminal 50, or may transmit the determination result to a web page or the like on the wide area communication network 40 that is accessible by the administrator terminal 50.

<Storage unit 2>
Next, a description will be given of the storage unit 2. The storage unit 2 may store measurement signal data 21, a trained model 22, estimation result data 23, and administrator terminal data 24.

The measurement signal data 21 is data of the measurement signal output from the odor measurement device 30 and acquired by the measurement signal acquisition unit 11. The measurement signal data 21 may be labeled with information such as the time of measurement, the location of measurement, the identification number of the odor measurement device 30, and the type of measurement signal pattern.

The trained model 22 is trained by machine learning using training data.
The training data includes the following explanatory variables and objective variables.
The explanatory variables include the measurement signal output from the odor measuring device 30 during the sample period.
The objective variable includes event information indicating an event actually identified as the cause of the change in odor in the toilet space corresponding to the measurement signal during the sample period. The sample period may be longer, shorter, or the same as the first time period. The trained model 22 may be generated using a known machine learning algorithm. Examples of machine learning algorithms that can be used to generate the trained model 22 include the k-nearest neighbor method, logistic regression, support vector machines, random forests, and neural networks.

In one embodiment, if the information processing system 100 is equipped with sensors other than the odor measuring device 30, the trained model 22 further includes, as explanatory variables, measurement signals output during the sample period from sensors other than the odor measuring device 30.

The estimation result data 23 is the result of estimating the causative events of the change in odor in the toilet space, output from the estimation unit 12. The estimation result data 23 may be labeled with the same information as the measurement signal data that served as the basis for the estimation.

The administrator terminal data 24 is data relating to the terminal owned by the administrator of the toilet space in which the odor measuring device 30 is installed. The administrator terminal data 24 is data for linking the odor measuring device 30 with the administrator terminal 50 owned by the administrator of the toilet space in which the odor measuring device 30 is installed. The administrator terminal data 24 may be, for example, data linking the device number of the odor measuring device 30 with the terminal number of the administrator terminal 50, or data linking the location of the toilet space in which the odor measuring device 30 is installed with the location of the administrator terminal owned by the administrator of the toilet space.

(Processing performed by information processing system 100)
An outline of an information processing method according to an embodiment of the present invention will be described with reference to Fig. 5. Fig. 5 is a flowchart showing an outline of an information processing method by the information processing system 100.

In step S1, the odor measuring device 30 measures the odor in the toilet space and outputs a measurement signal. At this time, the odor measuring device 30 may output the odor measurement results to the determination device 10 in real time, or may output them every first hour as described above.

In acquisition step S2, the measurement signal acquisition unit 11 acquires the measurement signal output from the odor measurement device 30. The measurement signal acquisition unit 11 may acquire the measurement signal output from the odor measurement device 30 in real time, or may acquire the measurement signal stored on the network every first time period. The measurement signal acquisition unit 11 may store the acquired measurement signal in the memory unit 2.

In estimation step S3, the estimation unit 12 inputs the measurement signal output from the odor measuring device 30 into the trained model, estimates the causative event of the change in odor in the toilet space, and outputs the estimation result. At this time, the trained model 22 is obtained by machine learning using training data. The explanatory variables and objective variables contained in the training data are as described above. The estimation unit 12 may store the output estimation result in the memory unit 2.

In determination step S4, the determination unit 13 determines the causative event for the change in odor in the toilet space based on the multiple estimation results output by the estimation unit 12. The information determined by the determination unit 13 is output by the output control unit 15. The output control unit 15 may output not only the causative event for the change in odor in the toilet space, but also information regarding the extent to which the causative event affects the odor in the toilet space, and/or information regarding the elimination of the causative event.

In step S5, the communication unit 14 transmits the determination result output by the output control unit 15.

Since the smell in a restroom space can constantly change due to various factors, it has been difficult to estimate the cause of the change in smell. By using the information processing system 100, the determination unit 13 makes a determination based on multiple estimation results rather than a single estimation result, making it possible to accurately determine the cause of the change in smell in the restroom space.

[Embodiment 2]
An overview of an information processing system 100a according to another embodiment of the present invention will be described below with reference to Fig. 6. Fig. 6 is a schematic diagram showing an example of the configuration of an information processing system 100a different from that of embodiment 1. Note that descriptions of matters that have already been described will be omitted.

As shown in FIG. 6, in the information processing system 100a, the measurement signal output by the odor measurement device 30 is transmitted to the administrator terminal 50. The administrator terminal 50 transmits the acquired measurement signal to the determination device 10 via the wide area communication network 40. The administrator terminal 50 also receives the determination result output from the determination device 10 based on the measurement signal via the wide area communication network 40.

The information processing system 100a includes a determination device 10, an odor measurement device 30, and an administrator terminal 50. The information processing system 100a may also include a wide area communication network 40, if necessary. As described above, in the information processing system 100a, the determination device 10 and the administrator terminal 50 may be connected via the wide area communication network 40. Furthermore, in the information processing system 100a, the odor measurement device 30 and the administrator terminal 50 may be connected via a local area network (LAN) connection, LTE communication, or the like, without going through a provider, etc.

With the above configuration, the measurement signal is sent from the administrator terminal 50, making it easy to link the measurement signal with the administrator terminal data 24.

[Embodiment 3]
An overview of an information processing system 100b according to another embodiment of the present invention will be described below with reference to Fig. 7. Fig. 7 is a schematic diagram showing an example of the configuration of the information processing system 100b. Note that descriptions of matters that have already been described will be omitted.

As shown in FIG. 7, in the information processing system 100b, the measurement signal output by the odor measuring device 30 is sent directly to the determination device 10a. The determination device 10a determines the cause of the change in odor in the toilet space based on the acquired measurement signal and outputs the determination result. In other words, in the information processing system 100b, the determination device 10a can be said to be integrated with the administrator terminal 50. Furthermore, in the information processing system 100b, the determination device 10a and the odor measuring device 30 may be connected via a local area network connection, LTE communication, etc., without going through a provider, etc.

(Configuration of information processing system 100b)
8 is a functional block diagram showing an example of the configuration of an information processing system 100b different from those of the first and second embodiments. The information processing system 100b includes a determination device 10a and an odor measurement device 30. The information processing system 100b may also include a wide area communication network 40 as necessary.

The determination device 10a includes a control unit 1a that controls all the components of the administrator terminal 50, a memory unit 2a that stores various data used by the information processing device, and an output unit 16 that outputs the determination results. The control unit 1a includes a measurement signal acquisition unit 11, an estimation unit 12, a determination unit 13, and an output control unit 15. The memory unit 2a stores measurement signal data 21, a trained model 22, and estimation result data 23.

<Control unit 1a>
The control unit 1 a includes a measurement signal acquisition unit 11 , an estimation unit 12 , a determination unit 13 , and an output control unit 15 .

The output control unit 15 causes the output unit 16 to output the determination result output by the determination unit 13. The output form of the output unit 16 is not particularly limited, and may be, for example, a display output, a print output, or an audio output.

With this configuration, the determination device 10a is integrated with the administrator terminal 50, reducing the time lag until the determination result is obtained.

[Embodiment 4]
An overview of an information processing system 100c according to another embodiment of the present invention will be described below with reference to Fig. 9. Fig. 9 is a schematic diagram showing an example of the information processing system 100c. Note that descriptions of matters that have already been described will be omitted. Hereinafter, when there is no need to distinguish between the odor measurement devices 30a and 30b, they will simply be referred to as "odor measurement device 30."

As shown in FIG. 9, the information processing system 100c includes odor measuring devices 30a and 30b. The odor measuring devices 30a and 30b may be installed, for example, in the same toilet space. In that case, the odor measuring devices 30a and 30b may be installed in different areas and/or positions in the same toilet space.

Specifically, for example, odor measuring device 30a may be installed near a urinal, and odor measuring device 30b may be installed near a toilet. As another example, odor measuring device 30a may be installed near the floor of the toilet space, and odor measuring device 30b may be installed near the ceiling of the toilet space.

Examples of areas within the toilet space where the odor measuring devices 30a and 30b may be installed include areas near urinals, toilets, powder rooms, hand washing areas, and cleaning tool drawers. One or more odor measuring devices 30 may be installed in at least one of these areas.

With this configuration, it is easy to determine where contamination has occurred within the toilet space. Furthermore, if only one of the multiple odor measuring devices 30 installed consistently detects values that are different from the other devices, it is easy to determine that that device is malfunctioning.

In the information processing system 100c, the odor measurement devices 30a and 30b transmit measurement results to the determination device 10 via the wide area communication network 40. The measurement results may also be transmitted to the administrator terminal 50. The wide area communication network 40 is as described in embodiment 1.

The odor measuring device 30 transmits a detection signal based on the odorous substance corresponding to the odor in the toilet space as a measurement result. In one embodiment, the odor measuring device 30 may also transmit data related to the odor measuring device 30 itself in association with the measurement result.

Data related to the odor measuring devices 30 include, for example, ID data for each odor measuring device 30, ID data for the odor sensor elements 31 included in each odor measuring device 30, and installation location data for each odor measuring device 30. Examples of ID data for the odor measuring devices 30 include the identification number of the SIM card included in each odor measuring device 30 and the device number assigned to each odor measuring device 30. Examples of ID data for the sensor elements included in the odor measuring devices 30 include the identification number assigned to each odor sensor element 31 and data related to the type of each odor sensor element 31. Examples of installation location data for the odor measuring devices 30 include ID data for the area in which each odor measuring device 30 is installed, data on the location where the odor measuring device 30 is installed (e.g., the distance from the floor), and data on the direction in which the odor measuring device 30 is installed (e.g., the direction of the air intake).

In one embodiment, the data transmitted by the odor measuring device 30 to the determination device 10 may include a detection signal based on an odor substance corresponding to the odor in the toilet space, the identification number of the SIM card possessed by each odor measuring device 30, the identification number of each odor sensor element 31, and location data based on the GPS equipped in each odor measuring device 30.

In addition to the data described above, the odor measuring device 30 may also transmit time data, such as the time when the detection signal was transmitted and the time when the detection signal was detected.

Although the information processing system 100c including an odor measurement device 30 has been described, it is not limited to this configuration. For example, the information processing system 100c may be configured to include three or more odor measurement devices 30.

[Embodiment 5]
An overview of an information processing system 100d according to another embodiment of the present invention will be described below with reference to FIG. 10. FIG. 10 is a schematic diagram showing an example of the information processing system 100d. Note that descriptions of matters that have already been described will be omitted. Below, when there is no need to distinguish between the odor measurement devices 30a to 30f, they will simply be referred to as "odor measurement device 30." Furthermore, below, when there is no need to distinguish between the administrator terminals 50a to 50c, they will simply be referred to as "administrator terminal 50." Furthermore, below, when there is no need to distinguish between the networks 60a to 60c, they will simply be referred to as "network 60."

As shown in FIG. 10, the information processing system 100d includes multiple odor measurement devices 30 installed at different locations, and an administrator terminal 50 corresponding to each odor measurement device 30 at each location. For example, odor measurement devices 30a and 30b shown in FIG. 10 are located in the same location as administrator terminal 50a.

The location may be, for example, a building, store, station, hospital, nursing home, park, town hall, or other public facility, or it may be a home. The locations where the combinations of odor measuring device 30 and administrator terminal 50 present in information processing system 100d are installed may be within the same building or different buildings. For example, an odor measuring device 30 may be installed in each toilet space within a building, store, station, etc., and an administrator terminal 50 may be installed in each building, store, or station where the toilet space is located. Alternatively, odor measuring devices 30 may be installed in different toilet spaces within the same building, and an administrator terminal 50 corresponding to each of the different toilet spaces may be installed.

In the information processing system 100d, the odor measurement device 30 transmits the measurement results to the determination device 10 via the wide area communication network 40. The wide area communication network 40 is as described in embodiment 1.

Furthermore, the odor measurement device 30 and the administrator terminal 50 located in the same location may be connected via a network connection 60. The network connection 60 is not particularly limited and may be selected from connection methods that can be used as the wide area communication network described above, or may be a local area network. In one embodiment, the odor measurement devices 30a and 30b may transmit measurement results to the administrator terminal 50a corresponding to the odor measurement devices 30a and 30b via the network connection 60a.

In one embodiment, the odor measuring device 30 may transmit data related to the location where the odor measuring device 30 is installed in association with the measurement results. Examples of the location data include GPS-based location data provided in each odor measuring device 30 and ID data for the location of the toilet space in which the odor measuring device 30 is installed. The odor measuring device 30 may also transmit the data described in embodiment 4.

The configuration of the information processing system 100d shown in Figure 10 makes it possible to compare changes in odors within spaces at multiple locations, as well as the events that cause those changes, thereby identifying the average cleanliness required for restroom spaces. Furthermore, if the installation conditions of the odor measuring devices 30 in each restroom space are similar, it is easy to identify a malfunctioning odor measuring device 30 that is outputting an abnormal value.

The information processing system 100d has been described as including an odor measurement device 30 and an administrator terminal 50, but is not limited to this configuration. For example, the information processing system 100d may be configured to further include an odor measurement device 30 and an administrator terminal 50.

[Software implementation example]
In the determination devices 10 and 10a provided in the information processing systems 100, 100a, 100b, 100c, and 100d, the control block (particularly the control unit 1) may be realized by a logic circuit (hardware) formed on an integrated circuit (IC chip) or the like, or may be realized by software.

In the latter case, the determination device 10, 10a includes a computer that executes instructions from a program, which is software that realizes each function. This computer includes, for example, one or more processors and a computer-readable recording medium that stores the program. The object of the present invention is achieved when the processor in the computer reads and executes the program from the recording medium. The processor may be, for example, a CPU (Central Processing Unit). The recording medium may be a "non-transitory tangible medium," such as a ROM (Read Only Memory), tape, disk, card, semiconductor memory, or programmable logic circuit. The device may also include a RAM (Random Access Memory) for expanding the program. The program may also be supplied to the computer via any transmission medium capable of transmitting the program (such as a communications network or broadcast waves). Note that one aspect of the present invention may also be realized when the program is embodied through electronic transmission in the form of a data signal embedded in a carrier wave.

The present invention is not limited to the above-described embodiments, and various modifications are possible within the scope of the claims. Embodiments obtained by appropriately combining the technical means disclosed in different embodiments are also included in the technical scope of the present invention.

〔summary〕
The information processing system according to aspect 1 of the present invention comprises an odor measuring device that measures an odor within a toilet space and outputs a measurement signal; an acquisition unit that acquires the measurement signal; an estimation unit that inputs the measurement signal output from the odor measuring device into a trained model obtained by machine learning using training data including an explanatory variable including the measurement signal output from the odor measuring device during a sample period and a target variable including event information indicating an event that has actually been identified as the cause of the change in odor within the toilet space corresponding to the measurement signal during the sample period, and outputs an estimation result that estimates the causative event of the change in odor within the toilet space; and a determination unit that determines the causative event of the change in odor within the toilet space based on the multiple estimation results output from the estimation unit, wherein the odor measuring device comprises multiple odor sensor elements that are capable of measuring different odor substances, and the measurement signal is output from each of the multiple odor sensor elements.

In the information processing system according to Aspect 2 of the present invention, in Aspect 1 above, the acquisition unit may acquire the measurement signal every first time, and the estimation unit may output the estimation result from each of the one or more measurement signals acquired by the acquisition unit.

In the information processing system according to aspect 3 of the present invention, in the above-mentioned aspect 1 or 2, the determination unit may further output information regarding the magnitude of the impact of the causal event on changes in the odor in the toilet space.

In the information processing system according to aspect 4 of the present invention, in any one of aspects 1 to 3, the determination unit may further output information regarding the resolution of the causal event.

The information processing system according to aspect 5 of the present invention is any one of aspects 1 to 4 and includes two or more of the odor measuring devices.

In the information processing system according to aspect 6 of the present invention, in any one of aspects 1 to 5 above, the event may include at least one of contamination of the toilet space by feces, contamination by urine, and contamination by vomit.

In the information processing system according to aspect 7 of the present invention, in any of aspects 1 to 6 above, the events may include events originating from users of the toilet space.

An information processing method according to aspect 8 of the present invention includes: an acquisition step in which a computer acquires a measurement signal from an odor measurement device that measures odors within a toilet space; an estimation step in which the computer inputs the measurement signal output from the odor measurement device into a trained model obtained by machine learning using training data including an explanatory variable including the measurement signal output from the odor measurement device during a sample period and a target variable including event information indicating an event actually identified as the cause of a change in odor within the toilet space corresponding to the measurement signal during the sample period, and outputs an estimation result that estimates the causative event of the change in odor within the toilet space; and a determination step in which the computer determines the causative event of the change in odor within the toilet space based on the multiple estimation results output in the estimation step, wherein the odor measurement device includes multiple odor sensor elements that can measure different odor substances, and the measurement signal is output from each of the multiple odor sensor elements.

Aspect 9 of the present invention may be a control program for causing a computer to function as the information processing system of aspects 1 to 7, and may be a control program for causing a computer to function as the acquisition unit, the estimation unit, and the determination unit.

Aspect 10 of the present invention may be a computer-readable recording medium on which the control program described in aspect 9 is recorded.

In any of aspects 1 to 7, the information processing system of the present invention may further include a sensor other than the odor measuring device.

10 Determination device 30, 30a, 30b, 30c, 30d, 30e, 30f Odor measuring device 31 Odor sensor element 40 Wide area communication network 50, 50a, 50b, 50c Administrator terminal 60a, 60b, 60c Network connection 311 Substrate 313A First metal wiring 313B Second metal wiring 315 Odorant receiving layer W Lead wire

Claims (9)

an odor measuring device that measures odors in the toilet space and outputs a measurement signal;
a measurement signal acquisition unit that acquires the measurement signal ;
an estimation unit that inputs the measurement signals output from the odor measuring device into a trained model obtained by machine learning using training data including explanatory variables including the measurement signals output from the odor measuring device during a sample period and objective variables including event information indicating an event actually identified as the cause of the change in odor in the toilet space corresponding to the measurement signals during the sample period, and outputs an estimation result that estimates the causative event of the change in odor in the toilet space;
a determination unit that determines a cause of the change in odor in the toilet space based on the multiple estimation results output from the estimation unit; and
Equipped with
The odor measuring device includes a plurality of odor sensor elements that can measure different odor substances,
the measurement signal is output from each of the plurality of odor sensor elements ,
the measurement signal acquisition unit acquires the measurement signal every first time;
the estimation unit outputs the estimation result from each of the one or more measurement signals acquired by the measurement signal acquisition unit .
Information processing system. The determination unit further outputs information regarding the magnitude of the influence of the causal event on the change in the smell of the toilet space.
The information processing system according to claim 1 . The determination unit further outputs information regarding elimination of the causal event.
The information processing system according to claim 1 . The information processing system described in claim 1, comprising two or more odor measurement devices. The event includes at least one of contamination of the toilet space by feces, contamination by urine, and contamination by vomit,
The information processing system according to claim 1 . The information processing system of claim 1, wherein the events include events originating from users of the toilet space. a measurement signal acquiring step in which a computer acquires a measurement signal from an odor measuring device that measures an odor in the toilet space;
an estimation step in which the computer inputs the measurement signals output from the odor measuring device into a trained model obtained by machine learning using training data including explanatory variables including the measurement signals output from the odor measuring device during a sample period and objective variables including event information indicating an event actually identified as the cause of the change in odor in the toilet space corresponding to the measurement signals during the sample period, and outputs an estimation result that estimates the causative event of the change in odor in the toilet space;
a determination step in which the computer determines a causal event of the change in odor in the toilet space based on the multiple estimation results output in the estimation step;
Including,
The odor measuring device includes a plurality of odor sensor elements that can measure different odor substances,
The measurement signal is output from each of the plurality of odor sensor elements.
Information processing methods. 2. A control program for causing a computer to function as the information processing system according to claim 1, the control program causing the computer to function as the measurement signal acquisition unit, the estimation unit, and the determination unit. A computer-readable recording medium on which the control program according to claim 8 is recorded.