JP2017219515A - Information processing device, information processing method, program, and information processing system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To predict the useful life of equipment more accurately.SOLUTION: An information processing device is equipped with a sensor that measures physical quantities in the environment of installation and outputs the result of measurement as sensor information, and an equipment life predictor that predicts, on the basis of the sensor information outputted from the sensor, the useful life of equipment varying with the environment of installation. The device is further equipped with a pattern holder that holds plural patterns, predefined for each physical quantity measured by the sensor in a curve representing the useful life of equipment with the lapse of time, and the equipment life predictor predicts the useful life of equipment by selecting, on the basis of the sensor information outputted from the sensor, a prescribed pattern out of the plural patterns held by the pattern holder. This technique is applicable to network monitoring camera systems for instance.SELECTED DRAWING: Figure 1

Description

  The present disclosure relates to an information processing device, an information processing method, a program, and an information processing system, and in particular, an information processing device, an information processing method, a program, and an information processing system that can predict a device lifetime more accurately. About.

  Conventionally, for a period until an electronic device fails and cannot be used (hereinafter referred to as device life or simply life), for example, life prediction in a specific assumed environment has been performed for each model. . Thus, since the installation environment in which each electronic device is actually installed is not considered, for example, for the same model, the same lifetime is predicted in all electronic devices, so the replacement period is It will be set uniformly.

  Also, in order to avoid encountering a failure during the operation of the electronic device, the replacement period tends to be set to a number that falls to the safe side. In addition, since the installation environment of the electronic device is not taken into consideration, the same conditions are applied even in an installation environment different from the preconditions when the life prediction is performed.

  By the way, when multiple electronic devices are installed, depending on the actual installation environment, the life of each device will be different, so that even if one electronic device fails, other electronic devices can be used. There is.

  For example, Patent Document 1 discloses a camera terminal that can shoot all areas to be imaged without blind spots even when some of the plurality of cameras break down.

International Publication No. 06/068049 Pamphlet

  As described above, since the lifetime varies depending on the installation environment of the electronic device, when the replacement is performed uniformly according to the replacement period, a useless period that is usable but not used occurs. In order to avoid the occurrence of such a useless period, it is required to accurately predict the device life.

  This indication is made in view of such a situation, and makes it possible to predict a device life more correctly.

  An information processing apparatus according to an aspect of the present disclosure measures a physical quantity in an installation environment and outputs the measurement result as sensor information, and changes according to the installation environment based on sensor information output from the sensor. A device life prediction unit for predicting the device life.

  An information processing method or program according to one aspect of the present disclosure acquires a measurement result output from a sensor that measures a physical quantity in an installation environment as sensor information, and depends on the installation environment based on the sensor information output from the sensor. Predicting a changing device lifetime.

  An information processing system according to one aspect of the present disclosure measures a physical quantity in an installation environment and outputs the measurement result as sensor information, and changes according to the installation environment based on sensor information output from the sensor. A plurality of first information processing devices having a device life prediction unit for predicting a device life, and a device life transmitted from the plurality of first information processing devices via a network is accumulated and stored, respectively. And a second information processing apparatus having a function for obtaining a general device life in an installation environment of the first information processing apparatus.

  In one aspect of the present disclosure, a measurement result output from a sensor that measures a physical quantity in an installation environment is acquired as sensor information, and based on the sensor information output from the sensor, a device life that varies depending on the installation environment is obtained. is expected.

  According to one aspect of the present disclosure, it is possible to predict the device lifetime more accurately.

It is a block diagram which shows the structural example of 1st Embodiment of the lifetime prediction system to which this technique is applied. It is a figure which shows the example of the pattern selected from temperature and humidity. It is a flowchart explaining the process performed in an electronic device. It is a block diagram which shows the structural example of 2nd Embodiment of the lifetime prediction system to which this technique is applied. It is a figure which shows the example of the prediction curve calculated | required by the estimation part. It is a flowchart explaining the process performed in an electronic device. It is a block diagram which shows the structural example of 3rd Embodiment of the lifetime prediction system to which this technique is applied. It is a flowchart explaining the process performed in an electronic device. It is a block diagram which shows the structural example of the apparatus cooperation system with which a some electronic device cooperates. And FIG. 18 is a block diagram illustrating a configuration example of an embodiment of a computer to which the present technology is applied.

  Hereinafter, specific embodiments to which the present technology is applied will be described in detail with reference to the drawings.

  FIG. 1 is a block diagram illustrating a configuration example of a first embodiment of a life prediction system to which the present technology is applied.

  As shown in FIG. 1, the life prediction system 11 includes an electronic device 12 and a presentation unit 13.

  The electronic device 12 can fail due to deterioration over time, such as an imaging device such as a digital still camera or a digital video camera, a receiving device such as a television receiver or a radio receiver, or a mobile phone terminal including a so-called smartphone. Consists of compatible hardware.

  The presentation unit 13 can be configured by a display unit such as a liquid crystal display, for example, displays life prediction data supplied from the electronic device 12, and presents the life prediction data to the user. Or the presentation part 13 may be comprised with the communication part which communicates via a network, and transmits the lifetime prediction data supplied from the electronic device 12 to a user's terminal, and makes the lifetime prediction data to a user. Can be presented.

  The electronic device 12 includes sensors 21-1 and 21-2, a pattern holding unit 22, and a pattern selection unit 23. Moreover, the electronic device 12 can acquire sensor information output from the sensor 21-3 included in another electronic device 12 (not shown) installed in the vicinity of the electronic device 12.

  The sensors 21-1 to 21-3 are composed of, for example, a temperature sensor, a humidity sensor, a vibration sensor, a clock, an image sensor, etc., and can measure various physical quantities that change depending on the time and situation, and can read out the measurement results. Is supplied to the pattern selection unit 23 as correct sensor information. The sensor 21 may be arranged around the electronic device 12 or on an accessible network in addition to the sensor 21 incorporated in the electronic device 12, and the electronic device 12 reads sensor information from the outside. It only has to be. In addition to using a dedicated sensor 21 for selecting a pattern for measuring the lifetime, the sensor 21 has a role other than selecting a pattern as an original purpose, for example, improving image quality. You may use things.

  The pattern holding unit 22 holds a plurality of predefined patterns.

  Here, the pattern is divided into several sections within the range that the sensor information output from the sensor 21 can take, and the failure rate and the degree of deterioration are defined for each section. Specifically, the sensor information output from the temperature sensor is divided into three patterns: -200 degrees to less than 0 degrees, 0 degrees to less than 50 degrees, and 50 degrees or more. The time until a failure occurs is defined individually.

  Moreover, as a pattern, when it defines independently for every sensor 21, the some sensor 21 can be put together into a table and one pattern can be selected from several sensor information. Further, the pattern holding unit 22 can hold a pattern defined in advance at the time of shipment of the electronic device 12, or can acquire and hold the latest pattern via a network or the like.

  The pattern selection unit 23 selects the most appropriate pattern from a plurality of patterns held by the pattern holding unit 22 based on the sensor information output from the sensors 21-1 to 21-3, and the pattern Is supplied to the presentation unit 13 as life prediction data.

  For example, as shown in FIG. 2, when the pattern holding unit 22 holds a pattern table based on temperature and humidity, the pattern selection unit 23 is uniquely determined from the temperature and humidity supplied as sensor information. Pattern can be selected.

  As described above, the pattern selection unit 23 can have a function of searching and selecting only a pattern that matches the sensor information from a plurality of patterns. Moreover, the pattern selection part 23 can be provided with the function which performs the calculation based on several sensor information, the selection conditions of a pattern, etc., for example, and selects what matches.

  Then, when the pattern to be selected is uniquely determined, the pattern selection unit 23 presents the pattern to the user as life prediction data. In addition, the pattern selection unit 23 determines that a plurality of patterns are to be used when the selected pattern is not uniquely determined because the results obtained from the plurality of sensor information are inconsistent or the range is wide. It can be presented to the user as prediction data and can be selected by the user.

  The pattern selection unit 23 may present the pattern to the user when recognizing that the situation has changed based on the sensor information.

  That is, since the sensor information output from the sensor 21 is not fixed and changes according to the situation, the pattern selection unit 23 can use the change in the situation as a trigger. For example, the pattern selection unit 23 performs notification when the sensor information changes even a little, or does not perform notification when there is no effect on the pattern selection result even if the sensor information changes. Notification can be made when the selection result is affected. In this way, the pattern selection unit 23 can control the notification frequency by selecting such notification conditions.

  Furthermore, the pattern selection unit 23 can increase the frequency of notification when recognizing that the lifetime is short based on the selected pattern. That is, the pattern selection unit 23 may change the behavior of performing notification according to the selected pattern.

  In addition, the pattern selection unit 23 presents a pattern that is the same as the pattern that has been notified once, presents a pattern that is different from the pattern that has been notified once, or presents a pattern that has changed significantly from the previous pattern. When doing so, it is possible to select a form for presenting the pattern, such as performing a special presentation.

  Thus, the life prediction system 11 is configured, and an appropriate pattern selected by the pattern selection unit 23 based on the sensor information output from the sensors 21-1 to 21-3 is used as life prediction data by the user. Presented to.

  Next, FIG. 3 is a flowchart for explaining processing executed in the electronic device 12.

  For example, when the electronic device 12 is activated, the process is started, and in step S11, the pattern selection unit 23 acquires sensor information output from the sensors 21-1 to 21-3.

  In step S <b> 12, the pattern selection unit 23 selects the most appropriate pattern from a plurality of patterns that are defined in advance and held in the pattern holding unit 22 based on the sensor information acquired in step S <b> 11.

  In step S13, the pattern selection unit 23 determines whether or not to present the pattern selected in step S12 to the user as life prediction data. For example, as described above, the pattern selection unit 23 can select to present to the user when there is a change in the sensor information.

  In step S13, when the pattern selection unit 23 determines that the pattern is presented to the user as life prediction data, the process proceeds to step S14, and the pattern selection unit 23 supplies the pattern selected in step S12 to the presentation unit 13. It is presented to the user as life prediction data.

  After the process of step S14 or when the pattern selection unit 23 determines in step S13 that the pattern is not presented to the user as life prediction data, the process returns to step S11, and the same process is repeated thereafter.

  As described above, in the electronic device 12, based on the sensor information output from the sensors 21-1 to 21-3, for example, when the sensor information has changed, the pattern selected by the pattern selection unit 23 is selected. It can be presented to the user as life prediction data. Thus, since the electronic device 12 can obtain | require lifetime prediction data based on sensor information, it can estimate a lifetime more correctly rather than the lifetime prediction in the specific assumption environment like the past. Thereby, for example, since a replacement period according to the installation environment of the electronic device 12 can be set, it is possible to avoid the electronic device 12 from being replaced when it can be used, that is, the electronic device 12. Can extend the product life.

  Next, FIG. 4 is a block diagram illustrating a configuration example of the second embodiment of the lifetime prediction system to which the present technology is applied. In the life prediction system 11A shown in FIG. 4, the detailed description of the configuration common to the life prediction system 11 in FIG. 1 is omitted.

  As illustrated in FIG. 4, the life prediction system 11A includes an electronic device 12A and a presentation unit 13, and the electronic device 12A includes sensors 21-1 and 21-2, a sensor information storage unit 24, and a prediction. The unit 25 is configured.

  The sensor information storage unit 24 stores changes in sensor information output from the sensors 21-1 to 21-3.

  For example, the sensor information storage unit 24 records the sensor information when the sensor information output from the sensors 21-1 to 21-3 changes regardless of whether or not the prediction by the prediction unit 25 is presented. Accumulate. For example, the sensor information storage unit 24 records the sensor information regardless of whether or not it has changed over time, or records the sensor information only when it has changed over time. You can choose the situation to do.

  In addition, the sensor information storage unit 24 is in a state where changes in sensor information can be acquired. For example, the sensor information storage unit 24 records all sensor information according to the storage capacity of the medium for recording the purpose of use, records sensor information only for a certain period, records the sensor information by thinning, etc. The specification of sensor information recording can be selected.

  The prediction unit 25 calculates a predicted value by predicting a future transition according to a change based on the passage of time of the sensor information stored in the sensor information storage unit 24.

  For example, the prediction unit 25 determines whether the sensor information stored in the sensor information storage unit 24 has a correlation, what kind of transition it is following, whether it is the same change from the beginning, or a characteristic change most recently. Prediction is derived by calculating a predicted value after a predetermined period in accordance with an algorithm used for prediction, such as whether a point is seen. The prediction unit 25 calculates one predicted value from one sensor information, calculates a plurality of predicted values from one sensor information, calculates a plurality of predicted values from a plurality of sensor information, One predicted value can be calculated from the sensor information. Furthermore, the prediction unit 25 can calculate another prediction value from a plurality of prediction values, that is, an average value, median value, maximum value, minimum value, and the like.

  Then, the prediction unit 25 can supply the most probable prediction value to the presentation unit 13 and present it to the user as life prediction data. Alternatively, the prediction unit 25 can supply a plurality of predicted values to the presenting unit 13 and present them to the user as life prediction data, and can be selected by the user from those predicted values.

  In this way, the life prediction system 11A is configured, and the prediction predicted by the prediction unit 25 based on the sensor information output from the sensors 21-1 to 21-3 and stored in the sensor information storage unit 24. The value is presented to the user as life prediction data.

  For example, as illustrated in FIG. 5, the prediction unit 25 has a probability that a failure is expected to occur over time based on sensor information (accumulated data) stored in the sensor information storage unit 24. An expected curve represented by a curve can be obtained. This forecast curve reflects the results based on the accumulated data with the passage of time, and the future transition is obtained as a new forecast from the accumulated data. Then, the prediction unit 25 can calculate, as a predicted value, the time when a failure will occur with a certain probability or more according to the predicted curve.

  Next, FIG. 6 is a flowchart illustrating processing executed in the electronic device 12A.

  For example, the processing starts when the electronic device 12A is activated. In step S21, the sensor information storage unit 24 acquires sensor information output from the sensors 21-1 to 21-3, and stores the sensor information.

  In step S <b> 22, the prediction unit 25 calculates a predicted value for predicting a future transition based on the sensor information stored in the sensor information storage unit 24.

  In step S23, the prediction unit 25 determines whether or not to present the predicted value calculated in step S22 to the user as life prediction data. For example, when there is a change in the predicted value, the prediction unit 25 can select to present the predicted value to the user as life prediction data.

  In Step S23, when it is determined that the prediction unit 25 presents the predicted value to the user as life prediction data, the process proceeds to Step S24, and the prediction unit 25 supplies the predicted value calculated in Step S22 to the presenting unit 13. It is presented to the user as life prediction data.

  After the process of step S24, or when the prediction unit 25 determines in step S23 that the predicted value is not presented to the user as life prediction data, the process returns to step S21, and the same process is repeated thereafter.

  As described above, based on the sensor information output from the sensors 21-1 to 21-3, for example, the electronic device 12 </ b> A uses the predicted value calculated by the prediction unit 25 when the predicted value has changed. It can be presented to the user as life prediction data. Thus, since the electronic device 12A can obtain the life prediction data based on the sensor information, the life can be predicted more accurately than the life prediction in a specific assumed environment as in the past. Thereby, for example, since an exchange period according to the installation environment of the electronic device 12A can be set, it is possible to avoid the electronic device 12A from being replaced when it can be used, that is, the electronic device 12A. Can extend the product life.

  By the way, when the prediction is performed as in the life prediction system 11A of FIG. 4, in the initial state, the data amount of the sensor information stored in the sensor information storage unit 24 is small, and the life of the sensor information is sufficiently accurate by the prediction unit 25. It is assumed that it cannot be predicted. Here, the initial state is immediately after the purchase of the electronic device 12A, immediately after the reset of the electronic device 12A, or immediately after the electronic device 12A is moved to a different environment.

  Therefore, for example, it is possible to construct a system that combines pattern selection in the life prediction system 11 in FIG. 1 and prediction in the life prediction system 11A in FIG.

  That is, FIG. 7 is a block diagram illustrating a configuration example of the third embodiment of the life prediction system to which the present technology is applied. In the life prediction system 11B shown in FIG. 7, the detailed description of the configuration common to the life prediction system 11 in FIG. 1 and the life prediction system 11A in FIG. 4 is omitted.

  As shown in FIG. 7, the life prediction system 11B includes an electronic device 12B and a presentation unit 13. The electronic device 12B includes sensors 21-1 and 21-2, a pattern holding unit 22, a pattern selection unit 23, a sensor information storage unit 24, a prediction unit 25, and a switching control unit 26.

  In other words, the life prediction system 11B is configured to include the switching control unit 26 in addition to the configurations provided in the life prediction system 11 in FIG. 1 and the life prediction system 11A in FIG.

  Based on whether the data amount of the sensor information stored in the sensor information storage unit 24 has sufficiently increased (the data amount is less than the specified value or greater than the specified value), the switching control unit 26 performs the pattern selection by the pattern selection unit 23. Control to switch from selection to prediction by the prediction unit 25 is performed.

  For example, the switching control unit 26 determines that sensor information having a sufficient amount of data has been stored in the sensor information storage unit 24 when a predetermined time has elapsed since the electronic device 12B entered the initial state. Control can be performed so as to switch from pattern selection to prediction by the prediction unit 25. Specifically, the switching control unit 26 switches from pattern selection by the pattern selection unit 23 to prediction by the prediction unit 25 when sensor information has accumulated for 30 days or more after the electronic device 12B is in the initial state. Control can be performed. Alternatively, the switching control unit 26 can perform control to switch from pattern selection by the pattern selection unit 23 to prediction by the prediction unit 25 when an arbitrary time point set by the user has elapsed.

  Furthermore, the switching control unit 26 can cause preliminary prediction by the prediction unit 25 to be performed a plurality of times while pattern selection by the pattern selection unit 23 is being performed. Then, the switching control unit 26 measures the variation in the prediction result of the preliminary prediction, and when the variation amount is equal to or less than a predetermined value (for example, 5% or less), the pattern selection unit 23 starts the pattern selection. Control can be performed so as to switch to prediction by the prediction unit 25.

  In addition, the switching control unit 26 may perform switching from pattern selection by the pattern selection unit 23 to prediction by the prediction unit 25 only once or may be performed repeatedly. Further, the switching control unit 26 may perform switching individually for each of the plurality of sensors 21 or may collectively switch the plurality of sensors 21.

  In this way, the life prediction system 11B can switch between pattern selection by the pattern selection unit 23 and prediction by the prediction unit 25, but combines predictions other than these, for example, predictions based on conventional built-in fixed information. Can be used. Further, the life prediction system 11B may switch these prediction methods individually for each of the plurality of sensors 21 or may collectively switch the plurality of sensors 21.

  Next, FIG. 8 is a flowchart illustrating processing executed in the electronic device 12B.

  For example, when the electronic device 12B is activated, the process is started. In step S31, the sensor information storage unit 24 acquires sensor information output from the sensors 21-1 to 21-3, and stores the sensor information.

  Thereafter, in steps S32 to S35, processing similar to that in steps S11 to S14 in FIG. 3 is performed, and the pattern selection unit 23 performs pattern selection and presentation.

  In step S <b> 36, the switching control unit 26 determines whether to switch from pattern selection by the pattern selection unit 23 to prediction by the prediction unit 25. For example, as described above, the switching control unit 26 switches from pattern selection by the pattern selection unit 23 to prediction by the prediction unit 25 when sensor information having a sufficient amount of data is stored in the sensor information storage unit 24. Is determined.

  In step S36, when the switching control unit 26 determines not to switch from pattern selection by the pattern selection unit 23 to prediction by the prediction unit 25, the process returns to step S31, and the same processing is repeated thereafter. On the other hand, if the switching control unit 26 determines in step S36 to switch from pattern selection by the pattern selection unit 23 to prediction by the prediction unit 25, the process proceeds to step S37.

  Thereafter, in steps S37 to S40, processing similar to that in steps S21 to S24 in FIG. 6 is performed, and prediction and presentation by the prediction unit 25 are performed.

  As described above, in the electronic device 12B, the pattern selection by the pattern selection unit 23 and the prediction by the prediction unit 25 can be switched. Thereby, the electronic device 12B can avoid the decline in the accuracy of predicting the lifetime in the initial state, and more accurately predict the lifetime.

  Next, a device cooperation system in which a plurality of electronic devices 12 cooperate will be described with reference to FIG.

  As illustrated in FIG. 9, the device cooperation system 31 is configured by connecting N electronic devices 12-1 to 12 -N to an information processing server 33 via a network 32.

  Each of the electronic devices 12-1 to 12 -N can obtain its own life prediction data, and can transmit the life prediction data to the information processing server 33 via the network 32.

  For example, when the electronic devices 12-1 to 12-N are installed in the same environment and are different models, life prediction data in the same environment of various models is aggregated. Further, when the electronic devices 12-1 to 12-N are installed in different environments and are the same model, life prediction data for different environments of the same model is aggregated. Note that the electronic devices 12-1 to 12-N may adopt the same prediction method, or may employ different prediction methods, and the introduction times thereof may be the same or individual. That is, various life prediction data can be aggregated and used by the electronic devices 12-1 to 12-N.

  The information processing server 33 collects and accumulates life prediction data transmitted from the electronic devices 12-1 to 12-N. In addition to installing a dedicated device as the information processing server 33, any one of the electronic devices 12-1 to 12 -N has a function as the information processing server 33. Also good. Further, the functions provided in the information processing server 33 may be distributed via the network 32.

  As illustrated, the information processing server 33 includes a prediction data storage unit 41, a prediction unit 42, a presentation unit 43, and a development data providing unit 44.

  The predicted data storage unit 41 stores life prediction data transmitted from the electronic devices 12-1 to 12-N via the network 32.

  The prediction unit 42 processes the life prediction data stored in the prediction data storage unit 41 to obtain a general prediction value in an environment in which each of the electronic devices 12-1 to 12-N is installed.

  For example, the prediction unit 42 can obtain an average value, a maximum value, a median value, a worst value, and the like of the life prediction data stored in the prediction data storage unit 41. Further, the prediction unit 42 extracts only the electronic device 12 of the same model in the same environment from the life prediction data stored in the prediction data storage unit 41, or obtains life prediction data of a plurality of electronic devices 12. It is possible to categorize life prediction data such as using all of them. In addition, the prediction unit 42 can categorize the electronic devices 12 from the life prediction data, such as collecting the electronic devices 12 having similar life prediction data.

  Then, the prediction unit 42 calculates a general prediction value in the environment based on the processed life prediction data, that is, a prediction value for predicting the tendency and overall life of the plurality of electronic devices 12 used this time. Then, the data is supplied to the presentation unit 43 and presented to the user.

  Further, the prediction unit 42 can calculate a new prediction value based on the general prediction value. For example, the prediction unit 42 can perform life prediction when a new electronic device 12 is introduced into the same environment by calculating general life prediction data in the environment. Further, the prediction unit 42 can detect a problem peculiar to the electronic device 12 by specifying the electronic device 12 that is significantly different from the calculated predicted value.

  In the device cooperation system 31, the plurality of electronic devices 12 can be rotated based on the prediction by the prediction unit 42. That is, when a plurality of electronic devices 12 are introduced, life prediction data can be acquired individually according to the environment, and the installation position of the electronic device 12 can be switched based on the individual differences. For example, it is assumed that there is a difference in life due to good sunlight, a difference in use time, individual differences of the electronic device 12, and the like. By obtaining life prediction data for each individual electronic device 12, the electronic device 12 having a short life is obtained. And the electronic device 12 having a long life can be replaced. In addition, it is possible to limit the use time so that a highly durable device can be installed in the harshest environment or the life of the electronic device 12 as a whole becomes uniform.

  In this way, by rotating the plurality of electronic devices 12, extending the lifetime of the entire group of the plurality of electronic devices 12 can avoid the risk by shifting the failure time. For example, by replacing the electronic device 12 that is predicted to have a failure at the nearest time with an electronic device 12 installed at another location, or replacing the electronic device 12 with another one, Life can be extended. In addition, when there is an electronic device 12 with a near failure time, there is a concern that if the replacement is performed at the same time, the operation time of the entire system may be reduced, or redundancy due to multiplexing may be sacrificed. In order to solve this problem, it is possible to improve the risk by taking measures such as shifting the replacement time.

  The development data providing unit 44 provides the life prediction data stored in the prediction data storage unit 41 and the predicted value predicted by the prediction unit 42 to the developer of the electronic device 12, so that the next generation electronic It can be used for the development of the device 12.

  Further, the development data providing unit 44 acquires sensor information stored in each of the electronic devices 12-1 to 12-N, and uses the life prediction data stored at a certain point in time as the electronic devices 12-1 to 12-N. Or can be obtained from.

  Further, the development data providing unit 44 can also acquire information such as the installation location and usage time of the electronic devices 12-1 to 12-N and use it in combination with the lifetime prediction data. In addition, the electronic devices 12-1 to 12-N are information that cannot be detected by the sensors of the electronic devices 12-1 to 12-N, such as information on sensors that are not mounted on a certain electronic device 12, special usage, etc. Information can be acquired.

  And the information provided by the development data providing unit 44 is different in each electronic device 12, how much the difference between the prediction and the actual is, and the information that could not be acquired this time is It is used to ask whether it is effective to some extent.

  The device cooperation system 31 configured as described above can be applied to, for example, a network monitoring camera system in which a monitoring camera is used as the electronic device 12 and the monitoring camera is connected via the network 32. For example, the image sensor provided in the monitoring camera is used as the sensor 21, and the number of corrections and the correction rate of the defective pixel, the time required for activation, and the like are used as sensor information, thereby improving the life prediction accuracy of the monitoring camera. be able to. Thereby, the operation period of the surveillance camera as the whole system can be set optimally. In addition, various sensors mounted on the monitoring camera can be used not for the purpose of improving the image quality but for predicting the lifetime.

  The device cooperation system 31 can be applied to, for example, an in-vehicle camera system in which an in-vehicle camera is used as the electronic device 12 and the in-vehicle camera is connected via the network 32. Thereby, according to the driving environment of a vehicle, the prediction precision of the lifetime of a vehicle-mounted camera can be improved for every vehicle.

  9 has a configuration example in which only the electronic device 12 and the information processing server 33 are connected to the network 32. For example, even if the sensor 21 is connected to the network 32, the device cooperation system 31 illustrated in FIG. Good. That is, the device cooperation system 31 can be configured such that measurement results such as temperature and humidity are transmitted from the sensor 21 to the information processing server 33 via the network 32. Also, a more detailed predicted value can be calculated with reference to FIG.

  Since the lifetime of the electronic device 12 can be accurately predicted as in the above-described embodiments, the possibility of encountering a failure during operation of the electronic device 12 can be greatly reduced. In addition, by appropriately setting the replacement period of the electronic device 12, it is possible to avoid being replaced even though it can be used, and it is possible to reduce the cost for replacement.

  In addition, it is possible to set an appropriate replacement period for each electronic device 12, and as a result of shifting the replacement time, it is possible to avoid replacing a large number of electronic devices 12 at the same time, or to group to some extent. You can control the number of replacements.

  And the exchange time as a whole can be changed by rotating and using the plurality of electronic devices 12. Moreover, since the exact replacement time of the electronic device 12 can be specified, it is possible to easily adjust the inventory and the operator standby.

  Furthermore, by developing the next-generation electronic device 12 using data actually measured in the electronic device 12, adjustments specific to a specific environment can be performed. Life can be extended.

  Conventionally, initial values are set by simulation or the like, but by using data actually measured in the electronic device 12, for example, an initial state in which no data is accumulated (initial prediction at the time of shipment) Even if a curve is used, the accuracy of predicting the life can be improved.

  Note that the processes described with reference to the flowcharts described above do not necessarily have to be processed in chronological order in the order described in the flowcharts, but are performed in parallel or individually (for example, parallel processes or objects). Processing). The program may be processed by one CPU, or may be distributedly processed by a plurality of CPUs.

  Further, in this specification, the system represents the entire apparatus constituted by a plurality of apparatuses.

  Further, the above-described series of processing (information processing method) can be executed by hardware or can be executed by software. When a series of processing is executed by software, a program constituting the software executes various functions by installing a computer incorporated in dedicated hardware or various programs. For example, the program is installed in a general-purpose personal computer from a program recording medium on which the program is recorded.

  FIG. 10 is a block diagram illustrating an example of a hardware configuration of a computer that executes the above-described series of processing by a program.

  In a computer, a CPU (Central Processing Unit) 101, a ROM (Read Only Memory) 102, a RAM (Random Access Memory) 103, and an EEPROM (Electronically Erasable and Programmable Read Only Memory) 104 are connected to each other by a bus 105. . An input / output interface 105 is further connected to the bus 104, and the input / output interface 105 is connected to the outside.

  In the computer configured as described above, for example, the CPU 101 loads the program stored in the ROM 102 and the EEPROM 104 to the RAM 103 via the bus 105 and executes the program, thereby performing the above-described series of processing. A program executed by the computer (CPU 101) can be written in the ROM 102 in advance, and can be installed or updated from the outside in the EEPROM 104 via the input / output interface 105.

In addition, this technique can also take the following structures.
(1)
A sensor that measures physical quantities in the installation environment and outputs the measurement results as sensor information;
An information processing apparatus comprising: a device life prediction unit that predicts a device life that changes in accordance with an installation environment based on sensor information output from the sensor.
(2)
For each physical quantity measured by the sensor, further comprising a pattern holding unit that holds a plurality of patterns defined in advance by a curve indicating the device lifetime over time,
The device life prediction unit predicts device life by selecting a predetermined pattern based on sensor information output from the sensor from among the plurality of patterns held in the pattern holding unit. The information processing apparatus according to 1).
(3)
A sensor information storage unit for storing sensor information output from the sensor;
The information processing apparatus according to (1), wherein the device life prediction unit predicts a device life according to a change based on a lapse of time of sensor information stored in the sensor information storage unit.
(4)
For each physical quantity measured by the sensor, a pattern holding unit that holds a plurality of patterns that are defined in advance by a curve indicating a device lifetime over time, and
A sensor information storage unit for storing sensor information output from the sensor;
A switching control unit that performs control to switch the prediction of the device life by the device life prediction unit according to the data amount of the sensor information stored in the sensor information storage unit,
The switching control unit
When the data amount of the sensor information stored in the sensor information storage unit is less than a specified value, the device life prediction unit outputs the pattern from the plurality of patterns held in the pattern holding unit. By predicting the device life by selecting a predetermined pattern based on the sensor information
When the data amount of the sensor information stored in the sensor information storage unit is equal to or greater than a specified value, the device life prediction unit performs the device life according to the change based on the passage of time of the sensor information stored in the sensor information storage unit. The information processing apparatus according to (1).
(5)
Obtain measurement results output from sensors that measure physical quantities in the installation environment as sensor information,
An information processing method including a step of predicting a device lifetime that changes in accordance with an installation environment based on sensor information output from the sensor.
(6)
Obtain measurement results output from sensors that measure physical quantities in the installation environment as sensor information,
A program for causing a computer to execute a process including a step of predicting a device lifetime that changes in accordance with an installation environment based on sensor information output from the sensor.
(7)
A sensor that measures a physical quantity in the installation environment and outputs the measurement result as sensor information, and a device life prediction unit that predicts a device life that changes according to the installation environment based on the sensor information output from the sensor. A plurality of first information processing apparatuses,
A function of collecting and accumulating device lifetimes transmitted from a plurality of the first information processing apparatuses via a network and obtaining a general device lifetime in an installation environment of each of the first information processing apparatuses is provided. An information processing system comprising: a second information processing apparatus.

  Note that the present embodiment is not limited to the above-described embodiment, and various modifications can be made without departing from the scope of the present disclosure.

  DESCRIPTION OF SYMBOLS 11 Life prediction system, 12 Electronic equipment, 13 Presentation part, 21 Sensor, 22 Pattern holding part, 23 Pattern selection part, 24 Sensor information storage part, 25 Prediction part, 26 Switching control part, 31 Device cooperation system, 32 Network, 33 Information processing server, 41 Prediction data storage unit, 42 Prediction unit, 43 Presentation unit, 44 Development data provision unit

Claims (7)

A sensor that measures physical quantities in the installation environment and outputs the measurement results as sensor information;
An information processing apparatus comprising: a device life prediction unit that predicts a device life that changes in accordance with an installation environment based on sensor information output from the sensor. For each physical quantity measured by the sensor, further comprising a pattern holding unit that holds a plurality of patterns defined in advance by a curve indicating the device lifetime over time,
The device life prediction unit predicts device life by selecting a predetermined pattern based on sensor information output from the sensor from the plurality of patterns held in the pattern holding unit. The information processing apparatus according to 1. A sensor information storage unit for storing sensor information output from the sensor;
The information processing apparatus according to claim 1, wherein the device life prediction unit predicts a device life according to a change based on a lapse of time of sensor information stored in the sensor information storage unit. For each physical quantity measured by the sensor, a pattern holding unit that holds a plurality of patterns that are defined in advance by a curve indicating a device lifetime over time, and
A sensor information storage unit for storing sensor information output from the sensor;
A switching control unit that performs control to switch the prediction of the device life by the device life prediction unit according to the data amount of the sensor information stored in the sensor information storage unit,
The switching control unit
When the data amount of the sensor information stored in the sensor information storage unit is less than a specified value, the device life prediction unit outputs the pattern from the plurality of patterns held in the pattern holding unit. By predicting the device life by selecting a predetermined pattern based on the sensor information
When the data amount of the sensor information stored in the sensor information storage unit is equal to or greater than a specified value, the device life prediction unit performs the device life according to the change based on the passage of time of the sensor information stored in the sensor information storage unit. The information processing apparatus according to claim 1. Obtain measurement results output from sensors that measure physical quantities in the installation environment as sensor information,
An information processing method including a step of predicting a device lifetime that changes in accordance with an installation environment based on sensor information output from the sensor. Obtain measurement results output from sensors that measure physical quantities in the installation environment as sensor information,
A program for causing a computer to execute a process including a step of predicting a device lifetime that changes in accordance with an installation environment based on sensor information output from the sensor. A sensor that measures a physical quantity in the installation environment and outputs the measurement result as sensor information, and a device life prediction unit that predicts a device life that changes according to the installation environment based on the sensor information output from the sensor. A plurality of first information processing apparatuses,
A function of collecting and accumulating device lifetimes transmitted from a plurality of the first information processing apparatuses via a network and obtaining a general device lifetime in an installation environment of each of the first information processing apparatuses is provided. An information processing system comprising: a second information processing apparatus.

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