JP2016212597A - Information collection program, information collection system, and information collection method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an information collection program, an information collection system, and an information collection method capable of reducing processing load.SOLUTION: An information collection program (server 20) causes a computer to execute a series of processing to identify a variation period of a context data based on the changes of a piece of context data collected by an apparatus (portable terminal 10). The information collection program (server 20) also causes the computer to execute a series of processing to set the apparatus an invalid period to prevent the collection of the context data based on the variation period identified.SELECTED DRAWING: Figure 1

Description

  The present invention relates to an information collection program, an information collection device, and an information collection method.

  For example, context data such as the user's location information and the temperature around the user, which represents the state of the surroundings of the terminal used by the user, is collected. There is a technique for providing a user with information corresponding to context data when the context data satisfies a predetermined condition.

  For example, a technique is known in which a server receives position information from a user terminal and transmits store information when the user approaches a specific store. In addition, a technique is known in which a server receives temperature from a user terminal and transmits a warning about heat stroke when the temperature around the user reaches a predetermined temperature. Also, a technology is known in which the server calculates the degree of relationship between the user and the scheduled action based on the context data received from the user terminal, and provides information to the user based on the rate of change of the degree of relationship. ing.

JP 2005-71026 A JP 2004-259261 A JP 2012-155357 A

  However, in the above technique, even when useless collection of context data that is unlikely to satisfy the predetermined condition occurs, it is determined whether or not the context data satisfies the predetermined condition. For this reason, the processing load of the user terminal or server that performs the context data collection processing may increase.

  An object of one aspect is to provide an information collection program, an information collection apparatus, and an information collection method that can reduce processing load.

  In one aspect, the information collection program causes a computer to execute a process of specifying a fluctuation period of context data based on a change in context data collected by the device. Further, the information collection program causes the computer to execute a process of setting an invalid period for suppressing the collection of context data in the apparatus based on the specified fluctuation period.

  According to one embodiment, the processing load of information collection can be reduced.

FIG. 1 is a functional block diagram illustrating an example of an information collection system. FIG. 2 is an explanatory diagram illustrating an example of activation parameters of the mobile terminal according to the first embodiment. FIG. 3 is an explanatory diagram illustrating an example of a data table according to the first embodiment. FIG. 4 is an explanatory diagram illustrating an example of temperature information stored in the history DB according to the first embodiment. FIG. 5 is an explanatory diagram illustrating an example of position information stored in the history DB according to the first embodiment. FIG. 6 is an explanatory diagram illustrating an example of a server startup parameter according to the first embodiment. FIG. 7 is a graph showing an example of measurement results of daytime air temperature in Example 1. FIG. 8 is a graph showing an example of an annual predicted maximum temperature in Example 1. FIG. 9 is an explanatory diagram illustrating an example of a determination result based on the measurement result of the daytime temperature in the first embodiment. FIG. 10 is an explanatory diagram illustrating an example of a determination result based on an annual predicted maximum temperature in the first embodiment. FIG. 11A is a flowchart illustrating an example of context data collection processing according to the first embodiment. FIG. 11B is a flowchart illustrating an example of the determination process according to the first embodiment. FIG. 11C is a flowchart illustrating an example of a process for specifying an invalidation period in the first embodiment. FIG. 12 is a flowchart illustrating an example of processing related to collection of context data by the mobile terminal according to the first embodiment. FIG. 13A is an explanatory diagram illustrating an example of activation parameters of the mobile terminal according to the second embodiment. FIG. 13B is an explanatory diagram illustrating an example of a server startup parameter according to the second embodiment. FIG. 14 is a flowchart illustrating an example of processing related to invalidation of processing based on position information in the second embodiment. FIG. 15A is an explanatory diagram illustrating an example of activation parameters of the mobile terminal according to the third embodiment. FIG. 15B is an explanatory diagram illustrating an example of a start parameter after updating the next execution date and time in the third embodiment. FIG. 15C is an explanatory diagram illustrating an example of a start parameter after updating the next execution date and time within the invalidation period according to the third embodiment. FIG. 15D is an explanatory diagram illustrating an example of a server startup parameter according to the third embodiment. FIG. 16 is a flowchart illustrating an example of processing for setting the next execution date and time in the third embodiment. FIG. 17 is an explanatory diagram illustrating a specific example of a change tendency in the fourth embodiment. FIG. 18 is an explanatory diagram of an execution frequency determination example according to the fourth embodiment. FIG. 19 is a diagram illustrating an example of a hardware configuration of the mobile terminal. FIG. 20 is a diagram illustrating an example of a hardware configuration of the server.

  Embodiments of an information collection program, an information collection apparatus, and an information collection method disclosed in the present application will be described below in detail with reference to the drawings. The disclosed technology is not limited by the present embodiment. Moreover, you may combine suitably each Example shown below in the range which does not cause contradiction.

[overall structure]
In the first embodiment, the server 20 collects context data such as temperature, humidity, location information of the mobile terminal 10 and the predicted maximum temperature, and when the context data satisfies a predetermined condition, the mobile terminal 10 is warned of heat stroke, etc. It is an example of the information collection system which notifies. FIG. 1 is a functional block diagram illustrating an example of the information collection system 1. In FIG. 1, the information collection system 1 includes a mobile terminal 10 and a server 20. Further, the server 20 can communicate with the other system 30 through the network. Here, in order to simplify the description, the case where there is one mobile terminal 10, one server 20, and one other system 30 will be described as an example.

  The mobile terminal 10 is a mobile terminal possessed by a user, and is an example of a mobile phone, a smartphone, a tablet terminal, or the like. The mobile terminal 10 collects peripheral context data according to the activation parameters set by the server 20 and transmits it to the server 20, and receives a notification such as a heat stroke warning from the server 20. The context data collected by the mobile terminal 10 is, for example, temperature, humidity, and position information of the mobile terminal 10. The context data is measured using a temperature sensor, a humidity sensor, a GPS sensor, or the like (not shown) included in the mobile terminal 10. The position information may be specified by the position of the radio base station that communicates with the mobile terminal 10.

  The server 20 is an example of an apparatus that collects context data from the mobile terminal 10 and the other system 30 and performs condition determination using the collected context data. When it is determined that the condition is satisfied as a result of the condition determination, the server 20 transmits a notification to the mobile terminal 10. For example, when it is determined that the condition such as “temperature 30 ° C. or higher” is satisfied, the server 20 transmits a notification such as a heat stroke warning to the mobile terminal 10. The server 20 can communicate with the mobile terminal 10 and the other system 30 by wire or wireless. The context data collected by the server 20 is data transmitted from the other system 30 such as the predicted maximum temperature.

  The other system 30 is an example of an apparatus that transmits context data to the server 20, such as a server that provides weather forecast data. For example, the other system 30 receives an acquisition request for data on the predicted maximum temperature specifying a point from the server 20, and transmits data on the predicted maximum temperature at the specified point to the server 20.

[Terminal configuration]
Each functional block of the mobile terminal 10 shown in FIG. 1 will be described. As illustrated in FIG. 1, the mobile terminal 10 includes an activation parameter 11, an activation control unit 12, an information acquisition unit 13, and a notification acquisition unit 15. The activation control unit 12, the information acquisition unit 13, and the notification acquisition unit 15 are an example of an electronic circuit or an example of a process executed by a processor. The activation parameter 11 is an example of data stored in a storage device such as a memory or a hard disk.

  The activation parameter 11 stores the timing for executing the context data collection process in the mobile terminal 10. The activation parameter 11 is updated with information received from the server 20.

  FIG. 2 is an explanatory diagram illustrating an example of activation parameters of the mobile terminal according to the first embodiment. As illustrated in FIG. 2, the activation parameter 11 of the mobile terminal 10 stores “data type”, “execution frequency”, and “invalidation period” in association with each other.

  “Data type” indicates context data to be collected. “Execution frequency” indicates how often the context data collection process is executed, and “invalidation period” indicates a period during which the context data collection process is suppressed.

  In the example of FIG. 2, the mobile terminal 10 measures the position and temperature every “10 minutes” and measures the humidity every “30 minutes”. Further, regarding the temperature and humidity, the period of “16:00 to 10:00” and the period of “October to June” are set as invalidation periods. Reduce the collection process of temperature and humidity. The “invalidation period” is blank in the initial setting, and is set by the update process of the activation parameter 11 described below.

  The activation control unit 12 outputs an execution instruction for context data collection processing to the information acquisition unit 13 according to the timing stored in the activation parameter 11. The activation control unit 12 outputs an execution instruction at intervals stored in the execution frequency of the activation parameter 11, and suppresses the output of the execution instruction during the invalidation period.

  For example, the activation control unit 12 determines whether or not the current date and time is included in the invalidation period when the time stored in the execution frequency of the activation parameter 11 has elapsed after the previous execution instruction is output. The activation control unit 12 outputs an execution instruction when the current date and time are not included in the invalidation period.

  In the activation parameter 11 illustrated in FIG. 2, an invalidation period is set for the temperature and humidity, but no invalidation period is set for the position information. However, a configuration is also conceivable in which, as in the present embodiment, even if the condition regarding the position information is satisfied, it is not determined that the condition for transmitting the notification is satisfied unless the condition regarding the temperature is also satisfied. In this case, since it is useless to collect only the position information without collecting the temperature and humidity, it may be configured to suppress the collection of the position information during the invalidation period.

  The information acquisition unit 13 collects context data such as temperature, humidity, and location information of the mobile terminal 10 according to the execution instruction of the activation control unit 12. In addition, the information acquisition unit 13 transmits the collected context data to the server 20.

  The notification acquisition unit 15 receives a notification such as a heat stroke warning from the server 20 and presents it to the user through a display unit (not shown).

[Server configuration]
Next, the configuration of the server 20 will be described. As shown in FIG. 1, the server 20 includes a data table 21, a history DB 22, a startup parameter 23, a parameter determination unit 24, a startup control unit 25, an information acquisition unit 26, a determination unit 27, and a notification unit. 28. The parameter determination unit 24, the activation control unit 25, the information acquisition unit 26, the determination unit 27, and the notification unit 28 are examples of electronic circuits and processes executed by the processor. The data table 21, the history DB 22, and the activation parameter 23 are examples of data stored in a storage device such as a memory or a hard disk.

  Each data stored in the storage device of the server 20 will be described. The data table 21 stores the type of context data handled by the information collection system 1, its collection method, and determination conditions. FIG. 3 is an explanatory diagram illustrating an example of a data table according to the first embodiment. As shown in FIG. 3, the data table 21 associates “data type”, “determination condition”, “execution frequency”, “execution subject”, “change tendency”, “cycle”, and “invalidation period”. And remember.

  “Data type” indicates the type of context data to be acquired. The “determination condition” indicates a condition for determining whether or not the server 20 transmits a notification to the mobile terminal 10. For example, in the example of FIG. 3, the current position of the mobile terminal 10 is “Tokyo” and “externally 30 minutes or more” exists, and the current temperature around the mobile terminal 10 is “30 degrees or more”. And the predicted maximum temperature after one hour is “32 ° C. or higher”. When the determination condition is satisfied, the server 20 transmits, for example, a heat stroke warning to the portable terminal 10 as a notification.

  The execution frequency indicates the frequency of collecting context data. The execution entity indicates an operation entity that collects context data. The example of FIG. 3 shows that the portable terminal 10 collects location information every 10 minutes, and the server 20 collects the predicted maximum temperature every hour.

  The change tendency indicates the relationship between the passage of time and the change of context data. The change tendency represents how much the context data such as the temperature fluctuates in a fixed time such as 1 second, 1 minute, 10 minutes, 1 hour, for example. The example of FIG. 3 shows that the temperature fluctuates “less than 0.5 degrees” in 1 minute, “less than 5 degrees” in 10 minutes, and “less than 15 degrees” in 1 hour.

  Note that the execution frequency is set to the minimum time unit in which an effective change is expected based on the change tendency, for example. For example, in FIG. 3, the execution frequency of the temperature is set to “10 minutes” in accordance with the change tendency in which the fluctuation range is “less than 5 degrees”. Note that the execution frequency and the change tendency are set by a configuration as described in Example 4 to be described later, for example.

  The period indicates the presence / absence of a fluctuation cycle of the context data. The period column stores a period such as “1 day” or “1 year” if the fluctuation cycle has periodicity, and stores “none” if the fluctuation cycle does not have periodicity and varies irregularly. To do. The invalidation period indicates a period during which the collection of context data is suppressed. The period and the invalidation period are blank in the initial setting, and are set by the invalidation period setting process described below.

  The history DB 22 stores context data collected by the server 20 in the past, such as position information collected from the mobile terminal 10, ambient temperature, and predicted maximum temperature and humidity collected from the other system 30. Here, examples of temperature and position information will be described with reference to FIGS. 4 and 5.

  FIG. 4 is an explanatory diagram illustrating an example of temperature information stored in the history DB according to the first embodiment. As illustrated in FIG. 4, the history DB 22 stores, for example, temperature information collected by the mobile terminal 10 in the past every hour. In FIG. 4, for example, the temperature around the mobile terminal 10 at “2014/7/2 0:00” is “25.3 degrees” and increases to “30.6 degrees” at “12:00” on the same day. . Similarly, the temperature at “2014/7/3 1:00” is “25.4 degrees”, and increases to “30.8 degrees” at “12:00” on the same day.

  FIG. 5 is an explanatory diagram illustrating an example of position information stored in the history DB according to the first embodiment. As illustrated in FIG. 5, the history DB 22 stores, for example, position information collected in the past every hour. For example, the position of the mobile terminal 10 at “2014/7/2 0:00” is “N35.40.50 E139.44.49”, and “N35.4.20 E139” at “12:00” on the same day. .47.56 ". In addition, at “12:00” of “2014/7/3” which is the next day, it has moved to “N35.34.52 E139.62.54”.

  The activation parameter 23 stores the timing at which the server 20 executes context data collection processing and determination processing. The activation parameter 23 is updated by the parameter determination unit 24.

  FIG. 6 is an explanatory diagram illustrating an example of a server startup parameter according to the first embodiment. As illustrated in FIG. 6, the activation parameter 23 of the server 20 stores “data / processing type”, “execution frequency”, and “invalidation period” in association with each other. When there are a plurality of mobile terminals 10, the configuration may be such that the activation parameter 23 is set for each mobile terminal 10.

  The activation parameter 23 of the server 20 stores not only the timing of data collection processing but also the timing of context data collection processing. In the example of FIG. 6, the server 20 executes a weather forecast and predicted maximum temperature collection process every “1 hour”, and executes a context data determination process every “10 minutes”.

  Since the period of “16:00 to 10:00” and the period of “October to June” are set as invalidation periods, the server 20 collects the predicted maximum temperature during this period. Execution and context data determination processing are suppressed. The “invalidation period” is blank in the initial setting, and is set by the update process of the activation parameter 23 described below.

  Next, each processing unit of the server 20 shown in FIG. 1 will be described. The parameter determination unit 24 is a processing unit that refers to the data table 21 and the history DB 22 and identifies the presence or absence of periodicity. In addition, the parameter determination unit 24 sets an invalidation period for collection of periodic context data and reflects it in the activation parameter 11 and the activation parameter 23. The parameter determination unit 24 is an example of a specifying unit and a setting unit. The process executed by the parameter determination unit 24 is mainly divided into three types: periodicity specification, invalidation period setting, and activation parameter update.

(Identification of periodicity)
First, the process in which the parameter determination unit 24 specifies the periodicity of the context data will be described. Specifically, the parameter determination unit 24 refers to the history DB 22 and specifies whether or not the context data has periodicity.

  Examples of graphing the context data stored in the history DB 22 are shown in FIGS. FIG. 7 is a graph showing an example of measurement results of daytime air temperature in Example 1. As shown in FIG. 7, the daytime temperature tends to decrease at night, continue to increase from about 6 am, and decrease again at the top of about 2 pm. Therefore, in the example of FIG. 7, it can be specified that the temperature has a period of 24 hours.

  The parameter determination unit 24 identifies periodicity by, for example, a known periodic regression analysis. For example, the parameter determining unit 24 combines periodic functions such as trigonometric functions and calculates a function that approximates a graph as shown in FIG.

  FIG. 8 is a graph showing an example of an annual predicted maximum temperature in Example 1. As shown in FIG. 8, there is a tendency that the predicted maximum temperature for the year rises from January, falls at the peak around August, and approaches the temperature in January in December. Therefore, in the example of FIG. 8, it can be specified that the predicted maximum temperature has a cycle of one year.

  On the other hand, for example, the position information history shown in FIG. 5 does not fluctuate according to a specific period, and fluctuates irregularly. In such a case, the parameter determination unit 24 specifies that the context data has no periodicity.

(Invalidation period setting)
Next, the process in which the parameter determination unit 24 sets the invalidation period will be described. Specifically, the parameter determination unit 24 sets an invalidation period for suppressing the collection of context data for the context data specified to have periodicity, and stores it in the data table 21. The invalidation period is a period corresponding to the context data determined to determine whether or not individual context data included in a specific cycle satisfies a predetermined condition, and not satisfy the predetermined condition. Here, examples of the context data “daytime temperature” and “expected maximum temperature” shown in FIGS. 7 and 8 will be described with reference to FIGS. 9 and 10.

  For example, FIG. 9 shows the determination result when the predetermined condition is “29.0 degrees or more” for the daytime air temperature. FIG. 9 is an explanatory diagram illustrating an example of a determination result based on the measurement result of the daytime temperature in the first embodiment. FIG. 9 shows the temperature to be determined and the determination result as to whether or not a predetermined condition is satisfied every other hour. In FIG. 9, “◯” in the determination column indicates that a predetermined condition is satisfied, and “X” indicates that the predetermined condition is not satisfied.

  As shown in FIG. 9, the daytime air temperature satisfies the predetermined condition “29.0 degrees or more” during the period from “10:00” to “16:00”, and the predetermined condition at other times. “29.0 degrees or more” is not satisfied. In such a case, the parameter determination unit 24 sets the period of “16:00 to 10:00” as the invalidation period.

  FIG. 10 shows a determination result when the predetermined condition is “28.0 degrees or more” for the context data “expected maximum temperature”. FIG. 10 is an explanatory diagram illustrating an example of a determination result based on an annual predicted maximum temperature in the first embodiment. FIG. 10 shows the predicted maximum temperature to be determined and the determination result whether or not a predetermined condition is satisfied every other month.

  As shown in FIG. 10, the predicted maximum temperature satisfies the predetermined condition “28.0 degrees or more” in the period from “July” to “September”, and “October to June”, which is the other period. Does not satisfy the predetermined condition “28.0 degrees or more”. In such a case, the parameter determination unit 24 sets a period of “October to June” that does not satisfy the predetermined condition as an invalidation period.

  In the example described above, context data having a certain cycle is set as a determination target, but context data having a plurality of cycles may be set as a determination target. For example, an average value of the predicted maximum temperature of “January” in the past 10 years may be calculated, and it may be determined whether the average value is equal to or higher than a predetermined temperature. In addition, for example, when there are eight or more predicted maximum temperatures in “January” in the past 10 years that are equal to or higher than a predetermined temperature, it is determined that a predetermined condition is satisfied. Also good.

  An example of the data table in which the invalidation period is set is as shown in FIG. As shown in FIG. 3, since the temperature and the predicted maximum temperature are specified to have periodicity, an invalidation period is set. On the other hand, the invalidation period is not set for the position information identified as having no periodicity.

(Update startup parameters)
Next, activation parameter update processing by the parameter determination unit 24 will be described. The parameter determination unit 24 refers to the data table 21 and updates the “invalidation period” fields of the activation parameter 11 of the mobile terminal 10 and the activation parameter 23 of the server 20. By the update process, the “invalidation period” that is blank in the initial setting in the activation parameter 11 and the activation parameter 23 is set as illustrated in FIGS. 2 and 6.

  Returning to FIG. 1, the activation control unit 25 outputs an execution instruction of the context data collection processing in the server 20 to the information acquisition unit 26 according to the timing stored in the activation parameter 23. In addition, the activation control unit 25 outputs an execution instruction for context data determination processing to the determination unit 27 in accordance with the timing stored in the activation parameter 23.

  For example, the activation control unit 25 refers to the contents of the activation parameter 23 shown in FIG. 6 and instructs the information acquisition unit 26 to execute the request for the weather forecast and the predicted maximum temperature to the other system 30 every other hour. Is output. In addition, the activation control unit 25 outputs a determination process execution instruction to the determination unit 27 every 10 minutes. However, the activation control unit 25 suppresses the output of the execution instruction during the invalidation period of “16:00 to 10:00” and “October to June”.

  For example, when the time stored in the execution frequency of the start parameter 23 has elapsed, the start control unit 25 determines whether the current date and time is included in the invalidation period. The activation control unit 25 outputs an execution instruction when the current date and time are not included in the invalidation period.

  The information acquisition unit 26 receives an execution instruction from the activation control unit 25, transmits a context data acquisition request to the other system 30, and stores the context data received from the other system 30 in the history DB 22. Further, the information acquisition unit 26 receives the context data acquired by the mobile terminal 10 and stores it in the history DB 22.

  The determination unit 27 refers to the data table 21 and the history DB 22 and determines whether the collected context data satisfies a predetermined condition stored in the data table 21. For example, when the current position of the mobile terminal 10, the current temperature around the mobile terminal 10, and the predicted maximum temperature after one hour satisfy the conditions shown in FIG. 3, the determination unit 27 determines that the collected context data satisfies a predetermined condition. Judging to meet. When the determination unit 27 determines that the context data satisfies a predetermined condition, the determination unit 27 outputs a notification instruction to the notification unit 28.

  The notification unit 28 receives a notification instruction from the determination unit 27 and transmits a notification to the mobile terminal 10. In the first embodiment, the notification unit 28 transmits a notification regarding a heat stroke warning.

[Processing flow of server]
Next, the flow of processing by the server 20 will be described. First, the flow of context data collection processing and determination processing will be described with reference to FIGS. 11A and 11B. The context data collection process and the determination process are executed for each row of “data / process type” stored in the activation parameter 23.

  FIG. 11A is a flowchart illustrating an example of context data collection processing according to the first embodiment. The activation control unit 25 of the server 20 determines whether or not the time stored in the “execution frequency” of the activation parameter 23 has elapsed since outputting the execution instruction of the context data collection process (step S1). When the time stored in the execution frequency has not elapsed (step S1: No), the process proceeds to step S4.

  When the time stored in the execution frequency has elapsed (step S1: Yes), the activation control unit 25 determines whether or not the current date and time is included in the “invalidation period” stored in the activation parameter 23 ( Step S2). When included in the invalidation period (step S2: Yes), the process returns to step S1.

  On the other hand, when not included in the invalidation period (step S <b> 2: No), the activation control unit 25 outputs an execution instruction for the context data collection process to the information acquisition unit 26. In response to the execution instruction, the information acquisition unit 26 executes context data collection processing (step S3).

  Next, the information acquisition unit 26 determines whether context data has been received (step S4). Note that the context data received in step S4 includes context data received from the mobile terminal 10 in addition to the context data acquired based on the collection process in step S3.

  When the context data is received (step S4: Yes), the information acquisition unit 26 stores the received context data in the history DB 22 (step S5), and returns to step S1. On the other hand, when context data is not received (step S4: No), it returns to step S1.

  Next, the flow of the context data determination process will be described. FIG. 11B is a flowchart illustrating an example of the determination process according to the first embodiment. First, the activation control unit 25 of the server 20 determines whether or not the time stored in the “execution frequency” of the activation parameter 23 has elapsed after outputting the execution instruction of the context data determination process (step S11). ). If the time stored in the execution frequency has not elapsed (step S11: No), the process returns to step S11 and waits again.

  When the time stored in the execution frequency has elapsed (step S11: Yes), the activation control unit 25 determines whether or not the current date and time is included in the “invalidation period” stored in the activation parameter 23 ( Step S12). When included in the invalidation period (step S12: Yes), the process returns to step S11 and waits again.

  On the other hand, when it is not included in the invalidation period (step S12: No), the activation control unit 25 outputs an execution instruction for the context data determination process to the determination unit 27. The determination unit 27 receives the execution instruction and executes a context data determination process (step S13). For example, the determination unit 27 determines whether or not the temperature stored in the history DB 22 is equal to or higher than the temperature stored in the determination condition of the data table 21.

  When it is determined that the context data satisfies the predetermined condition (step S14: Yes), the determination unit 27 outputs a notification instruction to the notification unit 28. The notification unit 28 receives the notification instruction and transmits a notification to the mobile terminal 10 (step S15). For example, the notification unit 28 transmits a notification regarding a heat stroke warning. Then, it returns to step S11 and waits again. On the other hand, when it is determined that the context data does not satisfy the predetermined condition (step S14: No), the process returns to step S11 and waits again.

  Next, the flow of processing for specifying the invalidation period will be described with reference to FIG. 11C. FIG. 11C is a flowchart illustrating an example of a process for specifying an invalidation period in the first embodiment. The process of specifying the invalidation period is started by an instruction from the administrator of the server 20, for example.

  The parameter determination unit 24 refers to past context data stored in the history DB 22 and identifies the presence or absence of periodicity (step S101). For example, when it is specified that there is no periodicity of the context data as in the position information (step S102: No), the parameter determination unit 24 ends the process.

  When the parameter determination unit 24 specifies the periodicity of the context data (step S102: Yes), the context data at a specific time point included in the specific cycle stored in the history DB 22 is compared with a predetermined condition (step S102). S103). For example, it is determined whether or not the temperature during a specific time is equal to or higher than a predetermined temperature. Note that, as described above, it may be configured to determine whether or not a predetermined condition is satisfied with respect to context data of a plurality of cycles or an average value of context data of a plurality of cycles.

  Next, the parameter determination unit 24 sets a period including a time point corresponding to context data that does not satisfy the predetermined condition as an invalidation period (step S104). For example, the parameter determination unit 24 sets the activation parameter 11 and the activation parameter 23 as invalidation periods of “16:00 to 10:00” that do not satisfy the predetermined condition “temperature 29.0 ° C. or higher”. Remember.

[Flow of mobile terminal processing]
Next, the flow of processing related to the collection of context data by the mobile terminal 10 will be described with reference to FIG. FIG. 12 is a flowchart illustrating an example of processing related to collection of context data by the mobile terminal according to the first embodiment. The activation control unit 12 of the mobile terminal 10 executes processing with reference to a specific “data type” line of the activation parameter 11, and when there are a plurality of “data type” lines in the activation parameter 11, The processing shown in FIG. 12 is executed for each row.

  The activation control unit 12 waits until the time stored in the “execution frequency” of the activation parameter 11 elapses after outputting the execution instruction of the context data collection process (step S201: No). When the time stored in the execution frequency has elapsed (step S201: Yes), the activation control unit 12 determines whether or not the current date and time is included in the “invalidation period” stored in the activation parameter 11 ( Step S202).

  If included in the invalidation period (step S202: Yes), the process returns to step S201 and waits again. On the other hand, when not included in the invalidation period (step S202: No), the activation control unit 12 outputs an execution instruction for the context data collection processing to the information acquisition unit 13. In response to the execution instruction, the information acquisition unit 13 executes context data collection processing (step S203), and transmits the collected context data to the server 20 (step S204). Then, it returns to step S201 and waits again.

  According to the first embodiment, the server 20 specifies the fluctuation cycle of the context data, sets an invalidation period with a low possibility of satisfying the condition, and suppresses the context data collection process in the invalidation period. Thereby, useless context data collection processing and determination processing in the mobile terminal 10 and the server 20 can be suppressed, and the processing load can be reduced.

[Disabling processing based on location information]
In the first embodiment, the invalidation period is set based on the fluctuation cycle of the context data. However, the embodiment is not limited to this. For example, in the information collection system 1 for notifying a heatstroke warning in Tokyo, if the user stays in another area, the context data collection process and determination process in the area may be useless.

  In the information collection system 1 according to the second embodiment, the collection of context data is suppressed based on the position information of the mobile terminal 10. For example, when the user of the mobile terminal 10 is outside Tokyo, the parameter determination unit 24 of the server 20 starts the startup parameter 11 and the startup so as to suppress the collection processing and determination processing of context data other than the location information of the mobile terminal 10. The parameter 23 is updated. Note that the configuration of the information collection system 1 in the second embodiment is the same as that in the first embodiment, and a detailed description thereof will be omitted.

[Parameter decision processing]
In the second embodiment, the parameter determination unit 24 acquires the latest position information of the mobile terminal 10. For example, when the information acquisition unit 26 acquires position information from the mobile terminal 10, the information acquisition unit 26 outputs the position information to the parameter determination unit 24. The parameter determination unit 24 refers to the data table 21 and determines whether or not the acquired position information satisfies the determination condition.

  In the second embodiment, as illustrated in FIG. 3, “Tokyo” is stored in the column of the determination condition in the row of the data type “position” of the data table 21. For example, when the position information acquired from the mobile terminal 10 is “Hokkaido”, the position information determination condition stored in the data table 21 is not satisfied. In this case, the parameter determination unit 24 sets “outside region” in the “invalidation period” column of the activation parameter 11 and the activation parameter 23.

  An example of the activation parameter 11 in which “outside the region” is set is shown in FIGS. 13A and 13B. FIG. 13A is an explanatory diagram illustrating an example of activation parameters of the mobile terminal according to the second embodiment. As shown in FIG. 13A, “outside area” is set in the “invalidation period” column of the data type row other than “position” in the activation parameter 11. In this case, the activation control unit 12 of the mobile terminal 10 also detects the temperature and humidity other than the “16:00 to 10:00” period and the “October to June” period that are the invalidation periods that have been set. Suppress the collection process.

  Also in this case, the activation control unit 12 of the mobile terminal 10 acquires the position information according to the execution frequency described in the activation parameter 11 and transmits it to the server 20. The acquisition of the position information is continued even when “outside area” is set in the activation parameter 11 when the mobile terminal 10 moves to an area that satisfies the determination condition of the position information. Is to be able to resume.

  FIG. 13B is an explanatory diagram illustrating an example of a server startup parameter according to the second embodiment. As shown in FIG. 13B, “outside the region” is set in the “invalidation period” column of all the rows of the activation parameter 23. In this case, the activation control unit 25 of the server 20 suppresses all context data collection processing and determination processing until the “outside area” setting of the activation parameter 23 is canceled. Note that the activation parameter 11 and the activation parameter 23 include, for example, a flag indicating whether or not “outside the region” is set in the “invalidation period” column, instead of “outside the region”. May be.

  On the other hand, when the position information acquired from the mobile terminal 10 satisfies the determination condition of the position information stored in the data table 21, the parameter determination unit 24 cancels the setting “out of area”. For example, the parameter determination unit 24 deletes the characters “outside the region” from the “invalidation period” column of the activation parameter 11 and the activation parameter 23.

[Process flow]
A processing flow of the parameter determination unit 24 in the second embodiment will be described. FIG. 14 is a flowchart illustrating an example of processing related to invalidation of processing based on position information in the second embodiment.

  First, the parameter determination unit 24 waits until the information acquisition unit 26 acquires position information from the mobile terminal 10 (step S301: No). When the information acquisition unit 26 acquires the position information from the mobile terminal 10, the parameter determination unit 24 receives the output of the position information from the information acquisition unit 26 (step S301: Yes). The parameter determination unit 24 refers to the data table 21 and determines whether or not the acquired position information satisfies the determination condition (step S302).

  When the acquired position information does not satisfy the determination condition (step S302: No), the parameter determination unit 24 sets “out of region” in the “invalidation period” column of the activation parameter 11 and the activation parameter 23 (step S302). S303). For example, when the position determination condition stored in the data table 21 is “Tokyo” and the acquired position information is “Hokkaido”, the parameter determination unit 24 sets “outside the region”. Then, it returns to step S301 and waits.

  On the other hand, when the acquired position information satisfies the determination condition (step S302: Yes), the parameter determination unit 24 confirms whether “outside the region” is set in the activation parameter 11 and the activation parameter 23 (step S304). ).

  When “outside area” is set (step S304: Yes), the parameter determination unit 24 cancels the setting of “outside area” in the start parameter 11 and the start parameter 23 (step S305). Then, it returns to step S301 and waits. On the other hand, when “outside area” is not set (step S304: No), the process returns to step S301 and waits.

  In the second embodiment, when the mobile terminal 10 is present outside the region to be determined, the context data collection process other than the position information and the determination process are suppressed. Thereby, useless processing in the mobile terminal 10 and the server 20 can be suppressed, and the processing load can be reduced.

[Configuration for setting the next execution date and time]
In the first and second embodiments, the activation control unit 12 of the mobile terminal 10 determines whether or not the current date / time is included in the “invalidation period” each time the time stored in the “execution frequency” of the activation parameter 11 elapses. Determine whether. Similarly, the activation control unit 25 of the server 20 determines whether or not the current date and time is included in the “invalidation period” each time the time stored in the “execution frequency” of the activation parameter 23 elapses. The activation control unit 12 and the activation control unit 25 output an execution instruction for context data collection processing or determination processing when the current date and time are not included in the “invalidation period”. However, the embodiment is not limited to this.

  For example, the parameter determination unit 24 may be configured to set the “next execution date and time” field in the activation parameter 11 and the activation parameter 23. At this time, the parameter determination unit 24 sets a date and time not included in the “invalidation period” in the “next execution date and time” field.

  In this case, the activation control unit 12 of the mobile terminal 10 collects the context data without determining whether or not the current date / time is included in the “invalidation period” at the time of “next execution date / time” of the activation parameter 11. Outputs process execution instructions. Further, the activation control unit 25 of the server 20 does not determine whether the current date / time is included in the “invalidation period” at the time of “next execution date / time” of the activation parameter 23, Outputs execution instructions for judgment processing.

  In the information collection system 1 according to the third embodiment, the parameter determination unit 24 of the server 20 sets the “last execution date” column and the “next execution date” column in the activation parameter 11 and the activation parameter 23. The configuration of the information collection system 1 in the third embodiment is the same as that in the first embodiment, and a detailed description thereof will be omitted.

[Data structure of startup parameters]
First, the startup parameter 11 in the third embodiment will be described. FIG. 15A is an explanatory diagram illustrating an example of activation parameters of the mobile terminal according to the third embodiment. As illustrated in FIG. 15A, the activation parameter 11 according to the third embodiment stores “data type”, “previous execution date / time”, “execution frequency”, and “next execution date / time” in association with each other. Among these, “data type” and “execution frequency” are the same as those in the example of the activation parameter 11 in the first embodiment, and thus detailed description thereof is omitted.

  The “previous execution date and time” column of the activation parameter 11 indicates the date and time when the activation control unit 12 of the portable terminal 10 performed the context data collection processing at the immediately preceding timing. The “next execution date / time” column indicates the timing at which the activation control unit 12 next outputs an execution instruction for the context data collection processing.

  For example, in the row where “data type” in FIG. 15A is “position”, the “previous execution date” is “2015/7/1 10:00:00”. In the “next execution date / time”, for example, a date / time α calculated by adding the time stored in “execution frequency” to “previous execution date / time” is set. In the example of FIG. 15A, “2015/7/1 10:10:00”, which is the date and time α obtained by adding “10 minutes” of “execution frequency” to “previous execution date and time”, is the “next execution date and time” column. Set to On the other hand, when the date and time α is included in the invalidation period, for example, the end date and time of the invalidation period is set as the “next execution date and time”.

[Startup parameter update processing]
Next, a process in which the parameter determination unit 24 updates the “last execution date / time” column and the “next execution date / time” column of the activation parameter 11 will be described. The parameter determination unit 24 performs update processing of the activation parameter 11 for each data type, for example. In the following, an example of processing for updating the “last execution date” and “next execution date” fields in the row where the “data type” of the activation parameter 11 shown in FIG. 15A is “position” will be described.

  The parameter determination unit 24 updates the activation parameter 11 shown in FIG. 15A at the time “2015/7/1 10:10:00”, which is the time when the “next execution date and time” has elapsed. The parameter determination unit 24 updates the activation parameter 11 after confirming that the activation control unit 12 has output an execution instruction of the context data collection process. However, the configuration may be such that the parameter determination unit 24 updates the activation parameter 11 regardless of whether or not the execution instruction is actually output.

  FIG. 15B is an explanatory diagram illustrating an example of a start parameter after updating the next execution date and time in the third embodiment. In the following description, FIG. 15A shows the activation parameter 11 before update, and FIG. 15B shows the activation parameter 11 after update.

  The parameter determination unit 24 sets, for example, the date and time set in the “next execution date and time” in FIG. 15A in the “previous execution date and time” column of FIG. 15B. As illustrated in FIG. 15B, the parameter determination unit 24 sets “2015/7/1 10:10:00” which is the “next execution date and time” in the “position” row of the activation parameter 11 before update illustrated in FIG. 15A. Is set in the “Previous execution date and time” column of the updated startup parameter 11.

  Next, the parameter determination unit 24 calculates the “next execution date and time” of the updated startup parameter 11. For example, the parameter determination unit 24 sets “2015/7/1 10:20” which is the date and time α obtained by adding “10 minutes” of “execution frequency” to the date and time set in the “previous execution date and time” column of FIG. 0:00 ”is set in the“ next execution date and time ”field of FIG. 15B. At the time of “2015/7/1 10:10:00”, the “next execution date” of the “humidity” line in FIG. 15A has not passed, so the parameter determination unit 24 sets the “humidity” line. Do not update the “last execution date” and “next execution date” fields.

  However, when the calculated date / time is included in the “invalidation period”, the end date / time of the “invalidation period” is set to “next execution date / time”. FIG. 15C is an explanatory diagram illustrating an example of a start parameter after updating the next execution date and time within the invalidation period according to the third embodiment. For example, in the row where “data type” in FIG. 15C is “position”, the “previous execution date / time” is “2015/7/1 16:00:00”. The date and time α obtained by adding “10 minutes” of “execution frequency” to this is “2015/7/1 16:10:00”.

  However, “2015/7/1 16:10:00” is included in the period of “16:00 to 10:00” that is the “invalidation period” stored in the data table 21. In this case, as shown in FIG. 15C, the parameter determination unit 24 sets “2015/7/2 10:00: 00” that is the end date / time of the “invalidation period” in the “next execution date / time” column. To do.

  Note that the activation parameter 23 of the server 20 can also be updated by a similar process. FIG. 15D is an explanatory diagram illustrating an example of a server startup parameter according to the third embodiment.

  In the example of FIG. 15D, in the “weather forecast” row and the “predicted maximum temperature” row, the date and time α obtained by adding “1 hour” of “execution frequency” to “previous execution date and time” is “2015/7/1. 16:10:00 ”and included in the“ invalidation period ”. Therefore, the parameter determination unit 24 sets “2015/7/2 10:00: The end date and time of the invalidation period as“ next execution date and time ”in the“ weather forecast ”row and the“ predicted maximum temperature ”row. 00 ”is set.

  On the other hand, in the row of “determination process” in FIG. 15D, the date and time α is “2015/7/1 15:20:00” and is not included in the “invalidation period”. Therefore, the parameter determination unit 24 sets the date and time α as the “next execution date and time”.

[Process flow]
Next, the flow of update processing of the startup parameter 11 by the parameter determination unit 24 will be described. FIG. 16 is a flowchart illustrating an example of processing for setting the next execution date and time in the third embodiment. The parameter determination unit 24 refers to the activation parameter 11 and waits until the next execution date / time is reached (step S401: No).

  When the next execution date / time is reached (step S401: Yes), the parameter determination unit 24 sets the date / time stored in the “next execution date / time” column of the activation parameter 11 to the “previous execution date / time” of the activation parameter 11. Set in the field (step S402). Then, the parameter determination unit 24 calculates the date and time α obtained by adding the “time stored in the execution frequency” to the set “previous execution date and time” (step S403).

  Next, the parameter determination unit 24 determines whether or not the date α calculated in step S403 is included in the invalidation period (step S404). When the date α is included in the “invalidation period” (step S404: Yes), the parameter determination unit 24 sets the end date / time of the “invalidation period” in the “next execution date / time” field (step S405). Then, it returns to step S401 and waits.

  On the other hand, when the date α is not included in the “invalidation period” (step S404: No), the parameter determination unit 24 sets the date α in the “next execution date” column (step S406). Then, it returns to step S401 and waits.

  In the third embodiment, the activation control unit 12 of the mobile terminal 10 and the activation control unit 25 of the server 20 suppress processing related to the collection of context data when the current time is included in the invalidation period. Thereby, useless processing in the mobile terminal 10 and the server 20 can be suppressed, and the processing load can be reduced.

[Set process execution frequency]
For example, in addition to setting an invalidation period that suppresses execution of context data collection processing and determination processing, by changing the execution frequency of processing, unnecessary processing in the mobile terminal 10 and the server 20 is suppressed, and processing is performed. The load can be reduced. On the other hand, if the time interval for collecting the context data is long, it is difficult to grasp the state around the mobile terminal 10 in detail.

  Therefore, a configuration may be adopted in which a time interval for collecting context data is determined based on a time-series change of context data representing the surrounding state of the mobile terminal 10. Thereby, the collection interval can be adjusted according to a change in the surrounding state of the mobile terminal 10, and the load on the process of collecting the context data can be provided while providing information matching the surrounding state of the mobile terminal 10 in a timely manner. Can be suppressed.

  In the information collection system 1 according to the fourth embodiment, the parameter determination unit 24 of the server 20 refers to the history DB 22 to calculate “change tendency” of context data and “execution frequency” of collection processing, and the like. Set to. The configuration of the information collection system 1 in the fourth embodiment is the same as that in the first embodiment, and thus detailed description thereof is omitted.

  For example, the parameter determination unit 24 refers to the history DB 22 and identifies a change tendency for each data type. FIG. 17 is an explanatory diagram illustrating a specific example of a change tendency in the fourth embodiment. The parameter determination unit 24 divides the predetermined period stored in the history DB 22 by each unit time of a plurality of unit times having different lengths, and specifies the amount of change per unit time as a change tendency. As an example of determining for each data type, for example, the parameter determination unit 24 calculates the duration itself included in the determination condition of the data type, the time “10 times” the duration, and the time “1/10 times”. Multiple unit times. In this embodiment, the plurality of unit times are “1 second”, “1 minute”, “10 minutes”, and “1 hour”.

  Moreover, the parameter determination part 24 calculates the variation | change_quantity of each unit time about the specific example of the variation | change_quantity per unit time. If the change amount of each unit time is within a predetermined range, the change amount per unit time is specified to be within the predetermined range. A plurality of predetermined ranges may exist for each unit time. For example, it is assumed that the predetermined range is “less than 5 degrees” for context data whose data type is “temperature”. If the amount of change every 10 minutes is “less than 5 degrees” within a predetermined range, such as “0 degree”, “1 degree”, and “4 degrees”, the parameter determination unit 24 is 10 minutes. The amount of change per hit is specified as “less than 5 degrees”. If the change amount every 10 minutes is not “less than 5 degrees” which is a predetermined range such as “0 degrees”, “8 degrees”, “4 degrees”, the parameter determination unit 24 Assume that the amount of change per hit cannot be specified.

  In addition, for each example of specifying the amount of change per unit time, the amount of change per unit time may not be specified, and the amount of change per other unit time may be specified. In this case, the parameter determination unit 24 sets the change amount of the specified unit time as a change tendency. For example, when the parameter determination unit 24 cannot specify the amount of change per “1 hour” and the amount of change per “1 second” to “10 minutes” for the context data whose data type is “temperature”, The change tendency is “less than X degrees / 1 second, less than Y degrees / 1 minute, less than Z degrees / 10 minutes”.

  FIG. 17A shows an example in which the change amount per 10 minutes and the change amount per hour are specified for the example where the data type is “temperature”. In the example of FIG. 17A, it is assumed that the user of the mobile terminal 10 is indoors at “10:00 to 10:15” and is outdoors at “10:15 to 11:00”. The parameter determination unit 24 specifies the amount of change per 10 minutes as less than 5 degrees and specifies the amount of change per hour as less than 15 degrees.

  FIG. 17B shows the result of specifying the change tendency for each data type. The parameter determination unit 24 identifies the context data whose data type is “position” as “no specific change tendency”. The reason for “no particular change tendency” is that, for example, the user of the mobile terminal 10 changes greatly depending on the situation, such as office, walking, train, or the like. In addition, the parameter determination unit 24 sets the context data of the data type “temperature” to “less than 0.1 degree / 1 second, less than 0.5 degree / 1 minute, less than 5 degree / 10 minutes, less than 15 degree / 1 hour. ". Similarly, the parameter determination unit 24 specifies the context data whose data type is “expected maximum temperature” as “0 degrees / 1 second, 0 degrees / 1 minute, 0 degrees / 10 minutes, 1 degree / 1 hour”.

  The parameter determination unit 24 determines the execution frequency based on the identified change tendency for each data type. Specifically, when there is a specific change tendency, the parameter determination unit 24 compares the effective minimum digit unit of the corresponding data type with the amount of change of each unit time included in the change tendency, and determines the effective minimum digit. Specify a unit time whose amount of change is greater than the unit. Then, the parameter determining unit 24 determines the minimum unit time among the specified unit times as the execution frequency of the corresponding data type. In addition, when there is no specific change tendency, the parameter determination unit 24 determines, as the execution frequency of the corresponding data type, the maximum one of the unit times that is equal to or shorter than the duration of the corresponding data type.

  FIG. 18 is an explanatory diagram of an execution frequency determination example according to the fourth embodiment. FIG. 18A shows an example of determining the execution frequency for data types “position”, “temperature”, and “expected maximum temperature”. Since there is no specific change tendency for the data type “position”, the parameter determination unit 24 becomes the maximum in the time of “30 minutes” or less, which is the continuation condition of “position”, among a plurality of unit times. “10 minutes” is determined as the execution frequency. In addition, since the data type is “temperature”, there is a specific change tendency. Therefore, the parameter determination unit 24 selects “10 minutes” or “1 hour” having a change amount larger than the effective minimum digit unit “1 degree”. The smaller “10 minutes” is determined as the execution frequency. In addition, since the data type “predicted maximum temperature” has a specific change tendency, the parameter determination unit 24 determines “1 hour” having a change amount larger than the effective minimum digit unit “1 degree” as the execution frequency. . FIG. 18B shows the execution frequency determined for the data type “position”, “temperature”, and “expected maximum temperature”.

  The parameter determination unit 24 determines the execution frequency of the context data determination process based on the determined execution frequency. The determination result of the context data determination process does not change even if the context data determination process is performed at an interval shorter than the context data collection process. For example, since the position information is updated only in units of 10 minutes, even if the context data determination process is executed at intervals of 1 second, the determination result of the context data determination process does not change until the position information is updated. Such a context data determination process is a useless process and causes a high processing load. Therefore, the parameter determination unit 24 determines the minimum execution frequency among the determined execution frequencies as the execution frequency of the context data determination process. In the example of FIG. 18, since the minimum execution frequency of the determined execution frequencies is “10 minutes”, the parameter determination unit 24 determines the execution frequency of the context data determination process to be “10 minutes”.

  As a result of the above processing, as shown in FIG. 3, “execution frequency” and “change tendency” of the data table 21 are set.

  With the configuration as described above, the collection interval can be adjusted according to the change in the surrounding state of the mobile terminal 10, and the context data is collected while providing information that matches the surrounding state of the mobile terminal 10 in a timely manner. It is possible to reduce the load on the machine.

  Although the embodiments of the present invention have been described so far, the present invention may be implemented in various different forms other than the above-described embodiments. For example, the processes shown in FIGS. 11A to 11C, FIG. 14 or FIG. 16 are not limited to the above order, and may be performed simultaneously as long as the process contents do not contradict each other. May be.

  In addition, among the processes described in the present embodiment, all or a part of the processes described as being automatically performed can be manually performed. Alternatively, all or part of the processing described as being performed manually can be automatically performed by a known method. In addition, the processing procedure, control procedure, specific name, and information including various data and parameters shown in the above-described document and drawings can be arbitrarily changed unless otherwise specified.

  Further, each component of each illustrated apparatus is functionally conceptual, and does not necessarily need to be physically configured as illustrated. That is, the specific form of distribution / integration of each device is not limited to that shown in the figure. That is, all or a part of them can be configured to be functionally or physically distributed / integrated in arbitrary units according to various loads or usage conditions. For example, the activation control unit 12 and the information acquisition unit 13 can be integrated, or the parameter determination unit 24 can be distributed to an invalidation period determination unit and a parameter setting unit. Further, all or a part of each processing function performed in each device may be realized by a CPU and a program analyzed and executed by the CPU, or may be realized as hardware by wired logic.

[Optimization of invalidation period]
Note that it may be possible to optimize the “invalidation period” set in the first embodiment. For example, there is a case where a target value of the processing load reduction rate is set by setting the invalidation period, and the invalidation period is extended so that the target value can be achieved. Hereinafter, for example, a case where the target value of the processing load reduction rate is set to “83.3%” will be described.

  In this case, for example, a configuration in which the invalidation period is multiplied by a predetermined coefficient may be used. In the first embodiment, when the invalidation period to be set is “16:00 to 10:00”, the actual reduction rate of the processing load due to the invalidation period setting is “75%”. The target value is not achieved. In this case, in order to achieve the target value, for example, the invalidation period may be corrected by dividing the invalidation period by the actual reduction rate and further multiplying by the target value of the reduction rate. . In the above example, the invalidation period after correction is “15: 00 to 11:00”.

  Moreover, the structure which proposes the change of the predetermined condition used when setting the invalidation period instead of correcting the invalidation period may be used. In the first embodiment, the predetermined condition is that “air temperature” is “29 ° C. or higher”, but the target value described above can also be achieved by, for example, correcting it to “30.3 ° C. or higher”. it can. In this case, since the temperatures of “10:00” and “11:00” also do not satisfy the predetermined condition, the invalidation period after correction is “16:00 to 12:00”.

[Storage location of startup parameters]
In the above embodiment, the mobile terminal 10 has the activation parameter 11. However, the configuration is not limited thereto, and the server 20 may have the activation parameter 11. In this case, for example, the activation control unit 25 of the server 20 transmits a command to the portable terminal 10 at the timing stored in the activation parameter 11, and the activation control unit 12 of the portable terminal 10 that has received the command performs a context data collection process. to start.

[Required period until the specified condition is met]
Further, in the second embodiment, when the mobile terminal 10 exists outside the region to be determined, the configuration for suppressing the collection processing and determination processing of context data other than the position information is disclosed. However, the collection processing of the position information itself is performed. The structure which suppresses is also considered. For example, when “Tokyo” is the determination target, the mobile terminal 10 exists in “Hokkaido”, and the time required for the mobile terminal 10 to move to “Tokyo” is “3 hours”. Can be considered. In this case, since there is no possibility that the position information satisfies the determination condition for at least 3 hours, the position information acquisition process is performed wastefully during that time.

  In this case, for example, a configuration in which “3 hours” is set as the “invalidation period” in the row where the “data type” of the activation parameter 11 is “position” may be used. Thereby, the useless process in the portable terminal 10 and the server 20 can be further suppressed, and the processing load can be reduced.

[Hardware configuration of mobile terminal]
Next, the hardware configuration of the mobile terminal 10 and the server 20 will be described with reference to FIGS. 19 and 20. FIG. 19 is a diagram illustrating an example of a hardware configuration of the mobile terminal. As illustrated in FIG. 19, the mobile terminal 2000 according to the embodiment includes an RF circuit 2001, an antenna 2002, a processor 2004, a storage device 2005, an input device 2006, an output device 2007, a thermometer 2011, a hygrometer 2012, a GPS 2013, and a clock 2022. Have An RF circuit 2001, a processor 2004, a storage device 2005, an input device 2006, an output device 2007, a thermometer 2011, a hygrometer 2012, a GPS 2013 and a clock 2022 are connected to each other via a bus 2008. The antenna 2002 is connected to the RF circuit 2001.

  The RF circuit 2001 communicates with the server 20 via the antenna 2002. For example, the functions of the information acquisition unit 13 and the notification acquisition unit 15 illustrated in FIG. 1 are realized by the RF circuit 2001, the processor 2004, and the storage device 2005.

  In addition, the processor 2004 and the storage device 2005 realize the functions of the activation control unit 12 and the like illustrated in FIG.

  For example, the processor 2004 reads various programs stored in the storage device 2005 and generates processes for realizing various functions on the storage device 2005. The processor 2004 performs various processes by executing processes generated on the storage device 2005 together with the respective units.

  The input device 2006 is a touch panel or a keyboard, and the output device 2007 is a display. As an example of the storage device 2005, other computer-readable storage devices such as a read only memory (ROM), a random access memory (RAM), and a CD-ROM may be used in addition to a hard disk drive (HDD).

  The thermometer 2011 is a sensor that measures the air temperature, and outputs the measured air temperature to the processor 2004. The hygrometer 2012 is a sensor that measures humidity, and outputs the measured humidity to the processor 2004. A GPS (Global Positioning System) 2013 is a sensor that acquires position information, and outputs the acquired position information to the processor 2004. The clock 2022 acquires the current time and outputs it to the processor 2004.

[Hardware Configuration of Server 20]
FIG. 20 is a diagram illustrating an example of a hardware configuration of the server. As illustrated in FIG. 20, the computer 3000 includes a communication interface 3001, a processor 3002, a storage device 3003, an input device 3004, and an output device 3005. 20 are connected to each other via a bus 3006.

  The input device 3004 is a mouse or a keyboard, the output device 3005 is a display or the like, and the communication interface 3001 is an interface such as a NIC. The communication interface 3001 communicates with the mobile terminal 10 and the other system 30 via a network. As an example of the storage device 3003, in addition to the HDD, other computer-readable storage devices such as a ROM, a RAM, and a CD-ROM may be used.

  In addition, the processor 3002 and the storage device 3003 realize functions such as the parameter determination unit 24, the activation control unit 25, the information acquisition unit 26, the determination unit 27, and the notification unit 28 illustrated in FIG.

  For example, the processor 3002 reads various programs stored in the storage device 3003 and generates processes for realizing various functions on the storage device 3003. The processor 3002 performs various processes by executing processes generated on the storage device 3003 together with the respective units.

DESCRIPTION OF SYMBOLS 10 Mobile terminal 11 Startup parameter 12 Startup control part 13 Information acquisition part 15 Notification acquisition part 20 Server 21 Data table 22 History DB
23 activation parameter 24 parameter determination unit 25 activation control unit 26 information acquisition unit 27 determination unit 28 notification unit 30 other system

Claims (6)

On the computer,
Based on the change in the context data collected by the device, the fluctuation period of the context data is identified,
An information collection program that causes the apparatus to execute an invalid period for suppressing the collection of the context data based on the identified fluctuation period. Receiving the context data collected by the device from the device, further causing the computer to execute a process of determining whether the context data satisfies a predetermined condition;
The information collection program according to claim 1, wherein the setting process sets the invalid period based on a fluctuation period of the context data and a determination result as to whether or not the predetermined condition is satisfied. .   In the setting process, a period in which the ratio of the context data collected in the past does not satisfy the predetermined condition is a predetermined value or more is determined as the invalid period, and the context data is transmitted to the device during the invalid period. The information collection program according to claim 2, further comprising: Receiving the context data collected by the device from the device, further causing the computer to execute a process of determining whether or not position information of the device from which the context data is collected satisfies a predetermined condition;
As a result of the determination process, when it is determined that the position information of the device does not satisfy the predetermined condition, the context data other than the position information of the device is updated until the position information of the device satisfies the predetermined condition. The information collection program according to claim 1, wherein the collection process is suppressed. A specifying unit that specifies a change period of the context data based on a change in the context data collected by the device;
An information collection device comprising: a setting unit configured to set an invalid period for suppressing the collection of the context data in the device based on the identified fluctuation period. Computer
A memory and a processor connected to the memory;
The processor is
Based on the change in the context data collected by the device, the fluctuation period of the context data is identified,
An information collection method comprising: executing an invalid period for suppressing collection of the context data in the device based on the identified fluctuation period.

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