Patent Publication Number: US-2020284640-A1

Title: Recording medium recording measurement control program, measurement control method and information processing device

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This application is a continuation application of International Application PCT/JP2017/042669 filed on Nov. 28, 2017 and designated the U.S., the entire contents of which are incorporated herein by reference. 
    
    
     FIELD 
     The embodiment relates to a measurement control program, a measurement control method, a measurement control device, and a measurement control system. 
     BACKGROUND 
     A monitoring system takes countermeasures against flood damage by installing a water level sensor in a river or a sewer, and monitoring the rising or overflow of the river or the sewer based on the measurement value of the water level sensor. Furthermore, in some cases, the water level sensor is configured as a battery-mounted type to achieve the simplification of the introduction work for the monitoring system. 
     Related art is disclosed in Japanese Laid-open Patent Publication No. 2008-50903, Japanese Laid-open Patent Publication No. 2011-42943, and Japanese Laid-open Patent Publication No. 2010-203964. 
     SUMMARY 
     According to an aspect of the embodiments, a non-transitory computer-readable recording medium records a measurement control program that controls a sensor that measures a water level, the measurement control program causing a computer to execute processing comprising: specifying a predicted peak value of the water level based on a prediction result for a change in the water level; calculating a reference value of the water level at which measurement of the water level is started, according to the predicted peak value that has been specified; specifying a timing at which the water level is predicted to reach the reference value that has been calculated, based on the prediction result; and controlling a start timing of measurement of the water level by the sensor based on the timing that has been specified. 
     The object and advantages of the invention will be realized and attained by means of the elements and combinations particularly pointed out in the claims. 
     It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory and are not restrictive of the invention. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG. 1  is an explanatory diagram illustrating an example of a measurement control method according to an embodiment. 
         FIG. 2  is an explanatory diagram illustrating an example of a monitoring system  200 . 
         FIG. 3  is a block diagram illustrating an exemplary hardware configuration of a measurement control device  100 . 
         FIG. 4  is an explanatory diagram illustrating an example of contents stored in an actual water level table  400 . 
         FIG. 5  is an explanatory diagram illustrating an example of contents stored in a predicted water level table  500 . 
         FIG. 6  is an explanatory diagram illustrating an example of contents stored in an actual rain amount table  600 . 
         FIG. 7  is an explanatory diagram illustrating an example of contents stored in a predicted rain amount table  700 . 
         FIG. 8  is an explanatory diagram illustrating an example of contents stored in a reference value table  800 . 
         FIG. 9  is a block diagram illustrating an exemplary hardware configuration of a sensor device  101 . 
         FIG. 10  is a block diagram illustrating an exemplary functional configuration of the measurement control device  100 . 
         FIG. 11  is an explanatory diagram (part 1) illustrating an example of predicting a change in water level. 
         FIG. 12  is an explanatory diagram (part 2) illustrating an example of predicting a change in water level. 
         FIG. 13  is an explanatory diagram (part 1) illustrating an example of designating a threshold value and a measurement interval. 
         FIG. 14  is an explanatory diagram (part 2) illustrating an example of designating a threshold value and a measurement interval. 
         FIG. 15  is an explanatory diagram (part 3) illustrating an example of designating a threshold value and a measurement interval. 
         FIG. 16  is an explanatory diagram (part 4) illustrating an example of designating a threshold value and a measurement interval. 
         FIG. 17  is an explanatory diagram (part 5) illustrating an example of designating a threshold value and a measurement interval. 
         FIG. 18  is an explanatory diagram (part 1) illustrating an example of controlling the sensor device  101 . 
         FIG. 19  is an explanatory diagram (part 2) illustrating an example of controlling the sensor device  101 . 
         FIG. 20  is an explanatory diagram (part 1) illustrating an example of displaying a screen. 
         FIG. 21  is an explanatory diagram (part 2) illustrating an example of displaying a screen. 
         FIG. 22  is a flowchart illustrating an example of an overall processing procedure. 
     
    
    
     DESCRIPTION OF EMBODIMENTS 
     For example, the amount of precipitation for each water catchment area is predicted based on a short-term predicted rainfall value, and, for each water catchment area, the amount of flow of water flowing into the river from the water catchment area is predicted based on the amount of precipitation predicted for each water catchment area. In addition, for example, the water level is non-contactly measured in a pipe from above by a water level measurement unit removably attached to a through-hole portion that is formed in a lid portion of a manhole unit and passes through in a vertical plane direction. Furthermore, for example, the frequency of data transmission is altered in a wireless station of a sensor node according to the measurement value of the water level in a sewer pipe, or the like. 
     However, the water level may not be measured efficiently. For example, if the water level sensor is set to constantly measure the water level, the water level is continuously measured even when the weather is fine or cloudy, or when it is raining but the amount of rain does not require to monitor the rising or overflow of a river or a sewer, for example, resulting in increases in processing load and power consumption of the water level sensor. 
     In one aspect, the water level may be efficiently measured according to the predicted value of the water level. 
     Hereinafter, embodiments of a measurement control program, a measurement control method, a measurement control device, and a measurement control system according to the present invention will be described in detail with reference to the drawings. 
     One Example of Measurement Control Method According to Embodiment 
       FIG. 1  is an explanatory diagram illustrating an example of a measurement control method according to an embodiment. In  FIG. 1 , a measurement control device  100  is a computer that controls a monitoring system. The purpose of the monitoring system is, for example, to take countermeasures against flood damage by installing a water level sensor in a river or a sewer, and monitoring the rising or overflow of the river or the sewer based on the measurement value of the water level sensor. 
     Here, there are cases where the water level sensor is desired to be configured as a battery-mounted type to achieve the simplification of the installation work for the monitoring system. In these cases, since the water level sensor is configured as a battery-mounted type, it is sometimes desired to achieve the reduction of the processing load, amount of communication, and power consumption of the water level sensor, and to achieve the reduction of the workload for the maintenance management of the monitoring system. Furthermore, it is preferable to achieve the reduction of the processing load, amount of communication, and power consumption of the water level sensor even if the water level sensor is not configured as a battery-mounted type. In some cases, however, the water level sensor cannot measure the water level efficiently, resulting in increases in processing load, amount of communication, and power consumption of the water level sensor. 
     To measure the water level efficiently means to measure the water level while suppressing increases in the processing load, amount of communication, and power consumption. To measure the water level efficiently means, for example, to make the number of times the water level is measured smaller in such a situation that there is less adverse influence on countermeasures against flood damage even without measuring the water level. Such a situation that there is less adverse influence on countermeasures against flood damage is, for example, a situation in a case where the weather is fine or cloudy, a case where it is raining but the amount of rain does not require to monitor the rising or overflow of a river or a sewer, or the like. To make the number of times the water level is measured smaller means, for example, to shorten the measurement period for the water level or to make the frequency of measurement of the water level smaller. 
     For example, if the water level sensor is set to constantly measure the water level, the water level sensor is caused to continuously measure the water level, for example, even when the weather is fine or cloudy, or when it is raining but the amount of rain does not require to monitor the rising or overflow of a river or a sewer. For this reason, the water level sensor will continuously measure the water level even in such a situation that there is little adverse influence on countermeasures against flood damage even without measuring the water level, resulting in increases in processing load, amount of communication, and power consumption of the water level sensor. 
     In contrast, it is conceivable that the water level sensor is set so as to constantly measure the water level at regular intervals, and when the measurement value of the water level exceeds a threshold value set by a user, to measure the water level at a greater frequency of measurement of the water level. However, since the water level sensor constantly measures the water level at regular intervals, the water level measurement cannot be stopped even in such a situation that the water level does not rise above a certain level and there is little adverse influence on countermeasures against flood damage even without measuring the water level. For this reason, the processing load, amount of communication, and power consumption of the water level sensor are increased as a result. 
     Furthermore, in the water level sensor, as the threshold value set by the user is made larger, the frequency of measurement of the water level cannot be made greater even in a situation where it is preferable to measure the water level for the purpose of countermeasures against flood damage, and it becomes difficult to take countermeasures against flood damage efficiently. Meanwhile, in the water level sensor, as the threshold value set by the user is made smaller, the frequency of measurement of the water level is more likely to be made greater in such a situation that the water level does not rise above a certain level, and there is little adverse influence on countermeasures against flood damage even without measuring the water level. For this reason, the processing load, amount of communication, and power consumption of the water level sensor are increased as a result. In addition, the user bears the workload for setting the threshold value. 
     In contrast, it is conceivable that the water level sensor is set so as not to measure the water level before the predicted value of the water level exceeds the threshold value set by the user, and after the predicted value of the water level exceeds the threshold value set by the user, to start measuring the water level. However, it is more difficult for the water level sensor to measure the water level efficiently as the prediction accuracy for the water level is lower. 
     Furthermore, as the threshold value set by the user is made larger, the water level sensor delays to start measuring the water level, and the user is slow in grasping a sudden rise in the water level, and the like; in consequence, it becomes difficult to take countermeasures against flood damage efficiently. Meanwhile, as the threshold value set by the user is made smaller, the water level sensor is caused to start measuring the water level even in such a situation that the water level does not rise above a certain level, and there is little adverse influence on countermeasures against flood damage even without measuring the water level. For this reason, the processing load, amount of communication, and power consumption of the water level sensor are increased as a result. In addition, the user bears the workload for setting the threshold value. 
     Accordingly, it is preferable that the water level sensor be kept stopped from measuring the water level in accordance with the situation. Furthermore, when the water level sensor is caused to start measuring the water level, it is preferable to make the number of times the water level is measured smaller as flood damage is less likely to occur, and to achieve the reduction of the processing load, amount of communication, and power consumption of the water level sensor. On the other hand, when the water level sensor is caused to start measuring the water level, it is preferable to make the number of times the water level is measured greater as flood damage is more likely to occur, and to achieve the improvement ire efficiency of countermeasures against flood damage. 
     Thus, in the present embodiment, a measurement control method will be described in which a reference value according to a predicted peak value of the water level is calculated based on a prediction result for a change in water level, and a start timing of the water level measurement is controlled based on a predicted timing at which the water level reaches the reference value. According to this embodiment, for example, the measurement control method can control the start timing of the water level measurement according to the degree of likelihood of the occurrence of flood damage, and can measure the water level efficiently, whereby countermeasures against flood damage can be taken efficiently. 
     In the example in  FIG. 1 , the monitoring system includes a sensor device  101 . The sensor device  101  is a computer that operates as a water level sensor and measures the water level at a target location. The target location corresponds to a location where the sensor device  101  is installed. The target location is, for example, a river or a sewer. The target location is, specifically, a pipe  110 . The measurement control device  100  is connected to the sensor device  101  so as to be able to communicate with each other. 
     The measurement control device  100  specifies the predicted peak value of the water level based on a prediction result for a change in water level. The unit of the water level is, for example, centimeter (cm). The prediction result for a change in water level is a collection of predicted values of the water level for every certain time. The measurement control device  100 , for example, predicts a change in water level in a certain period based on the amount of rain, and specifies a predicted peak value of the water level in the certain period based on a prediction result for the change in water level. 
     In the example in  FIG. 1 , the prediction result for a change in water level is a collection of predicted values of the water level at time points t+1, t+2, and t+3, and is given as a prediction result A or a prediction result B. The reference sign t denotes the current time. If the prediction result for a change in water level is given as the prediction result A, the measurement control device  100  specifies a predicted peak value p 1  of the water level. Furthermore, if the prediction result for a change in water level is given as the prediction result B, the measurement control device  100  specifies a predicted peak value p 2  of the water level. 
     The measurement control device  100  calculates a reference value of the water level at which the measurement of the water level is started, according to the specified predicted peak value. The measurement control device  100  calculates a reference value corresponding to the specified predicted peak value, for example, based on information representing a relationship between the predicted peak value and the reference value. The information representing the relationship between the predicted peak value and the reference value is, for example, a reference value table  800  described later with reference to  FIG. 8 . The relationship between the predicted peak value and the reference value has, for example, a relationship in which the larger the predicted peak value is, the smaller the reference value is. 
     In the example in  FIG. 1 , when the predicted peak value p 1  is specified, the measurement control device  100  calculates a reference value w 1  corresponding to the specified predicted peak value p 1 . Furthermore, when the predicted peak value p 2  is specified, the measurement control device  100  calculates a reference value w 2  corresponding to the specified predicted peak value p 2 . The reference value w 1  is, for example, smaller than the reference value w 2 . 
     Here, the predicted peak value of the water level serves as, on the one hand, an index value for evaluating the degree of likelihood of the occurrence of flood damage. The predicted peak value of the water level represents, for example, that the larger the value is, the higher the likelihood of overflow is. In addition, the predicted peak value of the water level represents, for example, that the larger the value is, the more flood damage is likely to occur in a case where a difference is produced between the prediction result for the water level and the actual transition result of the water level. 
     For this reason, the measurement control device  100  can control the reference value of the water level at which the measurement of the water level is started, according to the degree of likelihood of the occurrence of flood damage. The measurement control device  100  can control, for example, such that the more flood damage is likely to occur, the smaller the reference value of the water level at which the measurement of the water level is started, and the less flood damage is likely to occur, the larger the reference value of the water level at which the measurement of the water level is started. 
     The measurement control device  100  specifies a predicted timing at which the water level is predicted to reach the calculated reference value, based on the prediction result. In the example in  FIG. 1 , when the reference value w 1  is calculated, the measurement control device  100  specifies a predicted timing t+1 at which the calculated reference value w 1  is predicted to be reached. Furthermore, when the reference value w 2  is calculated, the measurement control device  100  specifies a predicted timing t+2 at which the calculated reference value w 2  is predicted to be reached. 
     The measurement control device  100  controls the start timing of the water level measurement by the sensor device  101  based on the specified predicted timing. The measurement control device  100 , for example, determines whether or not the specified predicted timing has come, and when the specified predicted timing has come, transmits a start instruction for the water level measurement to the sensor device  101 , thereby controlling the start timing of the water level measurement by the sensor device  101 . 
     In the example in  FIG. 1 , when the predicted timing t+1 is specified, the measurement control device  100  transmits a start instruction for the water level measurement to the sensor device  101  when the predicted timing t+1 has come, and causes the sensor device  101  to start measuring the water level. Furthermore, when the predicted timing t+2 is specified, the measurement control device  100  transmits a start instruction for the water level measurement to the sensor device  101  when the predicted timing t+2 has come, and causes the sensor device  101  to start measuring the water level. 
     With this control, the measurement control device  100  can efficiently measure the water level. The measurement control device  100 , for example, can suppress adverse influence on countermeasures against flood damage by keeping the measurement of the water level stopped, and also can suppress increases in the processing load, amount of communication, and power consumption of the sensor device  101 . In addition, the measurement control device  100  can achieve the reduction of the amount of use of the storage area of the sensor device  101 . Furthermore, the measurement control device  100  can achieve the reduction of the amount of use of a storage area for storing the measurement value of the water level acquired from the sensor device  101 . For this reason, the measurement control device  100  can achieve the reduction of the workload for the maintenance management of the monitoring system. 
     The measurement control device  100 , specifically, can make the number of times the water level is measured smaller, in such a situation that there is less adverse influence on countermeasures against flood damage even without measuring the water level, according to the predicted peak value of the water level that serves as an index value for evaluating the degree of likelihood of the occurrence of flood damage. The measurement control device  100  shortens the measurement period for the water level or makes the frequency of measurement of the water level smaller to make the number of times the water level is measured smaller. 
     The sensor device  101  does not need to constantly measure the water level, and can be kept stopped from measuring the water level in such a situation that the water level does not rise above a certain level, and there is little adverse influence on countermeasures against flood damage even without measuring the water level. Then, the sensor device  101  can suppress increases in the processing load, amount of communication, and power consumption. Furthermore, the sensor device  101  can achieve the reduction of the amount of use of the storage area. 
     In a situation where it is preferable to measure the water level for the purpose of countermeasures against flood damage, the sensor device  101  can hasten the start of the water level measurement or make the frequency of measurement of the water level greater. For this reason, the sensor device  101  can allow the user to grasp a sudden rise in the water level, and the like, such that countermeasures against flood damage can be taken efficiently. Furthermore, even if a difference is produced between the prediction result for a change in water level and the actual transition result of the water level, countermeasures against flood damage can be taken efficiently with the sensor device  101 . 
     Here, the case where the measurement control device  100  predicts a change in water level has been described, but the present invention is not limited to this. For example, there may be a case where a device different from the measurement control device  100  predicts a change in water level. In this case, the measurement control device  100  acquires the prediction result for a change in water level from, for example, a device that predicted the change in water level. 
     Here, the case where the relationship between the predicted peak value and the reference value has a relationship in which the larger the predicted peak value is, the smaller the reference value is has been described, but the present invention is not limited to this. For example, there may be a case where the relationship between the predicted peak value and the reference value has a relationship in which the reference value becomes larger when the predicted peak value is zero to a certain value, and the reference value becomes smaller when the predicted peak value is larger than the certain value. 
     Here, the case where the measurement control device  100  transmits a start instruction for the water level measurement to the sensor device  101  has been described, but the present invention is not limited to this. For example, there may be a case where the measurement control device  100  transmits information indicating the specified predicted timing to the sensor device  101 , and causes the sensor device  101  to determine whether or not the specified predicted timing has come, and to start measuring the water level. 
     Example of Monitoring System  200   
     Next, an example of a monitoring system  200  to which the measurement control device  100  illustrated in  FIG. 1  is applied will be described with reference to  FIG. 2 . 
       FIG. 2  is an explanatory diagram illustrating an example of the monitoring system  200 . In  FIG. 2 , the monitoring system  200  includes the measurement control device  100 , an information accumulation device  201 , a communication relay device  202 , a wireless communication device  203 , and the sensor device  101 . 
     In the monitoring system  200 , the measurement control device  100 , the information accumulation device  201 , and the communication relay device  202  are connected via a wired or wireless network  210 . Examples of the network  210  include a local area network (LAN), a wide area network (WAN), the Internet, and the like. Furthermore, in the monitoring system  200 , the communication relay device  202  and the wireless communication device  203  are wirelessly connected. In addition, in the monitoring system  200 , the wireless communication device  203  and the sensor device  101  are connected by wire. 
     The measurement control device  100  stores various tables described later with reference to  FIGS. 4 to 8 , and controls the sensor device  101 . The measurement control device  100 , for example, predicts a change in water level by utilizing various tables described later with reference to  FIGS. 4 to 7 , and specifies the predicted peak value. For example, the measurement control device  100  calculates the reference value, specifies the predicted timing, and controls the start timing of the water level measurement by utilizing the reference value table  800  described later with reference to  FIG. 8 . The measurement control device  100  may control the frequency of measurement of the water level. The measurement control device  100  may control an end timing of measurement of the water level. Examples of the measurement control device  100  include a server, a personal computer (PC), and the like. 
     The information accumulation device  201  is a computer that stores weather information and provides the weather information to the measurement control device  100 . The information accumulation device  201  provides, for example, an actual rain amount table  600  described later with reference to  FIG. 6 , a predicted rain amount table  700  described later with reference to  FIG. 7 , and the like, to the measurement control device  100  as weather information. Examples of the information accumulation device  201  include a server, a PC, and the like. The communication relay device  202  is a computer that relays communication between the measurement control device  100  and the sensor device  101  via the wireless communication device  203 . The wireless communication device  203  is a computer that relays communication between the communication relay device  202  and the sensor device  101 . 
     The sensor device  101  is a computer that operates as a water level sensor and measures the water level at a target location. The target location corresponds to a location where the sensor device  101  is installed. The target location is, for example, a river or a sewer. The target location is, specifically, the pipe  110 . The sensor device  101  stops measuring the water level or starts measuring the water level, for example, under the control of the measurement control device  100 . Furthermore, the sensor device  101  alters the frequency of measurement of the water level, for example, under the control of the measurement control device  100 . In addition, for example, similarly to the measurement of the water level, the sensor device  101  may stop measuring an object other than the water level, start measuring an object other than the water level, or alter the frequency of measurement of an object other than the water level. The object other than the water level is, for example, the flow velocity. 
     Here, the case where the monitoring system  200  includes one sensor device  101  has been described, but the present invention is not limited to this. For example, there may be a case where the monitoring system  200  includes two or more sensor devices  101 . In this case, the monitoring system  200  may include the measurement control device  100  that controls the sensor device  101  for each sensor device  101 . 
     Here, the case where the measurement control device  100  is a device different from the information accumulation device  201  has been described, but the present invention is not limited to this. For example, there may be a case where the measurement control device  100  is operable as the information accumulation device  201 . In this case, the monitoring system  200  may not include the information accumulation device  201 . 
     Here, the case where the sensor device  101  communicates with the measurement control device  100  via the wireless communication device  203  and the communication relay device  202  has been described, but the present invention is not limited to this. For example, there may be a case where the sensor device  101  can communicate with the measurement control device  100  not via the wireless communication device  203  and the communication relay device  202 . 
     Here, the case where the measurement control device  100  predicts a change in water level, specifies the predicted peak value, calculates the reference value, specifies the predicted timing, and controls the start timing of the water level measurement has been described, but the present invention is not limited to this. For example, there may be a case where the prediction of a change in water level, the specification of the predicted peak value, the calculation of the reference value, the specification of the predicted timing, and the control of the start timing of the water level measurement are implemented by the cooperation between two or more devices in a cloud system. 
     Exemplary Hardware Configuration of Measurement Control Device  100   
     Next, an exemplary hardware configuration of the measurement control device  100  will be described with reference to  FIG. 3 . 
       FIG. 3  is a block diagram illustrating an exemplary hardware configuration of the measurement control device  100 . In  FIG. 3 , the measurement control device  100  includes a central processing unit (CPU)  301 , a memory  302 , a network interface (I/F)  303 , a recording medium I/F  304 , a recording medium  305 , and a display  306 . Furthermore, each of those components is interconnected by a bus  300 . 
     Here, the CPU  301  integrally controls the measurement control device  100 . The memory  302  includes, for example, a read only memory (ROM), a random access memory (RAM), a flash ROM, and the like. Specifically, for example, the flash ROM or the ROM stores various programs, while the RAM is used as a work area for the CPU  301 . A program stored in the memory  302  is loaded into the CPU  301  to cause the CPU  301  to execute coded processing. 
     The network I/F  303  is connected to the network  210  through a communication line, and is connected to another computer via the network  210 . Then, the network I/F  303  manages an interface between the network  210  and an inside, and controls input-output of data from another computer. For example, a modem, a LAN adapter, or the like, can be employed as the network I/F  303 . 
     The recording medium I/F  304  controls read/write of data to/from the recording medium  305  under the control of the CPU  301 . Examples of the recording medium I/F  304  include a disk drive, a solid state drive (SSD), a universal serial bus (USB) port, and the like. The recording medium  305  is a nonvolatile memory that stores data written under the control of the recording medium IF  304 . Examples of the recording medium  305  include a disk, a semiconductor memory, a USB memory, and the like. The recording medium  305  may be removably installed on the measurement control device  100 . 
     The display  306  displays data such as a document, an image, and function information, as well as a cursor, an icon or a tool box. Examples of the display  306  include a cathode ray tube (CRT), a liquid crystal display, an organic electroluminescence (EL) display, and the like. The display  306  may be, for example, a touch panel and have a function as an input device. 
     The measurement control device  100  may further include, for example, a keyboard, a mouse, a printer, a scanner, a microphone, a speaker, or the like, in addition to the components described above. Furthermore, the measurement control device  100  may include a plurality of the recording medium I/Fs  304  and the recording media  305 . In addition, it is not necessary for the measurement control device  100  to include the recording medium I/F  304  and the recording medium  305 . Besides, it is not necessary for the measurement control device  100  to include the display  306 . 
     Contents Stored in Actual Water Level Table  400   
     Next, the contents stored in an actual water level table  400  will be described with reference to  FIG. 4 . The actual water level table  400  is implemented by a storage area such as the memory  302  or the recording medium  305  of the measurement control device  100  illustrated in  FIG. 3 , for example. 
       FIG. 4  is an explanatory diagram illustrating an example of contents stored in the actual water level table  400 . As illustrated in  FIG. 4 , the actual water level table  400  has fields of a past time point and an actual water level. In the actual water level table  400 , actual water level information is stored as a record by setting information in each field for each past time point. 
     In the field of the past time point, a time point at which the sensor device  101  measured the water level in the past is set as a past time point. In the field of the actual water level, the measurement value of the water level by the sensor device  101  at the past time point is set as an actual water level. The unit of the measurement value of the water level is, for example, centimeter (cm). The unit of the measurement value of the water level may be, for example, percentage (%). 
     Contents Stored in Predicted Water Level Table  500   
     Next, the contents stored in a predicted water level table  500  will be described with reference to  FIG. 5 . The predicted water level table  500  is implemented by a storage area such as the memory  302  or the recording medium  305  of the measurement control device  100  illustrated in  FIG. 3 , for example. 
       FIG. 5  is an explanatory diagram illustrating an example of contents stored in the predicted water level table  500 . As illustrated in  FIG. 5 , the predicted water level table  500  has fields of a prediction time point and a predicted water level. In the predicted water level table  500 , predicted water level information is stored as a record by setting information in each field for each prediction time point. 
     In the field of the prediction time point, a prediction time point indicating at what time point the water level was predicted is set. In the field of the predicted water level, the predicted value of the water level at the prediction time point is set as a predicted water level. The unit of the predicted value of the water level is, for example, centimeter (cm). The unit of the predicted value of the water level may be, for example, percentage (%). 
     Contents Stored in Actual Rain Amount Table  600   
     Next, the contents stored in an actual rain amount table  600  will be described with reference to  FIG. 6 . The actual rain amount table  600  is implemented by a storage area such as the memory  302  or the recording medium  305  of the measurement control device  100  illustrated in  FIG. 3 , for example. 
       FIG. 6  is an explanatory diagram illustrating an example of contents stored in the actual rain amount table  600 . As illustrated in  FIG. 6 , the actual rain amount table  600  has fields of a past time point, a region, and an actual amount of rain. In the actual rain amount table  600 , information on the actual amount of rain is stored as a record by setting information in each field for each past time point. 
     In the field of the past time point, any time point in the past is set as a past time point. In the field of the region, information indicating any region out of a plurality of regions divided in a mesh pattern is set. In the field of the actual amount of rain, the measurement value of the amount of rain in the region at the past time point is set as an actual amount of rain. The unit of the measurement value of the amount of rain is, for example, the rainfall intensity. The unit of the measurement value of the amount of rain is, for example, millimeters per hour (mm/h). 
     Contents Stored in Predicted Rain Amount Table  700   
     Next, the contents stored in a predicted rain amount table  700  will be described with reference to  FIG. 7 . The predicted rain amount table  700  is implemented by a storage area such as the memory  302  or the recording medium  305  of the measurement control device  100  illustrated in  FIG. 3 , for example. 
       FIG. 7  is an explanatory diagram illustrating an example of contents stored in the predicted rain amount table  700 . As illustrated in  FIG. 7 , the predicted rain amount table  700  has fields of a prediction time point, a region, and a predicted amount of rain. In the predicted rain amount table  700 , information on the predicted amount of rain is stored as a record by setting information in each field for each prediction time point. 
     In the field of the prediction time point, a prediction time point indicating at what time point the amount of rain was predicted is set. In the field of the region, information indicating any region out of a plurality of regions divided in a mesh pattern is set. In the field of the predicted amount of rain, the predicted value of the amount of rain in the region at the prediction time point is set as a predicted amount of rain. The unit of the predicted value of the amount of rain is, for example, the rainfall intensity. The unit of the predicted value of the amount of rain is, for example, millimeters per hour (mm/h). 
     Contents Stored in Reference Value Table  800   
     Next, the contents stored in a reference value table  800  will be described with reference to  FIG. 8 . The reference value table  800  is implemented by a storage area such as the memory  302  or the recording medium  305  of the measurement control device  100  illustrated in  FIG. 3 , for example. 
       FIG. 8  is an explanatory diagram illustrating an example of contents stored in the reference value table  800 . As illustrated in  FIG. 8 , the reference value table  800  has fields of a category, a reference value, and an interval. In the reference value table  800 , reference value information is stored as a record by setting information in each field for each category. 
     In the field of the category, information indicating the range of the predicted peak value is set as a category. In the field of the reference value, a corresponding reference value is set in a case where the predicted peak value is contained in the range indicated by the category. In the field of the interval, a corresponding interval is set in a case where the predicted peak value is contained in the range indicated by the category. 
     Exemplary Hardware Configuration of Sensor Device  101   
     Next, an exemplary hardware configuration of the sensor device  101  will be described with reference to  FIG. 9 . 
       FIG. 9  is a block diagram illustrating an exemplary hardware configuration of the sensor device  101 . In  FIG. 9 , the sensor device  101  includes a CPU  901 , a memory  902 , a network I/F  903 , a water level sensor  904 , and a battery  905 . Furthermore, each of those components is interconnected by a bus  900 . 
     Here, the CPU  901  integrally controls the sensor device  101 . The memory  902  includes, for example, a ROM, a RAM, a flash ROM, and the like. Specifically, for example, the flash ROM or the ROM stores various programs, while the RAM is used as a work area for the CPU  901 . A program stored in the memory  902  is loaded into the CPU  901  to cause the CPU  901  to execute coded processing. 
     The network I/F  903  is connected to the wireless communication device  203  through a communication line, and is connected to another computer via the wireless communication device  203 . Then, the network I/F  903  manages an interface between the wireless communication device  203  and an inside, and controls input-output of data from another computer. For example, a modem, a LAN adapter, or the like, can be employed as the network I/F  903 . 
     The water level sensor  904  measures the water level. The water level sensor  904  is, for example, a pressure sensor, and measures the water level by utilizing the fact that the water amount grows as the water level is heightened and the pressure applied to the water level sensor  904  grows. The water level sensor  904  may include, for example, a light emitting unit and a light receiving unit, so as to measure the water level by measuring the distance to the water surface. The battery  905  supplies electric power as a driving power supply for each unit of the sensor device  101 . The battery  905  may include a harvester so as to be capable of generating power based on a change in energy of the external environment at a location where the sensor device  101  is installed. Examples of the external environment include light, vibration, temperature, a radio wave, and the like. Furthermore, the sensor device  101  may include a sensor that measures an object other than the water level. 
     Exemplary Hardware Configuration of Information Accumulation Device  201   
     The exemplary hardware configuration of the information accumulation device  201  is similar to the exemplary hardware configuration of the measurement control device  100  illustrated in  FIG. 3 , and thus the description will be omitted. 
     Exemplary Functional Configuration of Measurement Control Device  100   
     Next, an exemplary functional configuration of the measurement control device  100  will be described with reference to  FIG. 10 . 
       FIG. 10  is a block diagram illustrating an exemplary functional configuration of the measurement control device  100 . The measurement control device  100  includes a storage unit  1000 , an acquisition unit  1001 , a learning unit  1002 , a prediction unit  1003 , a setting unit  1004 , and an output unit  1005 . 
     For example, the storage unit  1000  is implemented by a storage area such as the memory  302  or the recording medium  305  illustrated in  FIG. 3 . Hereinafter, the case where the storage unit  1000  is included in the measurement control device  100  will be described, but the present invention is not limited to this. For example, there may be a case where the storage unit  1000  is included in a device different from the measurement control device  100 , and the contents stored in the storage unit  1000  can be referred to from the measurement control device  100 . 
     The acquisition unit  1001  to the output unit  1005  are functions to be a controller. Specifically, for example, the acquisition unit  1001  to the output unit  1005  implement functions thereof by causing the CPU  301  to execute a program stored in the storage area such as the memory  302  or the recording medium  305  illustrated in  FIG. 3 , or by the network I/F  303 . A processing result of each functional unit is stored in the storage area such as the memory  302  or the recording medium  305 , illustrated in  FIG. 3 , for example. 
     The storage unit  1000  stores various types of information used for processing of each functional unit. The storage unit  1000  stores various types of information referred to or updated in processing of each functional unit. The storage unit  1000  may store the measurement value of the water level, the predicted value of the water level, and the like. The water level is represented, for example, by a length from the bottom to the water surface at the target location. The water level may be represented, for example, by the pipe fullness rate. The storage unit  1000  may store, for example, the actual water level table  400  illustrated in  FIG. 4 , the predicted water level table  500  illustrated in  FIG. 5 , and the like. The storage unit  1000  may store the measurement value of the amount of rain, the predicted value of the amount of rain, and the like. The storage unit  1000  may store, for example, the actual rain amount table  600  illustrated in  FIG. 6 , the predicted rain amount table  700  illustrated in  FIG. 7 , and the like. 
     The storage unit  1000  may store correspondence information representing a relationship between the predicted peak value and a first reference value. The predicted peak value is the maximum value among the predicted values of the water level for a certain period. The first reference value is a reference value of the water level at which the measurement of the water level is started. The correspondence information represents, for example, that the larger the predicted peak value is, the lower the first reference value is. The correspondence information is, specifically, a mathematical expression representing a relationship between the predicted peak value and the first reference value. 
     Specifically, the correspondence information may be information in which, among a plurality of ranges that do not overlap each other, a range with a relatively smaller upper limit value is associated with a relatively larger first reference value. The upper limit value of each of the plurality of ranges is a value that is at least larger than the maximum value of the measurement value of the water level in fine weather or cloudy weather. The storage unit  1000  may store, for example, the reference value table  800  illustrated in  FIG. 8 . 
     The storage unit  1000  may store correspondence information representing a relationship between the predicted peak value and a second reference value. The second reference value is a reference value of the water level at which the measurement of the water level is ended. The first reference value and the second reference value may be the same. The correspondence information represents, for example, that the larger the predicted peak value is, the lower the second reference value is. The correspondence information is, specifically, a mathematical expression representing a relationship between the predicted peak value and the second reference value. 
     Specifically, the correspondence information may be information in which, among a plurality of ranges that do not overlap each other, a range with a relatively smaller upper limit value is associated with a relatively larger second reference value. The upper limit value of each of the plurality of ranges is a value that is at least larger than the maximum value of the measurement value of the water level in fine weather or cloudy weather. The storage unit  1000  may store, for example, the reference value table  800  illustrated in  FIG. 8 . 
     The storage unit  1000  may store correspondence information representing a relationship between the predicted peak value and the frequency of measurement. The frequency of measurement is a frequency at which the water level is measured. The frequency is the number of times the water level is measured per unit time. The frequency of measurement may be represented by a measurement interval. The correspondence information represents, for example, that the larger the predicted peak value is, the greater the frequency of measurement is. The correspondence information is, specifically, a mathematical expression representing a relationship between the predicted peak value and the frequency of measurement. 
     Specifically, the correspondence information may be information in which, among a plurality of ranges that do not overlap each other, a range with a relatively smaller upper limit value is associated with a relatively larger measurement interval indicating a relatively smaller frequency of measurement. The upper limit value of each of the plurality of ranges is a value that is at least larger than the maximum value of the measurement value of the water level in fine weather or cloudy weather. The storage unit  1000  may store, for example, the reference value table  800  illustrated in  FIG. 8 . 
     The storage unit  1000  may store rules for learning a prediction model. The prediction model is a model representing a relationship between the water level and the amount of rain. The prediction model is, for example, a mathematical expression model. The mathematical expression model is, for example, a function representing a relationship between the water level and the amount of rain. The prediction model is used, for example, to predict a change in water level. The storage unit  1000  may store the learned prediction model. 
     The acquisition unit  1001  outputs various types of information used for processing of each functional unit to each functional unit. The acquisition unit  1001  may acquire, for example, various types of information used for processing of each functional unit from the storage unit  1000 , and output the acquired information to each functional unit. The acquisition unit  1001  may acquire, for example, various types of information used for processing of each functional unit from a device different from the measurement control device  100 , and output the acquired information to each functional unit. 
     The learning unit  1002  learns the prediction model. The learning unit  1002  learns the prediction model based on, for example, past water level and amount of rain. The learning unit  1002  learns, as a prediction model, a mathematical expression model that calculates a water level at a first time point by multiplying the amount of rain in one or more regions at one or more time points before the first time point by a coefficient and summing up the results, by machine learning. Consequently, the learning unit  1002  can make the water level predictable with reference to the prediction model. 
     The prediction unit  1003  predicts a change in water level. The prediction unit  1003  predicts a change in water level based on, for example, the predicted value of the amount of rain with reference to the prediction model learned by the learning unit  1002 . Specifically, the prediction unit  1003  calculates a predicted value of the water level at each time point out of one or more time points within a certain period, and stores the calculated predicted value using the predicted water level table  500 . 
     The prediction unit  1003  may predict a change in water level based on, for example, the measurement value of the amount of rain with reference to the prediction model learned by the learning unit  1002 . The prediction unit  1003  may predict a change in water level based on, for example, the measurement value of the amount of rain and the predicted value of the amount of rain with reference to the prediction model learned by the learning unit  1002 . 
     The prediction unit  1003  specifies the predicted peak value of the water level based on the prediction result for a change in water level. The prediction unit  1003  specifies, for example, the maximum value among the predicted values of the water level at respective time points of one or more time points stored in the predicted water level table  500 , as the predicted peak value of the water level. Consequently, the prediction unit  1003  can specify the predicted peak value of the water level that serves an index value for evaluating the degree of likelihood of the occurrence of flood damage, and can allow the specified predicted peak value to be utilized for controlling the measurement of the water level by the sensor device  101 . 
     The setting unit  1004  calculates the first reference value of the water level according to the specified predicted peak value. For example, the setting unit  1004  calculates the first reference value such that the larger the predicted peak value is, the lower the first reference value is. Specifically, the setting unit  1004  calculates the first reference value associated with a range containing the specified predicted peak value, based on the correspondence information stored in the storage unit  1000 . 
     Consequently, the setting unit  1004  can hasten the start timing at which the measurement of the water level is started, as flood damage is more likely to occur. Furthermore, the setting unit  1004  can delay the start timing at which the measurement of the water level is started, as flood damage is less likely to occur. 
     The setting unit  1004  calculates the second reference value of the water level according to the specified predicted peak value. For example, the setting unit  1004  calculates the second reference value such that the larger the predicted peak value is, the lower the second reference value is. Specifically, the setting unit  1004  calculates the second reference value associated with a range containing the specified predicted peak value, based on the correspondence information stored in the storage unit  1000 . 
     Consequently, the setting unit  1004  can delay the end timing at which the measurement of the water level is ended, as flood damage is more likely to occur. Furthermore, the setting unit  1004  can hasten the end timing at which the measurement of the water level is ended, as flood damage is less likely to occur. 
     The setting unit  1004  specifies a predicted timing at which the water level is predicted to reach the calculated first reference value, based on the prediction result. Then, the setting unit  1004  controls the start timing of the water level measurement by the sensor device  101  based on the specified predicted timing. 
     The setting unit  1004 , for example, monitors whether or not the predicted timing has passed, and in response to the predicted timing having passed, transmits a start instruction for the water level measurement to the sensor device  101 , thereby controlling the start timing of the water level measurement by the sensor device  101 . For example, by transmitting the predicted timing to the sensor device  101 , the setting unit  1004  may cause the sensor device  101  to monitor whether or not the predicted timing has passed, and to start measuring the water level in response to the predicted timing having passed. 
     Consequently, the setting unit  1004  can start measuring the water level earlier as flood damage is more likely to occur, such that countermeasures against flood damage can be taken efficiently. Furthermore, the setting unit  1004  can start measuring the water level later as flood damage is less likely to occur, and thus can achieve the reduction of the processing load, amount of communication, and power consumption of the sensor device  101 . 
     The setting unit  1004  controls the end timing of the water level measurement by the sensor device  101  based on the measurement value of the water level by the sensor device  101 . The setting unit  1004  controls the end timing based on, for example, a timing at which the measurement value falls below the calculated second reference value. 
     Specifically, the setting unit  1004  acquires the measurement value of the water level from the sensor device  101  every time the water level is measured by the sensor device  101 . The setting unit  1004  determines whether or not the acquired measurement value of the water level has fallen below the second reference value, and in response to the measurement value having fallen below the second reference value, transmits an end instruction for the water level measurement to the sensor device  101 , thereby controlling the end timing of the water level measurement by the sensor device  101 . Specifically, by transmitting the second reference value to the sensor device  101 , the setting unit  1004  may cause the sensor device  101  to monitor whether or not the measurement value of the water level has fallen below the second reference value, and to end measuring the water level in response to the measurement value having fallen below the second reference value. 
     Consequently, the setting unit  1004  can end measuring the water level later as flood damage is more likely to occur, such that countermeasures against flood damage can be taken efficiently. Furthermore, the setting unit  1004  can end measuring the water level earlier as flood damage is less likely to occur, and thus can achieve the reduction of the processing load, amount of communication, and power consumption of the sensor device  101 . 
     The setting unit  1004  controls the frequency of measurement of the water level by the sensor device  101  according to the specified predicted peak value. For example, the setting unit  1004  makes the frequency of measurement of the water level by the sensor device  101  higher as the predicted peak value is larger. Specifically, the setting unit  1004  calculates a measurement interval associated with a range containing the specified predicted peak value, based on the correspondence information stored in the storage unit  1000 . Then, the setting unit  1004  controls the frequency of measurement of the water level by the sensor device  101  by transmitting the calculated measurement interval to the sensor device  101 . 
     Consequently, the setting unit  1004  can make the frequency of measurement of the water level greater as flood damage is more likely to occur, such that countermeasures against flood damage can be taken efficiently. Furthermore, the setting unit  1004  can make the frequency of measurement of the water level smaller as flood damage is less likely to occur, and thus can achieve the reduction of the processing load, amount of communication, and power consumption of the sensor device  101 . 
     The setting unit  1004  may calculate the predicted power consumption of the sensor device  101  based on statistical information on a change in water level during a certain period. Consequently, the setting unit  1004  can allow the user to grasp the power consumption of the sensor device  101 , and can facilitate the user to decide the maintenance management schedule for the monitoring system  200 . 
     The output unit  1005  transmits various types of information to the sensor device  101  under the control of the setting unit  1004 . The output unit  1005  transmits, for example, the start instruction to the sensor device  101 . The output unit  1005  may transmit, to the sensor device  101 , a predicted timing at which the water level is predicted to reach the first reference value, for example. The output unit  1005  transmits, for example, the end instruction to the sensor device  101 . The output unit  1005  may transmit the second reference value to the sensor device  101 , for example. The output unit  1005  transmits, for example, the measurement interval to the sensor device  101 . 
     The output unit  1005  may output the processing result of each functional unit. The output is implemented as display on a display, print output to a printer, transmission to an external device by the network I/F  303 , or storage to the storage area such as the memory  302  and the recording medium  305 , for example. The output unit  1005  may output, for example, the calculated predicted power consumption. Consequently, the output unit  1005  can allow the user to be notified of the processing result of each functional unit, and can support the management and administration of the measurement control device  100 , such as updating the set value of the measurement control device  100 , for example, whereby the improvement in convenience of the measurement control device  100  can be achieved. 
     Here, the case where the setting unit  1004  controls the start timing of the water level measurement by the sensor device  101 , the end timing of the water level measurement by the sensor device  101 , and the frequency of measurement of the water level by the sensor device  101  has been described, but the present invention is not limited to this. For example, there may be a case where the setting unit  1004  does not control any of the start timing of the water level measurement by the sensor device  101 , the end timing of the water level measurement by the sensor device  101 , and the frequency of measurement of the water level by the sensor device  101 . 
     Here, the case where the measurement control device  100  includes the acquisition unit  1001  to the output unit  1005  has been described, but the present invention is not limited to this. For example, there may be a case where the measurement control device  100  does not include the learning unit  1002 , and acquires the prediction model from a device different from the measurement control device  100 . Furthermore, there may be a case where the measurement control device  100  does not include the learning unit  1002  and the prediction unit  1003 , and acquires the prediction result for the water level from a device different from the measurement control device  100 . 
     Example of Predicting Change in Water Level 
     Next, an operation example of the monitoring system  200  will be described with reference to  FIGS. 11 to 21 . First, an example in which the measurement control device  100  predicts a change in water level will be described with reference to  FIGS. 11 and 12 . 
       FIGS. 11 and 12  are explanatory diagrams illustrating an example of predicting a change in water level. In  FIG. 11 , the measurement control device  100  learns a prediction model  1100  used to predict a change in the water level of the pipe  110 . The prediction model  1100  is, for example, a mathematical expression model representing a relationship between the water level of the pipe  110  and the amount of rain in one or more regions at one or more time points. The measurement control device  100  learns the prediction model  1100  with reference to, for example, the actual water level table  400 , the actual rain amount table  600 , and the predicted rain amount table  700 . 
     Specifically, the measurement control device  100  analyzes, by machine learning, which region has the amount of rain that affects the water level of the pipe  110  at a time point t, and which time point before the time point t has the amount of rain that affects the water level of the pipe  110  at the time point t, for example. The region whose amount of rain affects the water level of the pipe  110  is, for example, at least any one region out of a region where the pipe  110  is located, a region where a pipe laid upstream of the pipe  110  is located, and the like. 
     Then, based on the analysis result, the measurement control device  100  creates a mathematical expression model that predicts the water level of the pipe  110  at the time point t based on the amounts of rain in several regions at time points t−1, t−2, . . . , and t−n. Consequently, the measurement control device  100  can make a change in water level predictable. Furthermore, the measurement control device  100  may periodically re-create the mathematical expression model to achieve the improvement in accuracy of predicting a change in water level. 
     Here, the case where the measurement control device  100  refers to the actual water level table  400 , the actual rain amount table  600 , and the predicted rain amount table  700  has been described, but the present invention is not limited to this. For example, there may be a case where the measurement control device  100  does not refer to the actual rain amount table  600 . Furthermore, for example, there may be a case where the measurement control device  100  does not refer to the predicted rain amount table  700 . Next, description of  FIG. 12  will be made. 
     In  FIG. 12 , the measurement control device  100  periodically predicts a change in water level for a certain period thereafter. For example, based on the actual rain amount table  600  and the predicted rain amount table  700 , the measurement control device  100  refers to the prediction model  1100  to predict a change in water level at each time point t+i within a certain period, and stores results of the prediction using the predicted water level table  500 . The reference sign i denotes a natural number equal to or larger than one. 
     Specifically, the measurement control device  100  refers to the mathematical expression model, and calculates the water level at the time point t+i based on the predicted water levels in one or more regions at the time points t+1, t+2, . . . , and t+i, and the actual water levels in one or more regions at the time points t−j, t−j+1, . . . , and t. Consequently, the measurement control device  100  can predict a change in water level for a certain period thereafter, and can enable the specification of the predicted peak value of the water level that serves as an index value for evaluating the degree of likelihood of the occurrence of flood damage. 
     Here, the case where the measurement control device  100  predicts the water level based on the predicted water level and the actual water level has been described, but the present invention is not limited to this. For example, there may be a case where the measurement control device  100  predicts the water level based on the actual water level without using the predicted water level. Furthermore, for example, there may be a case where the measurement control device  100  predicts the water level based on the predicted water level without using the actual water level. 
     Example of Designating Threshold Value and Measurement Interval 
     Next, an example in which the measurement control device  100  designates a threshold value and the measurement interval based on the prediction result for a change in water level will be described with reference to  FIGS. 13 to 17 . 
       FIGS. 13 to 17  are explanatory diagrams illustrating an example of designating the threshold value and the measurement interval. In  FIG. 13 , the measurement control device  100  stores the function of a threshold value curve  1300  as correspondence information representing a relationship between the predicted peak value of the water level and the threshold value. The threshold value corresponds to the first reference value that causes the sensor device  101  to start measuring the water level. The threshold value also corresponds to the second reference value that causes the sensor device  101  to end measuring the water level. The function of the threshold value curve  1300  is specified by the user, for example, and stored in the measurement control device  100 . 
     Based on the function of the threshold value curve  1300 , the measurement control device  100  calculates a threshold value corresponding to the predicted peak value of the water level specified from the prediction result for a change in water level for a certain period. For example, when the predicted peak value p 1  in Case 1 is specified, the measurement control device  100  calculates a comparably large threshold value. On the other hand, for example, when the predicted peak value p 2  in Case 2 is specified, the measurement control device  100  calculates a comparably small threshold value. 
     Consequently, the measurement control device  100  can hasten the start timing at which the measurement of the water level is started, as the predicted peak value is larger and flood damage is more likely to occur, such that countermeasures against flood damage can be taken efficiently. Furthermore, the measurement control device  100  can delay the start timing at which the measurement of the water level is started, as the predicted peak value is smaller and flood damage is less likely to occur, and thus can achieve the reduction of the processing load, amount of communication, and power consumption of the sensor device  101 . 
     Here, the case where the threshold value curve  1300  has a curve to the lower right has been described, but the present invention is not limited to this. For example, the threshold value curve  1300  may have a curve in which the threshold value is given as a comparably large constant value in a range where the predicted peak value is smaller than a predetermined value, and the threshold value becomes smaller once the predicted peak value falls within a range where predicted peak value is larger than the predetermined value. Consequently, the measurement control device  100  can achieve the reduction of the processing load, amount of communication, and power consumption of the sensor device  101  while the predicted peak value is smaller than the predetermined value and the likelihood of the occurrence of flood damage is equal to or less than a certain value. 
     Furthermore, for example, the threshold value curve  1300  may have a curve in which the threshold value becomes larger from when the predicted peak value is zero until becoming a predetermined value, and the threshold value becomes smaller once the predicted peak value becomes larger than the predetermined value. Consequently, the measurement control device  100  can achieve the reduction of the processing load, amount of communication, and power consumption of the sensor device  101  while the predicted peak value is smaller than the predetermined value and the likelihood of the occurrence of flood damage is equal to or less than a certain value. Next, description of  FIG. 14  will be made. 
     In  FIG. 14 , the measurement control device  100  stores the function of a measurement interval curve  1400  as correspondence information representing a relationship between the predicted peak value of the water level and the measurement interval. The measurement interval is a set value for controlling the frequency of measurement of the water level of the sensor device  101 . The function of the measurement interval curve  1400  is specified by the user, for example, and stored in the measurement control device  100 . 
     Based on the function of the measurement interval curve  1400 , the measurement control device  100  calculates a measurement interval corresponding to the predicted peak value of the water level specified from the prediction result for a change in water level for a certain period. For example, when the predicted peak value p 1  in Case 1 is specified, the measurement control device  100  calculates a comparably large measurement interval. On the other hand, for example, when the predicted peak value p 2  in Case 2 is specified, the measurement control device  100  calculates a comparably small measurement interval. 
     Consequently, the measurement control device  100  can make the frequency of measurement of the water level greater as the predicted peak value is larger and flood damage is more likely to occur, such that countermeasures against flood damage can be taken efficiently. Furthermore, the measurement control device  100  can make the frequency of measurement of the water level smaller as the predicted peak value is smaller and flood damage is less likely to occur, and thus can achieve the reduction of the processing load, amount of communication, and power consumption of the sensor device  101 . 
     Here, the case where the measurement interval curve  1400  has a curve to the lower right has been described, but the present invention is not limited to this. For example, the measurement interval curve  1400  may have a curve in which the measurement interval is given as a comparably large constant value in a range where the predicted peak value is smaller than a predetermined value, and the measurement interval becomes smaller once the predicted peak value falls within a range where predicted peak value is larger than the predetermined value. Consequently, the measurement control device  100  can achieve the reduction of the processing load, amount of communication, and power consumption of the sensor device  101  while the predicted peak value is smaller than the predetermined value and the likelihood of the occurrence of flood damage is equal to or less than a certain value. 
     Furthermore, for example, the measurement interval curve  1400  may have a curve in which the measurement interval becomes larger from when the predicted peak value is zero until becoming a predetermined value, and the measurement interval becomes smaller once the predicted peak value becomes larger than the predetermined value. Consequently, the measurement control device  100  can achieve the reduction of the processing load, amount of communication, and power consumption of the sensor device  101  while the predicted peak value is smaller than the predetermined value and the likelihood of the occurrence of flood damage is equal to or less than a certain value. 
     In the examples in  FIGS. 13 and 14 , the case where the measurement control device  100  designates the threshold value and the measurement interval based on the function of the threshold value curve  1300  and the function of the measurement interval curve  1400  has been described, but the present invention is not limited to this. For example, there is a case where it is difficult for the user to specify the function of the threshold value curve  1300  or the function of the measurement interval curve  1400  in advance. In this case, the measurement control device  100  designates the threshold value and the measurement interval, as described later with reference to  FIGS. 15 to 17 . 
     In  FIG. 15 , the user sets a plurality of water level categories with reference to a graph  1500  containing past measurement values and predicted values of the water level. In the example in  FIG. 15 , the user sets a category (low) of a water level with a pipe fullness rate of 0% or more and less than 33%, a category (medium) of a water level with a pipe fullness rate of 33% or more and less than 67%, and a category (high) of a water level with a pipe fullness rate of 67% or more. The pipe fullness rate is a ratio of the water level of the pipe  110  to a water level at which the pipe  110  is fully filled with water. 
     Then, the user creates correspondence information in which the threshold value and the measurement interval are associated with each other for each water level category, and causes the measurement control device  100  to store the created correspondence information as the reference value table  800 . The user creates correspondence information in which, for example, a category with a larger upper limit value is associated with a threshold value with a larger value and a measurement interval with a larger value. Next, description of  FIGS. 16 and 17  will be made; an example of designating a threshold value and a measurement interval based on the reference value table  800  will be described. 
     In  FIG. 16 , the measurement control device  100  calculates a threshold value corresponding to a predicted peak value of the water level specified from the prediction result for a change in water level for a certain period, based on a correspondence  1600  between the predicted peak value of the water level and the threshold value represented by the reference value table  800 . 
     For example, when the predicted peak value p 1  in Case 1 is specified, the measurement control device  100  calculates a comparably large threshold value corresponding to the category (low) containing the predicted peak value p 1 . On the other hand, for example, when the predicted peak value p 2  in Case 2 is specified, the measurement control device  100  calculates a comparably small threshold value corresponding to the category (high) containing the predicted peak value p 2 . 
     Consequently, the measurement control device  100  can hasten the start timing at which the measurement of the water level is started, as the predicted peak value is larger and flood damage is more likely to occur, such that countermeasures against flood damage can be taken efficiently. Furthermore, the measurement control device  100  can delay the start timing at which the measurement of the water level is started, as the predicted peak value is smaller and flood damage is less likely to occur, and thus can achieve the reduction of the processing load, amount of communication, and power consumption of the sensor device  101 . Next, description of  FIG. 17  will be made. 
     In  FIG. 17 , the measurement control device  100  calculates a measurement interval corresponding to a predicted peak value of the water level specified from the prediction result for a change in water level for a certain period, based on a correspondence  1700  between the predicted peak value of the water level and the measurement interval represented by the reference value table  800 . 
     For example, when the predicted peak value p 1  in Case 1 is specified, the measurement control device  100  calculates a comparably large measurement interval corresponding to the category (low) containing the predicted peak value p 1 . On the other hand, for example, when the predicted peak value p 2  in Case 2 is specified, the measurement control device  100  calculates a comparably small measurement interval corresponding to the category (high) containing the predicted peak value p 2 . 
     Consequently, the measurement control device  100  can make the frequency of measurement of the water level greater as the predicted peak value is larger and flood damage is more likely to occur, such that countermeasures against flood damage can be taken efficiently. Furthermore, the measurement control device  100  can make the frequency of measurement of the water level smaller as the predicted peak value is smaller and flood damage is less likely to occur, and thus can achieve the reduction of the processing load, amount of communication, and power consumption of the sensor device  101 . 
     In  FIG. 15 , the user may consider that the importance of the water level in fine weather or cloudy weather is lower for the purpose of countermeasures against flood damage, and thus may make the upper limit value of the category (low) at least larger than the maximum value of the measurement value of the water level in fine weather or cloudy weather. Consequently, the user can achieve the reduction of the processing load, amount of communication, and power consumption of the sensor device  101 . 
     In addition, in a case where, for example, the predicted value is comparably small but flood damage is more likely to occur as a result of referring to the graph  1500  because a difference between the measurement value and the predicted value is larger, and the measurement value tends to be larger than the predicted value, the user may make the lower limit value of the category (high) smaller. Consequently, the user can facilitate monitoring of the occurrence of flood damage, and can achieve the improvement in efficiency of countermeasures against flood damage. 
     Furthermore, the user may refer to past measurement values and the like of the water level in the graph  1500  to perform approximation using the Poisson distribution and calculate the probability that the measurement value of the water level belongs to each of the water level categories, and may calculate the number of times of measurement for a long term. Consequently, the user can predict long-term processing load, amount of communication, power consumption, and the like of the sensor device  101 , and can facilitate the maintenance management of the monitoring system  200 . 
     Example of Controlling Sensor Device  101   
     Next, an example in which the measurement control device  100  controls the sensor device  101  based on the threshold value and the measurement interval designated in  FIGS. 13 to 17  will be described with reference to  FIGS. 18 and 19 . 
       FIGS. 18 and 19  are explanatory diagrams illustrating an example of controlling the sensor device  101 . The example in  FIG. 18  corresponds to an example of a case where the measurement control device  100  calculates a threshold value and a measurement interval corresponding to the category (low) containing the predicted peak value p 1  in Case 1. In  FIG. 18 , the measurement control device  100  can delay the start of measurement because the threshold value is comparably large, can make the frequency of measurement smaller because the measurement interval is comparably large, and can hasten the end of measurement because the threshold value is comparably large. 
     In this manner, in Case 1 in which it is deemed that the predicted peak value is comparably small and the importance in countermeasures against flood damage is comparably low, the measurement control device  100  can achieve the reduction of the processing load, amount of communication, and power consumption of the sensor device  101 . Furthermore, even if the start of measurement is delayed and the frequency of measurement is made smaller, the measurement control device  100  can suppress adverse influence on countermeasures against flood damage. Next, description of  FIG. 19  will be made. 
     The example in  FIG. 19  corresponds to an example of a case where the measurement control device  100  calculates a threshold value and a measurement interval corresponding to the category (high) containing the predicted peak value p 2  in Case 2. In  FIG. 19 , the measurement control device  100  can hasten the start of measurement because the threshold value is comparably small, can make the frequency of measurement greater because the measurement interval is comparably small, and can delay the end of measurement because the threshold value is comparably small. 
     In this manner, in Case 2 in which it is deemed that the predicted peak value is comparably large and the importance in countermeasures against flood damage is comparably high, the measurement control device  100  can hasten the start of measurement and make the frequency of measurement greater. For this reason, the measurement control device  100  can facilitate the user to grasp a timing at which the water level rises, a speed at which the water level rises, and the like, and can allow countermeasures against flood damage to be efficiently carried out. 
     Furthermore, the measurement control device  100  can facilitate the user to grasp a change in measurement value of the water level around a timing at which the water level matches the peak value, and can allow countermeasures against flood damage to be efficiently carried out. In addition, the measurement control device  100  can facilitate the user to grasp a change in measurement value of the water level from immediately after the water level begins to rise until immediately before the water level is completely decreased, and can allow information useful for future countermeasures against flood damage to be utilized easily. 
     Example of Displaying Screen 
     Next, an example in which the measurement control device  100  displays a screen when controlling the sensor device  101  as in  FIG. 19  will be described with reference to  FIGS. 20 and 21 . 
       FIGS. 20 and 21  are explanatory diagrams illustrating an example of displaying a screen. The measurement control device  100  controls the sensor device  101 , and causes the display contents of the screen of the display  306  to shift every time the measurement value of the water level is acquired from the sensor device  101 . 
     In  FIG. 20 , the measurement control device  100  displays a screen  2000 , for example, when acquiring the measurement value of the water level at a time point t 20 . The screen  2000  displays, for example, a dotted line representing a change in predicted value of the water level, a white circle representing the measurement value of the water level, and a solid line representing a change in measurement value of the water level. Furthermore, the screen  2000  may display the designated threshold value or the measurement start point. 
     With this display, when it is deemed that flood damage is highly likely to occur, the user can begin to grasp a change in water level immediately after the water level begins to rise, and can grasp the magnitude of a difference between the measurement value of the water level and the predicted value of the water level. Therefore, when the measurement value of the water level is larger than the predicted value of the water level and it is considered that flood damage is more likely to occur than the prediction result, the user is allowed to carry out countermeasures against flood damage at an early stage. Next, description of  FIG. 21  will be made. 
     In  FIG. 21 , the measurement control device  100  displays a screen  2100 , for example, when acquiring the measurement value of the water level at a time point t 21 . The screen  2100  displays, for example, a dotted line representing a change in predicted value of the water level, a white circle representing the measurement value of the water level, and a solid line representing a change in measurement value of the water level. Furthermore, the screen  2100  may display the designated threshold value or the measurement start point. 
     With this display, when it is deemed that flood damage is highly likely to occur, the user can grasp a change in measurement value of the water level around a timing at which the water level matches the peak value, such that countermeasures against flood damage can be allowed to be carried out efficiently. The user can grasp, for example, whether or not the pipe  110  is fully filled with water, or can grasp the length of a period during which the pipe  110  is kept fully filled with water. In addition, the user can grasp a change in measurement value of the water level from immediately after the water level begins to rise until immediately before the water level is completely decreased, and can make use of the grasped change for future countermeasures against flood damage. 
     Overall Processing Procedure 
     Next, an example of an overall processing procedure executed by the measurement control device  100  will be described with reference to  FIG. 22 . The overall processing is implemented by, for example, the CPU  301 , a storage area such as the memory  302  and the recording medium  305 , and the network I/F  303  illustrated in  FIG. 3 . 
       FIG. 22  is a flowchart illustrating an example of an overall processing procedure. In  FIG. 22 , first, the measurement control device  100  acquires the actual rain amount table  600  (Step S 2201 ). Next, the measurement control device  100  acquires the predicted rain amount table  700  (Step S 2202 ). Then, the measurement control device  100  refers to the prediction model based on the acquired actual rain amount table  600  and predicted rain amount table  700  to predict a change in water level at a place where the sensor device  101  is installed (Step S 2203 ). 
     Next, the measurement control device  100  calculates the predicted peak value of the water level based on the prediction result for a change in water level (Step S 2204 ). Then, based on the reference value table  800 , the measurement control device  100  acquires a start threshold value, an end threshold value, and the frequency of the water level measurement associated with a category to which the calculated predicted peak value of the water level belongs (Step S 2205 ). 
     Next, the measurement control device  100  determines whether or not a timing at which the predicted value of the water level exceeds the acquired start threshold value has passed, based on the prediction result for the water level (Step S 2206 ). Here, when the timing has not passed (Step S 2206 : No), the measurement control device  100  returns to the processing in Step S 2206 . On the other hand, when the timing has passed (Step S 2206 : Yes), the measurement control device  100  proceeds to the processing in Step S 2207 . 
     In Step S 2207 , the measurement control device  100  causes the sensor device  101  to measure the water level in line with the acquired frequency of the water level measurement, and acquires the measurement value of the water level from the sensor device  101  (Step S 2207 ). 
     Next, the measurement control device  100  determines whether or not the measurement value of the water level is equal to or less than the acquired end threshold value (Step S 2208 ). Here, when the measurement value is not equal to or less than the end threshold value (Step S 2208 : No), the measurement control device  100  returns to the processing in Step S 2207 . On the other hand, when the measurement value is equal to or less than the end threshold value (Step S 2208 : Yes), the measurement control device  100  proceeds to the processing in Step S 2209 . 
     In Step S 2209 , the measurement control device  100  causes the sensor device  101  to end measuring the water level (Step S 2209 ). Then, the measurement control device  100  proceeds to the processing in Step S 2201 . With this procedure, the measurement control device  100  can cause the sensor device  101  to efficiently measure the water level. 
     As described above, according to the measurement control device  100 , the predicted peak value of the water level can be specified based on the prediction result for a change in water level, and the first reference value of the water level at which the measurement of the water level is started can be calculated according to the specified predicted peak value. According to the measurement control device  100 , the predicted timing at which the water level is predicted to reach the calculated first reference value can be specified based on the prediction result, and the start timing of the water level measurement by the sensor device  101  can be controlled based on the specified predicted timing. 
     Consequently, the measurement control device  100  can control the start timing of the water level measurement according to the predicted peak value of the water level that serves as an index value for evaluating the degree of likelihood of the occurrence of flood damage, and can allow the improvement in efficiency of the water level measurement to be achieved. For this reason, the measurement control device  100  can allow the improvement in efficiency of countermeasures against flood damage, or the reduction of the processing load, amount of communication, and power consumption of the sensor device  101  to be achieved. 
     According to measurement control device  100 , the first reference value can be calculated such that the larger the predicted peak value is, the lower the first reference value is. Consequently, the measurement control device  100  can hasten the start timing at which the measurement of the water level is started, as flood damage is more likely to occur, such that countermeasures against flood damage can be taken efficiently. Furthermore, the measurement control device  100  can delay the start timing at which the measurement of the water level is started, as flood damage is less likely to occur, and thus can achieve the reduction of the processing load, amount of communication, and power consumption of the sensor device  101 . 
     According to the measurement control device  100 , the frequency of measurement of the water level by the sensor device  101  can be made higher as the predicted peak value is larger. Consequently, the measurement control device  100  can make the frequency of measurement of the water level greater as flood damage is more likely to occur, such that countermeasures against flood damage can be taken efficiently. In addition, the measurement control device  100  can make the frequency of measurement of the water level smaller as flood damage is less likely to occur, and thus can achieve the reduction of the processing load, amount of communication, and power consumption of the sensor device  101 . 
     According to the measurement control device  100 , based on correspondence information in which, among a plurality of ranges that do not overlap each other, a range with a relatively smaller upper limit value is associated with a relatively larger first reference value, a first reference value associated with a range containing the specified predicted peak value can be calculated. Consequently, the measurement control device  100  can allow the first reference value to be calculated without specifying a function representing a relationship between the predicted peak value and the first reference value. 
     According to measurement control device  100 , the upper limit value of each of the plurality of ranges can be set to a value that is at least larger than the maximum value of the measurement value of the water level in fine weather or cloudy weather. Consequently, the measurement control device  100  can delay the start timing at which the measurement of the water level is started, as flood damage is less likely to occur, and thus can efficiently reduce the processing load, amount of communication, and power consumption of the sensor device  101 . 
     According to the measurement control device  100 , the end timing of the water level measurement by the sensor device  101  can be controlled based on the measurement value of the water level by the sensor device  101 . Consequently, the measurement control device  100  can delay the end timing at which the measurement of the water level is ended, as flood damage is more likely to occur, such that countermeasures against flood damage can be taken efficiently. Furthermore, the measurement control device  100  can hasten the end timing at which the measurement of the water level is ended, as flood damage is less likely to occur, and thus can achieve the reduction of the processing load, amount of communication, and power consumption of the sensor device  101 . 
     According to the measurement control device  100 , the second reference value of the water level at which the measurement of the water level is ended can be calculated according to the specified predicted peak value. According to the measurement control device  100 , the end timing can be controlled based on a timing at which the measurement value falls below the calculated second reference value. Consequently, the measurement control device  100  can change the end timing depending on the second reference value. 
     According to the measurement control device  100 , the predicted power consumption of the sensor device  101  can be calculated based on statistical information on a change in water level during a certain period. According to the measurement control device  100 , the calculated predicted power consumption can be output. Consequently, the measurement control device  100  can facilitate the user to maintain and manage the monitoring system  200 . 
     According to the measurement control device  100 , a prediction model representing a relationship between the water level and the amount of rain can be learned based on the past water level and amount of rain. According to the measurement control device  100 , a change in water level can be predicted based on the predicted value of the amount of rain with reference to the learned prediction model. Consequently, the measurement control device  100  can automatically predict a change in water level. 
     Note that the measurement control method described in this embodiment can be implemented by executing a prepared program on a computer such as a personal computer or a workstation. The measurement control program described in the present embodiment is recorded on a computer-readable recording medium such as a hard disk, flexible disk, compact disk read only memory (CD-ROM), magneto-optical disk (MO), or digital versatile disc (DVD), and is read from the recording medium to be executed by the computer. Furthermore, the measurement control program described in the present embodiment may be distributed via a network such as the Internet. 
     All examples and conditional language provided herein are intended for the pedagogical purposes of aiding the reader in understanding the invention and the concepts contributed by the inventor to further the art, and are not to be construed as limitations to such specifically recited examples and conditions, nor does the organization of such examples in the specification relate to a showing of the superiority and inferiority of the invention. Although one or more embodiments of the present invention have been described in detail, it should be understood that the various changes, substitutions, and alterations could be made hereto without departing from the spirit and scope of the invention.