Electronic device, wrist device, electronic device control method, and program

Abstract

To suppress a large error generated when obtaining a road gradient value.SOLUTION: A road gradient meter 1 includes a GPS unit 15 and a CPU 10 that calculate an integrated distance. The CPU 10 determines a method of calculating a road gradient on the basis of the integrated distance calculated by the GPS unit 15 and the CPU 10, and calculates the road gradient on the basis of the determined method of calculating.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to an electronic device, a wrist device, a control method for an electronic device, and a program. [Background technology]

[0002] Conventionally, a technique that uses position information acquired by a GPS (Global Positioning System) and atmospheric pressure information acquired by an atmospheric pressure sensor to calculate the gradient of a road along which a user has traveled is known. This technique makes it possible to calculate the gradient of a road along a route traveled by a user from the values ​​of changes in position information and changes in atmospheric pressure information.

[0003] Here, for example, a portable information terminal has been proposed that calculates the slope of the route traveled by the user by using satellite signal information acquired by a GPS receiver and atmospheric pressure information acquired by an atmospheric pressure sensor (for example, see Patent Document 1). [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2015-184045 A Summary of the Invention [Problem to be solved by the invention]

[0005] However, since the atmospheric pressure information is affected by the weather regardless of the user's movement, the road gradient value calculated while the user is moving at a low speed often contains errors. For example, when the user's moving speed is close to zero, slight artifacts (i.e., noise) in the atmospheric pressure measurement may cause the error in the road gradient value to become large.

[0006] For this reason, it is expected that a large error will occur if the road gradient is observed when the user's moving speed is extremely slow or while the user is stopped.

[0007] An object of the present invention is to provide an electronic device, a wrist device, a control method for an electronic device, and a program that can prevent large errors from occurring when calculating a road gradient value. [Means for solving the problem]

[0008] In order to achieve the above object, the present invention provides Includes information about distance traveled A movement status acquisition unit that acquires a movement status; A pressure sensor for acquiring pressure information; A control unit that calculates a road gradient, The control unit is changing an acquisition interval of the movement status based on a predetermined condition; If the total value of the travel distances corresponding to the predetermined section in the past is equal to or greater than a threshold value, the road gradient corresponding to the predetermined section is calculated based on the atmospheric pressure information and the travel status; The threshold value is set according to an acquisition interval of the movement status. The electronic device is characterized by the above. Effect of the Invention

[0009] According to the present invention, the electronic device can prevent large errors from occurring when determining a road gradient value. [Brief description of the drawings]

[0010] [Figure 1] 1 is a hardware block diagram showing a configuration of a road gradient meter according to an embodiment of the present invention. [Diagram 2] 4 is a flowchart showing a process performed by the road gradient meter according to the first embodiment until the road gradient is calculated. [Diagram 3] 4 is a threshold table showing various thresholds in the first embodiment. [Figure 4] 10 is a flowchart showing a process performed by a road gradient meter according to a second embodiment until the road gradient is calculated. [Diagram 5] 10 is a flowchart showing a process performed by a road gradient meter according to a third embodiment to calculate a road gradient. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] Hereinafter, an embodiment of the present invention will be described in detail with reference to the accompanying drawings. Note that the present invention is not limited to the examples. Note that the same components are given the same reference numerals, and the description will be omitted as appropriate.

[0012] <First embodiment> [Road gradient meter configuration] A road gradient meter 1 (electronic device) according to this embodiment will be described with reference to Fig. 1. Note that this embodiment, the second embodiment, and the third embodiment will be described taking as an example a road gradient meter 1 that measures the road gradient when a user travels by bicycle.

[0013] Fig. 1 is a hardware block diagram showing the configuration of a road gradient meter 1 according to this embodiment. As shown in Fig. 1, the road gradient meter 1 includes a CPU (Central Processing Unit) 10, a ROM (Read Only Memory) 11, an air pressure sensor 12, an acceleration sensor 13, a RAM (Random Access Memory) 14, a GPS (Global Positioning System) unit 15, a Bluetooth communication unit 16, a speed sensor 17, and a thermometer 18.

[0014] The CPU 10 constitutes a control unit that performs various arithmetic processing and controls each part of the road gradient meter 1. The CPU 10 loads a specified application program from various application programs stored in the ROM 11 into a work memory in the RAM 14. The CPU 10 further executes various processes according to the application program loaded into the work memory in response to input data.

[0015] The CPU 10 acquires the travel status based on the position information consisting of latitude and longitude acquired by the GPS unit 15, determines the calculation method of the road gradient, and calculates the road gradient based on the determined calculation method. The combination of the CPU 10 and the GPS unit 15 functions as a travel status acquisition unit. The road gradient meter 1 includes an air pressure sensor 12 that acquires air pressure information, so the CPU 10 calculates the road gradient based on the air pressure information acquired by the air pressure sensor 12. The determination of the calculation method of the road gradient will be described later. In the first embodiment, the travel status includes information on the travel distance, and in the second embodiment, the travel status includes information on the travel distance and speed information. In the first and second embodiments, the GPS unit 15 and the CPU 10 acquire the user's travel status, but this is not limited thereto, and the GPS unit 15 may acquire the travel status using information acquired from a satellite and transmit it to the CPU 10.

[0016] The CPU 10 calculates the road gradient based on the location information acquired by the GPS unit 15 and the atmospheric pressure information acquired by the atmospheric pressure sensor 12 in response to the acquisition of the location information. The CPU 10 also changes the method of calculating the road gradient based on the travel situation. Note that the timing of acquisition of the travel situation by the GPS unit 15 and the timing of acquisition of the atmospheric pressure information by the atmospheric pressure sensor 12 do not need to be synchronized. If they are not synchronized, for example, the road gradient may be calculated based on the travel situation and the atmospheric pressure information acquired close to each other.

[0017] The ROM 11 holds various control programs and initial setting data, and various application programs (not shown) are read by the CPU 10 when the road gradient meter 1 is started up and are executed continuously.

[0018] The atmospheric pressure sensor 12 acquires atmospheric pressure information. The atmospheric pressure sensor 12 detects the atmospheric pressure around the atmospheric pressure sensor 12 and acquires it as atmospheric pressure information (atmospheric pressure value). In this way, the atmospheric pressure sensor 12 acquires the atmospheric pressure information at the time of measurement and outputs the acquired atmospheric pressure information to the CPU 10.

[0019] The acceleration sensor 13 is a sensor that senses three-dimensional acceleration. The acceleration sensor 13 is attached to the road gradient meter 1 and senses the operation of the road gradient meter 1 accurately.

[0020] The RAM 14 is composed of volatile memory such as SRAM (Static Random Access Memory) or DRAM (Dynamic Random Access Memory), and provides a working memory space for the CPU 10. The RAM 14 can also temporarily store acquired data, user setting data, and the like.

[0021] The GPS unit 15 acquires position information. The GPS unit 15 acquires current position information of the road gradient meter 1 based on signals received by a GPS antenna from multiple satellites, and outputs the current position information to the CPU 10. Note that the GPS unit 15 is merely an example and is not limited thereto. For example, the current position information may be acquired using other satellite positioning systems.

[0022] The Bluetooth communication unit 16 constitutes a communication unit that performs short-range wireless communication with the speed sensor 17. The Bluetooth communication unit 16 only needs to be able to connect to the speed sensor 17 for receiving signals, and the present invention is not limited to BLE. For example, a desired communication unit can be formed using NIC (Near Field Communication), WiFi (registered trademark), ZigBee (registered trademark), or the like.

[0023] The speed sensor 17 is, for example, a cadence sensor. The cadence sensor detects the number of rotations of the wheel by the number of times a magnet passes while the user is riding the bicycle, and measures the number of rotations of the crank on the bicycle per minute. The number indicated by the cadence sensor indicates the speed at which the person riding the bicycle rotates the pedals, and calculates speed information from the measured number of rotations. In this way, the speed sensor 17 detects the number of rotations of the crank and transmits the calculated speed information to the Bluetooth communication unit 16.

[0024] In this embodiment, only the speed sensor 17 is set as a communication destination with the Bluetooth communication unit 16, but the road gradient meter 1 may communicate with an electronic device having the various configurations shown in FIG. 1 to obtain necessary information. The road gradient meter 1 may also be equipped with the speed sensor 17. The speed sensor 17 is not limited to a cadence sensor, and the speed information may be calculated from the displacement of the position information using a GPS. When the user is moving by walking, the speed information may be calculated from a pedometer having an acceleration sensor.

[0025] The thermometer 18 acquires the ambient temperature where the road gradient meter 1 is located as the temperature of the road gradient meter 1. The thermometer 18 sends the acquired temperature of the road gradient meter 1 to the CPU 10.

[0026] [Control method of road gradient meter] Next, a control method for the road gradient meter 1 will be described with reference to the flowchart shown in Fig. 2. Fig. 2 is a flowchart showing the process from when the road gradient meter 1 according to the first embodiment is mounted on a bicycle to when the road gradient is calculated.

[0027] First, in step S001, the CPU 10 of the road gradient meter 1 acquires data to be used in calculating the road gradient, for example, 11 times. In this embodiment, the data to be used in calculating the road gradient is position information indicating the position of the road gradient meter 1 and atmospheric pressure information. For example, the CPU 10 acquires atmospheric pressure information from the atmospheric pressure sensor 12 every second, and acquires current position information from the GPS unit 15. Note that a configuration may be adopted in which other data, such as speed information, is further acquired as data to be used in calculating the road gradient.

[0028] In the first embodiment, a non-measurement period is provided in which the road gradient is not calculated. The non-measurement period corresponds to a period in which the position information and atmospheric pressure information used to calculate the road gradient in step S001 are acquired a predetermined number of times (11 times in this embodiment). In the non-measurement period, "0" is stored as the initial value of the road gradient. In the first non-measurement period, the road gradient value does not need to be displayed. Then, the CPU 10 changes the calculation method of the road gradient based on the acquired travel situation.

[0029] Fig. 3 is a threshold table showing various thresholds in the first embodiment. In the threshold table shown in Fig. 3, row items include data acquisition of location information and atmospheric pressure information (every 1 second), data acquisition of location information and atmospheric pressure information (every 5 seconds), and data acquisition of location information and atmospheric pressure information (every 120 seconds) as update periods, while column items include a column for update, a column for the number n of data items of location information and atmospheric pressure information, and a column for threshold value Ls.

[0030] In the threshold table shown in Fig. 3, when the GPS unit 15 acquires position information every second, the number of newly acquired data is 10 [pieces] and the threshold Ls is 10 [m]. When the GPS unit 15 acquires position information every 5 seconds, the number of newly acquired data is 10 [pieces] and the threshold Ls is 40 [m]. On the other hand, when the GPS unit 15 acquires position information every 120 seconds, it is set that the CPU 10 stops the function of calculating the road gradient. This threshold table is stored in the RAM 14 in a rewritable manner, for example. Here, a case where the GPS unit 15 acquires position information every second will be described.

[0031] To elaborate on the threshold table shown in FIG. 3, the location information is acquired at a predetermined timing (update period), for example, every 1 second, every 5 seconds, every 120 seconds, etc. The temporary distance ΔL is a parameter acquired from the location information, and is similarly calculated every 1 second, every 5 seconds, or every 120 seconds. These timings (update periods) can be determined, for example, by the remaining battery level or a user operation. For example, in low power mode, location information is acquired every 120 seconds to obtain minimum location information, and in high performance mode, location information is acquired every second to obtain more precise location information.

[0032] The number of data items, 10 (n items), represents the number of temporary distances ΔL used when calculating the road gradient. In other words, the temporary distances ΔL are accumulated when calculating the road gradient as described below, and the number of temporary distances ΔL accumulated when calculating one road gradient is 10 (n items). The number of data items can be changed to 10 items, and by increasing the number to 20 or 30 items, more data can be averaged, so the effect of atmospheric pressure errors is reduced. However, if the number of data items is increased too much, it becomes difficult to reflect changes in the slope of the route traveled by the user. Conversely, the number of data items can be reduced to 5 or 2 items, which is less than 10 items. In this case, it becomes easier to reflect changes in the slope of the route traveled by the user, but there is a risk that errors from the atmospheric pressure sensor will be significantly included.

[0033] Next, the distance threshold Ls is 10m or 40m, which is determined depending on whether the interval for acquiring the temporary distance ΔL is every 1 second or every 5 seconds. The distance threshold Ls is a numerical value to be compared when n temporary distances ΔL are accumulated, and if the accumulated value of the past 10 temporary distances ΔL (accumulated distance ΣL described later) exceeds the distance threshold Ls, it is considered that the user has moved, and the road gradient is calculated based on the past 10 temporary distances ΔL and the past 10 atmospheric pressure information. On the other hand, if the accumulated value of the past 10 temporary distances ΔL does not exceed the distance threshold Ls, it is considered that the user has not moved significantly, and the influence of atmospheric pressure errors can be suppressed by performing a process in which the previous gradient is used as the current gradient.

[0034] In this embodiment, the distance threshold Ls is set to different values, 10 m and 40 m, depending on whether the acquisition interval of the temporary distance ΔL is every second or every 5 seconds. This is because the distance (accumulated distance) that the user can move is significantly different depending on whether the acquisition interval of the temporary distance ΔL is every second or every 5 seconds. When the acquisition of the temporary distance ΔL is every second, it takes a total of 10 seconds to acquire 10 temporary distances ΔL. In this embodiment, the value that can be considered as the minimum movement in 10 seconds is set to, for example, 10 m. Also, when the acquisition of the temporary distance ΔL is every 5 seconds, it takes a total of 50 seconds to acquire 10 temporary distances ΔL. By simple calculation, the user can move five times more than in 10 seconds when the temporary distance ΔL is accumulated every second, and the minimum distance threshold can be set larger when the temporary distance ΔL is accumulated every 5 seconds than when the temporary distance ΔL is accumulated every second.

[0035] Also, 10m every 10 seconds is a value that is considered for a user riding a bicycle, and for example, when used by a user who is walking, the threshold Ls may be set a little lower. Also, the function is prohibited every 120 seconds, but this is because it is considered that even if the temporary distance ΔL is calculated every 120 seconds and the road gradient is calculated, the road gradient that the user actually traveled cannot be obtained well, and the function is set to be disabled. Normally, with 120 seconds, many users repeatedly go up and down the road, and it is considered that the change in the road gradient of the route traveled by the user cannot be expressed very well.

[0036] The CPU 10 calculates the altitude value H for each piece of acquired atmospheric pressure information (step S003). The CPU 10 acquires atmospheric pressure values ​​(atmospheric pressure information) every second. Here, the altitude value H is calculated using formula (1).

[0037]

number

[0038] The standard atmospheric pressure Br indicates the sea level pressure, the current atmospheric pressure Br indicates the current atmospheric pressure value (atmospheric pressure information) acquired by the CPU 10 from the atmospheric pressure sensor 12, and the reference temperature Tr is a reference temperature, for example, the temperature of the road gradient meter 1 acquired by the thermometer 18.

[0039] Next, the CPU 10 calculates the interim altitude difference ΔH from the calculated altitude value H (step S005). The interim altitude difference ΔH is the altitude difference each time atmospheric pressure information data is acquired. Since the CPU 10 acquires atmospheric pressure information data every second, it calculates the interim altitude difference ΔH for one second using formula (2). That is, the current altitude value H p Previous altitude value H p-1 By subtracting, the temporary height difference ΔH p is calculated.

[0040]

number

[0041] Note that p is the index number of the location information and atmospheric pressure information data that indicates the latest situation. Specifically, it is a number assigned in the chronological order in which the location information and atmospheric pressure information data are acquired, and is used when calculating the road gradient. Note that p is incremented by one each time new location information and atmospheric pressure information data is acquired.

[0042] Next, the CPU 10 calculates the accumulated altitude difference ΣH (step S007). The CPU 10 calculates the altitude difference by adding up the n number of interim altitude differences ΔH. In the case of this embodiment, the altitude difference is calculated by accumulating 10 pieces of data (interim altitude differences ΔH) of atmospheric pressure information data acquired every second. Note that on a downward gradient, the accumulated altitude difference ΣH is a negative value. Since the CPU 10 acquires atmospheric pressure information data every second, it calculates the sum of the n number of interim altitude differences ΔH using equation (3).

[0043]

number

[0044] Note that n indicates the number of pieces of position information and atmospheric pressure information used to calculate the road gradient (see FIG. 3), and in this case, 10 temporary elevation differences ΔH are added up.

[0045] Next, the CPU 10 calculates the temporary distance ΔL from the change in the position information (step S009). Since the CPU 10 calculates the altitude value every second, it is preferable to obtain the temporary distance ΔL every second. The temporary distance ΔL can be calculated using the formula (4).

[0046]

number

[0047] Next, the CPU 10 calculates the accumulated distance ΣL (step S011). The CPU 10 calculates the accumulated movement distance by summing up n pieces of temporary distance ΔL. In this embodiment, the CPU 10 calculates the distance by summing up 10 pieces of position information data (temporary distance ΔL) acquired every second. The CPU 10 calculates the sum of n pieces of temporary distance ΔL using formula (5).

[0048]

number

[0049] The CPU 10 determines whether the accumulated distance ΣL (the sum of the temporary distances ΔL) is equal to or greater than a predetermined distance (threshold Ls) (step S013), and if it is equal to or greater than the threshold Ls (Yes in step S013), it divides the accumulated elevation difference ΣH by the accumulated distance ΣL to calculate the road gradient (step S015), and obtains the next position information and atmospheric pressure information data (step S019).

[0050] On the other hand, if the accumulated distance ΣL (the total value of the temporary distance ΔL) is less than the threshold value Ls (No in step S013), the road gradient is not calculated, the previous road gradient is set as the current road gradient (step S017), and the next position information and atmospheric pressure information data are obtained (step S019).

[0051] In step S019, the CPU 10 acquires the atmospheric pressure information and the position information used to calculate the road gradient one second later, and thereafter repeats the same process.

[0052] As described above, the road gradient meter 1 of the first embodiment is configured to include the air pressure sensor 12, the GPS unit 15, and the CPU 10. The CPU 10 calculates the integrated distance ΣL, and if the integrated distance ΣL is equal to or greater than the threshold Ls, calculates the road gradient, and if the integrated distance ΣL is less than the threshold Ls, does not calculate the road gradient and applies the previous road gradient to the current road gradient. In other words, the CPU 10 changes the calculation method depending on the integrated distance ΣL.

[0053] In this embodiment, changing the road gradient calculation method means switching between a case where the road gradient is calculated and a case where the road gradient is not calculated, and when the road gradient is not calculated, the calculation method is changed to one where the road gradient is not calculated because the integrated distance ΣL is small and the error is large. In other words, if the integrated distance ΣL is equal to or greater than the threshold value Ls, the road gradient is calculated, but if the integrated distance ΣL is less than the threshold value Ls, it is selected not to calculate the road gradient.

[0054] As a result, the road gradient is calculated using the atmospheric pressure information and the position information only when the integrated distance ΣL is equal to or greater than the threshold value Ls, so that even if the atmospheric pressure information contains artifacts, it is possible to prevent a large error from occurring in the road gradient. Also, when the integrated distance ΣL is less than the threshold value Ls, the user has not moved significantly, so it is highly likely that the gradient of the road on which the user is located has not changed much. Therefore, by applying the previous road gradient to the current road gradient, it is possible to prevent a large error from occurring in the road gradient.

[0055] Therefore, the road gradient meter 1 of the first embodiment can prevent large errors in road gradient that occur, for example, when the speed range is extremely low while riding a bicycle or when the bicycle is stopped.

[0056] In the flowchart of Fig. 2, the processing of steps S003 to S011 is not limited to the order of processing, and the processing can be performed in the same manner even if the order of processing is changed. Also, the processing of steps S003 to S011 may be performed simultaneously in parallel. For example, steps S003 and S005 may be performed, and steps S007 and S009 may be performed simultaneously in parallel.

[0057] <Second embodiment> The CPU 10 of the road gradient meter 1 according to the second embodiment repeatedly acquires atmospheric pressure information from the atmospheric pressure sensor 12, and changes the method of calculating the road gradient by changing the number of pieces of atmospheric pressure information used to calculate the road gradient based on the travel conditions.

[0058] According to the second embodiment, the CPU 10 can change the number of pieces of atmospheric pressure information used to calculate the road gradient based on the travel situation, and therefore can calculate the road gradient with higher accuracy.

[0059] The road gradient meter 1 according to the second embodiment can be realized with the same configuration as the road gradient meter 1 according to the first embodiment, but the processing operations are different. Therefore, the processing of the second embodiment will be described using a flowchart corresponding to the second embodiment.

[0060] [Control method of road gradient meter] A control method for the road gradient meter 1 according to the second embodiment will be described with reference to the flowchart shown in Fig. 4. Fig. 4 is a flowchart showing the process performed when the road gradient meter 1 according to the second embodiment is mounted on a bicycle and calculates the road gradient. The road gradient meter 1 of the second embodiment determines whether the integrated distance ΣL is equal to or greater than the threshold value Ls each time it acquires location information data.

[0061] First, the CPU 10 of the road gradient meter 1 acquires two pieces of atmospheric pressure information and position information at one-second intervals (step S100). Next, the CPU 10 assigns 1 to n (step S101).

[0062] In the second embodiment, in order to dynamically change the temporary elevation difference ΔH, the number of the temporary elevation differences ΔH or the number of the temporary distances ΔL used in the calculation of the road gradient is explained as a variable n. The variable p is an index number of the data of the position information and the atmospheric pressure information, and is incremented by one each time new data of the position information and the atmospheric pressure information is acquired.

[0063] Next, the CPU 10 calculates the temporary distance ΔL from the change in the position information for one second using the formula (4) (step S103).Then, the CPU 10 calculates the integrated distance ΣL using the formula (5) and the variable n (step S105).

[0064] Next, the CPU 10 calculates the interim altitude difference ΔH from the change in the atmospheric pressure altitude difference for one second using the formula (2) (step S107).Then, the CPU 10 calculates the integrated altitude difference ΣH using the formula (3) and the variable n (step S109).

[0065] The CPU 10 determines whether the accumulated distance ΣL (total value of the temporary distance ΔL) is equal to or greater than the threshold Ls (step S111), and if it is equal to or greater than the threshold Ls (Yes in step S111), it divides the accumulated elevation difference ΣH by the accumulated distance ΣL to calculate the road gradient (step S113), and obtains the next position information data one second later (step S115).Then, the CPU 10 returns to step S101 and repeats the same process.

[0066] On the other hand, if the cumulative distance ΣL (total value of the temporary distances ΔL) is less than the threshold value Ls (No in step S111), the CPU 10 adds 1 to the number n of the temporary distances ΔL (step S117) and determines whether the number n of the temporary distances ΔL is 20 or more (step S119).

[0067] If the number n of temporary distances ΔL is not 20 or more (No in step S119), the CPU 10 acquires the next position information data after one second (step S123). The CPU 10 returns to step S103 and repeats the processes from step S103 to step S111 for the next number n of temporary distances ΔL (for example, n=2).

[0068] On the other hand, if the number n of temporary distances ΔL is 20 or more (Yes in step S119), it is determined that measurement is impossible (step S121), and the CPU 10 acquires the next position information data (step S115) and repeats the processes from step S101 to step S115. Note that, when it is determined that measurement is impossible, control may be performed so that calculation of the road gradient is stopped.

[0069] If it is determined in step S121 that measurement is impossible, the CPU 10 may, for example, display on the display unit the previously calculated road gradient, or may display on the display unit a message that measurement was not possible or that an error has occurred.

[0070] In this way, in the second embodiment, the CPU 10 can change the number n of the temporary elevation differences ΔH or the number n of the temporary distances ΔL used when calculating the road gradient. In other words, when the integrated distance ΣL is less than the threshold value Ls, the CPU 10 increases the number n of the temporary elevation differences ΔH or the number n of the temporary distances ΔL used when calculating the road gradient, thereby reducing the influence of errors in the atmospheric pressure information, and therefore the road gradient can be calculated even when the user's moving speed is low.

[0071] As described above, the CPU 10 of the road gradient meter 1 of the second embodiment repeatedly acquires atmospheric pressure information from the atmospheric pressure sensor 12, and changes the number n of pieces of atmospheric pressure information used to calculate the road gradient based on the travel situation.

[0072] As a result, the road gradient meter 1 of the second embodiment can change the number n of pieces of atmospheric pressure information used when calculating the road gradient based on the travel situation, and can therefore calculate the road gradient with higher accuracy.

[0073] <Third embodiment> The road gradient meter 1 according to the third embodiment includes a speed sensor 17 (speed information acquisition unit) that acquires speed information of the vehicle itself as a travel status acquisition unit, instead of the GPS unit 15, and a travel distance acquisition unit that acquires travel distance from the speed information. In this case, the CPU 10 also functions as the travel distance acquisition unit. In this case, the CPU 10 calculates the road gradient based on the travel distance acquired by the travel distance acquisition unit and the change in the atmospheric pressure information acquired by the atmospheric pressure sensor 12 in response to the acquisition of the speed information.

[0074] The CPU 10 of the road gradient meter 1 according to the third embodiment acquires speed information of the vehicle from the speed sensor 17, and changes the calculation method of the road gradient based on the speed information. When the speed information indicates a speed lower than a predetermined speed, the CPU 10 does not calculate the road gradient.

[0075] Thus, according to the third embodiment, the CPU 10 can suppress large errors in road gradient that occur when the speed range is extremely low while riding the bicycle or when the bicycle is stopped, based on the acquired speed information, not limited to the travel distance.

[0076] Since the road gradient meter 1 according to the third embodiment differs in part from the road gradient meter 1 according to the first embodiment, the processing of the third embodiment will be described using a flowchart corresponding to the third embodiment.

[0077] [Control method of road gradient meter] A control method for the road gradient meter 1 according to the third embodiment will be described with reference to the flowchart shown in Fig. 5. Fig. 5 is a flowchart showing the process from when the road gradient meter 1 according to the third embodiment is mounted on a bicycle to when the road gradient is calculated. The road gradient meter 1 of the third embodiment determines whether the integrated distance ΣL is equal to or greater than the threshold value Ls, similar to the flowchart in Fig. 2.

[0078] First, in the flowchart of FIG. 5, the CPU 10 of the road gradient meter 1 performs the same processes as those from step S001 to step S007 in the flowchart of FIG.

[0079] Then, the CPU 10 calculates the temporary distance ΔL (step S009A). The CPU 10 calculates the moving distance for one second in the same manner as in the first embodiment. The moving distance for one second calculated in step S009A corresponds to the temporary distance ΔL in formula (4).

[0080] Specifically, there is a correlation between speed information and travel distance, and the travel distance can be calculated by multiplying the speed information of the own aircraft by time. Therefore, when position information data is acquired every second, the travel distance for one second can be calculated by multiplying the speed information by one second, which corresponds to the temporary distance ΔL in this embodiment.

[0081]

number

[0082] As a result, the CPU 10 calculates the accumulated distance ΣL using equation (5) (step S011), as in the first embodiment, and if the accumulated distance ΣL (the total value of the temporary distance ΔL) is greater than or equal to the threshold value Ls (Yes in step S013), it divides the accumulated elevation difference ΣH by the accumulated distance ΣL to calculate the road gradient (step S015), and acquires the next location information data (step S019).

[0083] On the other hand, if the accumulated distance ΣL (the sum of the temporary distances ΔL) is less than the threshold value Ls (No in step S013), the road gradient is not calculated, the previous road gradient is set as the current road gradient (step S017), and the next position information and atmospheric pressure information data are obtained (step S019).

[0084] In this way, the CPU 10 can calculate the road gradient based on the travel distance acquired by the travel distance acquisition unit and the change in the atmospheric pressure information acquired by the atmospheric pressure sensor 12 in response to the acquisition of the speed information.

[0085] (Modification) The above-described embodiments of the present invention are presented as examples and are not intended to limit the scope of the invention. These new embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the present invention. For example, the following (a) to (d) are available.

[0086] (a) Regarding the invention of the road gradient meter disclosed in the first to third embodiments, the contents of the invention may be applied in combination with each other. (b) The road gradient meter disclosed in the first to third embodiments may be provided in a wrist device that is worn on the user's body. (c) In the road gradient meters disclosed in the first to third embodiments, the speed sensor 17 is configured as a cadence sensor, but this is not limited thereto. For example, the speed sensor 17 may be a speed measuring instrument that utilizes the Doppler effect. The Doppler effect refers to a phenomenon in which the frequency of a wave (such as a sound wave or electromagnetic wave) is observed differently depending on the relative speed between the source (such as a sound source or light source) of the wave and the observer. As a result, the speed sensor 17 that utilizes the Doppler effect may detect a change in the frequency of light reflection that is proportional to the speed, and calculate the speed.

[0087] (d) In the road gradient meters disclosed in the first to third embodiments, the CPU 10 calculates the altitude value H for each piece of acquired atmospheric pressure information. However, for example, if the altitude value can be acquired directly, the altitude value may be acquired directly.

[0088] The inventions described in the claims originally attached to this application are set forth below. The claim numbers in the appended claims are the same as those in the claims originally attached to this application.

[0089] [Additional Notes] <Claim 1> A movement status acquisition unit that acquires a movement status; a control unit that determines a calculation method for a road gradient based on the movement status acquired by the movement status acquisition unit, and calculates the road gradient based on the determined calculation method; Equipped 1. An electronic device comprising: <Claim 2> Equipped with a pressure sensor that acquires pressure information, The control unit is calculating the road gradient based on the atmospheric pressure information acquired by the atmospheric pressure sensor; 2. The electronic device according to claim 1 . <Claim 3> The control unit is the atmospheric pressure information is repeatedly acquired from the atmospheric pressure sensor, and the number of pieces of the atmospheric pressure information used for calculating the road gradient is changed based on the moving state, thereby changing the method of calculating the road gradient. 3. The electronic device according to claim 2 . <Claim 4> The control unit acquires a movement status from the movement status acquisition unit in response to acquiring the atmospheric pressure information from the atmospheric pressure sensor. 4. The electronic device according to claim 2 or 3. <Claim 5> The travel status includes information regarding a travel distance, The control unit calculates the road gradient based on information about the travel distance. 5. The electronic device according to claim 1, wherein the electronic device is a semiconductor device. <Claim 6> The control unit is If the total value of the past travel distances corresponding to the predetermined section is equal to or greater than a predetermined distance, the road gradient corresponding to the predetermined section is calculated; When the total value of the travel distances corresponding to the predetermined section is less than the predetermined distance, the road gradient corresponding to the predetermined section is not calculated. 6. The electronic device according to claim 5, <Claim 7> The control unit is calculating a section in which the total value of the past travel distance is equal to or greater than a predetermined distance, and calculating the road gradient based on the total value corresponding to the section and a change in atmospheric pressure information corresponding to the section; 7. The electronic device according to claim 5 or 6. <Claim 8> the movement status acquisition unit includes a speed information acquisition unit that acquires speed information of the own aircraft and a movement distance acquisition unit that acquires a movement distance from the speed information; the control unit calculates a road gradient based on the travel distance acquired by the travel distance acquisition unit and a change in atmospheric pressure information acquired by the atmospheric pressure sensor in response to acquisition of the speed information. 3. The electronic device according to claim 2 . <Claim 9> The control unit is acquiring speed information of the own aircraft from the speed information acquisition unit; changing a method for calculating the road gradient based on the speed information; 9. The electronic device according to claim 8, <Claim 10> the control unit changes a method of calculating the road gradient by changing the number of pieces of the atmospheric pressure information used to calculate the road gradient based on the speed information. 10. The electronic device according to claim 8 or 9. <Claim 11> The control unit does not calculate the road gradient when the speed information is less than a predetermined speed. 11. The electronic device according to claim 8, wherein the electronic device is a semiconductor device. <Claim 12> the control unit, when the speed information indicates a speed greater than or equal to a predetermined speed, reduces the number of pieces of atmospheric pressure information used in calculating the road gradient as the speed information indicates an increase in the speed. 12. The electronic device according to claim 8, wherein the electronic device is a semiconductor device. <Claim 13> A wrist device comprising the electronic device according to any one of claims 1 to 12. <Claim 14> A movement status acquisition unit; A control method for an electronic device including a control unit, A step of the movement status acquisition unit acquiring a movement status; determining a road gradient calculation method based on the travel status acquired by the travel status acquisition unit; calculating a road gradient based on the determined calculation method; 13. A method for controlling an electronic device comprising: <Claim 15> On the computer, A step of acquiring a movement status; determining a method for calculating a road gradient based on the acquired moving status; calculating a road gradient based on the determined calculation method; A program that executes the following. [Explanation of symbols]

[0090] 1 Road gradient meter 10 CPU 11 ROM 12 Barometric pressure sensor 13 Acceleration Sensor 14 RAM 15 GPS unit 16 Bluetooth Communication Department 17 Speed ​​Sensor

Claims

1. A movement status acquisition unit that acquires a movement status including information regarding a movement distance; A pressure sensor for acquiring pressure information; A control unit that calculates a road gradient, The control unit is changing an acquisition interval of the movement status based on a predetermined condition; If the total value of the travel distances corresponding to the predetermined section in the past is equal to or greater than a threshold value, the road gradient corresponding to the predetermined section is calculated based on the atmospheric pressure information and the travel status; The threshold value is set according to an acquisition interval of the movement status.

1. An electronic device comprising:

2. The control unit stops calculating the road gradient when the acquisition interval of the movement status is equal to or longer than a predetermined interval.

2. The electronic device according to claim 1 .

3. The threshold value can be set according to the type of activity.

3. The electronic device according to claim 1, wherein the first and second electrodes are electrically connected to the first and second electrodes.

4. The predetermined condition is a condition related to a user's operation or a battery remaining amount.

4. The electronic device according to claim 1, wherein the first and second electrodes are arranged in a first direction.

5. The control unit acquires the atmospheric pressure information from the atmospheric pressure sensor in response to acquiring the movement status from the movement status acquisition unit.

5. The electronic device according to claim 1, wherein the first and second electrodes are arranged in a first direction.

6. The control unit changes a method of calculating the road gradient based on information related to the travel distance.

6. The electronic device according to claim 1, wherein the first and second electrodes are arranged in a first direction.

7. The control unit calculates the road gradient based on information regarding the travel distance.

7. The electronic device according to claim 1, wherein the first and second electrodes are arranged in a first direction.

8. The control unit is If the total value of the travel distances corresponding to the predetermined section is equal to or greater than a predetermined distance, the road gradient corresponding to the predetermined section is calculated; When the total value of the travel distances corresponding to the predetermined section is less than the predetermined distance, the road gradient corresponding to the predetermined section is not calculated.

8. The electronic device according to claim 1, wherein the first and second electrodes are arranged in a first direction.

9. The control unit is calculating a section in which the total value of the past travel distance is equal to or greater than a predetermined distance, and calculating the road gradient based on the total value of the travel distance corresponding to the section and a change in atmospheric pressure information corresponding to the section; 9. The electronic device according to claim 1, wherein the first and second electrodes are arranged in a first direction.

10. the movement status acquisition unit includes a speed information acquisition unit that acquires speed information of the own aircraft and a movement distance acquisition unit that acquires a movement distance from the speed information; the control unit calculates a road gradient based on the travel distance acquired by the travel distance acquisition unit and a change in atmospheric pressure information acquired by the atmospheric pressure sensor in response to acquisition of the speed information.

2. The electronic device according to claim 1 .

11. The control unit is acquiring speed information of the own aircraft from the speed information acquisition unit; changing a method for calculating the road gradient based on the speed information; 11. The electronic device according to claim 10.

12. A wrist device comprising the electronic device according to claim 1 .

13. A movement status acquisition unit; An air pressure sensor; A control method for an electronic device including a control unit, A step in which the travel status acquisition unit acquires a travel status including information regarding a travel distance; The pressure sensor acquires pressure information; changing an acquisition interval of the movement status based on a predetermined condition; if the total value of the past travel distances corresponding to the predetermined section is equal to or greater than a threshold, calculating a road gradient corresponding to the predetermined section based on the atmospheric pressure information and the travel status; The threshold value is set according to an acquisition interval of the movement status.

23. A method for controlling an electronic device comprising:

14. On the computer, acquiring a travel status including information regarding a travel distance; Acquiring atmospheric pressure information; changing an acquisition interval of the movement status based on a predetermined condition; a step of calculating a road gradient corresponding to the predetermined section based on the atmospheric pressure information and the travel status when the total value of the past travel distances corresponding to the predetermined section is equal to or greater than a threshold value; Run the command, The threshold value is set according to an acquisition interval of the movement status. A program characterized by:

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