Information processing device and information processing method

Abstract

To provide an information processing device and an information processing method capable of readily upgrading the usefulness of information to be recorded.SOLUTION: An information processing device includes a recording unit that records time-series data, which represents a result of each measurement including at least one of an acceleration, angular speed, speed and altitude and a position which are measured on a moving body, in association with a predetermined section based on a result of measurement of the position, an analysis unit that analyzes the time-series data for each section, and an output unit that outputs a result of the analysis.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to an information processing device and an information processing method. [Background technology]

[0002] Patent Document 1 describes a driving status display method that, based on vehicle operation information recorded using, for example, a drive recorder, displays a special condition indicating that the speed has exceeded a set speed on a map that displays the vehicle's trajectory when the speed has exceeded a set speed for a predetermined period of time. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2008-299657 Summary of the Invention [Problem to be solved by the invention]

[0004] However, in the driving condition display method described in Patent Document 1, vehicle operation information is recorded unconditionally and cyclically on a recording medium. In this configuration, for example, when the vehicle is in operation, the operation information is recorded even when the vehicle is stopped. Therefore, there is a problem in that information unnecessary for analyzing special conditions, for example, is recorded on the recording medium.

[0005] The present disclosure has been made to solve the above-mentioned problems, and aims to provide an information processing device and an information processing method that can easily improve the usefulness of recorded information. [Means for solving the problem]

[0006] In order to solve the above problem, the information processing device according to the present disclosure includes a recording unit that records time series data representing each measurement result of at least one of acceleration, angular velocity, velocity, or altitude and position measured on a moving body, in association with a predetermined section based on the measurement result of the position, an analysis unit that analyzes the time series data for each section, and an output unit that outputs the analyzed results.

[0007] The information processing method according to the present disclosure includes the steps of recording time series data representing the measurement results of at least one of acceleration, angular velocity, velocity, or altitude and position measured on a moving body in association with a predetermined section based on the position measurement results, analyzing the time series data for each section, and outputting the analyzed results. [Effects of the Invention]

[0008] According to the information processing device and information processing method disclosed herein, it is easy to record, for example, only time-series data corresponding to a specified section, thereby easily improving the usefulness of the recorded information. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is a block diagram of an information processing device according to an embodiment of the present disclosure. [Figure 2] FIG. 1 is a diagram illustrating a display example of an information processing device according to an embodiment of the present disclosure. [Figure 3] 10 is a flowchart illustrating an example of the operation of a recording unit according to an embodiment of the present disclosure. [Figure 4] 10A and 10B are diagrams illustrating an example of correction of sampling timing in a recording unit according to an embodiment of the present disclosure. [Figure 5] FIG. 10 is a diagram illustrating an example of the frequency characteristics of an acceleration sensor according to an embodiment of the present disclosure. [Figure 6] FIG. 10 is a diagram illustrating an example of an acceleration waveform according to an embodiment of the present disclosure. [Figure 7] FIG. 10 is a diagram illustrating an example of an acceleration waveform as a comparative example to an embodiment of the present disclosure. [Figure 8]FIG. 1 is a perspective view illustrating an example of installation of an information processing device according to an embodiment of the present disclosure. [Figure 9] FIG. 1 is a perspective view illustrating an example of a case according to an embodiment of the present disclosure. [Figure 10] FIG. 1 is a schematic block diagram illustrating the configuration of a computer according to at least one embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, an information processing apparatus and an information processing method according to an embodiment of the present disclosure will be described with reference to the drawings. Note that the same or corresponding components in each drawing are designated by the same reference numerals and descriptions thereof will be omitted as appropriate.

[0011] First Embodiment (Configuration of information processing device) FIG. 1 is a block diagram of an information processing device according to an embodiment of the present disclosure. As shown in FIG. 1, the information processing device 1 according to this embodiment includes a sensor unit 2, a recording unit 3, an analysis unit 4, an output unit 5, a timer 6, a communication unit 7, and a storage unit 8. The information processing device 1 according to this embodiment can be configured using a mobile terminal (smart device, etc.) such as a smartphone or a tablet terminal. The information processing device 1 includes units 2 to 8 as a functional configuration configured, for example, by a combination of hardware such as a computer, peripheral circuits and peripheral devices of the computer, and software such as a program executed by the computer. In this embodiment, the information processing device 1 is installed on a moving object 10 such as a vehicle or carried by a passenger of the moving object 10.

[0012] (sensor part) The sensor unit 2 includes an acceleration sensor 21, a gyro sensor 22, a GNSS (Global Navigation Satellite System) sensor 23, a barometer 24, an inclinometer 25, a microphone 26, and a camera 27. The output unit 5 includes a display device 51 and an external output device 52. The memory unit 8 stores time-series data 81 as temporary storage information, and also stores a time-series data file 82, a comparison data file 83, etc. as non-volatile information.

[0013] The sensor unit 2 includes an acceleration sensor 21, a gyro sensor 22, a GNSS (Global Navigation Satellite System) sensor 23, a barometer 24, an inclinometer 25, a microphone 26, and a camera 27. The acceleration sensor 21 detects acceleration in three axes and outputs the detected acceleration values ​​(data (hereinafter the same)). The gyro sensor 22 detects rotation and changes in orientation around three axes as angular velocity and outputs the detected angular velocity values. The GNSS sensor 23 outputs position information such as latitude, longitude, and altitude detected based on signals received from GNSS satellites, as well as a differential value (velocity) of the position information. The barometer 24 detects atmospheric pressure and outputs the detected atmospheric pressure or an altitude value estimated based on the detected atmospheric pressure. The inclinometer 25 detects tilt of the information processing device 1 in three axes and outputs the detected tilt value. The microphone 26 converts picked up sound waves into electrical signals and outputs them. The camera 27 captures still or moving images and outputs image information representing the captured images.

[0014] (Recording Department) The recording unit 3 stores time series data representing each measurement result (including calculation results) of at least one of acceleration, angular velocity, velocity, and altitude output by the sensor unit 2 (or calculated based on the output of the sensor unit 2) and position in the memory unit 8 as time series data 81, and after performing a predetermined processing on the time series data 81, records the processed time series data in the memory unit 8 as a time series data file 82 in association with a predetermined section based on the position measurement result.

[0015] In this embodiment, the time series data is a time series of data acquired by the recording unit 3 from the sensor unit 2 (or output by the sensor unit 2) at a predetermined sampling period, and each piece of data is associated with information indicating the sampling time (for example, information indicating the date and time). In this embodiment, the time series data includes time series data 81 and a time series data file 82. In this embodiment, a predetermined section is a section between certain points on a route, such as a track or road, that is subject to monitoring based on the data recorded by the recording unit 3. The certain point is, for example, a station or a landmark. Recording by the recording unit 3 in association with a section means that when the time series data is saved as a time series file 83 in the storage unit 8, it is saved in association with information identifying one or more sections.

[0016] The recording unit 3 also corrects the time series data so that deviation in the sampling period of the time series data is reduced (details will be described later). The recording unit 3 also attenuates frequency components higher than a predetermined frequency contained in the time series data, as will be described later. The recording unit 3 can also calibrate the time series data by assuming that the value at the start of the interval is zero, and then record the calibrated time series data. The recording unit 3 records relative changes by setting each parameter to 0 at the start, for example.

[0017] The time-series data may include data representing noise measurement results. When the time-series data includes speed or acceleration, the recording unit 3 can record the time-series data by setting data from a predetermined time before the speed or acceleration reaches a predetermined threshold as the leading time data, and by setting data from a predetermined time after the speed or acceleration falls below the threshold as the trailing time data. The time-series data may be measured, for example, by a sensor unit 2 (measurement means) placed on a seat (not shown) of the moving object 10 and loaded vertically downward on the seat (e.g., when a passenger is seated on the information processing device 1). When multiple information processing devices 1 are used simultaneously and time-series data is recorded by each information processing device 1, the recording unit 3 can synchronize the recording time with that of the other information processing devices 1 to record the time-series data.

[0018] (Analysis Department) The analysis unit 4 analyzes the time-series data for each interval. The analysis unit 4 analyzes the timing at which maximum and minimum values ​​occur for, for example, acceleration, the output of the gyro sensor 22 (data such as pitch angle, roll angle, and yaw angle (also referred to as gyro data)), speed, and altitude, and outputs the analysis results to be plotted on a map or the like. The analysis unit 4 outputs, for example, the location information (latitude and longitude) at which the maximum and minimum values ​​occur as the analysis results. Note that the analysis results may also include altitude information, and be displayed in 3D (three-dimensional) on a map together with the altitude. Furthermore, the analysis unit 4 may perform calculation of effective values ​​and frequency analysis on the acceleration and gyro data, and output the results as the analysis results.

[0019] The analysis unit 4 may also analyze time-series data by comparing it with other time-series data measured in the same section. For example, information representing the maximum values ​​and effective values ​​of acceleration, gyro data, etc. previously measured in the same section is recorded as a comparison data file 83. The analysis unit 4 matches the past data and newly acquired data with past data (data linked to position) using a dynamic programming (DP) matching method, and then outputs the analysis results so that the user can check how the acceleration or gyro has changed in a section where a certain threshold value or above occurs or in a predetermined section. The analysis unit 4 may also perform the above process for each specific section while measuring acceleration.

[0020] Figures 6 and 7 show examples of acceleration waveforms obtained when the same vehicle travels 10 times under the same track and speed conditions. Figure 6 shows the enlarged waveforms of the reference acceleration waveform and the nonlinear stretch-measured acceleration waveform obtained when DP matching is performed using one of the 10 waveforms as the reference acceleration waveform. Figure 7 shows the enlarged waveforms obtained around 56 seconds and 64.4 seconds when 10 waveforms are matched at the acceleration peak around 56 seconds. In the example shown in Figure 7, even if the timing of a certain acceleration peak is adjusted to match, the timing of other acceleration peaks will be shifted, which requires time for evaluation. On the other hand, when DP matching is performed, the acceleration peaks are accurately matched, as shown in Figure 6. Matching measured waveforms using the DP matching method makes it possible to monitor track conditions from on-board sensors. Furthermore, even in sections where GNSS positioning information is not available, if the distance between stations is known, it is possible to monitor track conditions by matching the data with data from past travel between those stations.

[0021] Furthermore, when the time-series data includes sound data, the analysis unit 4 may output the analysis results so that, for example, the time change in noise level (dB(A)) can be output as a graph. Furthermore, the analysis unit 4 may output the analysis results in a format that allows the locations where high noise levels occurred to be plotted on a map. In this configuration, by recording and analyzing not only acceleration but also sound signals, it becomes possible to identify impact sounds when large accelerations occur, and this can be used for factor analysis.

[0022] (output section) As described above, the output unit 5 includes the display device 51 and the external output device 52. The display device 51 is, for example, a touch panel display that serves as both an input device and an input / output device. The external output device 52 is a device for outputting information to an external display device or the like. FIG. 2 shows an example of a display on the display device 51. FIG. 2 shows an example of a screen 510 when the mobile object 10 travels a section from station A to station B. In this case, the screen 510 includes information 512 representing the current time 511, accelerations ax, ay, and az (output of the acceleration sensor 21), accelerations gx, gy, and gz (output of the inclinometer 25), and gyro data (pitch angle, roll angle, yaw angle) (output of the gyro sensor 22). The screen 510 further includes information 513 that indicates the latitude, longitude, and vehicle speed (output (or calculated value based on the output) of the GNSS sensor 23) and the output of the altitude (barometer 24). The information 511, 512, and 513 indicates measurement results and the like in real time.

[0023] The screen 510 also includes information 514 that indicates the analysis results by the analysis unit 4. The information 514 is displayed after the information processing device 1 has traveled a predetermined section from station A to station B. The horizontal axis is latitude and the vertical axis is longitude, and for example, a hollow circle indicates the maximum value of the acceleration amplitude, a solid circle indicates the minimum value of the acceleration amplitude, a hollow triangle indicates the maximum value of the roll angle, and a solid triangle indicates the minimum value of the roll angle.

[0024] Furthermore, screen 510 includes button 515 for recording time series data 81 as a time series data file 82, and button 516 for deleting already recorded time series data file 82 (or deleting time series data 81 without recording it as time series data file 82). Recording unit 3 can determine whether or not to record time series data 81 as time series data file 82, for example, by operating button 515 or 516. For example, if the operator confirms information 514 and the like and recognizes that some kind of problem has occurred in the time series data 81, the operator can delete already recorded time series data file 82 or discard the time series data 81 without recording it.

[0025] (Timer) The timer 6 is a timer that operates at various cycles with the time of an internal clock function, such as a real-time clock, as its initial value.

[0026] (Communications Department) The communication unit 7 transmits and receives information to and from external terminals and the like via a public mobile communication network and the like.

[0027] (Example of recording unit operation) Next, an example of the operation of the recording unit 3 will be described with reference to FIG. 3. The process shown in FIG. 3 is started when, for example, an operator instructs the information processing device 1 to record time-series data 81. In the process shown in FIG. 3, first, the recording unit 3 determines whether the data acquisition time has arrived (step S11). If it is not the acquisition time (step S11: NO), the recording unit 3 executes the determination process of step S11 again, for example, after a predetermined time has elapsed. Note that in step S11, multiple types of data acquisition times can be set for each type of sensor. For example, the sampling frequency for acceleration information can be set to tens to hundreds of Hz, and the sampling frequency for position information can be set to 1 to several Hz. If it is the acquisition time (step S11: YES), the recording unit 3 acquires data from the sensor unit 2 (step S12), associates the acquired data with information on the sampling time, and stores the data in the storage unit 8 as time-series data 81 (step S13).

[0028] Next, the recording unit 3 determines whether the start time has been stored (step S14). The start time is, for example, the time when it is determined that the moving object 10, which has been stopped at a station, has started traveling in the section. If the start time has not been stored (step S14: NO), the recording unit 3 determines, for example, whether the latest acceleration or speed is equal to or greater than a predetermined threshold (step S15). If the acceleration or speed is not equal to or greater than the predetermined threshold (step S15: NO), the recording unit 3 executes the determination process of step S11 again. If the acceleration or speed is equal to or greater than the predetermined threshold (step S15: YES), the recording unit 3 stores the current time as the start time in, for example, a predetermined area of ​​the memory unit 8 (step S16), and executes the determination process of step S11 again.

[0029] If the start time has been stored in step S14 (step S14: YES), the recording unit 3 determines whether the end time has been stored (step S17). The end time is, for example, the time when it is determined that the moving object 10 traveling in the section has arrived at a station. If the end time has not been stored (step S17: NO), the recording unit 3 determines, for example, whether the latest acceleration or speed is equal to or less than a predetermined threshold (step S18). If the acceleration or speed is equal to or less than the predetermined threshold (step S18: NO), the recording unit 3 executes the determination process of step S11 again. If the acceleration or speed is equal to or less than the predetermined threshold (step S18: YES), the recording unit 3 stores the current time as the end time in, for example, a predetermined area of ​​the storage unit 8 (step S16), and executes the determination process of step S11 again.

[0030] If the start time has been stored in step S14 (step S14: YES), the recording unit 3 determines whether the end time has been stored (step S17). The end time is, for example, the time when it is determined that the moving object 10 traveling in the section has arrived at a station. If the end time has not been stored (step S17: NO), the recording unit 3 determines, for example, whether the latest acceleration or speed is equal to or less than a predetermined threshold (step S18). If the acceleration or speed is equal to or less than the predetermined threshold (step S18: NO), the recording unit 3 executes the determination process of step S11 again. If the acceleration or speed is equal to or less than the predetermined threshold (step S18: YES), the recording unit 3 stores the current time as the end time in, for example, a predetermined area of ​​the storage unit 8 (step S199), and executes the determination process of step S11 again.

[0031] If the end time has been stored in step S17 (step S17: YES), the recording unit 3 determines whether a predetermined time has elapsed since the end time was stored (step S20). If the predetermined time has not elapsed (step S20: NO), the recording unit 3 executes the determination process of step S11 again. If the predetermined time has elapsed (step S20: YES), the recording unit 3 performs a predetermined process on the time series data 81, creates and records a time series data file 82 (step S21), and ends the process shown in FIG.

[0032] As a predetermined process in step S21, the recording unit 3 corrects the time series data 81, for example, so that the deviation of the sampling period of the time series data 81 is reduced. Figure 4 shows an example of sampling timing correction in the recording unit 3. The horizontal axis is time, and the vertical axis is the sensor value (output value of the sensor unit 2). Open circles represent data during default recording, and filled circles represent data after uniform sampling conversion. "dt" is a uniform sampling period. For example, if the information processing device 1 is configured as a smart device, in the case of high-speed sampling, the processing may not be able to keep up, making it impossible to acquire data at uniform sampling. When performing frequency analysis, the data must be uniformly sampled, and in that case, it is converted to uniformly sampled data by interpolation.

[0033] Furthermore, as a predetermined process in step S21, the recording unit 3 attenuates, for example, frequency components higher than a predetermined frequency contained in the time-series data 81. The built-in sensor for acquiring data has a low sampling frequency, and attempting to acquire data at high frequencies can result in aliasing. To prevent this, the recording unit 3 filters the output data of the sensor unit 2 before outputting and saving the data. The filter frequency is set by performing a vibration test, such as by placing the smart device on a vibrator, and comparing the data acquired by a reference device, such as a conventional piezoelectric or strain-type accelerometer, to confirm the frequency characteristics. In Figure 5, the horizontal axis represents frequency, and the vertical axis represents the ratio of the sensor output value (numerator) of the sensor unit 2 to the output value (denominator) of the reference sensor. For example, if the ratio deviates from 1 by more than a predetermined value at high frequencies, the high-frequency components are attenuated using a low-pass filter with a corresponding cutoff frequency to prevent the error from affecting the analysis results (such as reducing the accuracy of the analysis results). According to this configuration, by setting the filter characteristics after checking the characteristics of the smart device, it is possible to prevent the analysis of acceleration data containing frequency components that cannot be evaluated in the first place.

[0034] In the above operation example, when the vehicle speed or acceleration exceeds a threshold, data acquisition for, for example, several seconds before that point begins, and when the vehicle speed (or acceleration) falls below the threshold, measurement stops. According to this operation example, it is possible to save data separated into only data between stations. It is also possible to identify the interval between stations in which the train is traveling from information on the start and end positions of the journey. Even if measurement is performed without performing the above processing, it is also possible to divide the data into data for each interval between stations when the vehicle speed or acceleration exceeds the threshold after measurement. With this configuration, there is no need to manually start and stop measurement.

[0035] (Action and effect) According to this embodiment, the information processing device 1 includes a recording unit 3 that records time-series data representing measurement results of at least one of acceleration, angular velocity, velocity, and altitude measured on a moving object 10 and the position, in association with a predetermined section based on the position measurement results, an analysis unit 4 that analyzes the time-series data for each section, and an output unit 5 that outputs the analyzed results. With this configuration, it is easy to record, for example, only time-series data associated with a predetermined section, which makes it possible to easily improve the usefulness of the recorded information.

[0036] Second Embodiment The basic configuration of the second embodiment is the same as that of the first embodiment. In the second embodiment, the analysis unit 4 has some different functions. In the second embodiment, the analysis unit 4 is added with a function to perform frequency analysis on acquired acceleration data and calculate the corrected acceleration effective value according to ISO 2631-1. In the second embodiment, this data can be compared with data measured on other vehicles traveling between the same stations. It can also be compared with past data from the same vehicle. Furthermore, by adding a function to calculate the jerk (jerk) of longitudinal acceleration after measurement, the quality of driving (whether there is sudden acceleration or deceleration) can be evaluated in the case of manually operated vehicles. Furthermore, the system can also measure the ride comfort when seated on a smart device, for example. According to this embodiment, changes in ride comfort over a long period of time can be confirmed over a time series. Furthermore, according to this embodiment, by measuring with a smart device instead of a conventional accelerometer, seat acceleration can be measured without a special seat sensor.

[0037] <Third embodiment> The basic configuration of the third embodiment is the same as that of the first embodiment. In the third embodiment, synchronization is established between an information processing device 1 and other information processing devices 1 as follows. Vibration measurements at multiple points can be performed simultaneously using multiple information processing devices 1. However, even when measurements are performed simultaneously after time synchronization, there is a possibility of slight discrepancies. If time synchronization is not possible, manual synchronization is performed in advance based on the waveform obtained when the smart devices are placed on top of each other and vibrated, or on the audio waveform. In this embodiment, after data acquisition, the data can be aggregated on a single smart device, allowing for transfer function evaluation and vibration mode drawing. Furthermore, when one person uses multiple devices for measurement, it is desirable to be able to monitor the acceleration measurement status of the other smart devices using one smart device. According to this embodiment, there is no need to connect each information processing device 1 to a single recorder; data can be analyzed by synchronizing the time.

[0038] <Fourth embodiment> In this embodiment, the smart device is fixed to a rigid block 101, such as a metal block, via a smart device case 102, as shown in FIGS. 8 and 9 . The rigid block 101 and case 102 are fixed with adhesive. The camera portion is slightly protruding. In this state, measurement of the floor surface 10R of the moving object 10 can be performed. That is, in this embodiment, the information processing device 1 is a mobile terminal attached to a case 102 that is adhered to the rigid block 101 fixed to the floor surface 10R of the moving object 10, with a portion of the case protruding. This embodiment is easy to carry and enables immediate measurement. Furthermore, while a smart device attached entirely to a rigid block, such as a metal block, can be difficult to remove, this embodiment makes removal easy. Furthermore, a hole is usually drilled in the case 102 at the camera position, making it easy to remove the smart device from the rigid block 101 and case 102.

[0039] Fifth Embodiment In this embodiment, the information processing device 1 has a function to acquire images (videos) during measurement. It also has a function to automatically take photos with a camera at the start and end of measurement. This embodiment can also have a function to take photos when acquired data, such as acceleration values, exceeds a threshold. According to this embodiment, if a video is used, it is possible to check whether the smart device is moving during vibration measurement. Even with only the first and last photos, it is possible to check whether the attitude of the smart device has changed at the start and end of measurement. Still images are easier to check than videos. It is also possible to determine where values ​​such as acceleration become large not only from GNSS location information but also from photos.

[0040] Sixth Embodiment In this embodiment, the information processing device 1 acquires weather information (weather, wind speed, humidity, etc.) from the Internet or the like at the timing of starting measurement, and stores it together with data such as acceleration. According to this embodiment, it is easy to judge the situation at the time of measurement later.

[0041] Seventh Embodiment In this embodiment, the acquired data is automatically stored in the cloud, and the locally stored data is deleted. This embodiment does not put a strain on the capacity of the smart device.

[0042] (Action and effect) In the information processing device and information processing method having the above-described configuration, time-series data representing the measurement results of at least one of acceleration, angular velocity, velocity, and altitude measured on a moving object and the position are recorded in association with a predetermined section based on the position measurement results, the time-series data are analyzed for each section, and the analyzed results are output. With this configuration, for example, it is easy to record only the time-series data associated with the predetermined section, thereby easily improving the usefulness of the recorded information.

[0043] (Other embodiments) The above describes in detail the embodiments of the present disclosure with reference to the drawings, but the specific configuration is not limited to this embodiment, and design changes and the like are also included within the scope that does not deviate from the gist of the present disclosure.

[0044] <Computer Configuration> FIG. 10 is a schematic block diagram illustrating the configuration of a computer according to at least one embodiment. The computer 90 includes a processor 91 , a main memory 92 , a storage 93 , and an interface 94 . The information processing device 1 described above is implemented in a computer 90. The operations of the above-described processing units are stored in the form of a program in a storage 93. A processor 91 reads the program from the storage 93, loads it into a main memory 92, and executes the above-described processing in accordance with the program. The processor 91 also allocates storage areas in the main memory 92 corresponding to the above-described storage units in accordance with the program.

[0045] The program may be for realizing some of the functions to be performed by the computer 90. For example, the program may be combined with other programs already stored in storage or other programs implemented in other devices to perform the functions. In other embodiments, the computer may include a custom LSI (Large Scale Integrated Circuit) such as a PLD (Programmable Logic Device) in addition to or instead of the above configuration. Examples of PLDs include PAL (Programmable Array Logic), GAL (Generic Array Logic), CPLD (Complex Programmable Logic Device), and FPGA (Field Programmable Gate Array). In this case, some or all of the functions realized by the processor may be realized by the integrated circuit.

[0046] Examples of storage 93 include a hard disk drive (HDD), a solid state drive (SSD), a magnetic disk, a magneto-optical disk, a compact disc read-only memory (CD-ROM), a digital versatile disc read-only memory (DVD-ROM), and a semiconductor memory. Storage 93 may be an internal medium directly connected to the bus of computer 90, or an external medium connected to computer 90 via interface 94 or a communication line. Furthermore, when this program is distributed to computer 90 via a communication line, computer 90 that receives the program may load the program into main memory 92 and execute the above-described processing. In at least one embodiment, storage 93 is a non-transitory tangible storage medium.

[0047] <Additional Notes> The information processing device 1 described in each embodiment can be understood, for example, as follows.

[0048] (1) An information processing device 1 according to a first aspect includes a recording unit 3 that records time-series data representing measurement results of at least one of acceleration, angular velocity, velocity, and altitude measured on a moving object 10 and position, in association with a predetermined section based on the position measurement results, an analysis unit 4 that analyzes the time-series data for each section, and an output unit 5 that outputs the analyzed results. According to this aspect and each of the following aspects, for example, it is easy to record only time-series data associated with a predetermined section, which makes it possible to easily improve the usefulness of the recorded information.

[0049] (2) The information processing device 1 of a second aspect is the information processing device 1 of (1), in which the recording unit corrects the time-series data so that deviation of the sampling period of the time-series data becomes small.

[0050] (3) The information processing device 1 of a third aspect is the information processing device 1 of (1) or (2), wherein the recording unit attenuates frequency components higher than a predetermined frequency contained in the time-series data.

[0051] (4) The information processing device 1 of a fourth aspect is the information processing device 1 of (1) to (3), in which the recording unit records the time-series data assuming that the value at the start of the interval is zero.

[0052] (5) The information processing device 1 of a fifth aspect is the information processing device 1 of (1) to (4), in which the time-series data includes data representing a measurement result of noise.

[0053] (6) The information processing device 1 of the sixth aspect is the information processing device 1 of (1) to (5), wherein the time series data includes speed or acceleration, and the recording unit records the time series data such that when the speed or acceleration is equal to or greater than a predetermined threshold, the data from a predetermined time before that is the data at the leading time, and when the speed or acceleration is equal to or less than the threshold, the data from the predetermined time after that is the data at the trailing time.

[0054] (7) The information processing device 1 of the seventh aspect is the information processing device 1 of (1) to (6), in which the time series data is measured by a measuring means placed on a seat of the moving body and loaded downward from the vertical direction of the seat.

[0055] (8) An information processing device 1 of an eighth aspect is an information processing device 1 of (1) to (7), wherein the analysis unit analyzes the time series data by comparing it with other time series data measured in the same section.

[0056] (9) The information processing device 1 of a ninth aspect is the information processing device 1 of any one of (1) to (8), wherein the recording unit records the time-series data by synchronizing the recording time with that of another information processing device.

[0057] (10) The information processing device 1 of the tenth aspect is an information processing device 1 of (1) to (9), which is a mobile terminal attached to a case that is adhered to a rigid block fixed to the floor surface of a moving body so that a portion of the case protrudes from the case. [Explanation of symbols]

[0058] 1...Information processing device 2...Sensor section 3...Recording section 4…Analysis Department 5...Output section 8…Storage section 10...Mobile

Claims

1. a recording unit that records time-series data representing measurement results of at least one of acceleration, angular velocity, velocity, and altitude measured on a moving object and a position, in association with a predetermined section based on the measurement results of the position; an analysis unit that analyzes the time-series data for each interval; An output section that outputs the analyzed results; An information processing device comprising:

2. The recording unit corrects the time series data so that deviation of the sampling period of the time series data becomes small. The information processing device according to claim 1 .

3. The recording unit attenuates frequency components higher than a predetermined frequency included in the time-series data. The information processing device according to claim 2 .

4. The recording unit records the time series data assuming that the value at the start of the interval is zero. The information processing device according to claim 3 .

5. The time-series data includes data representing noise measurement results. The information processing device according to claim 4 .

6. the time-series data includes velocity or acceleration; The recording unit records the time series data as data of a leading time when the speed or acceleration is equal to or greater than a predetermined threshold, and as data of a trailing time when the speed or acceleration is equal to or less than the threshold. The information processing device according to claim 5 .

7. The time series data is measured by a measuring means placed on a seat of the moving body and with a load applied downward from the vertical direction of the seat. The information processing device according to claim 6 .

8. The analysis unit analyzes the time series data by comparing it with other time series data measured in the same section. The information processing device according to claim 7 .

9. The recording unit synchronizes recording time with other information processing devices and records the time-series data. The information processing device according to claim 8 .

10. A mobile terminal attached to a case that is partially attached to a rigid block fixed to the floor of a moving object. The information processing device according to any one of claims 1 to 9.

11. a step of recording time series data representing measurement results of at least one of acceleration, angular velocity, velocity, and altitude measured on a moving object and a position, in association with a predetermined section based on the measurement results of the position; analyzing the time series data for each interval; outputting the analyzed results; An information processing method including:

Images