Patent Application
20210227348
The present invention generally relates to sensing technology.
This type of sensing technology includes a technique disclosed in US 2019/0005807 which is a previous application of the applicant of the present application. According to the technique disclosed in US 2019/0005807, it is possible to reduce power consumption in a wireless sensor node in a case of using a sensor that needs to perform a plurality of times of measurement in a relatively short period of time.
The wireless sensor node is configured to perform measurement based on a parameter value group that is one or more parameter values affecting the measurement. The wireless sensor node measures a value of a predetermined measurement item belonging to a surrounding environment of the wireless sensor node. A parameter value group of the wireless sensor node is preferably optimal in the surrounding environment of the wireless sensor node.
It is considered that the wireless sensor node is used to measure a surrounding environment of a train. Since a huge number of wireless sensor nodes are required if the wireless sensor nodes are installed along a line, it is considered to install the wireless sensor node on the train.
However, a surrounding environment of the wireless sensor node changes with a movement of the train. For example, the train may enter or exit a closed system (for example, a tunnel). When a parameter value group of the wireless sensor node is constant, optimal measurement is not always performed.
According to the invention, a sensing system includes one or a plurality of wireless sensor nodes and a sensing control device. Each wireless sensor node performs measurement based on a parameter value group that is one or a plurality of parameter values affecting the measurement and is installed on a train. The sensing control device specifies a position of the train, determines, for at least one wireless sensor node, a parameter value group of the wireless sensor node corresponding to the specified position of the train, and performs control to set the determined parameter value group in the wireless sensor node.
Even when the surrounding environment of the wireless sensor node changes with a movement of the train, optimal measurement by the wireless sensor node can be maintained.
In the following description, a “communication interface device” may be one or more communication interface devices. The one or more communication interface devices may be one or more communication interface devices of the same type (for example, may be one or more network interface card (NIC)), or two or more communication interface devices of different types (for example, an NIC and a host bus adapter (HBA)).
In the following description, a “memory” may be one or more memory devices which is an example of one or more storage devices, and typically may be a main storage device. At least one memory device in the memory may be a volatile memory device or a non-volatile memory device.
In the following description, a “persistent storage device” may be one or more persistent storage devices which are each an example of one or more storage devices. Typically, the persistent storage device may be a non-volatile storage device (for example, an auxiliary storage device). Specific examples of the persistent storage device include a hard disk drive (HDD), a solid state drive (SSD), a non-volatile memory express (NVMe) drive, and a storage class memory (SCM).
In the following description, a “storage device” may be either the “memory” or the “persistent storage device”.
In the following description, a “processor” may be one or more processor devices. Typically, at least one processor device is a microprocessor device such as a central processing unit (CPU). Alternatively, the processor device may be another type of processor device such as a graphics processing unit (GPU). The at least one processor device may be a single core or a multi-core. The at least one processor device may be a processor core. The at least one processor device may be a processor device in a broad sense such as a circuit (for example, a field-programmable gate array (FPGA), a complex programmable logic device (CPLD), and an application specific integrated circuit (ASIC)) that is an aggregation of gate arrays by a hardware description language that executes a part of or all processings.
In the following description, an expression such as “xxx table” may be used to describe information that is acquired as an output for an input. The information may be data of any structure (for example, may be structured data or may be unstructured data), or may be a learning model represented by a neural network, a genetic algorithm, or a random forest that generates an output for an input. Therefore, the “xxx table” can be referred to as “xxx information”. In the following description, a configuration of each table is an example, one table may be divided into two or more tables, and all or a part of the two or more tables may be one table.
In the following description, an expression of “xxx unit” may be used to describe a function. The function may be implemented by a processor executing one or more computer programs, or may be implemented by one or more hardware circuits (for example, an FPGA or an ASIC), or may be implemented by a combination of the above implementation methods. When a function is implemented by a processor executing a program, a predetermined processing is executed by appropriately using a storage device and/or an interface device, so that the function may be at least a part of the processor. A processing described using the function as a subject may be a processing executed by a processor or by a device including the processor. The program may be installed from a program source. The program source may be, for example, a recording medium (for example, a non-transitory recording medium) that can be read by a program distribution computer or a computer. Description for each function is an example, a plurality of functions may be combined into one function, or one function may be divided into a plurality of functions.
In the following description, among reference numerals, a common reference numeral may be used when elements of the same type are described without distinction, and different reference numerals may be used when elements of the same type are distinguished.
In the following description, a “parameter” includes a parameter item (for example, an amplification factor) and a parameter value (for example, a value of an amplification factor).
In the following description, for a wireless sensor node, a “measurement data set” is a data set indicating one or more values measured according to a parameter value group set in the wireless sensor node and the respective measurement time points of the one or more values. For each parameter value group set in the wireless sensor node, a “measurement data set group” is one or more measurement data sets corresponding to the parameter value group. A “data set” is one logical block of electronic data as viewed from a program such as an application program, and may be any one of a record, a file, a key value pair, a tuple, and the like.
A train 130 includes an operation control device 100 (for example, a device that is provided in an operation room of the train 130 and controls an operation of the train 130), a sensor group 110 that is one or a plurality of wireless sensor nodes, and a sensing control device 120 that controls measurement by each of the wireless sensor nodes. The sensing control device 120 may be provided in the train 130 as shown in
As described above, the sensor group 110 includes the one or the plurality of wireless sensor nodes 201. For example, the sensor group 110 includes a sound sensor node 201A (a wireless sensor node including a sound sensor), a vibration sensor node 201B (a wireless sensor node including a vibration sensor), a gas sensor node 201C (a wireless sensor node including a gas sensor), a temperature sensor node 201D (a wireless sensor node including a temperature sensor), a humidity sensor node 201E (a wireless sensor node including a humidity sensor), a barometric pressure sensor node 201F (a wireless sensor node including a barometric pressure sensor), an illuminance sensor node 201G (a wireless sensor node including an illuminance sensor), an image sensor node 201H (a wireless sensor node including an image sensor), and an air flow sensor node 201I (a wireless sensor node including an air flow sensor). The image sensor node 201H may be, for example, a camera that takes a still image or a dynamic image. Each of the wireless sensor nodes 201 is installed on the train 130 at a position suitable for measurement by the corresponding wireless sensor node. Among the wireless sensor nodes 201, a part of the wireless sensor nodes 201 may be omitted, or a part of the wireless sensor nodes 201 may be other wireless sensor nodes 201. At least one of the wireless sensor nodes 201 may be installed in two or more.
The wireless sensor node 201 is a terminal that includes an independent power supply system 301, and implements a sensor function by operating a sensor 302 and a measurement circuit 303 with generated electric power of the independent power supply system 301. The sensor function includes measurement of various surrounding physical quantities and wirelessly transmission of a measurement data set indicating measured results to the sensing control device 120. Here, “measurement” refers to an entire processing of preparing the measurement data set to be transmitted for one time by the wireless sensor node 201. For example, when the wireless sensor node 201 shown in
In most cases, it is difficult for the wireless sensor node 201 to secure a line for supplying power. Therefore, the independent power supply system 301 may include a power generation element such as a solar cell, a piezo element, and a Peltier element, a power supply and storage element such as a battery, a power supply control circuit, a rectifier circuit, and the like. The independent power supply system 301 can supply electric power to the sensor 302 and the measurement circuit 303 without being supplied with electric power from outside of the wireless sensor node 201.
The measurement circuit 303 performs a shaping processing on an output signal of the sensor 302, thereafter converts the output signal into a digital value, and wirelessly transmits a data set including the digital value serving as a measurement data set to the sensing control device 120. The measurement circuit 303 includes a processing circuit 306, an analog-to-digital converter (ADC) 307, a control circuit 308, and a wireless communication interface device (wireless I/F) 309.
The processing circuit 306 may include, for example, at least one of a band-pass filter circuit, an amplitude value detection circuit, an integration circuit, and an amplification circuit.
The band-pass filter circuit may be configured such that a pass-band is variable according to a control signal from the control circuit 308. For example, the band-pass filter circuit may include a plurality of band-pass filters having different pass-bands, and may switch to a band-pass filter to be used according to the control signal from the control circuit 308. The band-pass filter circuit may output an input from the sensor 302 as it is without filtering under the control of the control circuit 308.
The amplitude value detection circuit may be a circuit that outputs a voltage in proportion to an amplitude value of a signal output from the band-pass filter circuit. The amplitude value detection circuit may include a signal level detection circuit, a rectifier circuit, a maximum value circuit, and the like. Further, the amplitude value detection circuit may output an input from the band-pass filter circuit as it is without detecting the amplitude value under the control of the control circuit 308. Alternatively, the amplitude value detection circuit may be omitted.
The integration circuit may be a circuit that integrates input signals from the amplitude value detection circuit for a certain period of time and outputs a voltage value in proportion to an integrated value. The integration circuit may control a period of time during which the input signals are to be integrated and reset the integrated value according to the control signal from the control circuit 308. Further, the integration circuit may output an input from the amplitude value detection circuit as it is without integration under the control of the control circuit 308. Alternatively, the integration circuit may be omitted.
The ADC 307 is a circuit that converts an input signal from the processing circuit 306 (for example, the integration circuit) into a digital signal. The processing circuit 306 may include an amplification circuit provided between the integration circuit and the ADC 307. The amplification circuit may amplify an analog signal.
The control circuit 308 includes a CPU and a memory, generates and outputs a measurement data set to be transmitted to the sensing control device 120 via the wireless I/F 309, and receives a signal from the sensing control device 120. The control circuit 308 controls an operation of each block of the sensor 302 and the measurement circuit 303 based on the received signal.
The wireless I/F 309 is a circuit that wirelessly transmits a signal from the control circuit 308 and receives a wireless signal from the sensing control device 120. The wireless I/F 309 is not particularly limited to a wireless frequency or a wireless system. For example, a wireless system generally used in a sensing system may be a wireless system conforming to a standard such as Wi-SUN (registered trademark), Zigbee (registered trademark), Wi-Fi (registered trademark), and WirelessHART (registered trademark). Alternatively, communication may be performed by a unique protocol.
The sensing control device 120 may be a general-purpose computer or a dedicated machine. The sensing control device 120 includes a wireless I/F 351, a storage device 352, and a processor 353 connected to the wireless I/F 351 and the storage device 352.
The wireless I/F 351 is an example of the communication interface device. The communication interface device may include other types of communication interface devices in addition to the wireless I/F 351. The wireless I/F 351 receives a measurement data set from the wireless sensor node 201 and transmits a parameter value group to the wireless sensor node 201. The wireless I/F 351 periodically or non-periodically receives a speed data set from the operation control device 100. The speed data set is a data set indicating a speed of the train 130 and a time point when the speed is measured.
The storage device 352 stores one or more programs to be executed by the processor 353. The storage device 352 stores a measurement table 361, a parameter item table 362, and an operation management table 363.
The measurement table 361 is a table including one or more measurement data set groups for each wireless sensor node 201. The measurement table 361 includes, for each wireless sensor nodes 201, a measurement data set group for each parameter value group of the corresponding wireless sensor node.
The parameter item table 362 is a table indicating a relationship between the wireless sensor node 201 and a parameter item group (one or more parameter items).
The operation management table 363 is a table indicating a relationship between a position and the speed of the train 130 and the parameter value group.
The processor 353 executes one or more programs stored in the storage device 352, thereby implementing a collection unit 371, a specifying unit 372, a learning unit 373, and a control unit 374 in the processor 353.
The collection unit 371 collects a measurement data set from the wireless sensor node 201 and stores the collected measurement data set in the storage device 352. The collection unit 371 collects a speed data set from the operation control device 100 and stores the collected speed data set in the storage device 352.
The specifying unit 372 specifies a position of the train 130 based on the operation management table 363. The specifying unit 372 specifies the speed of the train 130 based on the speed data set.
The learning unit 373 performs a learning processing that is a process of learning a relationship between the position and the speed of the train and an optimal parameter value group.
The control unit 374 performs control (for example, transmitting the parameter value group to the wireless sensor node 201) to set an optimal parameter value group for the position and the speed specified by the specifying unit 372 in the wireless sensor node 201.
The parameter item table 362 includes a record for each type of the wireless sensor nodes 201. Each record stores information such as a sensor type name 401 and a parameter item group 402. One sensor type will be described as an example (“a target sensor type” in
The sensor type name 401 indicates a name of the target sensor type.
The parameter item group 402 is one or a plurality of parameter items respectively corresponding to one or a plurality of parameter values required in the wireless sensor nodes 201 belonging to the target sensor type. According to an example shown in
The operation management table 363 includes a record for each position/speed of the train 130. The “position/speed” refers to a set of a position and a speed. Each record stores information such as a position name 501, a speed 502, a period of time 503, a sensor ID 504, a date 505, measurement data 506, and a parameter value group 507. One position/speed will be described as an example (“a target position/speed” in
The position name 501 indicates a name of a position in the target position/speed. Here, the “position” is a position in a facility (for example, a structure) where the train 130 passes or stops. Types of the “facility” can be roughly classified into a space structure facility that forms a space through which the train 130 passes or stops, and a non-space structure facility that does not form such a space. Examples of the space structure facility include a tunnel (for example, a mountain tunnel or an underground tunnel), and an underground station platform. An example of the non-space structure facility includes a railroad bridge. For example, a line may be divided into a plurality of sections having different surrounding environments, and each section may correspond to a position.
The speed 502 indicates a speed of the target position/speed. The speed 502 may be a speed specified from a speed data set, or may be a pre-registered scheduled speed.
The period of time 503 indicates a time point range corresponding to the target position/speed. A “time point” is described in unit of second, minute, hour, day, month, and year. Alternatively, a unit of the time point may be rougher or finer, or may be a different unit.
The sensor ID 504 indicates an ID of the wireless sensor node 201 that performs measurement at the target position/speed. The date 505 indicates a date when the wireless sensor node 201 performs measurement at the target position/speed. The measurement data 506 is data including one or more values measured by the wireless sensor node 201 at the target position/speed, and is, for example, one or more measurement data sets. The parameter value group 507 is a parameter value group determined for the target position/speed in the wireless sensor node 201.
In the present embodiment, there is a preparation phase and an operation phase. The preparation phase is a phase in which an optimal parameter value group for each position/speed is learned for each wireless sensor node 201. The operation phase is a phase in which an optimal parameter value group for a changed position/speed is set in the wireless sensor node 201 each time a position/speed of the train 130 changes. The parameter value group set in the operation phase is a parameter value group learned in the preparation phase or a parameter value group that is re-learned in the operation phase.
Hereinafter, a processing in each of the preparation phase and the operation phase will be described with reference to
In an initial state (an initial mode), the wireless sensor node 201 acquires multiple points in one time measurement in an initial parameter value group (for example, a default parameter value group with which a vibration spectrum analysis can be performed) (S601). The wireless sensor node 201 stores a measurement data set including measured values in a memory of the control circuit 308, and transmits the measurement data set to the sensing control device 120 (S602). When the collection unit 371 of the sensing control device 120 receives the measurement data set (S611: Yes), the measurement data set is stored in the measurement table 361 (S612).
S601 and S602 are performed at a predetermined cycle X (for example, once per hour). For example, when the collection unit 371 of the sensing control device 120 issues a query to the wireless sensor node 201 at the cycle X, S601 and S602 may be performed by the wireless sensor node 201. For example, the collection unit 371 periodically (or non-periodically) receives a speed data set from the operation control device 100, specifies the period of time 503 to which a time point indicated by the speed data set belongs from the operation management table 363, and records the speed indicated by the speed data set in the operation management table 363 as the speed 502 corresponding to the period of time 503.
The learning unit 373 determines whether a learning condition (a condition for performing a learning processing) is satisfied (S621). The learning condition may be, for example, a condition in which a measurement data set group at a predetermined amount or a predetermined period (for example, one day) is accumulated in at least one wireless sensor node 201. When a determination result in S621 is false (S621: No), the collection unit 371 continues to collect a measurement data set.
When the determination result in S621 is true (S621: Yes), the learning unit 373 performs a learning processing (S622). In the learning processing, for example, the specifying unit 372 specifies a relationship of [position/speed/period of time] between the position/speed and the period of time based on the operation management table 363. Based on the specified relationship of [position/speed/period of time], the learning unit 373 determines an optimal parameter value group for the corresponding position/speed for one or more specified positions/speeds of the train by analyzing one or more measurement data set groups of one or more wireless sensor nodes 201 including the corresponding wireless sensor node 201. The control unit 374 registers the determined optimal parameter value group for each position/speed of the corresponding wireless sensor node 201 in the operation management table 363 as the parameter value group 507. One or a plurality of parameter items of one or a plurality of parameter values constituting the optimal parameter value group are specified from the parameter item table 362 using, for example, a sensor type name specified from the sensor ID 504 (for example, an ID including a sensor type name) corresponding to position/speed/period of time (a set of a position, a speed, and a period of time) as a key.
The specifying unit 372 of the sensing control device 120 determines whether the position/speed of the train 130 changes with reference to the operation management table 363 (S701). “A change in the position” may correspond to at least one of, for example, a case in which the train 130 exits a facility (facility indicated by the position name 501) in which the train 130 is present and a case in which the train 130 enters a facility in which the train 130 is not present. “A change in the speed” may refer to that, for example, the speed 502 close to a latest speed of the train 130 is shifted to another speed 502.
When a determination result in S701 is true (S701: Yes), the control unit 374 specifies an optimal parameter value group corresponding to the changed position/speed from the operation management table 363 for the corresponding wireless sensor node 201, and transmits, to the wireless sensor node 201, a measurement instruction that is an instruction for performing measurement according to the optimal parameter value group including the specified optimal parameter value group (S702). The wireless sensor node 201 receives the measurement instruction from the sensing control device 120, and sets the optimal parameter value group included in the measurement instruction (S711). The wireless sensor node 201 performs measurement according to the set optimal parameter value group (S712), and transmits a measurement data set indicating measured values to the sensing control device 120 (S713). When the collection unit 371 of the sensing control device 120 receives the measurement data set (S721: Yes), the measurement data set is stored in the operation management table 363 (specifically, the measurement data set is stored in the measurement data 506 corresponding to the changed position/speed.) (S722).
The number of samples and a data volume in the measurement according to the optimal parameter value group are smaller than those in the measurement according to the initial parameter value group. That is, in steps S712 and S713, data limited to the initial state is transmitted once. Therefore, measurement can be performed in a relatively high frequency even in view of average power consumption that can be achieved by the independent power supply system 301. In other words, a cycle Y of the measurement according to the optimal parameter value group can be made shorter than the above-described cycle X, that is, the measurement according to the optimal parameter value group can be performed at a higher frequency (for example, a frequency of once per minute) than the measurement according to the initial parameter value group.
The learning unit 373 determines whether the learning condition is satisfied (S731). When a determination result in S731 is true (S731: Yes), the learning unit 373 performs the learning processing (S732).
A method for determining a parameter value group in the learning processing may be a method shown in FIGS. 3A and 3B in US 2019/0005807, or may be a method shown in
The learning processing according to the method shown in
Based on the operation management table 363, the specifying unit 372 specifies a relationship of [position/speed/period of time] that is a relationship between a position/speed and a period of time. According to the example shown in
The learning unit 373 learns an optimal parameter value group of the sensor A for each of L1/V1, L2/V2, L3/V3, and L4/V4. Specifically, the learning unit 373 checks, for example, the following two items (1) and (2) related to each of the L1/V1, L2/V2, L3/V3, and L4/V4 for each of the parameter value groups A and B.
(1) The learning unit 373 checks whether there is a characteristic change in measurement values of the sensor A.
(2) The learning unit 373 checks whether a correlation with measurement values of the sensor B is high (whether there is a characteristic change in the measurement values of the sensor B).
The learning unit 373 determines, for each of the L1/V1, L2/V2, L3/V3, and L4/V4, a parameter value group in which both the two items (1) and (2) have positive results (“good”) as an optimal parameter value group. In the example shown in
When there is a position/speed for which not all of the two items (1) and (2) for any one of the parameter value groups has positive results (the optimal parameter value group=“unknown”), the learning unit 373 continues to learn an optimal parameter value group for the position/speed.
The method shown in
The embodiment described above can be summarized as follows. The following summary may include description (for example, a modification) not included in the above description.
The sensing control device 120 includes the specifying unit 372 and the control unit 374. The specifying unit 372 specifies a position of the train 130. For at least one wireless sensor node 201 among the one or the plurality of wireless sensor nodes 201, the control unit 374 determines a parameter value group of the wireless sensor node 201 corresponding to the specified position, and performs control to set the determined parameter value group in the wireless sensor node 201.
A surrounding environment of the wireless sensor node 201 installed on the train 130 changes with a movement of the train 130. When the surrounding environment changes, measurement performed according to a set parameter value group is not always optimal. Although a position and a speed are targeted as factors of the surrounding environment of the wireless sensor node 201 in the embodiment described above, the position is particularly targeted in the summary. One or both of a position and a speed may be used as a factor of the surrounding environment. Alternatively, other types of factors in addition to or instead of the one or both of a position and a speed may be used as factors of the surrounding environment. For example, the specifying unit 372 may specify a speed of the train 130 in addition to a position of the train 130, and the control unit 374 may determine, for at least one wireless sensor node 201, the parameter value group of the wireless sensor node 201 corresponding to the specified position and speed of the train 130.
The parameter value group that is set in the wireless sensor node 201 and affects the measurement is an optimal parameter value group for the position of the train 130. Accordingly, even when the surrounding environment of the wireless sensor node 201 changes with the movement of the train 130, optimal measurement by the wireless sensor node 201 can be maintained.
The “control to set the determined parameter value group” may be, for example, any one of the following.
“Specifying the position of the train 130” may refer to specifying any one of a previous position, a current position, and a future position of the train 130. The current position may be specified from, for example, a GPS signal. The previous position or the future position may be specified from management information (information including information indicating a relationship between a period of time and a position) such as the operation management table 363.
Alternatively, “specifying the position of the train 130” may refer to specifying which type of facility among one or more types of facilities the train 130 is positioned at. When the position of the train 130 changes from a first position (a position in a first type of facility (any one type of facility)) to a second position (a position in a second type of facility (any one type of facility other than the first type of facility)) (for example, S701: Yes), the control unit 374 performs control, for each of at least one wireless sensor node 201 among the one or the plurality of wireless sensor nodes 201, to change a parameter value group of the wireless sensor node 201 to a parameter value group corresponding to the second position. In this manner, even when the position of the train 130 changes, optimal measurement can be maintained.
Similar to the “control to set the determined parameter value group”, the “control to change to the parameter value group corresponding to the second position” may be, for example, any one of the following.
The control unit 374 may select one or more wireless sensor nodes 201 according to which type of facility the specified position is at, and may determine, for each of the selected one or more wireless sensor nodes 201, a parameter value group corresponding to the specified position. That is, required sensor types may be different depending on a position (facility). For example, in a space structure facility such as a tunnel, measurement by the gas sensor node 201C is considered to be valid, and at a position other than the space structure facility (for example, outdoors), measurement by the gas sensor node 201C is considered to be unnecessary. Unnecessary measurement is performed, which results in wasteful power in the wireless sensor node 201. Such a problem can be avoided. The selected “one or more wireless sensor nodes 201” are one or more wireless terminals 201 specified from, for example, the operation management table 363. Examples of a position and the wireless sensor node 201 are as follows.
The position of the train 130 may be specified, for example, based on the operation management table 363 including the information indicating the relationship between the period of time and the position of the train 130. The operation management table 363 or operation information (such as diagram information) based on the table 363 is information used for controlling operation of the train 130, and such information may be effectively used for specifying the position of the train 130 so as to perform sensing control. As shown in
The collection unit 371 may collect a measurement data set from each of the one or the plurality of wireless sensor nodes 201. For each of the wireless sensor nodes 201, the learning unit 373 may perform a learning processing of learning the relationship between the position of the train 130 and the optimal parameter value group. For each of the wireless sensor nodes 201, the learning processing may include determining, for each of one or more specified positions of the train 130, the optimal parameter value group for the position by analyzing one or more measurement data set groups of one or more wireless sensor nodes 201 including the wireless sensor node 201 based on the operation management table 363. The relationship between the position of the train 130 and the optimal parameter value group can be maintained by performing such a learning processing.
The independent power supply system 301 of the gas sensor node 201C may include a solar cell. As shown in
For example, as shown in
Although one embodiment has been described above, the embodiment is merely an example for describing the invention, and is not intended to limit the scope of the invention to the embodiment. The invention can be implemented in various other forms.
For example, the position of the train 130 may be specified based on at least a part of speed information, positioning information (such as information from a GPS sensor), and other information instead of or in addition to the operation management table 363. The operation management table 363 may be generated based on diagram information of the train 130. For example, a measurement value of the wireless sensor node 201 such as the illuminance sensor node 201G may be used to detect whether the train 130 is in the space structure facility such as the tunnel.
For example, the speed of the train 130 may be specified (estimated) from at least one measurement value of the sound sensor node 201A, the barometric pressure sensor node 201F, and the air flow sensor node 201I, instead of the speed data set from the operation control device 100.
The invention may be applied to a moving object other than the train, such as an automobile (a bus serving as atypical example having operation management information) and an aircraft (utilizing flight management information of the aircraft). Further, the moving object may be a bicycle or a pedestrian by utilizing position information from a GPS sensor instead of or in addition to the operation management information.
| Number | Date | Country | Kind |
|---|---|---|---|
| 2020-006356 | Jan 2020 | JP | national |
