JP6772486B2 - Sensor data processing device, sensor data processing system, sensor data processing method, and sensor data processing program - Google Patents

Description

The present invention relates to a technique of collecting measurement results by a plurality of sensors and transmitting the measurement results to an apparatus using the measurement results.

In recent years, a technology called IoT (Internet of Things), in which a large number of various terminals or sensors are connected to the Internet to collect data, analyze it as big data, and use it, has attracted attention. In order to realize such IoT, it is possible to reliably and efficiently collect measurement results (hereinafter, may be referred to as "measurement data" or simply "data" in the present application) from a large number of sensors and the like. Technology is expected.

As an example of such a technique, Patent Document 1 discloses an information collecting device for grouping measurement data necessary for presenting presentation information. This device has a data collection timing adjusting unit and a data acquisition unit. The data collection timing adjustment unit adjusts so that the collection timing of the measurement data in the group is synchronized. The data acquisition unit acquires measurement data from one or a plurality of measurement devices (sensors) at the collection timing adjusted by the data collection timing adjustment unit.

Further, Patent Document 2 discloses a sensor node that collects sensor data in a hierarchical tree-structured network topology. This sensor node divides the sensor data series into partial data series, and singularly decomposes the processed data series obtained by collecting a certain number of these partial data series to obtain a plurality of base series common to the partial data series. calculate. This sensor node selects a predetermined number of reference base series as approximate base series that approximate the base series in the order of the degree of contribution to the restoration of sensor data among these base series. Based on the obtained approximate base series, this sensor node calculates an approximate coefficient series for obtaining the partial data series by the linear weighted sum of the approximate base series for each partial data series. Then, this sensor node transmits the approximate base series and the approximate coefficient series of the processed data series as compressed data of the original sensor data by wireless communication.

Further, Patent Document 3 discloses a data classification device that classifies a plurality of input data into a plurality of categories. The device selects the prototype in the category closest to the read input data and evaluates whether the selected prototype is valid. This device adds a prototype if the selected prototype is not valid. This device corrects at least one of the region determination parameters and the prototype that define the size of the region of the category for each category, if the prototype selected is valid.

Further, in Patent Document 4, the information terminal collects the measured value from the meter and reads the meter by performing wireless communication between the master unit connected to the information terminal and the slave unit connected to the meter. A wireless meter reading system that performs the above is disclosed. In this system, the slave unit periodically acquires the measured value from the meter and sequentially accumulates the measured value in the measured value accumulating means. The data compression means in this system compresses the measured values stored in the measured value accumulating means. The data compression notification means in this system generates communication mode information indicating that the compressed data is transmitted. Then, the wireless transmission means in this system responds to the meter reading request from the master unit, adds communication mode information to the data compressed by the data compression means, and transmits the data to the master unit.

JP-A-2015-80116 Japanese Unexamined Patent Publication No. 2012-44449 Japanese Patent Application Laid-Open No. 2009-42997 Japanese Unexamined Patent Publication No. 2006-277378

In the above-mentioned IoT, when the server that collects information from the sensor is installed in a specific place such as a data center, the response is delayed due to the long distance from the terminal or sensor to the server. There is a problem that it ends up. In addition, since the amount of data to be processed increases as the number of sensors increases, the processing load in the data center or the load on the transmission path for transferring data from the sensor to the data center increases, and the response is further delayed. Occurs.

In order to deal with such a problem, a technique called edge computing is used in various systems. In this edge computing, geographically distributed edge servers are connected to a center server in a data center, and sensors and terminals are connected to neighboring edge servers. Then, the edge server collects output data from the sensor or the terminal, and performs primary analysis, processing, storage, and the like. The edge server can reduce the load on the center server and the transmission path by collectively sending the primary processed data to the center server.

In recent years, the number of terminals and sensors connected to the Internet has increased rapidly due to the automatic operation of equipment or the progress of centralized management of equipment, and the amount of data collected from those terminals and sensors has exploded. It is increasing. Due to such an increase in the amount of data, there is a problem that the amount of data stored in the edge server and the center server and the load on the transmission path for transferring data from the edge server to the center server are rapidly increasing. In order to deal with such a problem, for example, it is conceivable to compress the data collected from the sensor, but in that case, it is a problem to realize the information compression at low cost and with high efficiency. It cannot be said that the techniques described in Patent Documents 1 to 4 described above are sufficient to solve this problem. A main object of the present invention is to provide a sensor data processing device or the like that solves this problem.

The sensor data processing device according to one aspect of the present invention includes an acquisition means for obtaining measurement results by a plurality of sensors that individually measure values indicated by a plurality of measurement targets at predetermined timings, and the acquisition means obtained by the acquisition means. A calculation means for calculating the maximum value and the minimum value in the measured value indicated by the measurement result, a determination means for determining whether or not the difference between the maximum value and the minimum value satisfies a predetermined condition, and the difference is a predetermined value. When the conditions are satisfied, the normalization means that performs information compression by normalization on the measured value based on the calculation result by the calculation means, and the normalization control information that represents the control content of the information compression by the normalization. An output means for outputting the measured value obtained by performing the information compression by the normalization means to an external device.

From another point of view of achieving the above object, the sensor data processing method according to one aspect of the present invention measures measurement results by a plurality of sensors individually measuring values indicated by a plurality of measurement targets by an information processing apparatus at a predetermined timing. The maximum value and the minimum value in the measured value indicated by the obtained measurement result are calculated, it is determined whether or not the difference between the maximum value and the minimum value satisfies a predetermined condition, and the difference is a predetermined value. When the above conditions are satisfied, information compression by normalization is performed on the measured value based on the calculation results of the maximum value and the minimum value, and the normalization control information representing the control content of the information compression by the normalization is obtained. , The measured value obtained by information compression by the normalization is output to an external device.

Further, from the further viewpoint of achieving the above object, the sensor data processing program according to one aspect of the present invention obtains measurement results by a plurality of sensors that individually measure values indicated by a plurality of measurement targets at predetermined timings. Whether or not the acquisition process, the calculation process for calculating the maximum value and the minimum value in the measurement value indicated by the measurement result obtained by the acquisition process, and the difference between the maximum value and the minimum value satisfy a predetermined condition. The determination process for determining the above, the normalization process for compressing information by normalization for the measured value based on the calculation result by the calculation process when the difference satisfies a predetermined condition, and the normalization process. To make a computer execute a normalization control information representing the control content of information compression and an output process of outputting the measured value obtained by the normalization process to compress the information to an external device. It is a program.

Further, the present invention can also be realized by a computer-readable, non-volatile recording medium in which the sensor data processing program (computer program) is stored.

The present invention makes it possible to dynamically improve the efficiency of a device that collects measurement results by a large number of sensors to transmit the measurement results to another device by a simple configuration.

It is a block diagram which shows the structure of the sensor data processing system 1 which concerns on 1st Embodiment of this invention. It is a figure which illustrates the structure of the acquisition measurement value information 160 which concerns on 1st Embodiment of this invention. It is a figure which illustrates the structure of the output measurement value information 170 which concerns on 1st Embodiment of this invention. It is a flowchart which shows the operation of the sensor data processing apparatus 10 which concerns on 1st Embodiment of this invention. It is a flowchart which shows the operation of the external device 40 which concerns on 1st Embodiment of this invention. It is a figure which illustrates the time transition of the value which each sensor which concerns on 1st Embodiment of this invention has a measurement target. It is a block diagram which shows the structure of the sensor data processing apparatus 50 which concerns on 2nd Embodiment of this invention. It is a block diagram which shows the structure of the information processing apparatus which can execute the sensor data processing apparatus which concerns on each embodiment of this invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

<First Embodiment>
FIG. 1 is a block diagram conceptually showing the configuration of the sensor data processing system 1 according to the first embodiment of the present invention. The sensor data processing system 1 is a system that collects data measured by a large number of sensors and analyzes the collected data as, for example, big data.

The sensor data processing system 1 according to the present embodiment is roughly classified into a sensor data processing device 10, sensors 20-1 to 20-n (n is an arbitrary integer of 2 or more), a communication network 30, and an external device 40. Have.

The sensors 20-1 to 20-n are, for example, sensors that measure the same type of measurement target, and in the present embodiment, for example, the power consumption (power consumption) of n houses in a building such as an apartment is individually measured. .. The sensors 20-1 to 20-n are, for example, smart meters in a smart grid. The sensors 20-1 to 20-n may be sensors that measure a measurement target other than the power consumption, such as room temperature.

The sensors 20-1 to 20-n transmit the measurement result and the identifier that identifies the own sensor to the center data processing device 10 at any time. When the sensors 20-1 to 20-n are connected to the center data processing device 10 by, for example, Ethernet (registered trademark), the sensors 20-1 to 20-n transmit an IP (Internet Protocol) address as the identifier. The sensors 20-1 to 20-n may be individually connected to n communication ports included in the sensor data processing device 10. In that case, the sensors 20-1 to 20-n do not have to transmit the identifier that identifies the own sensor to the center data processing device 10.

The sensor data processing device 10 is, for example, an edge server installed in the vicinity of the sensors 20-1 to 20-n and included in a building management system or the like, and obtains data measured by the sensors 20-1 to 20-n. collect. The sensor data processing device 10 includes an acquisition unit 11, a calculation unit 12, a determination unit 13, a normalization unit 14, an output unit 15, an input storage unit 16, and an output storage unit 17.

The acquisition unit 11 includes a sampling timer 110. The sampling timer 110 is a timer for the acquisition unit 11 to measure the timing (sampling timing) for capturing the measurement result and the identifier transmitted from the sensors 20-1 to 20-n. The acquisition unit 11 may acquire the measurement results output from the sensors 20-1 to 20-n at any time at the sampling timing, or obtain the measurement results by accessing the sensors 20-1 to 20-n. In some cases.

When the sampling timer 110 indicates the sampling timing, the acquisition unit 11 stores the measurement result as the input measurement value information 160 in the input storage unit 16. The input storage unit 16 is a storage device such as an electronic memory or a magnetic disk.

FIG. 2 is a diagram illustrating the configuration of the input measured value information 160 according to the present embodiment. As illustrated in FIG. 2, the input measured value information 160 is information in which the measured values X (1) to X (n) output from the sensors 20-1 to 20-n are stored. In FIG. 2, the measured value X (i) output from the sensor 20-i (i is an integer of 1 to n) is stored as the measured value output from the sensor #i.

The calculation unit 12 shown in FIG. 1 has a maximum measurement value Xmax, which is the maximum value among the measurement values X (1) to X (n) obtained by the acquisition unit 11, and a minimum measurement value, which is the minimum value. Calculate Xmin.

The determination unit 13 calculates the difference between the maximum measured value Xmax calculated by the calculation unit 12 and the minimum measured value Xmin, and determines whether or not the difference is equal to or less than the normalization determination threshold value A. The determination unit 13 inputs the determination result to the normalization unit 14. In addition, whether the difference satisfies a predetermined condition by changing the determination standard according to the measurement target measured by the sensors 20-1 to 20-n or the communication environment of the communication network 30 or the like. It may be determined whether or not.

When the determination unit 13 determines that the difference between the maximum measured value Xmax and the minimum measured value Xmin is larger than the normalization determination threshold value A, the normalization unit 14 outputs the obtained measured value information 160 as it is. The information 170 is stored in the output storage unit 17. When the determination unit 13 determines that the difference between the maximum measured value Xmax and the minimum measured value Xmin is equal to or less than the normalization determination threshold value A, the normalization unit 14 sends the input storage unit 16 as the obtained measurement value information 160. Information compression processing by normalization is performed on the stored measured values X (1) to X (n) according to the following procedure.

That is, the normalization unit 14 calculates the normalized measured values Y (1) to Y (n) by subtracting Xmin from the measured values X (1) to X (n). Therefore, the normalized measured values Y (1) to Y (n) are measured values based on Xmin. In this case, the number of bits representing the measured values X (1) to X (n) (that is, the value indicating the dynamic range of the signal output by the sensors 20-1 to 20-n) is a, and the normalized measurement is performed. Assuming that the number of bits representing the values Y (1) to Y (n) is b, there is a relationship of “a ≧ b”.

This relationship will be described with a concrete example. For example, it is assumed that the measured values X (1) to X (n) are represented by 8 bits (that is, "a = 8"). Then, it is assumed that Xmax is "79" and Xmin is "64" at any of the sampling timings. In this case, the difference between Xmax and Xmin is "15", so that the normalized measured values Y (1) to Y (n) are any of 0 to 15. Therefore, the normalized measurements Y (1) to Y (n) can be represented by 4 bits (ie, "b = 4"). Generally, b can be calculated as the integer part excluding the decimal point indicated by "log ₂ (Xmax-Xmin) +1"("log ₂ " represents the logarithm with "2" as the base). it can.

The normalization unit 14 calculates b using the above-mentioned mathematical formula, and then expresses the normalized measured values Y (1) to Y (n) packed in b bits to represent the normalized measured value. Y (1) to Y (n) are stored in the output storage unit 17 as output measurement value information 170. The output storage unit 17 is a storage device such as an electronic memory or a magnetic disk.

FIG. 3 is a diagram illustrating the configuration of the output measurement value information 170 according to the present embodiment. As shown in FIG. 3, the output measurement value information 170 includes “number of sensors”, “minimum value”, “number of bits before normalization”, in addition to the normalized measurement values Y (1) to Y (n). It contains normalization control information including the item "number of bits after normalization". The “number of sensors” is the number of sensors for which the sensor data processing device 10 collects measured values, and is “n” in the present embodiment. The "minimum value" is the minimum measured value Xmin. The “number of bits before normalization” is the number of bits representing the measured values X (1) to X (n), and is “a” in the present embodiment. The “number of bits after normalization” is the number of bits representing the normalized measured values Y (1) to Y (n), and is “b” in the present embodiment. The normalization unit 14 associates the normalization control information with the normalized measured values Y (1) to Y (n), and stores the normalized measurement value information 170 as the output measured value information 170 in the output storage unit 17.

The output unit 15 reads out the output measurement value information 170 stored in the output storage unit 17 and transmits the output measurement value information 170 to the external device 40 via the communication network 30. The communication network 30 may be the Internet, or may be a dedicated communication network that connects the sensor data processing device 10 and the external device 40.

The external device 40 is, for example, a center server installed in a data center or the like. The external device 40 normalizes the normalized measured values Y (1) to Y (n) by using the normalized control information included in the output measured value information 170 received from the sensor data processing device 10. The measured values X (1) to X (n) before the information compression is performed by. The external device 40 analyzes the measured values X (1) to X (n) as big data.

Next, the operation (processing) of the sensor data processing device 10 according to the present embodiment will be described in detail with reference to the flowchart of FIG.

The acquisition unit 11 refers to the sampling timer 110 and confirms whether it is the timing to acquire the measured value from each sensor (step S101). If it is not the timing to obtain the measured value (No in step S102), the process returns to step S101.

When it is time to obtain the measured value (Yes in step S102), the obtaining unit 11 obtains the measured value from the sensors 20-1 to 20-n (step S103). The acquisition unit 11 stores the acquired measurement value as the acquisition measurement value information 160 in the input storage unit 16 (step S104).

The calculation unit 12 calculates the maximum measured value Xmax and the minimum measured value Xmin from the measured values obtained by the acquisition unit (step S105). The determination unit 13 determines whether or not the difference between the maximum measured value Xmax and the minimum measured value Xmin is equal to or less than the normalization determination threshold value A (step S106).

When the difference is larger than the normalization determination threshold value A (No in step S107), the normalization unit 14 stores the obtained measurement value information 160 as the output measurement value information 170 in the output storage unit 17 (step). S111). The output unit 15 transmits the output measurement value information 170 stored in the output storage unit 17 to the external device 40 (step S112), and the entire process ends.

When the difference is equal to or less than the normalization determination threshold value A (Yes in step S107), the normalization unit 14 determines the number of bits after normalization “b” from the logarithm of the difference between the maximum measured value Xmax and the minimum measured value Xmin. "(Step S108). The normalization unit 14 stores the normalization control information as output measurement value information 170 in the output storage unit 17 (step S109). The normalization unit 14 packs the value obtained by subtracting the minimum measured value Xmin from each measured value in the obtained measured value information 160 into b bits, and outputs the output measured value information 170 by associating it with the normalized control information. It is stored in the unit 17 (step S110), and the process proceeds to step S112.

Next, the operation (processing) of the external device 40 according to the present embodiment will be described in detail with reference to the flowchart of FIG.

The external device 40 receives the output measurement value information 170 transmitted from the sensor data processing device 10 (step S201). The external device 40 confirms whether or not the received output measurement value information 170 includes the normalization control information (step S202).

When the output measurement value information 170 does not include the normalization control information (No in step S203), the external device 40 executes the process for the output measurement value information 170 (step S205), and the entire process ends. When the output measurement value information 170 includes the normalization control information (Yes in step S203), the external device 40 compresses the output measurement value information 170 by normalization by using the normalization control information. The value is returned to the previous value (step S204), and the process proceeds to step S205.

The sensor data processing device 10 according to the present embodiment can dynamically improve the efficiency of transmitting measurement results by a large number of collected sensors to an external device by a simple configuration. The reason is that the sensor data processing device 10 calculates the difference between the maximum value and the minimum value in the measurement result obtained from the sensor at a predetermined timing, and when the difference is equal to or less than the threshold value, the difference is obtained with respect to the measurement result. This is because information is compressed by normalization.

The effects realized by the sensor data processing device 10 according to the present embodiment will be described in detail below.

In recent years, the number of terminals and sensors connected to the Internet has increased rapidly due to the automatic operation of equipment or the progress of centralized management of equipment, and the amount of data collected from those terminals and sensors has exploded. It is increasing. Due to such an increase in the amount of data, there is a problem that the amount of data stored in the edge server and the center server and the load on the transmission path for transferring data from the edge server to the center server are rapidly increasing. In order to deal with such a problem, for example, it is conceivable to compress the data collected from the sensor, but in that case, it is a problem to realize the information compression at low cost and with high efficiency.

FIG. 6 is a diagram illustrating a time transition of a value measured by the sensors 20-1 to 20-n according to the present embodiment. As shown in FIG. 6, the values of the power consumption of the plurality of houses measured by the sensors 20-1 to 20-n according to the present embodiment may be similar to each other or greatly different depending on the time zone. is there. For example, in the early morning or late night, the residents are at home in each house, so that the power consumption values of the plurality of houses are often similar to each other. On the other hand, during the daytime hours, some houses have no residents and some have residents at home, so the power consumption values of multiple houses often differ greatly from each other.

Further, even when the sensors 20-1 to 20-n according to the present embodiment monitor the operating status of a mechanical or industrial plant, the measured values may be similar to each other depending on the time zone. If so, it can be very different. For example, the sensors 20-1 to 20-n individually monitor the operating status of a plurality of machines that may perform the same process or different processes depending on the stage in the manufacturing process. In this case, when the plurality of machines are performing the same processing, the measured values by the sensors 2-1 to 20-n are similar to each other, and when the plurality of machines are performing different processing, the sensors. The measured values from 20-1 to 20-n will be significantly different from each other.

When the values measured by the sensors 20-1 to 20-n are similar to each other (that is, the difference between the maximum value and the minimum value of the measured values is small), the efficiency of information compression by normalization becomes high. On the contrary, when the measured values by the sensors 20-1 to 20-n are significantly different from each other (that is, the difference between the maximum value and the minimum value of the measured values is large), the efficiency of information compression by normalization becomes low. ..

When the edge server compresses the measured value and sends it to the center server, the edge server undergoes the process of compressing the measured value, and the center server undergoes the process of returning the compressed measured value to the original value. .. Therefore, when the efficiency of information compression is low, the effect of the overhead associated with information compression is greater than the effect of information compression. Therefore, information compression causes the efficiency of transmitting measured values to decrease. It becomes. As described above, when the value of the power consumption of a plurality of houses is to be measured, the efficiency of information compression varies greatly depending on the time zone. Therefore, for example, when information compression is always performed, the measured value depends on the time zone. Will be less efficient to send.

In response to such a problem, in the sensor data processing device 10 according to the present embodiment, the acquisition unit 11 obtains measured values from sensors 20-1 to 20-n that individually measure values indicated by a plurality of measurement targets. Obtain at the specified timing. The calculation unit 12 calculates the maximum measured value Xmax and the minimum measured value Xmin in the measured values obtained by the acquisition unit 11. The determination unit 13 determines whether or not the difference between the maximum measured value Xmax and the minimum measured value Xmin is equal to or less than the normalization determination threshold value A. When the difference is equal to or less than the normalization determination threshold value A, the normalization unit 14 performs information compression by normalization on the measured value based on the calculation result by the calculation unit 12.

That is, the sensor data processing device 10 according to the present embodiment determines for each sampling timing (that is, dynamically) whether or not the effect of information compression by normalization is greater than the effect of overhead due to information compression. The necessity of information compression is determined according to the determination result. Specifically, the sensor data processing device 10 executes information compression by normalization at the sampling timing t1 shown in FIG. 6, and does not execute information compression by normalization at the sampling timing t2. Then, the sensor data processing device 10 according to the present embodiment has a simple calculation process called normalization (that is, calculation cost (load)) using the maximum value and the minimum value of the measured values used when performing the determination as they are. Information is compressed by arithmetic processing) that does not use a large and complicated information compression algorithm. As a result, the sensor data processing device 10 according to the present embodiment can dynamically improve the efficiency of transmitting the measurement results of a large number of collected sensors to the external device by a simple configuration.

<Second embodiment>
FIG. 7 is a block diagram conceptually showing the configuration of the sensor data processing device 50 according to the second embodiment.

The sensor data processing device 50 according to the present embodiment includes an acquisition unit 51, a calculation unit 52, a determination unit 53, a normalization unit 54, and an output unit 55.

The acquisition unit 51 acquires the measurement results by a plurality of sensors 60-1 to 60-n (n is an arbitrary integer of 2 or more) that individually measures the values indicated by the plurality of measurement targets at a predetermined timing.

The calculation unit 52 calculates the maximum value and the minimum value of the measured values indicated by the measurement results obtained by the acquisition unit 51.

The determination unit 53 determines whether or not the difference between the maximum value and the minimum value satisfies a predetermined condition.

When the difference satisfies a predetermined condition, the normalization unit 54 performs information compression by normalization on the measured value based on the calculation result by the calculation unit 52.

The output unit 55 outputs the normalization control information representing the control content of the information compression by the normalization and the measured value obtained by the information compression by the normalization by the normalization unit 54 to the external device 70.

The sensor data processing device 50 according to the present embodiment can dynamically improve the efficiency of transmitting measurement results by a large number of collected sensors to an external device by a simple configuration. The reason is that the sensor data processing device 50 calculates the difference between the maximum value and the minimum value in the measurement result obtained from the sensor at a predetermined timing, and when the difference satisfies the predetermined condition, the measurement result is obtained. This is because information is compressed by normalization.

<Hardware configuration example>
In each of the above-described embodiments, each part of the sensor data processing device shown in FIGS. 1 and 7 can be realized by a dedicated HW (HardWare) (electronic circuit). Further, in FIGS. 1 and 7, at least the following configuration can be regarded as a function (processing) unit (software module) of the software program.
・ Acquisition parts 11 and 51,
・ Calculation units 12 and 52,
・ Judgment units 13 and 53,
・ Normalization units 14 and 54,
-Output units 15 and 55.

However, the division of each part shown in these drawings is a configuration for convenience of explanation, and various configurations can be assumed at the time of mounting. An example of the hardware environment in this case will be described with reference to FIG.

FIG. 8 is a diagram illustrating an example of a configuration of an information processing device 900 (computer) capable of executing the sensor data processing device according to each embodiment of the present invention. That is, FIG. 8 is a configuration of a computer (information processing device) capable of realizing the sensor data processing device shown in FIGS. 1 and 7, and represents a hardware environment capable of realizing each function in the above-described embodiment. ..

The information processing apparatus 900 shown in FIG. 8 includes the following as components.
-CPU (Central_Processing_Unit) 901,
-ROM (Read_Only_Memory) 902,
・ RAM (Random_Access_Memory) 903,
-Hard disk (storage device) 904,
-Communication interface 905 with an external device,
・ Bus 906 (communication line),
A reader / writer 908 that can read and write data stored in a recording medium 907 such as a CD-ROM (Compact_Disc_Read_Only_Memory),
-Input / output interface 909.

That is, the information processing device 900 including the above components is a general computer in which these components are connected via the bus 906. The information processing apparatus 900 may include a plurality of CPUs 901 or may include a CPU 901 configured by a multi-core processor.

Then, the present invention described by taking the above-described embodiment as an example supplies the computer program capable of realizing the following functions to the information processing apparatus 900 shown in FIG. The function is the above-described configuration in the block configuration diagrams (FIGS. 1 and 7) referred to in the description of the embodiment, or the function of the flowchart (FIG. 4). The present invention is then achieved by reading, interpreting, and executing the computer program in the CPU 901 of the hardware. Further, the computer program supplied in the device may be stored in a readable / writable volatile memory (RAM 903) or a non-volatile storage device such as a hard disk 904.

Further, in the above case, as a method of supplying the computer program into the hardware, a general procedure can be adopted at present. As the procedure, for example, there are a method of installing in the device via various recording media 907 such as a CD-ROM, a method of downloading from the outside via a communication line such as the Internet, and the like. Then, in such a case, the present invention can be regarded as being composed of a code constituting the computer program or a recording medium 907 in which the code is stored.

The invention of the present application has been described above using the above-described embodiment as a model example. However, the present invention is not limited to the above-described embodiments. That is, the present invention can apply various aspects that can be understood by those skilled in the art within the scope of the present invention.

1 Sensor data processing system 10 Sensor data processing device 11 Acquisition unit 110 Sampling timer 12 Calculation unit 13 Judgment unit 14 Normalization unit 15 Output unit 16 Input storage unit 160 Obtained measurement value information 17 Output storage unit 170 Output measurement value information 20-1 ~ 20-n sensor 30 communication network 40 external device 50 sensor data processing device 51 acquisition unit 52 calculation unit 53 judgment unit 54 normalization unit 55 output unit 60-1 to 60-n sensor 70 external device 900 information processing device 901 CPU
902 ROM
903 RAM
904 hard disk (storage device)
905 Communication interface 906 Bus 907 Recording medium 908 Reader / writer 909 Input / output interface

Claims (10)

A means of obtaining measurement results by a plurality of sensors that individually measure values indicated by a plurality of measurement targets at a predetermined timing, and an acquisition means.
A calculation means for calculating the maximum value and the minimum value in the measured values indicated by the measurement results obtained by the acquisition means, and
A determination means for determining whether or not the difference between the maximum value and the minimum value satisfies a predetermined condition,
If the difference satisfies a predetermined condition, based on the calculation result by the calculating means, have the line information compression by normalizing with respect to the measured value, if the difference does not satisfy the predetermined condition, the Normalization means that does not compress the information on the measured value ,
An output means for outputting the normalization control information representing the control content of information compression by the normalization and the measured value obtained by the information compression by the normalization means to an external device.
A sensor data processing device equipped with. The predetermined condition indicates that the effect of the information compression due to the normalization is greater than the effect of the overhead associated with the information compression.
The sensor data processing device according to claim 1. The determination means determines whether or not the difference is equal to or less than a threshold value.
The sensor data processing device according to claim 1 or 2 . The normalizing means obtains a value obtained by subtracting the minimum value from each of the measured values represented by using the first bit number, and obtains the value obtained from the difference from the first bit number. Information compression by the normalization is performed by expressing using a second number of bits having a smaller value than.
The sensor data processing device according to any one of claims 1 to 3 . The normalization means obtains the second bit number by calculating the logarithm of the difference.
The sensor data processing device according to claim 4 . An input storage means for storing the measured value obtained by the acquisition means at the predetermined timing is further provided.
The sensor data processing device according to any one of claims 1 to 5 . An output storage means for storing the measured value obtained by compressing the information by the normalization by the normalization means and the normalization control information is further provided.
The output means outputs the measured value stored in the output storage means and the normalized control information.
The sensor data processing device according to any one of claims 1 to 6 . The sensor data processing device according to any one of claims 1 to 7.
With the plurality of sensors
With the external device
Sensor data processing system with. Depending on the information processing device
Obtain the measurement results by multiple sensors that individually measure the values indicated by multiple measurement targets at a predetermined timing, and obtain them.
Calculate the maximum and minimum values of the measured values indicated by the obtained measurement results,
It is determined whether or not the difference between the maximum value and the minimum value satisfies a predetermined condition.
When the difference satisfies a predetermined condition, information compression by normalization is performed on the measured value based on the calculation result of the maximum value and the minimum value, and when the difference does not satisfy the predetermined condition. , Do not perform the information compression on the measured value,
The normalization control information representing the control content of the information compression by the normalization and the measured value obtained by the information compression by the normalization are output to an external device.
Sensor data processing method. The acquisition process to obtain the measurement results by multiple sensors that individually measure the values indicated by multiple measurement targets at a predetermined timing, and
A calculation process for calculating the maximum and minimum values in the measured values indicated by the measurement results obtained by the acquisition process, and
A determination process for determining whether or not the difference between the maximum value and the minimum value satisfies a predetermined condition, and
If the difference satisfies a predetermined condition, based on the calculation result of the calculation process, have rows of information compression by normalizing with respect to the measured value, if the difference does not satisfy the predetermined condition, the Normalization processing that does not compress the information on the measured value ,
An output process for outputting the normalization control information representing the control content of information compression by the normalization and the measured value obtained by the information compression by the normalization by the normalization process to an external device.
A sensor data processing program that lets a computer run.

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