JP2014071495A - Data management method, information processor, and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To appropriately classify sensor data received from a plurality of sensor devices.SOLUTION: A receiving section 11 receives, from each of sensor devices 21 and 22, sensor data to which identification information is added by the sensor device. On the basis of a determination rule stored in a determination information storage section for storing the determination rule indicating the regularity of the sensor data to which the same identification information is added, a data processing section 12 determines whether or not two or more sensor devices use the same identification information, and, according to the result of the determination, classifies the sensor data to which the same identification information is added.

Description

  The present invention relates to a data management method, an information processing apparatus, and a program.

  Currently, a sensor network system that collects and analyzes sensor data generated by a plurality of sensor devices has been proposed. The sensor data indicates physical states detected by various sensors. For example, a system that collects and monitors sensor data indicating power consumption from a sensor device mounted on a power strip and controls a power strip or an electronic device connected to the power strip according to fluctuations in power consumption can be considered. . Also, sensor data indicating the current position is collected and monitored from the sensor device mounted on the mobile terminal device, and if a mobile terminal device that has moved beyond the permitted range is detected, use of the mobile terminal device is restricted. A system that can be considered.

  Regarding mobility management, ID (Identification) is given to the vehicle-mounted device at the entrance of the expressway, and IDs transmitted by the vehicle-mounted device are monitored in the middle of the expressway or at the exit to detect duplication or disappearance of IDs. Therefore, a system for detecting unauthorized use of the vehicle-mounted device has been proposed. In addition, regarding a duplicated ID, a broadcast station system that controls a plurality of content transmission devices, and when different program information having the same event ID is registered in the program timetable, the event ID is temporarily renamed. Has proposed a system that performs normal transmission control.

JP 2001-67584 A JP 2009-182610 A

  By the way, in a system that collects sensor data from a plurality of sensor devices, each sensor device may give consistent identification information to the sensor data so that a set of sensor data generated by the same sensor device can be identified. . The identification information used by each sensor device is preferably different from the communication address assigned to that sensor device. By using identification information different from the communication address, the communication address of the sensor device can be allowed to change, and the degree of freedom in network design can be increased. For example, the sensor device can dynamically acquire an IP (Internet Protocol) address from a DHCP (Dynamic Host Configuration Protocol) server, or the sensor device can move across multiple network segments with different network addresses. it can.

  However, when each sensor device voluntarily gives identification information to sensor data, there is a problem that two or more sensor devices may use the same identification information. For example, the same identification information may be accidentally set in different sensor devices by different users. Further, there is a possibility that the identification information set in the sensor device is falsified so that the identification information is duplicated due to malicious intention (for example, to confuse the system). If the collected sensor data includes sensor data to which the same identification information is given despite being generated by different sensor devices, the sensor data cannot be used easily.

  In one aspect, an object of the present invention is to provide a data management method, an information processing device, and a program for appropriately classifying sensor data received from a plurality of sensor devices.

  In one aspect, a data management method executed by an information processing system is provided. In the data management method, sensor data to which identification information is added by the sensor device is received from each of the plurality of sensor devices. Two or more sensor devices that use the same identification information based on the determination rule stored in the determination information storage unit that stores the determination rule indicating the regularity of the sensor data to which the same identification information is added Determine if there is. The sensor data to which the same identification information is added is classified according to the determination result.

  In one aspect, an information processing apparatus having a receiving unit and a data processing unit is provided. The receiving unit receives sensor data to which identification information is added by the sensor device from each of the plurality of sensor devices. The data processing unit uses the same identification information based on the determination rule stored in the determination information storage unit that stores the determination rule indicating the regularity of the sensor data to which the same identification information is added. It is determined whether there are two or more sensor devices, and the sensor data to which the same identification information is added is classified according to the determination result.

  In one embodiment, a program to be executed by a computer is provided. A computer that executes the program receives sensor data to which identification information is added by each of the plurality of sensor devices. Two or more sensor devices that use the same identification information based on the determination rule stored in the determination information storage unit that stores the determination rule indicating the regularity of the sensor data to which the same identification information is added Determine if there is. The sensor data to which the same identification information is added is classified according to the determination result.

  In one aspect, sensor data received from a plurality of sensor devices can be appropriately classified.

It is a figure which shows the information processing apparatus of 1st Embodiment. It is a figure which shows the information processing system of 2nd Embodiment. It is a block diagram which shows the hardware example of a power strip. It is a block diagram which shows the hardware example of a data management server. It is a block diagram which shows the function example of a power strip and a server. It is a figure which shows the example of a sensor data table. It is a figure which shows the example of a duplication determination table. It is a flowchart which shows the example of a procedure of data registration. It is a flowchart which shows the example of a procedure of determination information update. It is a flowchart (continuation) which shows the example of a procedure of determination information update. It is a flowchart which shows the example of a procedure of address feature integration. It is a figure which shows the 1st update result example of a duplication determination table. It is a figure which shows the 2nd update result example of a duplication determination table. It is a flowchart which shows the example of a procedure of data extraction. It is a block diagram which shows the modification of a data management server. It is a figure which shows the example of a movement characteristic table and an analysis result table. It is a figure which shows the example of an extraction condition table. It is a figure which shows the example of an access history table.

Hereinafter, the present embodiment will be described with reference to the drawings.
[First Embodiment]
FIG. 1 is a diagram illustrating the information processing apparatus according to the first embodiment. The information processing apparatus 10 according to the first embodiment communicates with a plurality of sensor devices including the sensor devices 21 and 22.

  The sensor devices 21 and 22 include a sensor device and a communication interface. The sensor device is a device that detects a physical state, and is, for example, a power sensor that detects power consumption of a power tap or a position sensor that detects a current position of a mobile terminal device. The sensor devices 21 and 22 generate sensor data including a value (for example, a numerical value) indicating the detected physical state, and transmit the sensor data to the information processing device 10 via the network. The sensor devices 21 and 22 transmit sensor data continuously (for example, regularly or irregularly). The communication interface provided in the sensor devices 21 and 22 may be a wired interface or a wireless interface.

  Consistent identification information is added to the series of sensor data transmitted by the sensor device 21 so that the set of sensor data generated by the sensor device 21 can be identified. Similarly, consistent identification information is added to the series of sensor data transmitted by the sensor device 22 by the sensor device 22. The identification information used by the plurality of sensor devices including the sensor devices 21 and 22 is preferably different from each other. However, two or more sensor devices out of a plurality of sensor devices may use the same identification information. For example, the sensor devices 21 and 22 may both use identification information = IDa.

  The information processing apparatus 10 collects and manages sensor data from a plurality of sensor devices including the sensor devices 21 and 22. The information processing apparatus 10 is, for example, a server computer that is always connected to a network. The sensor data collected by the information processing apparatus 10 can be used from application software executed by the information processing apparatus 10 or another information processing apparatus. The application software is, for example, software for controlling a power strip or an electronic device connected to the power strip according to power consumption, software for controlling a mobile terminal device according to the current position, and the like. In the first embodiment, the function of collecting and managing sensor data is realized by using one information processing device (information processing device 10). A function may be realized.

The information processing apparatus 10 includes a receiving unit 11 and a data processing unit 12.
The receiving unit 11 continuously receives sensor data to which the identification information is added from each of a plurality of sensor devices including the sensor devices 21 and 22 via a network. The receiving unit 11 is a communication interface connected to a wired network, for example.

  The data processing unit 12 classifies the sensor data received by the receiving unit 11 based on the identification information. The data processing unit 12 includes, for example, a processor. The “processor” may be a CPU (Central Processing Unit) or a DSP (Digital Signal Processor), or may include an electronic circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array). The “processor” may be a set of multiple processors (multiprocessor). The processor executes a program stored in a memory such as a RAM (Random Access Memory).

  As described above, the data processing unit 12 classifies the sensor data according to the identification information. At this time, the data processing unit 12 determines whether there are two or more sensor devices using the same identification information by checking the regularity of the set of sensor data to which the same identification information is added. To do. When it is determined that two or more sensor devices use the same identification information, the data processing unit 12 further classifies the sensor data to which the same identification information is assigned into a plurality of sets.

  As the regularity of the sensor data, for example, the regularity of the time stamp included in the sensor data is used. This is because the same sensor device is likely to generate sensor data at regular timing. For example, when a set of sensor data having the same identification information includes sensor data generated at 0 minutes per hour and sensor data generated at 15 minutes per hour, the data processing unit 12 includes two sensors. It is determined that the device is using the same identification information. In this case, the data processing unit 12 classifies the set of sensor data having the same identification information into a set of sensor data generated at 0 minutes per hour and a set of sensor data generated at 15 minutes per hour. In addition, for example, when sensor data having certain identification information is generated at a period of 10 minutes and the sensor data generated at a timing that does not conform to the period is received, the data processing unit 12 receives the same identification information. It is determined that another sensor device to be used has appeared.

  Further, as the regularity of the sensor data, for example, the regularity of the difference (delay time) between the time stamp included in the sensor data and the time when the sensor data is received by the information processing apparatus 10 is used. This is because the time from the generation of sensor data to the arrival of the information processing device 10 often does not vary greatly for the same sensor device. For example, when sensor data having certain identification information is received within a delay time of 1 second and sensor data having a delay time greatly exceeding 1 second is received, the data processing unit 12 uses the same identification information. It is determined that the sensor device has appeared. In this case, the data processing unit 12 classifies the set of sensor data having the same identification information into two sets of sensor data according to the delay time.

  Further, as the regularity of the sensor data, for example, an address variation characteristic used by the sensor device that is the sensor data transmission source is used. This is because whether or not the address changes is often determined depending on what kind of device the sensor device is mounted on, and hardly changes during the process. For example, when sensor data having certain identification information is continuously transmitted from a sensor device having the same source address and then received from the sensor device having a different source address, the data processing unit 12 performs the same identification. It is determined that another sensor device that uses the information has appeared. In this case, the data processing unit 12 separates the set of sensor data transmitted using the new source address from the set of sensor data transmitted using the conventional source address, thereby identifying the same Classify a set of sensor data with information.

  As described above, examples of the regularity of the sensor data include the regularity of the time stamp, the regularity regarding the reception time, and the regularity of the source address. The data processing unit 12 may classify the sensor data using any one of a plurality of types of regularity as described above, or may use two or more types of regularity in an AND condition. Data may be classified.

  According to the information processing apparatus 10 of the first embodiment, even if the sensor device 21 and the sensor device 22 add the same identification information to the sensor data, 2 It is detected that the above sensor devices use the same identification information. Based on the regularity, the set of sensor data extracted based on the identification information is further classified into a set of sensor data generated by the sensor device 21 and a set of sensor data generated by the sensor device 22. There is expected. Thereby, it becomes easy to utilize the sensor data collected by the information processing apparatus 10. For example, it becomes easy to provide a set of appropriately classified sensor data to application software that performs data processing such as aggregation of values included in sensor data and detection of abnormal values for each sensor device.

In the second embodiment described below, an example of a sensor network system in which a sensor device mounted on a power strip generates sensor data indicating power consumption is given.
[Second Embodiment]
FIG. 2 illustrates an information processing system according to the second embodiment. In the information processing system according to the second embodiment, a service for monitoring power consumption and controlling an electronic device according to a change in power consumption is provided using cloud computing technology.

  The information processing system includes networks 31, 32, a plurality of power strips including power strips 100, 100a, a data management server 200, and an application server 300. The network 31 is a wide area network such as the Internet, and the network 32 is a local network in the data center. The power strips 100 and 100a are connected to the network 31. The data management server 200 and the application server 300 are connected to the network 32. The data management server 200 can be accessed through the networks 31 and 32 from the power strips 100 and 100a. The data management server 200 is an example of the information processing apparatus 10 according to the first embodiment.

  The power strips 100 and 100a include a plurality of power sockets and distribute power to a plurality of electronic devices such as computers connected to the power sockets. The power strips 100 and 100a are provided with sensor devices that measure power consumption and generate sensor data including measurement values. The power strips 100 and 100a continuously transmit sensor data to the data management server 200 via the networks 31 and 32 at regular timings, respectively.

  Here, the IP addresses assigned to the power strips 100 and 100a may change. For example, the power strips 100 and 100a are dynamically assigned IP addresses from a DHCP server (not shown). For example, when the location where the power strips 100 and 100a are arranged is changed, an IP address that can be used in the network segment at the changed location is assigned to the power strips 100 and 100a. Therefore, each of the sensor devices of the power strips 100 and 100a adds sensor ID, which is identification information different from the IP address, to the sensor data when transmitting the sensor data. In principle, the same sensor ID is consistently added to sensor data transmitted from the same sensor device.

  The data management server 200 is a server computer that manages sensor data. The data management server 200 continuously receives sensor data from the power strips 100 and 100 a via the networks 31 and 32. The data management server 200 classifies the collected sensor data based on the sensor ID so that the sensor data for each power strip can be distinguished from the sensor data for other power strips. Further, the data management server 200 provides a set of sensor data in response to a request from the application server 300.

  Here, the sensor IDs set in the sensor devices of the plurality of power strips are preferably different from each other. However, the sensor ID already used by the sensor device of another power strip (for example, the power strip 100) is duplicated in the sensor device of a certain power strip (for example, the power strip 100a) due to a user's mistake or malicious intention. There is a possibility of setting. Therefore, the data management server 200 monitors the regularity of the sensor data to which the same sensor ID is added, and detects that a new sensor device has started to use the existing sensor ID based on the regularity. To do. When duplicate sensor IDs are detected, the data management server 200 classifies sensor data to which the same sensor ID is added based on regularity.

  The application server 300 is a server computer that executes application software for analyzing sensor data. The application server 300 acquires a set of sensor data for each power tap from the data management server 200 and checks whether the measured value of power consumption is abnormal. For example, when the power consumption of a certain power strip exceeds a threshold value, the application server 300 instructs the electronic device connected to the power strip to suppress power consumption or to use an alternative power source. To do.

  FIG. 3 is a block diagram illustrating a hardware example of the power strip. The power strip 100 includes a plurality of power sockets and distributes power supplied from an external power source to electronic devices connected to the plurality of power sockets. The sensor device included in the power tap 100 includes a sensor device 101, a calculation unit 102, a memory 103, and a communication interface 104. The power strip 100a can also be realized by the same hardware configuration as the power strip 100.

  The sensor device 101 is a power sensor that measures current power consumption. The sensor device 101 may measure the power consumption for each power socket (that is, for each electronic device connected to the power tap 100), or may measure the power consumption of the entire power tap 100.

  The calculation unit 102 continuously generates sensor data including a numerical value of power consumption measured by the sensor device 101 at regular timing (for example, every 10 minutes). A sensor ID set in the sensor device of the power strip 100 is added to the sensor data by the calculation unit 102. Note that the arithmetic unit 102 may be a processor, and may include a processor that executes a program and a volatile memory that stores the program.

  The memory 103 is a non-volatile memory that stores the sensor ID. It may be allowed to write the sensor ID into the memory 103 through a user operation. The sensor ID stored in the memory 103 is added to the sensor data by the calculation unit 102.

  The communication interface 104 transmits the sensor data generated by the calculation unit 102 to the data management server 200 via the network 31 as an IP packet. The communication interface 104 may be a wireless interface that connects to the network 31 wirelessly, or a wired interface that connects to the network 31 using a cable. When power line communication (PLC) is used as a communication method, the communication interface 104 is connected to a power line that receives power from an external power source. The IP address used as the source address by the communication interface 104 can be changed.

  FIG. 4 is a block diagram illustrating a hardware example of the data management server. The data management server 200 includes a CPU 201, a RAM 202, an HDD (Hard Disk Drive) 203, an image signal processing unit 204, an input signal processing unit 205, a disk drive 206, and a communication interface 207. Each of the above units is connected to the bus 208. The application server 300 can also be realized by the same hardware configuration as the data management server 200.

  The CPU 201 is a processor including an arithmetic unit that executes program instructions. The CPU 201 loads at least a part of the program and data stored in the HDD 203 into the RAM 202 and executes the program. The CPU 201 may include a plurality of processor cores, the data management server 200 may include a plurality of processors, and the processes described below may be executed in parallel using a plurality of processors or processor cores. A set of two or more processors may be called a “processor” (multiprocessor).

  The RAM 202 is a volatile memory that temporarily stores programs executed by the CPU 201 and data used for calculations. Note that the data management server 200 may include a type of memory other than the RAM, and may include a plurality of volatile memories.

  The HDD 203 is a non-volatile storage device that stores software programs and data such as an OS (Operating System), firmware, and application software. The data management server 200 may include other types of storage devices such as an SSD (Solid State Drive), and may include a plurality of nonvolatile storage devices.

  The image signal processing unit 204 outputs an image to the display 41 connected to the data management server 200 in accordance with an instruction from the CPU 201. As the display 41, various displays such as a CRT (Cathode Ray Tube) display, a liquid crystal display, an organic EL (Electro-Luminescence) display, and a plasma display can be used. Further, the display 41 may be formed integrally with the housing of the data management server 200.

  The input signal processing unit 205 acquires an input signal from the input device 42 connected to the data management server 200 and notifies the CPU 201 of the input signal. As the input device 42, various input devices such as a pointing device such as a mouse and a touch panel and a keyboard can be used. A plurality of input devices may be connected to the data management server 200. Further, the input device 42 may be formed integrally with the housing of the data management server 200.

  The disk drive 206 is a drive device that reads programs and data recorded on the recording medium 43. As the recording medium 43, for example, a magnetic disk such as a flexible disk (FD) or HDD, an optical disk such as a CD (Compact Disc) or a DVD (Digital Versatile Disc), or a magneto-optical disk (MO). Can be used. The disk drive 206 stores the program and data read from the recording medium 43 in the RAM 202 or the HDD 203 in accordance with an instruction from the CPU 201.

  However, the data management server 200 does not have to include the disk drive 206. When the data management server 200 is accessible from a terminal device (for example, a client computer) operated by the user, the image signal processing unit 204 or the input signal processing unit 205 may not be provided. The set of the CPU 201 and the RAM 202 is an example of the data processing unit 12 according to the first embodiment, and the communication interface 207 is an example of the receiving unit 11 according to the first embodiment.

FIG. 5 is a block diagram illustrating an example of functions of the power strip and the server.
The power strip 100 includes a data generation unit 110 and a data transmission unit 120. When the processing performed by the calculation unit 102 is controlled by software, the data generation unit 110 and the data transmission unit 120 can be realized as software modules. The power strip 100a can also be realized by a software configuration similar to that of the power strip 100.

  The data generation unit 110 determines the timing for transmitting sensor data using a hardware timer or a software timer. When a timing that satisfies a predetermined condition (for example, 10 minutes / 20 minutes / 30 minutes / 40 minutes / 50 minutes per hour) arrives, the data generation unit 110 generates sensor data. Sensor data includes numerical values of power consumption measured by the sensor device 101 (power consumption of the entire power tap 100 or each electronic device connected to the power tap 100), a time stamp indicating the current time, and a sensor stored in the memory 103. Includes ID.

  The data transmission unit 120 instructs the communication interface 104 to transmit the sensor data generated by the data generation unit 110 to the data management server 200. The sensor data is transmitted in a packet format using the IP address of the power strip 100 as a transmission source address and the IP address of the data management server 200 as a destination address.

  The data management server 200 includes a data storage unit 210, a determination information storage unit 220, a data reception unit 230, a duplication determination unit 240, a determination information update unit 250, and a data provision unit 260. The data storage unit 210 and the determination information storage unit 220 can be realized as a storage area secured in the RAM 102 or the HDD 103. The data receiving unit 230, the duplication determining unit 240, the determination information updating unit 250, and the data providing unit 260 can be realized as software modules.

  The data storage unit 210 stores sensor data collected from a plurality of power strips including the power strips 100 and 100a. Management information for the data management server 200 to classify the sensor data is added to the sensor data stored in the data storage unit 210.

  The determination information storage unit 220 stores a determination rule for determining duplication of sensor IDs. The determination rule indicates regularity of sensor data generated by the same sensor device. The determination rule stored in the determination information storage unit 220 can be automatically created by the duplication determination unit 240 and the determination information update unit 250 as described later, and may be created by a user operation. One or more determination rules are created for one sensor ID. While it is determined that a certain sensor ID is used by only one sensor device, one determination rule is created for that sensor ID. If it is determined that a new sensor device that uses an existing sensor ID in an overlapping manner appears, a new determination rule is added to the sensor ID.

  The data receiving unit 230 continuously receives sensor data from a plurality of power strips including the power strips 100 and 100a. When receiving the sensor data, the data receiving unit 230 checks the reception time and the transmission source address of the sensor data. Then, the data reception unit 230 passes the sensor data to which the reception time and the transmission source address are added to the duplication determination unit 240.

  The duplication determination unit 240 searches the determination information storage unit 220 for a determination rule corresponding to the sensor ID included in the sensor data. When the feature of the received sensor data matches any one of the retrieved determination rules, the duplication determination unit 240 determines that no new duplicate use of the sensor ID has occurred, and the ID ( Duplicate resolution ID) is added to the sensor data. On the other hand, if the feature of the received sensor data does not match any of the retrieved determination rules, the duplication determination unit 240 determines that a new duplicate use of the sensor ID has occurred, and creates a new determination rule temporarily. The duplicate resolution ID of the determination rule is added to the sensor data. The duplication determination unit 240 stores the sensor data to which the duplication resolution ID is added in the data storage unit 210.

  The determination information update unit 250 organizes the determination rules stored in the determination information storage unit 220. The determination information update unit 250 is implemented as a software module that performs batch processing, for example. The determination information update unit 250 periodically executes the following processing in a time zone where the load on the data management server 200 is small, for example, once a day at night. The determination information update unit 250 calculates the regularity of the sensor data that is determined not to conform to the existing determination rule in the received sensor data. Regularity includes the periodicity of time stamps and the similarity between the time stamp and the reception time. The determination information update unit 250 integrates the determination rules temporarily created by the duplication determination unit 240 so that a set of sensor data having regularity can be specified.

  The data providing unit 260 receives an extraction request from the application server 300, extracts a set of sensor data from the data storage unit 210, and transmits it to the application server 300. In the extraction request, the sensor ID is specified. In the extraction request, an extraction condition other than the sensor ID may be specified in addition to the sensor ID. The data providing unit 260 extracts a set of sensor data based on the sensor ID or the combination of the sensor ID and the extraction condition.

  The application server 300 has a data analysis unit 310. The data analysis unit 310 can be realized as a software module. The data analysis unit 310 transmits an extraction request to the data management server 200 in accordance with a preset timing condition or user operation, and acquires a set of sensor data. As described above, the extraction request may include a sensor ID, and may further include an extraction condition other than the sensor ID (for example, a transmission source address). The data analysis unit 310 analyzes the power consumption value included in the acquired sensor data. For example, when the data analysis unit 310 detects that the power consumption of a certain power strip exceeds a threshold value, the data analysis unit 310 transmits a power suppression command to the power strip or an electronic device connected to the power strip.

  FIG. 6 is a diagram illustrating an example of a sensor data table. The sensor data table 211 is stored in the data storage unit 210. The sensor data table 211 includes items of time stamp, sensor ID, address, measurement value, reception time, and duplicate resolution ID.

  In the time stamp item, a time included in the sensor data as a time stamp is set. The time stamp is estimated as the time when the sensor data is generated. The sensor ID included in the sensor data is set in the item of sensor ID. One sensor ID may be used by two or more different sensor devices. In the address item, the IP address (source IP address) of the sensor device that transmits the sensor data is set. The IP address used by the sensor device may change.

  In the measurement value item, a numerical value indicating power consumption included in the sensor data is set. In the item of the reception time, a time when the data reception unit 230 receives the sensor data is set. In the duplicate resolution ID item, the ID of a determination rule that matches the sensor data is set. The duplicate resolution ID includes a sensor ID and a character string other than the sensor ID. By referring to the overlap resolution ID, sensor data of two or more sensor devices using the same sensor ID can be distinguished from each other.

  FIG. 7 is a diagram illustrating an example of a duplication determination table. The duplication determination table 221 is stored in the determination information storage unit 220. The duplication determination table 221 includes items of sensor ID, duplication resolution ID, address feature, time stamp feature, reception time feature, and start time.

  In the sensor ID item, a sensor ID of sensor data to which the determination rule is applied is set. An ID for identifying a determination rule is set in the duplicate resolution ID item. The duplicate resolution ID is expressed as the item number in the sensor ID + “::” + sensor ID, for example, “IDa :: 0”. The determination rule of item number = 0 for a certain sensor ID is the determination rule indicating the regularity of the initial sensor data that has been created for the sensor ID, that is, the sensor data including the sensor ID has started to appear. It is. There is a possibility that a sensor ID in which a determination rule other than item number = 0 exists is used by a plurality of sensor devices. Note that the determination rule of item number = 0 may be created by a user operation.

  In the address feature item, a transmission source address of the sensor data or a range of the transmission source address is set. If the source address does not change, one IP address is set. When it is determined that the transmission source address has changed in the past, a plurality of IP addresses or IP address ranges are set. In the item of the time stamp feature, a cycle of the time stamp included in the sensor data is set. For example, a time stamp feature of “10 minute intervals” means that the time stamp difference between one sensor data received from the same sensor device and the next sensor data is about 10 minutes. Show.

  In the item of the reception time feature, a range of a difference between the time stamp included in the sensor data and the reception time of the sensor data is set. For example, when the reception time feature is “within 1 second”, the delay time from when the sensor device generates sensor data until the sensor data reaches the data management server 200 is consistently within 1 second. It is shown that. In the start time item, the time stamp (or reception time) of the sensor data first corresponding to the determination rule is set. Note that since there is no determination rule that matches the received sensor data, the time stamp feature and the reception time feature are blank in the determination rule that is temporarily generated.

FIG. 8 is a flowchart illustrating an example of a data registration procedure. The process shown in FIG. 8 is executed every time the data management server 200 receives sensor data.
(Step S11) The data receiving unit 230 receives sensor data.

(Step S12) The data receiving unit 230 confirms the transmission source address and reception time used for packet communication, and adds the transmission source address and reception time to the sensor data.
(Step S13) The duplication determination unit 240 searches the duplication determination table 221 stored in the determination information storage unit 220 for a determination rule corresponding to the sensor ID included in the received sensor data. Here, one or more decision rules can be searched.

(Step S14) The duplication determination unit 240 selects one searched determination rule.
(Step S15) The duplication determination unit 240 determines whether the sensor data matches the address feature of the selected determination rule. That is, the duplication determination unit 240 determines whether the transmission source address added to the sensor data is included in the address list or address range described as the address feature. If the sensor data matches the address feature, the process proceeds to step S16. If the sensor data does not match the address feature, the process proceeds to step S19.

  (Step S16) The duplication determination unit 240 determines whether the sensor data matches the time stamp feature of the selected determination rule. The determination of the time stamp characteristic is performed by the following procedure, for example. The overlap determination unit 240 calculates the difference (duration) between the time stamp included in the sensor data and the start time of the determination rule, and calculates the remainder when the duration is divided by the period described as the time stamp feature. . If the remainder is less than a threshold value (for example, 1% of the period), the overlap determination unit 240 determines that the time stamp feature is suitable, and determines that the remainder does not match the time stamp feature if the remainder is equal to or greater than the threshold value. However, the duplication determination unit 240 extracts the previously received sensor data corresponding to the selected determination rule from the data storage unit 210, and determines whether the time stamp difference matches the period described as the time stamp feature. Also good. If the sensor data matches the time stamp feature, the process proceeds to step S17. If the sensor data does not match the time stamp feature, the process proceeds to step S19. If the time stamp feature is blank, it is determined that the time stamp feature is not suitable.

  (Step S17) The duplication determination unit 240 determines whether the sensor data matches the reception time feature of the selected determination rule. That is, the duplication determination unit 240 calculates the difference (delay time) between the time stamp included in the sensor data and the reception time, and determines whether the delay time satisfies the condition described as the reception time feature. When the reception time feature is “indefinite”, it is considered to be suitable for the reception time feature. If the sensor data matches the reception time feature, the process proceeds to step S18. If the sensor data does not match the reception time feature, the process proceeds to step S19. Note that if the reception time feature is blank, it is determined that it is not suitable.

  (Step S18) The duplication determination unit 240 determines that the received sensor data corresponds to the determination rule selected in step S14, that is, no new duplication of sensor IDs has occurred. The duplication determination unit 240 selects the duplication resolution ID of the selected determination rule.

  (Step S19) The duplication determination unit 240 determines whether all of the retrieved determination rules have been selected in step S14. If all the determination rules are selected, the process proceeds to step S20. If there is an unselected determination rule, the process proceeds to step S14.

  (Step S20) The duplication determination unit 240 determines that the received sensor data does not correspond to any determination rule, that is, a new duplication use of the sensor ID has occurred. The duplication determination unit 240 registers a temporary determination rule in the duplication determination table 221. The sensor ID of the provisional determination rule is the sensor ID of the received sensor data, the duplicate resolution ID is an ID different from the existing duplicate resolution ID, and the start time is the time stamp (or reception time) of the received sensor data. It is. Further, the address feature of the provisional determination rule is the source address of the received sensor data, and the time stamp feature and the reception time feature are blank.

(Step S21) The duplication determination unit 240 selects the duplication resolution ID of the determination rule registered in the duplication determination table 221 in step S20.
(Step S22) The duplication determination unit 240 adds the duplication resolution ID selected in step S18 or step S21 to the sensor data. Then, the duplication determination unit 240 registers sensor data in the sensor data table 211 stored in the data storage unit 210.

  In FIG. 8, it is determined whether the sensor data corresponds to the determination rule by using three of the address feature, the time stamp feature, and the reception time feature as AND conditions. However, only one of the above three features may be used, or any two may be used as an AND condition. Moreover, you may perform the process of said step S15-S17 in arbitrary orders.

FIG. 9 is a flowchart illustrating an exemplary procedure for updating the determination information. The process illustrated in FIG. 9 is executed as a batch process, for example, during a time period when the load on the data management server 200 is small.
(Step S <b> 31) The determination information update unit 250 selects one sensor ID and searches the determination rule for the selected sensor ID from the duplication determination table 221 stored in the determination information storage unit 220. Here, a plurality of determination rules can be searched.

(Step S32) The determination information updating unit 250 selects one address feature and extracts a determination rule having the address feature from the determination rules searched in step S31.
(Step S33) The determination information update unit 250 extracts a determination rule whose time stamp feature is blank from the determination rules extracted in step S32.

  (Step S <b> 34) The determination information update unit 250 stores a set of sensor data (sensor data to which any duplicate resolution ID is assigned) corresponding to any of the determination rules extracted in Step S <b> 33 in the data storage unit 210. Search from the stored sensor data table 211.

  (Step S35) The determination information update unit 250 sorts the sensor data retrieved in Step S34 according to the time stamp, and calculates the distribution of the number of receptions with respect to time. The time may be rounded in consideration of time stamp errors. Then, the determination information update unit 250 performs spectrum analysis on the distribution of the number of receptions with respect to time by discrete Fourier transform. Thereby, the frequency spectrum (frequency component distribution) can be calculated.

  (Step S36) The determination information updating unit 250 detects a frequency whose level is equal to or higher than a threshold value from the frequency spectrum calculated in Step S35. The level threshold is, for example, a certain ratio (such as one third) of the total number of sensor data searched in step S34.

  (Step S37) The determination information updating unit 250 determines whether or not a frequency whose level is equal to or higher than the threshold value is detected in Step S36. If a frequency whose level is equal to or higher than the threshold is detected, the process proceeds to step S38. If not detected, the process proceeds to step S47.

  (Step S38) The determination information updating unit 250 calculates the reciprocal of the frequency f detected in Step S36 = 1 / f as the time stamp period ω. Note that the method for calculating the period of the time stamp described above is an example, and the period may be calculated by other methods.

FIG. 10 is a flowchart (continued) illustrating an example of the procedure for updating the determination information.
(Step S41) The determination information updating unit 250 extracts sensor data corresponding to the cycle ω calculated in Step S38 from the sensor data searched in Step S34. For example, if the distribution of the number of receptions with respect to the time calculated in step S35 is f (t), the determination information update unit 250 may maximize the value of the convolution integral between sin (ωt + θ) and f (t). By obtaining the correct phase θ, a set of sensor data having periodicity is specified.

  (Step S42) The determination information update unit 250 extracts a determination rule including the duplicate resolution ID added to each sensor data extracted in step S41 from the determination rules extracted in step S33. Here, a plurality of determination rules can be extracted.

  (Step S43) The determination information update unit 250 integrates the determination rules extracted in Step S42. That is, the determination information update unit 250 selects the determination rule with the oldest start time as the determination rule to be left, and registers the period calculated in step S38 as the time stamp feature of the selected determination rule. Then, the determination information update unit 250 deletes the determination rule that is not selected from the extracted determination rules from the duplication determination table 221.

(Step S44) The determination information update unit 250 updates the duplicate resolution ID of the sensor data extracted in Step S41 to the duplicate resolution ID of the determination rule selected in Step S43.
(Step S45) The determination information updating unit 250 calculates the reception time feature of the sensor data extracted in Step S41 and registers it as the reception time feature of the determination rule selected in Step S43. For example, the determination information update unit 250 calculates the distribution of the difference (delay time) between the time stamp and the reception time, and determines whether the delay time distribution is within a predetermined range from the average delay time. The determination information updating unit 250 sets the reception time feature as the range when it is within the predetermined range, and sets the reception time feature as “undefined” when it is not within the predetermined range. The method for calculating the range of the delay time is an example, and the range may be calculated by a method other than this.

  (Step S46) The determination information updating unit 250 determines whether there is a determination rule remaining unintegrated in Step S43 among the determination rules extracted in Step S33. If there are remaining determination rules, the process proceeds to step S35, and the sensor data corresponding to the remaining determination rules is subjected to spectrum analysis. If there are no remaining determination rules, the process proceeds to step S47.

  (Step S47) The determination information update unit 250 determines whether all address features have been selected in step S32. If all address features have been selected, the process proceeds to step S48. If there is an unselected address feature, the process proceeds to step S32.

  (Step S48) The determination information updating unit 250 determines whether all sensor IDs have been selected in Step S31. If all sensor IDs have been selected, the process ends. If there is an unselected sensor ID, the process proceeds to step S31.

  As described above, a provisional determination rule is created every time sensor data that does not correspond to an existing determination rule is received. Since the time stamp feature and the reception time feature are unknown in the provisional determination rule, it is not determined that other sensor data corresponds to the provisional determination rule. For this reason, when duplicate use of the sensor ID is newly detected, provisional determination rules increase for a while. Thereafter, the determination information update unit 250 integrates a plurality of provisional determination rules to generate a determination rule in which the time stamp feature and the reception time feature are determined.

  In the above description, the determination information update unit 250 identifies a set of sensor data from the periodicity of the time stamp, and determines the regularity of the delay time for the identified set of sensor data. However, the determination information update unit 250 may specify a set of sensor data from the regularity of the delay time, and may determine the periodicity of the time stamp for the specified set of sensor data.

  In the above description, the determination information update unit 250 first classifies sensor data not corresponding to the existing determination rule based on the transmission source address, and classifies sensor data having the same transmission source address based on the time stamp feature. Yes. Here, when two or more determination rules having the same time stamp characteristic and reception time characteristic but different address characteristics are generated, there is a possibility that the IP address of the same sensor device has changed. Therefore, the determination information update unit 250 may further integrate the determination rules generated by the processes of FIGS.

FIG. 11 is a flowchart illustrating an exemplary procedure for address feature integration.
(Step S51) The determination information updating unit 250 searches the duplication determination table 221 for two or more determination rules having the same sensor ID, time stamp characteristic, and reception time characteristic.

(Step S52) The determination information update unit 250 searches the sensor data table 211 for sensor data corresponding to the determination rule searched in step S51.
(Step S53) The determination information update unit 250 integrates the determination rules searched in Step S51. That is, the determination information update unit 250 selects the determination rule having the oldest start time as the determination rule to be left, and adds the IP address described as the address feature of the determination rule that has not been selected to the address feature of the selected determination rule. . Then, the determination information update unit 250 deletes the determination rule that has not been selected from the duplication determination table 221.

(Step S54) The determination information updating unit 250 updates the duplicate resolution ID of the sensor data searched in Step S52 to the duplicate resolution ID of the determination rule selected in Step S53.
(Step S55) The determination information update unit 250 determines whether there are any remaining determination rules that satisfy the condition of Step S51. If a determination rule that satisfies the condition remains, the process proceeds to step S51; otherwise, the process ends.

FIG. 12 is a diagram illustrating a first update result example of the duplication determination table.
When sensor data including sensor ID = IDa and not corresponding to the determination rule of duplicate resolution ID = IDa :: 0 is received, the duplicate determination unit 240 creates a temporary determination rule of duplicate resolution ID = IDa :: 1. The duplicate resolution ID = IDa :: 1 is assigned to the sensor data. When sensor data that includes sensor ID = IDa and does not correspond to the determination rule of duplicate resolution ID = IDa :: 0 is further received, the duplicate determination unit 240 creates a temporary determination rule of duplicate resolution ID = IDa :: 2. Then, the duplicate resolution ID = IDa :: 2 is assigned to the sensor data.

  In this way, when sensor data that includes sensor ID = IDa and does not correspond to the determination rule of duplicate resolution ID = IDa :: 0 is received seven times, seven temporary determination rules are created. The time stamp characteristics of these seven provisional determination rules are blank. As shown in FIG. 12, it is assumed here that the address feature (source address) of the determination rule of duplicate resolution ID = IDa :: 6 is AD4, and the address features of the other six determination rules are AD2.

  When integrating the determination rules, the determination information update unit 250 extracts six determination rules with sensor ID = IDa, address feature = AD2, and time stamp feature = empty. Then, the determination information update unit 250 extracts sensor data for six times corresponding to these six determination rules, and calculates a time stamp characteristic of the extracted sensor data. In the example of FIG. 12, time stamp feature = 5 minute intervals is calculated. As a result, the six temporary determination rules are unified into the determination rule of duplicate resolution ID = IDa :: 1. The determination rule of duplicate resolution ID = IDa :: 6 is not integrated with other determination rules, and the time stamp characteristic remains unknown.

  FIG. 13 is a diagram illustrating a second update result example of the duplication determination table. Here, as a result of the processing shown in FIG. 12, a determination rule that address feature = AD2, time stamp feature = 5-minute interval, reception time feature = indeterminate, address feature = AD3, time stamp feature = 5-minute interval, reception It is assumed that a determination rule that time feature = indefinite is generated. Then, the determination information update unit 250 integrates two determination rules having the same time stamp characteristics and reception time characteristics, and sets the address characteristics of the determination rules after integration as AD2 and AD3. This indicates that sensor data corresponding to the determination rule after integration is generated by a sensor device whose IP address changes.

FIG. 14 is a flowchart illustrating an exemplary procedure for data extraction. The process shown in FIG. 14 is executed every time the data management server 200 receives an extraction request.
(Step S61) The data providing unit 260 receives an extraction request from the data analysis unit 310 of the application server 300 via the network 32. The extraction request includes at least a sensor ID. The extraction request may further include extraction conditions other than the sensor ID (for example, a transmission source address, a time stamp cycle, etc.).

  (Step S62) The data providing unit 260 determines whether the extraction request received in step S61 includes an extraction condition other than the sensor ID. If the extraction condition is included, the process proceeds to step S64; otherwise, the process proceeds to step S63.

  (Step S63) The data providing unit 260 searches the duplication determination table 221 for a determination rule with the oldest start time (determination rule with item number = 0) among the determination rules corresponding to the sensor ID included in the extraction request. Then, the process proceeds to step S67.

(Step S64) The data providing unit 260 searches the duplication determination table 221 for a determination rule corresponding to the sensor ID and the extraction condition included in the extraction request.
(Step S65) The data providing unit 260 determines whether a determination rule that meets the conditions is found in step S64. If a determination rule that meets the conditions is found, the process proceeds to step S67; otherwise, the process proceeds to step S66.

(Step S66) The data providing unit 260 searches the duplication determination table 221 for all determination rules corresponding to the sensor ID included in the extraction request.
(Step S67) The data providing unit 260 selects the duplicate resolution ID of the determination rule searched in any of steps S63, S64, and S66. If a plurality of determination rules are searched in step S66, a plurality of duplicate resolution IDs are selected.

  (Step S68) The data providing unit 260 extracts from the sensor data table 211 a set of sensor data to which the duplicate resolution ID selected in step S67 is assigned, and transmits the extracted set of sensor data to the data analysis unit 310. .

  As described above, when only the sensor ID is designated, the application server 300 acquires only the sensor data having the original regularity at which the sensor data including the sensor ID has started to be collected. That is, only sensor data corresponding to the determination rule of item number = 0 is acquired. If it is desired to acquire sensor data of a sensor device that has started to use the sensor ID later, the application server 300 may specify an extraction condition such as a transmission source address.

Next, a modification of the data management server of the second embodiment will be described.
The data management server 200a according to the modified example monitors a set of transmission source addresses corresponding to each sensor ID, and the characteristics of the transmission source address have changed (for example, the transmission source address that has been fixed to one has changed). If it is detected, the user is warned. In addition, the data management server 200a allows the extraction conditions specified by the application server 300 in the extraction request to be selected from the list of extraction conditions defined in the data management server 200a. Further, the data management server 200a manages the time when the data management server 200a is first accessed (access start time) for each data analysis software executed by the application server 300. Then, the data management server 200a controls a set of sensor data to be provided from the relationship between the access start time and the determination rule start time.

  FIG. 15 is a block diagram illustrating a modification of the data management server. The data management server 200a includes a data storage unit 210, a determination information storage unit 220, a data reception unit 230, a duplication determination unit 240, a determination information update unit 250a, a data provision unit 260a, a movement information storage unit 270, an extraction condition storage unit 280, and A history storage unit 290 is included. The determination information updating unit 250a and the data providing unit 260a correspond to the determination information updating unit 250 and the data providing unit 260 of the data management server 200. The movement information storage unit 270, the extraction condition storage unit 280, and the history storage unit 290 can be realized as a storage area secured in the RAM 102 or the HDD 103.

  The movement information storage unit 270 stores movement information indicating characteristics (movement characteristics) of a set of transmission source addresses corresponding to each sensor ID. There are three types of mobility characteristics: the source address does not change, the source address changes within one network segment, and the source address is converted across multiple network segments. The movement information stored in the movement information storage unit 270 is created by the determination information update unit 250a.

  The extraction condition storage unit 280 stores a list of extraction conditions that can be specified by the application server 300 in the extraction request. When using this list of extraction conditions, the application server 300 may insert the identification name of the specified extraction condition into the extraction request. The list of extraction conditions stored in the extraction condition storage unit 280 is created by a user operation.

  The history storage unit 290 stores history information indicating the time (access start time) when an extraction request specifying the sensor ID is first received for each set of data analysis software and sensor ID executed by the application server 300. . The history information stored in the history storage unit 290 is created by the data providing unit 260a.

  After integrating the determination rules registered in the duplication determination table 221, the determination information update unit 250a calculates a set of transmission source addresses described as address features for each sensor ID. Then, the determination information update unit 250a refers to the movement information stored in the movement information storage unit 270, and determines whether there is a sensor ID whose movement characteristics have changed since the previous integration of the determination rules. When a sensor ID whose movement characteristics have changed is detected, the determination information update unit 250a warns the user (may be an administrator of the data management server 200a) to that effect.

  The user who has received the warning confirms the usage state of the sensor device and edits the duplication determination table 221 as appropriate. For example, when the transmission source address changes due to a change in the usage method of the sensor device, the user rewrites the address characteristic of the determination rule from a fixed IP address to an address range. In addition, for example, when it is considered that the usage of the sensor device is not changed and the duplicate use of the sensor ID has occurred, the user does not integrate two or more determination rules having different transmission source addresses for the sensor ID. Separated into Note that the determination information update unit 250a may not warn the user as a learning period for a certain period (for example, 3 days) after the change of the movement characteristic is first detected. If the change in the movement characteristics continues even after the learning period has elapsed, the determination information update unit 250a warns the user.

  The data providing unit 260a allows the extraction request including the sensor ID and the identification name of the extraction condition to be received from the application server 300. In this case, the data providing unit 260a selects an extraction condition corresponding to the specified identification name from the list of extraction conditions stored in the extraction condition storage unit 280, and extracts a set of sensor data according to the sensor ID and the extraction condition. .

  In addition, the data providing unit 260a permits the application server 300 to accept an extraction request that includes the sensor ID but does not include the extraction condition (or the identification name of the extraction condition). In this case, the data providing unit 260a confirms the data analysis software that has issued the extraction request, and searches the history information stored in the history storage unit 290 for the access start time corresponding to the combination of the data analysis software and the sensor ID. . And the data provision part 260a controls extraction of sensor data from the relationship between access start time and the start time of each determination rule.

  For example, if there is only one determination rule whose start time is older than the access start time for the specified sensor ID (only the determination rule with item number = 0), the data providing unit 260a corresponds to that determination rule. Only sensor data to be extracted. This is because, when such a condition is satisfied, a set of sensor data intended by the data analysis software that has issued the extraction request is clear. On the other hand, if there are two or more determination rules whose start time is older than the access start time, the data providing unit 260a notifies the data analysis software of an error. This is because, when such a condition is satisfied, it is not clear which sensor data set intended by the data analysis software corresponds to one of two or more determination rules.

FIG. 16 is a diagram illustrating an example of the movement characteristic table and the analysis result table.
The movement characteristic table 271 is stored in the movement information storage unit 270. The movement characteristic table 271 includes items of movement characteristic name, movement characteristic, and parameter name. In the item of the movement characteristic name, an identification name of the movement characteristic is registered. In the item of the movement characteristic, the content of the movement characteristic is described. In the movement characteristics, the address is fixed to one (characteristic 1 = no movement), the address changes within one network segment (characteristic 2 = moves within the segment), and the address changes across multiple network segments. There are three (characteristic 3 = movement range is indefinite). Parameters to be set for each characteristic are registered in the parameter name item. The parameter of characteristic 1 is one address, and the parameters of characteristics 2 and 3 are two or more addresses.

  The analysis result table 272 is stored in the movement information storage unit 270. The analysis result table 272 includes items of sensor ID, analysis time, and analysis result. In the analysis time item, the time when the determination information update unit 250a analyzes the duplication determination table 221 is registered. In the analysis result item, the movement characteristics and parameters of each sensor ID are registered.

  For example, when the source address corresponding to a certain sensor ID is only AD1, the movement characteristic = characteristic 1, parameter = AD1. For example, when the transmission source addresses are AD1 and AD2, and the two transmission source addresses are addresses of the same network segment, mobility characteristic = characteristic 2, parameter = AD1, AD2. For example, when the source addresses are AD1 and AD2 and the two source addresses are addresses of different network segments, mobility characteristics = characteristic 3 and parameters = AD1, AD2.

  In this manner, the determination information update unit 250a extracts the address used for transmitting the sensor data including the sensor ID for each sensor ID and registers the address in the analysis result table 272. And the determination information update part 250a can detect sensor ID from which the movement characteristic changed by comparing the last analysis result and this analysis result. Note that there are three types of changes in the movement characteristics: characteristics 1 to 2, characteristics 2 to 3, and characteristics 1 to 3.

  FIG. 17 is a diagram illustrating an example of the extraction condition table. The extraction condition table 281 is stored in the extraction condition storage unit 280. The extraction condition table 281 includes condition name and condition items. In the condition name item, an identification name of the extraction condition is registered. The condition item describes the contents of the extraction condition. In the example of FIG. 17, three extraction conditions are registered.

  Condition 1 (the first registered address) is an extraction condition that limits the sensor data to be extracted to those transmitted using the same source address as the first sensor data. When condition 1 is designated, the data providing unit 260a searches for sensor data corresponding to the determination rule of item number = 0. Condition 2 (address that has passed a predetermined period since registration) is an extraction condition that limits sensor data to be extracted to those that have been transmitted using a source address that has passed a predetermined period since registration in the duplication determination table 221. is there. When condition 2 is specified, the data providing unit 260a searches for sensor data corresponding to a determination rule in which the difference between the start time and the current time is equal to or greater than a threshold (for example, three months). Condition 3 (all addresses) indicates that no extraction condition other than the sensor ID is designated. When condition 3 is specified, the data providing unit 260a searches for sensor data using all the determination rules corresponding to the sensor ID.

  FIG. 18 is a diagram illustrating an example of an access history table. The access history table 291 is stored in the history storage unit 290. The access history table 291 includes items of application name, sensor ID, and access start time. The name of the data analysis software is registered in the application name item. The application name can be included in the extraction request. A sensor ID that has been designated by the data analysis software is registered in the sensor ID item. In the access start time item, the time at which the data management server 200 first received an extraction request including the sensor ID from the data analysis software is registered for the set of the data analysis software and the sensor ID.

  Here, in the example of FIG. 18, the software α registers the determination rule (determination rule 0) of the duplicate resolution ID = IDa :: 0, and then determines the determination rule (determination rule 1) of the conflict resolution ID = IDa :: 1. ) Has started data analysis before it is registered. In addition, the software β starts data analysis after the determination rule 1 is registered. In this case, it is presumed that the software α analyzes the sensor data corresponding to the determination rule 0, and the sensor data corresponding to the determination rule 0 is provided to the software α. On the other hand, since it is unclear whether the software β analyzes the sensor data corresponding to the determination rule 0 or the determination rule 1, the software β cannot narrow down the sensor data only by the sensor ID. The software β narrows down the sensor data by designating extraction conditions other than the sensor ID.

  According to the information processing system of the second embodiment, even if the sensor device of the power strip 100a starts to use the same sensor ID as that of the sensor device of the power strip 100, the sensor ID becomes regular due to the regularity of the sensor data. It is possible to detect the occurrence of duplicate use. And based on the regularity of sensor data, the sensor data of the power strip 100 and the sensor data of the power strip 100a can be distinguished. Therefore, it becomes easy to monitor the power consumption of each of the power taps 100 and 100a using the collected sensor data.

  Further, even when the IP address assigned to the sensor device of the power strip 100, 100a changes, the sensor data can be appropriately classified based on the time stamp characteristics. Therefore, the degree of freedom in network design is greater than in the case where the IP address of the sensor device is fixed. Moreover, compared with the case where the sensor ID set in each sensor device cannot be tampered (for example, the sensor ID is encrypted and cannot be changed), the circuit of each sensor device can be prevented from becoming complicated, Moreover, the load of the data management servers 200 and 200a can be suppressed.

  As described above, the functions of the first embodiment can be realized by causing the information processing apparatus 10 to execute a program. The functions of the second embodiment can be realized by causing the data management servers 200 and 200a and the application server 300 to execute a program. The program can be recorded on a computer-readable recording medium (for example, the recording medium 43). As the recording medium, for example, a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like can be used. Magnetic disks include FD and HDD. Optical discs include CD, CD-R (Recordable) / RW (Rewritable), DVD, and DVD-R / RW. The program may be recorded and distributed on a portable recording medium. In that case, the program may be copied from a portable recording medium to another recording medium such as an HDD and then executed.

DESCRIPTION OF SYMBOLS 10 Information processing apparatus 11 Receiving part 12 Data processing part 21, 22 Sensor apparatus

Claims (7)

A data management method executed by an information processing system,
From each of a plurality of sensor devices, sensor data to which identification information is added by the sensor device is received,
Two or more sensor devices that use the same identification information based on the determination rule stored in the determination information storage unit that stores the determination rule indicating the regularity of the sensor data to which the same identification information is added Determine if there is
Classifying the sensor data to which the same identification information is added according to the result of the determination;
Data management method.   The data management method according to claim 1, wherein each sensor data includes a time stamp, and the determination rule uses periodicity of the time stamp.   The data management method according to claim 1, wherein each sensor data includes a time stamp, and the determination rule uses a regularity of a difference between the time stamp and a reception time in the information processing system.   The data management method according to claim 1, wherein the determination rule uses a variation characteristic of a source address when each sensor data is transmitted.   When a request for extracting a set of sensor data is received and the extraction request specifying the same identification information is received, the sensor data with the oldest timing generated among the sets of two or more sensor data obtained by the classification The data management method according to claim 1, wherein a set including the data is extracted. A receiving unit that receives sensor data to which identification information is added by each of the plurality of sensor devices,
Two or more sensor devices that use the same identification information based on the determination rule stored in the determination information storage unit that stores the determination rule indicating the regularity of the sensor data to which the same identification information is added A data processing unit that classifies sensor data to which the same identification information is added according to the determination result;
An information processing apparatus. On the computer,
From each of a plurality of sensor devices, sensor data to which identification information is added by the sensor device is received,
Two or more sensor devices that use the same identification information based on the determination rule stored in the determination information storage unit that stores the determination rule indicating the regularity of the sensor data to which the same identification information is added Determine if there is
Classifying the sensor data to which the same identification information is added according to the result of the determination;
A program that executes processing.

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