WO2017104284A1 - Data processing device, data processing method, and data processing program - Google Patents

Data processing device, data processing method, and data processing program Download PDF

Info

Publication number
WO2017104284A1
WO2017104284A1 PCT/JP2016/082640 JP2016082640W WO2017104284A1 WO 2017104284 A1 WO2017104284 A1 WO 2017104284A1 JP 2016082640 W JP2016082640 W JP 2016082640W WO 2017104284 A1 WO2017104284 A1 WO 2017104284A1
Authority
WO
WIPO (PCT)
Prior art keywords
data
drawing content
past
newly acquired
acquired
Prior art date
Application number
PCT/JP2016/082640
Other languages
French (fr)
Japanese (ja)
Inventor
真理子 上野
博信 阿倍
健央 川浦
広泰 田畠
保之 冨高
康次 長谷川
Original Assignee
三菱電機株式会社
三菱電機ビルテクノサービス株式会社
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 三菱電機株式会社, 三菱電機ビルテクノサービス株式会社 filed Critical 三菱電機株式会社
Priority to JP2017556408A priority Critical patent/JP6440868B2/en
Priority to CN201680071574.5A priority patent/CN108369560A/en
Publication of WO2017104284A1 publication Critical patent/WO2017104284A1/en

Links

Images

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F12/00Accessing, addressing or allocating within memory systems or architectures
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F13/00Interconnection of, or transfer of information or other signals between, memories, input/output devices or central processing units

Definitions

  • the present invention relates to a technique for determining whether drawing data has been updated.
  • Patent Literature 1 disclose methods for collecting update information or network commands of servlets of Web pages operating on the server side and notifying the collected update information or network commands to the user.
  • there are many free softwares for automatic web patrol tools that automatically change web pages when a specified time arrives or when some condition is satisfied, and operate the web pages. Some of such Web automatic patrol tools have a function of transmitting Web page information to a user.
  • Patent Document 4 and Patent Document 5 disclose a technique for notifying that a screen has been updated when the screen is updated on a Web page, or a technique for highlighting an image to notify that the screen has been updated. Is disclosed.
  • Patent Document 6 discloses a technique for comparing a screen automatically generated from a HyperText Markup Language (HTML) command with a display screen and confirming whether the display screen is normally displayed.
  • HTML HyperText Markup Language
  • the main object of the present invention is to solve such problems. That is, the main object of the present invention is to obtain a configuration for determining whether or not the drawing content of drawing data whose drawing content is updated with the passage of time is updated with the passage of time.
  • the data processing apparatus The drawing content of past acquired data that is drawing data acquired in the past from the data update device that updates the drawing content of drawing data as time passes, and the newly acquired data that is drawing data newly acquired from the data update device And a data determination unit for determining whether or not the drawing content of the newly acquired data is the drawing content updated from the past acquired data.
  • the drawing content of the past acquisition data is compared with the drawing content of the new acquisition data, and it is determined whether or not the drawing content of the new acquisition data is the drawing content updated from the past acquisition data.
  • it can be determined whether or not the drawing content of the drawing data whose drawing content is updated with the passage of time is updated with the passage of time.
  • FIG. 3 is a diagram illustrating an example of a system configuration according to the first embodiment.
  • FIG. 3 shows a configuration example of a data processing apparatus according to the first embodiment.
  • FIG. 3 is a flowchart showing an operation example of the data processing apparatus according to the first embodiment.
  • FIG. 4 is a diagram illustrating an example of a system configuration according to a second embodiment.
  • FIG. 6 is a diagram illustrating a configuration example of a monitoring PC according to the second embodiment.
  • FIG. 9 is a flowchart showing an operation example of the monitoring PC according to the second embodiment.
  • FIG. 9 is a flowchart showing an operation example of the monitoring PC according to the second embodiment.
  • FIG. 10 is a diagram illustrating an example of a collation method according to the second embodiment.
  • FIG. 10 is a diagram illustrating an example of a collation method according to the second embodiment.
  • FIG. 10 is a diagram showing a system configuration example according to the third embodiment.
  • FIG. 10 is a diagram illustrating a configuration example of a monitoring PC according to a third embodiment.
  • FIG. 9 is a flowchart showing an operation example of a monitoring PC according to the third embodiment.
  • FIG. 9 is a flowchart showing an operation example of the data processing apparatus according to the fourth embodiment.
  • FIG. *** Explanation of configuration *** FIG. 1 shows a system configuration example according to the present embodiment.
  • Each of the data processing device 10, the notification destination device 20, and the data update device 30 is a computer.
  • the data processing apparatus 10 determines whether or not the drawing content of the drawing data whose drawing content is updated with the passage of time has been updated with the passage of time.
  • the notification destination device 20 is a notification destination for notifying that the data processing device 10 has not updated the drawing data when the data processing device 10 determines that the drawing data has not been updated.
  • the data update device 30 updates the drawing content of the drawing data with the passage of time. More specifically, the data update device 30 updates the drawing content of the drawing data at every predetermined update timing.
  • the data processing device 10, the notification destination device 20 and the data update device 30 are connected by a LAN (Local Area Network) 40.
  • the data processing device 10 and the notification destination device 20 communicate with each other via the LAN 40. Further, the data processing apparatus 10 notifies the notification destination apparatus 20 through the LAN 40 that the drawing data has not been updated.
  • FIG. 2 shows a configuration example of the data processing apparatus 10 according to the present embodiment.
  • the data processing apparatus 10 includes a processor 901, a storage device 902, and a communication device 903 as hardware.
  • the data processing device 10 includes a data determination unit 11 and a notification unit 12 as functional configurations.
  • the storage device 902 stores programs that realize the functions of the data determination unit 11 and the notification unit 12. Then, the processor 901 executes these programs and performs operations of a data determination unit 11 and a notification unit 12 described later.
  • FIG. 2 schematically illustrates a state in which the processor 901 is executing a program that realizes the functions of the data determination unit 11 and the notification unit 12.
  • the communication device 903 communicates with the notification destination device 20 and the data update device 30 via the LAN 40.
  • the data determination unit 11 collates the drawing contents of the past acquired data with the drawing contents of the newly acquired data.
  • the past acquired data is drawing data acquired by the communication device 903 from the data update device 30 in the past.
  • the newly acquired data is drawing data newly acquired from the data update device 30.
  • the data determination unit 11 determines whether or not the drawing content of the newly acquired data is the updated drawing content from the past acquired data by collating the drawing content of the previously acquired data with the drawing content of the newly acquired data.
  • the data update device 30 updates the drawing content of the drawing data at each predetermined update timing.
  • the data determination unit 11 draws the past acquisition data acquired from the data update device 30 at the update timing immediately before the current update timing and the data update device 30 at the current update timing.
  • the drawing contents of newly acquired data newly acquired from the above are collated.
  • the process performed by the data determination unit 11 corresponds to a data determination process.
  • the notification unit 12 is notified via the communication device 903 as a notification destination.
  • the apparatus 20 is notified that the drawing content of the newly acquired data is not the drawing content updated from the past acquired data.
  • the operation procedure shown in FIG. 3 corresponds to an example of a data processing method and a data processing program.
  • the data determination unit 11 determines whether or not the drawing data update timing in the data update device 30 has arrived.
  • the data update device 30 updates the drawing data at a constant update cycle. For example, the data determination unit 11 sets the update period of the drawing data in the data update device 30 in the timer, and determines that the update timing of the drawing data has arrived when the timer notification is received.
  • the data determination unit 11 acquires drawing data from the data update device 30 in step ST302. More specifically, the data determination unit 11 generates a drawing data acquisition request destined for the data update device 30 and outputs the generated acquisition request to the communication device 903.
  • the communication device 903 transmits an acquisition request to the data update device 30 via the LAN 40.
  • the data update device 30 transmits drawing data to the data processing device 10 via the LAN 40 as a response to the acquisition request.
  • the communication device 903 receives the drawing data and outputs the received drawing data to the data determination unit 11.
  • the drawing data acquired in step ST302 is newly acquired data.
  • step ST303 the data determination unit 11 reads past acquired data from the storage device 902.
  • the past acquisition data is drawing data acquired immediately before the new acquisition data acquired in step ST302.
  • step ST304 the data determination unit 11 collates new acquired data with past acquired data.
  • the drawing data includes an update target area in which the drawing contents are updated, and the data determination unit 11 collates the drawing contents of the update target area of the past acquired data with the drawing contents of the update target area of the newly acquired data.
  • the data determination unit 11 compares the drawing contents of the past acquired data with the drawing contents of the newly acquired data, and calculates the similarity between the drawing contents of the past acquired data and the drawn contents of the newly acquired data.
  • step ST305 the data determination unit 11 compares the calculated similarity with a threshold value to determine whether the newly acquired data has been updated from the past acquired data, that is, the drawing content of the newly acquired data is acquired in the past. It is determined whether or not the drawing content is updated from the data.
  • the data determining unit 11 notifies the notifying unit 12 that the newly acquired data has not been updated in step ST306. Then, the notification unit 12 notifies the notification destination device 20 that the new acquired data has not been updated. More specifically, the notification unit 12 generates a notification message that notifies that no update has been made in the newly acquired data.
  • the notification message is, for example, an e-mail message. Then, the notification unit 12 outputs a notification message to the communication device 903.
  • the communication device 903 transmits a notification message to the notification destination device 20 via the LAN 40.
  • step ST307 the data determination unit 11 stores newly acquired data in the storage device 902.
  • the newly acquired data stored in the storage device 902 is read as past acquired data in step ST303 at the next update timing.
  • Embodiment 2 FIG. In this embodiment, the operation procedure described in Embodiment 1 will be described more specifically.
  • data for drawing graphs and characters such as electric energy and temperature in real time is taken as an example of drawing data.
  • FIG. 4 shows a system configuration example according to the present embodiment.
  • the monitoring PC 100, the administrator PC 200, and the Web server 300 are connected via the LAN 40.
  • the LAN 40 is the same as that shown in FIG.
  • the Web server 300 executes a Web application and updates Web page screen data for drawing graphs and characters such as electric energy and temperature in real time.
  • Web page screen data corresponds to an example of drawing data.
  • the Web server 300 corresponds to the data update device 30 described in the first embodiment.
  • the monitoring PC 100 acquires Web page screen data from the Web server 300 and collates Web page screen data corresponding to newly acquired data with Web page screen data corresponding to past acquired data. Further, the monitoring PC 100 determines whether the Web page screen data has been updated. Furthermore, when the Web page screen data is not updated, the monitoring PC 100 transmits a notification message notifying that the Web page screen data is not updated to the administrator PC 200.
  • the content of the notification message may notify only that there was an abnormality in the update of the Web page screen data, or the details of the abnormality such as whether the abnormality of the entire graph or the updating of a specific part May be notified.
  • the monitoring PC 100 corresponds to the data processing apparatus 10 described in the first embodiment.
  • the administrator PC 200 is a Web application administrator's PC.
  • the administrator PC 200 receives the notification message from the monitoring PC 100.
  • the administrator PC 200 corresponds to the notification destination apparatus 20 described in the first embodiment.
  • FIG. 5 shows a configuration example of the monitoring PC 100 according to the present embodiment.
  • the processor 901, the storage device 902, and the communication device 903 are the same as those described in the first embodiment.
  • the monitoring PC 100 includes a browser 101, a screen acquisition processing unit 102, and a screen collation processing unit 103 as functional configurations.
  • the screen acquisition processing unit 102 accesses the Web application of the Web server 300 using the browser 101.
  • the screen acquisition processing unit 102 performs automatic transition of a Web page by transmitting an HTTP (Hypertext Transfer Protocol) request, and captures Web page screen data to be verified.
  • the screen acquisition processing unit 102 stores the captured web page screen data in the storage device 902.
  • HTTP Hypertext Transfer Protocol
  • the screen collation processing unit 103 performs web page screen data collation processing, and transmits a notification message to the administrator PC 200 when the web page screen data is not updated.
  • the screen acquisition processing unit 102 and the screen collation processing unit 103 correspond to the data determination unit 11 and the notification unit 12 described in the first embodiment.
  • FIG. 6 is a flowchart showing an operation example of the monitoring PC 100 according to the present embodiment.
  • ST101 is a process performed by the screen acquisition processing unit 102
  • ST102 is a process performed by the screen collation processing unit 103.
  • the screen acquisition processing unit 102 transmits an HTTP request to the Web server 300 using the browser 101, and displays a Web page (step ST1011). Furthermore, the screen acquisition processing unit 102 transmits an HTTP request to the web server 300 using the browser 101, performs automatic transition of the web page, and transitions to the page to be verified (steps ST1012 and ST1014). The screen acquisition processing unit 102 performs screen capture on the transitioned page to be collated (ST1013, ST1015).
  • the flowchart in FIG. 6 shows an example in which two types of Web page screen data are acquired in a single process. In screen capture, the screen acquisition processing unit 102 may acquire screen shot data of Web page screen data, or may acquire Web page screen data itself.
  • screen collation processing section 103 reads Web page screen data acquired in the past from storage device 902, and performs screen collation processing (step ST1021). If the display is abnormal, that is, if the Web page screen data has not been updated (YES in step ST1022), screen collation processing unit 103 transmits a notification message to administrator PC 200 (step ST1023). Finally, screen collation processing unit 103 stores the Web page screen data in storage device 902 (step ST1024).
  • the monitoring PC 100 repeats this series of processes at every update timing of the Web page screen data on the Web server 300. For example, when the graph or the like is updated every hour in the Web server 300, the screen acquisition processing unit 102 and the screen collation processing unit 103 perform the process of FIG. 6 every hour.
  • FIG. 7 is a flowchart showing details of the screen matching process (ST1021 in FIG. 6).
  • the flowchart of FIG. 7 shows the flow of processing when performing a two-stage verification process.
  • ST203 represents the first-stage collation process
  • ST204 represents the second-stage collation process.
  • processing similar to ST203 or ST204 may be inserted between ST204 and ST1023.
  • the screen acquisition processing unit 102 reads parameters such as a collation area and a threshold used for collation in steps ST203 and ST204 from the storage device 902 in step ST201.
  • the parameter may be described in a text file by the user.
  • the parameters may be set from a setting screen by GUI (Graphical User Interface).
  • the screen collation processing unit 103 reads the web page screen data to be collated from the storage device 902 in step S202.
  • screen collation processing section 103 sets the first collation area in step ST2031. Further, screen collation processing section 103 calculates the similarity in step ST2032, and determines in step ST2033 whether the similarity falls within the range of the first-stage collation threshold. If the degree of similarity is not within the range of the first-stage collation threshold (NO in step ST2033), screen collation processing unit 103 transmits a notification message to administrator PC 200 (step ST1023), and performs collation processing. finish. If the similarity is within the threshold range for the first stage collation (YES in step ST2033), screen collation processing unit 103 performs the second stage collation process (step ST204).
  • step ST204 similarly to the first-stage collation process (step ST203), the screen collation processing unit 103 sets the second-stage collation area in step ST2041, and in step ST2042 Calculate similarity. Then, in ST2043, screen collation processing section 103 determines whether or not the similarity is within the range of the second-stage collation threshold. If the similarity does not fall within the threshold range for the second stage collation (NO in step ST2043), screen collation processing unit 103 transmits a notification message to administrator PC 200 (step ST1023), and ends the collation process. To do. If the degree of similarity is within the range of the second-stage collation threshold (YES in step ST2043), the process proceeds to step ST1024. When the process of FIG. 7 ends, the screen matching processing unit 103 may output a result that the update is normal / abnormal as a log file.
  • FIG. 8 illustrates a collation method example 1 by the screen collation processing unit 103.
  • screen collation processing unit 103 is displaying graphs such as bar graphs and line graphs that are displayed according to time correctly? Determine.
  • the screen collation processing unit 103 compares the Web page screen data at the previous time with the Web page screen data at the current time, and determines whether or not the location corresponding to the time has changed. When the similarity of the part corresponding to the time is large, the display is not changed between the Web page screen at the previous time and the Web page screen data at the current time, and the screen matching processing unit 103 is abnormal. judge.
  • the screen collation processing unit 103 determines that it is normal.
  • screen collation processing section 103 sets the display location corresponding to the time as the collation area of the collation area setting of ST2031 or ST2041 in the flowchart of FIG. 7, and whether the similarity is within the threshold in ST2033 or ST2043 It is determined whether the display is normal / abnormal. For example, when the similarity is 30% and the threshold is 0% or more and 70% or less, the screen matching processing unit 103 determines that the display is normal.
  • a broken line bar graph is a predicted value graph
  • a solid line bar graph is a measured value graph.
  • the 9:00 graph is a predicted value.
  • the Web page screen data of FIG. 8B is obtained when one hour has elapsed, the 9:00 graph is updated to the actual measurement value. That is, the degree of similarity between the 9:00 graph of FIG. 8A and the 9:00 graph of FIG. 8B is low.
  • the Web page screen data of FIG. 8C is obtained when one hour has passed, the graph of 9:00 is not updated with the predicted value. That is, the degree of similarity between the 9:00 graph in FIG. 8A and the 9:00 graph in FIG. 8C is high.
  • FIG. 9 shows a collation method example 2 by the screen collation processing unit 103.
  • the screen collation processing unit 103 causes a display abnormality in which a graph is not drawn at all due to data reading failure or an abnormality of the browser 101 of the monitoring PC 100 Is detected.
  • the screen collation processing unit 103 compares the Web page screen data at the previous time with the Web page screen data at the current time, and determines whether a graph is drawn. When the similarity of the graph part is small, the screen collation processing unit 103 determines that the display is abnormal because it is different from the Web page screen at the previous time and the graph is not displayed at all.
  • the screen collation processing unit 103 sets the graph part as a collation area for the collation area setting of ST2031 and ST2041 in the flowchart of FIG. 7, and whether the similarity is within the threshold in ST2033 or ST2043 is displayed. Determine whether it is normal / abnormal. For example, when the similarity is 10% and the threshold value is 70% or more and 100% or less, the screen matching processing unit 103 determines that the display is abnormal. On the other hand, when the similarity is 90% at the same threshold, the screen matching processing unit 103 determines that the display is normal.
  • the threshold value may be determined from screen data collected during an arbitrary period. For example, an abnormal label or a normal label is manually added to each of the Web page screen data collected for one week, and the screen matching processing unit 103 determines a threshold value from a set of the label and the similarity. Alternatively, the screen matching processing unit 103 may learn the determination model (threshold value) from the feature amount of the screen data acquired at the current time and the data trend, and automatically update the model (threshold value).
  • the screen collation processing unit 103 determines whether at least a part of the web page screen data is updated according to the collation method example 2 of FIG. When at least a part of the web page screen data is updated, the screen collation processing unit 103 determines whether the web page screen data is properly updated according to the collation method example 1 of FIG.
  • Embodiment 3 FIG. Also in the present embodiment, the operation procedure described in the first embodiment will be described more specifically.
  • the native application compares the screen shot at the current time with the past screen shot by GUI screen collation. Then, the native application determines whether the GUI screen is normally displayed, and notifies the administrator PC when the display is abnormal.
  • a GUI screen generated by a native application corresponds to an example of drawing data.
  • FIG. 10 shows a system configuration example according to the present embodiment.
  • the monitoring PC 110 and the administrator PC 200 are connected via the LAN 40.
  • the administrator PC 200 and the LAN 40 are the same as those shown in FIG. That is, the administrator PC 200 corresponds to the notification destination apparatus 20 described in the first embodiment.
  • the monitoring PC 110 corresponds to the data processing device 10 and the data update device 30 described in the first embodiment.
  • FIG. 11 shows a configuration example of the monitoring PC 110 according to the present embodiment.
  • the processor 901, the storage device 902, and the communication device 903 are the same as those described in the first embodiment.
  • the monitoring PC 100 includes a native application 111, a screen acquisition processing unit 102, and a screen collation processing unit 103 as functional configurations.
  • the screen acquisition processing unit 102 activates the native application 111, automatically reproduces an operation by sending an event, and captures screen data to be verified. Further, the screen acquisition processing unit 102 stores the captured screen data in the storage device 902. For automatic operation reproduction, commercially available or free operation automatic reproduction software may be used.
  • the screen verification processing unit 103 performs a screen data verification process, and transmits a notification message to the administrator PC 200 if the screen data has not been updated.
  • the screen acquisition processing unit 102 and the screen matching processing unit 103 correspond to the data determination unit 11 and the notification unit 12 described in the embodiment.
  • the native application 111 corresponds to the data update device 30.
  • a plurality of native applications 111 may be arranged in the same network and screen verification may be performed simultaneously. For example, screen collation may be performed simultaneously for PCs having different resolutions, and PCs having different versions of OS (Operating System) and Java (registered trademark).
  • OS Operating System
  • Java registered trademark
  • FIG. 12 is a flowchart showing an operation example of the monitoring PC 100 according to the present embodiment.
  • ST301 is a process performed by the screen acquisition processing unit 102
  • ST302 is a process performed by the screen collation processing unit 103.
  • the screen acquisition processing unit 102 activates the native application 111 (step ST3011).
  • the screen acquisition processing unit 102 outputs a command such as an event to the native application 111, performs automatic reproduction of the operation, and transitions to screen data to be collated (ST3012, ST3014).
  • the screen acquisition processing unit 102 performs screen capture with the screen data to be collated (ST3013, ST3015).
  • the flowchart of FIG. 12 shows an example in which two types of screen data are acquired in a single process. In the screen capture, the screen acquisition processing unit 102 may acquire screen shot data of the screen data, or may acquire the screen data itself.
  • screen collation processing section 103 reads screen data acquired in the past from storage device 902, and performs screen collation processing (step ST3021). If the display is abnormal, that is, if the screen data has not been updated (YES in step ST3022), screen collation processing unit 103 transmits a notification message to administrator PC 200 (step ST3023). Finally, screen collation processing unit 103 stores the screen data in storage device 902 (step ST3024).
  • the monitoring PC 100 repeats this series of processing at each screen data update timing in the native application 111. For example, when the graph or the like is updated every hour in the native application 111, the screen acquisition processing unit 102 and the screen collation processing unit 103 perform the process of FIG. 12 every hour.
  • the flow of the collation process is the same as that in the second embodiment, as shown in the flowchart of FIG.
  • the collation method, similarity calculation method, and threshold determination method may be the same as those in the first embodiment.
  • the monitoring PC 100 may calculate the similarity after performing the area enlargement / reduction process as a pre-process when collating screens with different resolutions or screens with different versions of OS or Java (registered trademark). Good.
  • the monitoring PC 100 detects a display abnormality due to the abnormality of the native application 111 by screen collation for the area of the graph portion in the screen, and notifies the administrator PC 200 by e-mail, for example, if it is abnormal.
  • Embodiment 4 FIG. In the present embodiment, a configuration capable of detecting a drawing abnormality or a drawing change point will be described. *** Explanation of configuration *** A system configuration example according to the present embodiment is as shown in FIG. Hereinafter, differences from the first embodiment will be mainly described. Matters not described below are the same as those in the first embodiment.
  • the data update device 30 updates the drawing content of the drawing data with the passage of time. More specifically, the data update device 30 updates the drawing content of the drawing data at every predetermined update timing.
  • the data processing apparatus 10 holds model data in the storage device 902.
  • an unsteady pattern that is an unsteady drawing pattern in the drawing data is defined.
  • An unsteady pattern is, for example, a drawing time transition in drawing data when a drawing abnormality occurs.
  • the model data includes, for example, a drawing pattern whose current time value is less than 1 ⁇ 2 of the previous time value in the graph shown in FIG.
  • a drawing pattern that is twice or more the numerical value of the previous time is defined as an unsteady pattern.
  • an unsteady pattern in which a drawing change point is indicated may be defined in the model data. In this case, in the model data, for example, in a graph as shown in FIG.
  • the current time value is 2/3 or less (however, 1/2 or more) of the value of the previous time.
  • a drawing pattern in which the numerical value of the pattern or the current time is 1.5 times or more (but less than twice) the numerical value of the previous time is defined as an unsteady pattern.
  • drawing data acquired in the past can be used as model data.
  • the user of the data processing apparatus 10 can arbitrarily define model data and non-stationary patterns. Note that the above values such as “1/2”, “2/3”, “1.5” times, and “2” times are examples, and the user can arbitrarily define the values used for the unsteady pattern. .
  • the data determination unit 11 compares the model data with the drawing content of the newly acquired data, and whether the drawing content of the newly acquired data matches the unsteady pattern. Determine whether or not. That is, the data determination unit 11 determines whether there is a drawing abnormality or a change in drawing tendency defined in the model data in the drawing data. In addition, when the data determination unit 11 determines that the drawing content of the newly acquired data matches the non-steady pattern, the notification unit 12 displays the drawing content of the newly acquired data in the notification destination device 20 that is the default notification destination. Notify that it matches an unsteady pattern.
  • the data determination unit 11 determines whether or not the timing set in advance by the user has arrived. For example, the data determination unit 11 captures a network command and determines that the timing set by the user has arrived when the network command registered in advance by the user is captured. When the timing designated by the user has arrived (YES in step ST1301), the data determination unit 11 acquires drawing data from the data update device 30 in step ST1302. More specifically, the data determination unit 11 generates a drawing data acquisition request destined for the data update device 30 and outputs the generated acquisition request to the communication device 903. The communication device 903 transmits an acquisition request to the data update device 30 via the LAN 40.
  • the data update device 30 transmits drawing data to the data processing device 10 via the LAN 40 as a response to the acquisition request.
  • the communication device 903 receives the drawing data and outputs the received drawing data to the data determination unit 11.
  • the drawing data acquired in step ST1302 is newly acquired data.
  • step ST1303 the data determination unit 11 reads model data from the storage device 902. Note that the user of the data processing apparatus 10 may define the newly acquired data acquired in step ST1302 at the previous update timing as model data.
  • step ST1304 the data determination unit 11 collates newly acquired data with model data.
  • the drawing data includes an update target area in which the drawing content is updated, and the data determination unit 11 collates the drawing content (unsteady pattern) in the update target area of the model data with the drawing content in the update target area of the newly acquired data. . Further, the data determination unit 11 collates the drawing contents of the model data with the drawing contents of the newly acquired data, and calculates the similarity between the drawing contents of the model data and the drawing contents of the newly acquired data.
  • step ST1305 the data determination unit 11 compares the calculated similarity with a threshold value and determines whether or not the drawing content of the newly acquired data matches the unsteady pattern defined in the model data. . That is, the data determination unit 11 determines whether or not there is a drawing abnormality or a change in drawing tendency in the newly acquired data. If the similarity is greater than or equal to the threshold, the data determination unit 11 determines that the drawing content of the newly acquired data matches the unsteady pattern defined in the model data.
  • step ST1305 If it is determined in step ST1305 that the drawing content of the newly acquired data matches the unsteady pattern defined in the model data, in step ST1306, the data determining unit 11 sends the drawing content of the newly acquired data to the notification unit 12. Is in conformity with the unsteady pattern defined in the model data. Then, the notification unit 12 indicates that the drawing content of the newly acquired data matches the non-stationary pattern defined in the model data in the notification destination device 20, that is, the drawing abnormality or the change in the drawing tendency occurs in the newly acquired data. Notify that More specifically, the notification unit 12 generates a notification message notifying that a drawing abnormality or a change in drawing tendency has occurred in the newly acquired data.
  • the notification message is, for example, an e-mail message.
  • the notification unit 12 outputs a notification message to the communication device 903.
  • the communication device 903 transmits a notification message to the notification destination device 20 via the LAN 40.
  • the data determination unit 11 stores newly acquired data in the storage device 902. As described above, the newly acquired data stored in the storage device 902 here may be read as model data in step S1303 of the next update timing.
  • the drawing contents of the model data defined by the user and the drawing contents of the newly acquired data are collated with respect to the drawing data acquired in the past or the drawing data of the screen assumed when the drawing abnormality or the drawing tendency changes. To do. Then, it is determined whether or not the drawing abnormality or change defined in the model data has occurred in the drawing content of the newly acquired data. For this reason, according to the present embodiment, it is determined whether or not the drawing abnormality or change defined in the model data has occurred in the drawing contents of the drawing data whose drawing contents are updated as time passes. Can do.
  • the processor 901 is an IC (Integrated Circuit) that performs processing.
  • the processor 901 is a CPU (Central Processing Unit), a DSP (Digital Signal Processor), or the like.
  • the storage device 902 includes a RAM (Random Access Memory), a ROM (Read Only Memory), a flash memory, and an HDD (Hard Disk). Drive) and the like.
  • the communication device 903 includes a receiver that receives data and a transmitter that transmits data.
  • the communication device 903 is, for example, a communication chip or a NIC (Network Interface Card).
  • the storage device 902 also stores an OS (Operating System). Then, at least a part of the OS is executed by the processor 901.
  • the processor 901 implements the functions of the data determination unit 11, the notification unit 12, the screen acquisition processing unit 102, and the screen collation processing unit 103 (hereinafter collectively referred to as “unit”) while executing at least a part of the OS. Run the program.
  • the data processing device 10 the monitoring PC 100, and the monitoring PC 110 may include a plurality of processors.
  • information, data, signal values, and variable values indicating the processing results of “unit” are stored in the storage device 902, a register in the processor 901, or a cache memory.
  • the program for realizing the function of “unit” may be stored in a portable storage medium such as a magnetic disk, a flexible disk, an optical disk, a compact disk, a Blu-ray (registered trademark) disk, or a DVD.
  • “part” may be read as “circuit” or “process” or “procedure” or “processing”.
  • the data processing device 10, the monitoring PC 100, and the monitoring PC 110 are composed of a logic IC (Integrated Circuit), a GA (Gate Array), an ASIC (Application Specific Integrated Circuit), and an FPGA (Field-Programmable Gate) electronic circuit circuit. May be.
  • each “unit” is realized as part of an electronic circuit.
  • the processor and the electronic circuit are also collectively referred to as a processing circuit.
  • the LAN 40 is described as an example of a network, but a network other than the LAN 40 may be used.
  • 10 data processing device 11 data determination unit, 12 notification unit, 20 notification destination device, 30 data update device, 40 LAN, 100 monitoring PC, 101 browser, 102 screen acquisition processing unit, 103 screen verification processing unit, 110 for monitoring PC, 111 native application, 200 administrator PC, 300 Web server.

Abstract

A data assessment unit (11): compares rendering content of previously acquired data, which is rendered data which has previously been acquired from a data update device which updates the rendering content of rendered data in accordance with elapsed time, with rendering content of newly acquired data, which is rendered data which has been newly acquired from the data update device; and assesses whether the rendering content of the newly acquired data is rendering content which has been updated from the previously acquired data.

Description

データ処理装置、データ処理方法及びデータ処理プログラムData processing apparatus, data processing method, and data processing program
 本発明は、描画データが更新されているか否かを判定する技術に関する。 The present invention relates to a technique for determining whether drawing data has been updated.
 サーバサイドで動作するWebページのサーブレットの更新情報又はネットワークコマンドを収集し、収集した更新情報又はネットワークコマンドを利用者に通知する方法が特許文献1、特許文献2及び特許文献3に開示されている。
 また、規定された時刻が到来した際又は何らかの条件が満たされた際に自動でWebページを遷移させ、Webページを操作するWeb自動巡回ツールにはフリーソフトが多数存在する。このようなWeb自動巡回ツールには、利用者にWebページの情報を送信する機能を有するものが存在する。
 その他、特許文献4及び特許文献5には、Webページにおいて画面が更新された場合に画面が更新されたことを通知する技術又は画面が更新されたことを通知するために画像を強調表示する技術が開示されている。
 また、特許文献6には、HTML(HyperText Markup Language)コマンドから自動生成された画面と表示画面とを比較し、表示画面が正常に表示されているかどうか確認する技術が開示されている。
Patent Literature 1, Patent Literature 2 and Patent Literature 3 disclose methods for collecting update information or network commands of servlets of Web pages operating on the server side and notifying the collected update information or network commands to the user. .
In addition, there are many free softwares for automatic web patrol tools that automatically change web pages when a specified time arrives or when some condition is satisfied, and operate the web pages. Some of such Web automatic patrol tools have a function of transmitting Web page information to a user.
In addition, Patent Document 4 and Patent Document 5 disclose a technique for notifying that a screen has been updated when the screen is updated on a Web page, or a technique for highlighting an image to notify that the screen has been updated. Is disclosed.
Patent Document 6 discloses a technique for comparing a screen automatically generated from a HyperText Markup Language (HTML) command with a display screen and confirming whether the display screen is normally displayed.
特開平11-259354号公報JP 11-259354 A 特開2002-99557号公報JP 2002-99557 A 特表2012-529687号公報Special table 2012-5296687 gazette 特開2011-204048号公報JP 2011-2004048 A 特開2005-190443号公報JP 2005-190443 A
 特許文献1~6に開示されている従来方式のネットワークコマンドによる確認では、時間の経過に伴って描画内容が更新される描画データの描画内容が時間の経過に伴って更新されているか否かを判定することができないという課題がある。
 本発明は、このような課題を解決することを主な目的とする。つまり、本発明は、時間の経過に伴って描画内容が更新される描画データの描画内容が時間の経過に伴って更新されているか否かを判定する構成を得ることを主な目的とする。
In the confirmation using the conventional network command disclosed in Patent Documents 1 to 6, it is determined whether or not the drawing contents of the drawing data whose drawing contents are updated as time passes are updated as time passes. There is a problem that it cannot be determined.
The main object of the present invention is to solve such problems. That is, the main object of the present invention is to obtain a configuration for determining whether or not the drawing content of drawing data whose drawing content is updated with the passage of time is updated with the passage of time.
 本発明に係るデータ処理装置は、
 時間の経過に伴って描画データの描画内容を更新するデータ更新装置から過去に取得した描画データである過去取得データの描画内容と、前記データ更新装置から新たに取得した描画データである新規取得データの描画内容とを照合し、前記新規取得データの描画内容が前記過去取得データから更新された描画内容になっているか否かを判定するデータ判定部を有する。
The data processing apparatus according to the present invention
The drawing content of past acquired data that is drawing data acquired in the past from the data update device that updates the drawing content of drawing data as time passes, and the newly acquired data that is drawing data newly acquired from the data update device And a data determination unit for determining whether or not the drawing content of the newly acquired data is the drawing content updated from the past acquired data.
 本発明によれば、過去取得データの描画内容と新規取得データの描画内容とを照合し、新規取得データの描画内容が過去取得データから更新された描画内容になっているか否かを判定することで、時間の経過に伴って描画内容が更新される描画データの描画内容が時間の経過に伴って更新されているか否かを判定することができる。 According to the present invention, the drawing content of the past acquisition data is compared with the drawing content of the new acquisition data, and it is determined whether or not the drawing content of the new acquisition data is the drawing content updated from the past acquisition data. Thus, it can be determined whether or not the drawing content of the drawing data whose drawing content is updated with the passage of time is updated with the passage of time.
実施の形態1に係るシステム構成例を示す図。FIG. 3 is a diagram illustrating an example of a system configuration according to the first embodiment. 実施の形態1に係るデータ処理装置の構成例を示す図。FIG. 3 shows a configuration example of a data processing apparatus according to the first embodiment. 実施の形態1に係るデータ処理装置の動作例を示すフローチャート図。FIG. 3 is a flowchart showing an operation example of the data processing apparatus according to the first embodiment. 実施の形態2に係るシステム構成例を示す図。FIG. 4 is a diagram illustrating an example of a system configuration according to a second embodiment. 実施の形態2に係る監視用PCの構成例を示す図。FIG. 6 is a diagram illustrating a configuration example of a monitoring PC according to the second embodiment. 実施の形態2に係る監視用PCの動作例を示すフローチャート図。FIG. 9 is a flowchart showing an operation example of the monitoring PC according to the second embodiment. 実施の形態2に係る監視用PCの動作例を示すフローチャート図。FIG. 9 is a flowchart showing an operation example of the monitoring PC according to the second embodiment. 実施の形態2に係る照合方式の例を示す図。FIG. 10 is a diagram illustrating an example of a collation method according to the second embodiment. 実施の形態2に係る照合方式の例を示す図。FIG. 10 is a diagram illustrating an example of a collation method according to the second embodiment. 実施の形態3に係るシステム構成例を示す図。FIG. 10 is a diagram showing a system configuration example according to the third embodiment. 実施の形態3に係る監視用PCの構成例を示す図。FIG. 10 is a diagram illustrating a configuration example of a monitoring PC according to a third embodiment. 実施の形態3に係る監視用PCの動作例を示すフローチャート図。FIG. 9 is a flowchart showing an operation example of a monitoring PC according to the third embodiment. 実施の形態4に係るデータ処理装置の動作例を示すフローチャート図。FIG. 9 is a flowchart showing an operation example of the data processing apparatus according to the fourth embodiment.
 実施の形態1.
***構成の説明***
 図1は、本実施の形態に係るシステム構成例を示す。
 データ処理装置10、通知先装置20及びデータ更新装置30は、それぞれコンピュータである。
 データ処理装置10は、時間の経過に伴って描画内容が更新される描画データの描画内容が時間の経過に伴って更新されているか否かを判定する。
 通知先装置20は、データ処理装置10が描画データが更新されていないと判定した場合に、データ処理装置10が描画データが更新されていない旨を通知する通知先である。
 データ更新装置30は、時間の経過に伴って描画データの描画内容を更新する。
 より具体的には、データ更新装置30は、既定の更新タイミングごとに描画データの描画内容を更新する。
 データ処理装置10、通知先装置20及びデータ更新装置30はLAN(Local Area Network)40により接続されている。データ処理装置10と通知先装置20はLAN40を介して相互に通信を行う。また、データ処理装置10はLAN40を介して通知先装置20に描画データが更新されていない旨を通知する。
Embodiment 1 FIG.
*** Explanation of configuration ***
FIG. 1 shows a system configuration example according to the present embodiment.
Each of the data processing device 10, the notification destination device 20, and the data update device 30 is a computer.
The data processing apparatus 10 determines whether or not the drawing content of the drawing data whose drawing content is updated with the passage of time has been updated with the passage of time.
The notification destination device 20 is a notification destination for notifying that the data processing device 10 has not updated the drawing data when the data processing device 10 determines that the drawing data has not been updated.
The data update device 30 updates the drawing content of the drawing data with the passage of time.
More specifically, the data update device 30 updates the drawing content of the drawing data at every predetermined update timing.
The data processing device 10, the notification destination device 20 and the data update device 30 are connected by a LAN (Local Area Network) 40. The data processing device 10 and the notification destination device 20 communicate with each other via the LAN 40. Further, the data processing apparatus 10 notifies the notification destination apparatus 20 through the LAN 40 that the drawing data has not been updated.
 図2は、本実施の形態に係るデータ処理装置10の構成例を示す。
 データ処理装置10は、ハードウェアとして、プロセッサ901、記憶装置902及び通信装置903を備える。
 また、データ処理装置10は、機能構成として、データ判定部11及び通知部12を備える。
 記憶装置902には、データ判定部11及び通知部12の機能を実現するプログラムが記憶されている。
 そして、プロセッサ901がこれらプログラムを実行して、後述するデータ判定部11及び通知部12の動作を行う。
 図2では、プロセッサ901がデータ判定部11及び通知部12の機能を実現するプログラムを実行している状態を模式的に表している。
 通信装置903は、LAN40を介して通知先装置20及びデータ更新装置30と通信を行う。
FIG. 2 shows a configuration example of the data processing apparatus 10 according to the present embodiment.
The data processing apparatus 10 includes a processor 901, a storage device 902, and a communication device 903 as hardware.
The data processing device 10 includes a data determination unit 11 and a notification unit 12 as functional configurations.
The storage device 902 stores programs that realize the functions of the data determination unit 11 and the notification unit 12.
Then, the processor 901 executes these programs and performs operations of a data determination unit 11 and a notification unit 12 described later.
FIG. 2 schematically illustrates a state in which the processor 901 is executing a program that realizes the functions of the data determination unit 11 and the notification unit 12.
The communication device 903 communicates with the notification destination device 20 and the data update device 30 via the LAN 40.
***動作の説明***
 データ判定部11は、過去取得データの描画内容と新規取得データの描画内容とを照合する。
 過去取得データは、通信装置903がデータ更新装置30から過去に取得した描画データである。
 新規取得データは、データ更新装置30から新たに取得した描画データである。
 データ判定部11は、過去取得データの描画内容と新規取得データの描画内容との照合により、新規取得データの描画内容が過去取得データから更新された描画内容になっているか否かを判定する。
 前述したように、データ更新装置30は、既定の更新タイミングごとに描画データの描画内容を更新する。このため、データ判定部11は、更新タイミングごとに、現在の更新タイミングの1つ前の更新タイミングでデータ更新装置30から取得した過去取得データの描画内容と、現在の更新タイミングでデータ更新装置30から新たに取得した新規取得データの描画内容とを照合する。
 なお、データ判定部11により行われる処理は、データ判定処理に相当する。
*** Explanation of operation ***
The data determination unit 11 collates the drawing contents of the past acquired data with the drawing contents of the newly acquired data.
The past acquired data is drawing data acquired by the communication device 903 from the data update device 30 in the past.
The newly acquired data is drawing data newly acquired from the data update device 30.
The data determination unit 11 determines whether or not the drawing content of the newly acquired data is the updated drawing content from the past acquired data by collating the drawing content of the previously acquired data with the drawing content of the newly acquired data.
As described above, the data update device 30 updates the drawing content of the drawing data at each predetermined update timing. For this reason, for each update timing, the data determination unit 11 draws the past acquisition data acquired from the data update device 30 at the update timing immediately before the current update timing and the data update device 30 at the current update timing. The drawing contents of newly acquired data newly acquired from the above are collated.
The process performed by the data determination unit 11 corresponds to a data determination process.
 通知部12は、データ判定部11により新規取得データの描画内容が過去取得データから更新された描画内容になっていないと判定された場合に、通信装置903を介して、通知先である通知先装置20に、新規取得データの描画内容が過去取得データから更新された描画内容になっていないことを通知する。 When the data determination unit 11 determines that the drawing content of the newly acquired data is not the updated drawing content from the past acquired data, the notification unit 12 is notified via the communication device 903 as a notification destination. The apparatus 20 is notified that the drawing content of the newly acquired data is not the drawing content updated from the past acquired data.
 次に、図3のフローチャートを参照して、本実施の形態に係るデータ処理装置10の動作例を説明する。
 なお、図3に示す動作手順は、データ処理方法及びデータ処理プログラムの例に相当する。
Next, an operation example of the data processing apparatus 10 according to the present embodiment will be described with reference to the flowchart of FIG.
The operation procedure shown in FIG. 3 corresponds to an example of a data processing method and a data processing program.
 先ず、ステップST301において、データ判定部11は、データ更新装置30における描画データの更新タイミングが到来したか否かを判定する。
 データ更新装置30では一定の更新周期で描画データを更新している。
 データ判定部11は、例えば、タイマにデータ更新装置30における描画データの更新周期を設定し、タイマ通知があった場合に描画データの更新タイミングが到来したと判定する。
First, in step ST301, the data determination unit 11 determines whether or not the drawing data update timing in the data update device 30 has arrived.
The data update device 30 updates the drawing data at a constant update cycle.
For example, the data determination unit 11 sets the update period of the drawing data in the data update device 30 in the timer, and determines that the update timing of the drawing data has arrived when the timer notification is received.
 更新タイミングが到来した場合(ステップST301でYES)は、ステップST302において、データ判定部11はデータ更新装置30から描画データを取得する。
 より具体的には、データ判定部11はデータ更新装置30を宛先とする描画データの取得リクエストを生成し、生成した取得リクエストを通信装置903に出力する。
 通信装置903は、取得リクエストをLAN40を介してデータ更新装置30に送信する。
 データ更新装置30は、取得リクエストに対する応答として、描画データをLAN40を介してデータ処理装置10に送信する。
 データ処理装置10では、通信装置903が描画データを受信し、受信した描画データをデータ判定部11に出力する。
 ステップST302で取得した描画データは新規取得データである。
If the update timing has arrived (YES in step ST301), the data determination unit 11 acquires drawing data from the data update device 30 in step ST302.
More specifically, the data determination unit 11 generates a drawing data acquisition request destined for the data update device 30 and outputs the generated acquisition request to the communication device 903.
The communication device 903 transmits an acquisition request to the data update device 30 via the LAN 40.
The data update device 30 transmits drawing data to the data processing device 10 via the LAN 40 as a response to the acquisition request.
In the data processing device 10, the communication device 903 receives the drawing data and outputs the received drawing data to the data determination unit 11.
The drawing data acquired in step ST302 is newly acquired data.
 次に、ステップST303において、データ判定部11が記憶装置902から過去取得データを読み出す。
 過去取得データは、ステップST302で取得した新規取得データの1つ前に取得した描画データである。
Next, in step ST303, the data determination unit 11 reads past acquired data from the storage device 902.
The past acquisition data is drawing data acquired immediately before the new acquisition data acquired in step ST302.
 次に、ステップST304において、データ判定部11は新規取得データと過去取得データを照合する。
 描画データには描画内容が更新される更新対象領域があり、データ判定部11は過去取得データの更新対象領域の描画内容と新規取得データの更新対象領域の描画内容とを照合する。
 また、データ判定部11は過去取得データの描画内容と新規取得データの描画内容とを照合して、過去取得データの描画内容と新規取得データの描画内容との類似度を算出する。
Next, in step ST304, the data determination unit 11 collates new acquired data with past acquired data.
The drawing data includes an update target area in which the drawing contents are updated, and the data determination unit 11 collates the drawing contents of the update target area of the past acquired data with the drawing contents of the update target area of the newly acquired data.
In addition, the data determination unit 11 compares the drawing contents of the past acquired data with the drawing contents of the newly acquired data, and calculates the similarity between the drawing contents of the past acquired data and the drawn contents of the newly acquired data.
 次に、ステップST305において、データ判定部11は、算出した類似度を閾値と比較して、新規取得データが過去取得データから更新されているか否か、すなわち、新規取得データの描画内容が過去取得データから更新された描画内容になっているか否かを判定する。 Next, in step ST305, the data determination unit 11 compares the calculated similarity with a threshold value to determine whether the newly acquired data has been updated from the past acquired data, that is, the drawing content of the newly acquired data is acquired in the past. It is determined whether or not the drawing content is updated from the data.
 ステップST305で新規取得データにおいて更新がなされていないと判定した場合は、ステップST306において、データ判定部11が通知部12に新規取得データにおいて更新がなされていない旨を通知する。そして、通知部12が通知先装置20に新規取得データにおいて更新がなされていない旨を通知する。
 より具体的には、通知部12は、新規取得データにおいて更新がなされていない旨を通知する通知メッセージを生成する。
 通知メッセージは、例えば、電子メールメッセージである。
 そして、通知部12は通知メッセージを通信装置903に出力する。
 通信装置903は通知メッセージをLAN40を介して通知先装置20に送信する。
If it is determined in step ST305 that the newly acquired data has not been updated, the data determining unit 11 notifies the notifying unit 12 that the newly acquired data has not been updated in step ST306. Then, the notification unit 12 notifies the notification destination device 20 that the new acquired data has not been updated.
More specifically, the notification unit 12 generates a notification message that notifies that no update has been made in the newly acquired data.
The notification message is, for example, an e-mail message.
Then, the notification unit 12 outputs a notification message to the communication device 903.
The communication device 903 transmits a notification message to the notification destination device 20 via the LAN 40.
 次に、ステップST307において、データ判定部11が新規取得データを記憶装置902に格納する。
 なお、ここで記憶装置902に格納した新規取得データは、次の更新タイミングのステップST303において過去取得データとして読み出される。
Next, in step ST307, the data determination unit 11 stores newly acquired data in the storage device 902.
Here, the newly acquired data stored in the storage device 902 is read as past acquired data in step ST303 at the next update timing.
***実施の形態の効果の説明***
 本実施の形態では、過去取得データの描画内容と新規取得データの描画内容とを照合し、新規取得データの描画内容が過去取得データから更新された描画内容になっているか否かを判定する。このため、本実施の形態によれば、時間の経過に伴って描画内容が更新される描画データの描画内容が時間の経過に伴って更新されているか否かを判定することができる。
*** Explanation of the effect of the embodiment ***
In the present embodiment, the drawing contents of the past acquisition data and the drawing contents of the new acquisition data are collated, and it is determined whether or not the drawing contents of the new acquisition data are the drawing contents updated from the past acquisition data. For this reason, according to the present embodiment, it is possible to determine whether or not the drawing contents of the drawing data whose drawing contents are updated with the passage of time are updated with the passage of time.
 実施の形態2.
 本実施の形態では、実施の形態1で説明した動作手順をより具体的に説明する。
 本実施の形態では、リアルタイムに電力量や気温等のグラフや文字を描画するデータを描画データの例とする。
Embodiment 2. FIG.
In this embodiment, the operation procedure described in Embodiment 1 will be described more specifically.
In the present embodiment, data for drawing graphs and characters such as electric energy and temperature in real time is taken as an example of drawing data.
***構成の説明***
 図4は、本実施の形態に係るシステム構成例を示す。
 本実施の形態では、監視用PC100、管理者PC200及びWebサーバ300がLAN40で接続されている。
 LAN40は、図1に示したものと同じである。
*** Explanation of configuration ***
FIG. 4 shows a system configuration example according to the present embodiment.
In the present embodiment, the monitoring PC 100, the administrator PC 200, and the Web server 300 are connected via the LAN 40.
The LAN 40 is the same as that shown in FIG.
 Webサーバ300は、Webアプリケーションを実行して、電力量や気温等のグラフ及び文字を描画するWebページ画面データをリアルタイムに更新する。
 本実施の形態では、Webページ画面データが描画データの例に相当する。
 Webサーバ300は、実施の形態1で説明したデータ更新装置30に相当する。
The Web server 300 executes a Web application and updates Web page screen data for drawing graphs and characters such as electric energy and temperature in real time.
In the present embodiment, Web page screen data corresponds to an example of drawing data.
The Web server 300 corresponds to the data update device 30 described in the first embodiment.
 監視用PC100は、Webサーバ300からWebページ画面データを取得し、新規取得データに相当するWebページ画面データと過去取得データに相当するWebページ画面データとを照合する。
 また、監視用PC100は、Webページ画面データが更新されているかを判定する。
 更に、監視用PC100は、Webページ画面データが更新されていない場合に、Webページ画面データが更新されていない旨を通知する通知メッセージを管理者PC200に送信する。
 通知メッセージの内容は、Webページ画面データの更新に異常があったことのみを通知してもよいし、グラフ全体の更新異常であるのか、特定の部分の更新異常であるのか等の異常の詳細を通知してもよい。
 監視用PC100は、実施の形態1で説明したデータ処理装置10に相当する。
The monitoring PC 100 acquires Web page screen data from the Web server 300 and collates Web page screen data corresponding to newly acquired data with Web page screen data corresponding to past acquired data.
Further, the monitoring PC 100 determines whether the Web page screen data has been updated.
Furthermore, when the Web page screen data is not updated, the monitoring PC 100 transmits a notification message notifying that the Web page screen data is not updated to the administrator PC 200.
The content of the notification message may notify only that there was an abnormality in the update of the Web page screen data, or the details of the abnormality such as whether the abnormality of the entire graph or the updating of a specific part May be notified.
The monitoring PC 100 corresponds to the data processing apparatus 10 described in the first embodiment.
 管理者PC200は、Webアプリケーション管理者のPCである。
 管理者PC200は、監視用PC100から通知メッセージを受信する。
 管理者PC200は、実施の形態1で説明した通知先装置20に相当する。
The administrator PC 200 is a Web application administrator's PC.
The administrator PC 200 receives the notification message from the monitoring PC 100.
The administrator PC 200 corresponds to the notification destination apparatus 20 described in the first embodiment.
 図5は、本実施の形態に係る監視用PC100の構成例を示す。
 プロセッサ901、記憶装置902及び通信装置903は、実施の形態1で説明したものと同じである。
FIG. 5 shows a configuration example of the monitoring PC 100 according to the present embodiment.
The processor 901, the storage device 902, and the communication device 903 are the same as those described in the first embodiment.
 監視用PC100は、機能構成として、ブラウザ101、画面取得処理部102及び画面照合処理部103を備える。
 画面取得処理部102は、ブラウザ101を用いてWebサーバ300のWebアプリケーションにアクセスする。また、画面取得処理部102は、HTTP(Hypertext Transfer Protocol)リクエスト送信によるWebページの自動遷移を行い、照合対象のWebページ画面データをキャプチャする。
 また、画面取得処理部102は、キャプチャしたWebページ画面データを記憶装置902に格納する。
 Webページの自動遷移については、市販又はフリーのWeb自動巡回ソフトを使用してもよい。
 画面照合処理部103は、Webページ画面データの照合処理を行い、Webページ画面データにおいて更新が行われていない場合は、管理者PC200に通知メッセージを送信する。
 本実施の形態では、画面取得処理部102及び画面照合処理部103が、実施の形態1で説明したデータ判定部11及び通知部12に相当する。
The monitoring PC 100 includes a browser 101, a screen acquisition processing unit 102, and a screen collation processing unit 103 as functional configurations.
The screen acquisition processing unit 102 accesses the Web application of the Web server 300 using the browser 101. In addition, the screen acquisition processing unit 102 performs automatic transition of a Web page by transmitting an HTTP (Hypertext Transfer Protocol) request, and captures Web page screen data to be verified.
Further, the screen acquisition processing unit 102 stores the captured web page screen data in the storage device 902.
For automatic transition of Web pages, commercially available or free Web automatic patrol software may be used.
The screen collation processing unit 103 performs web page screen data collation processing, and transmits a notification message to the administrator PC 200 when the web page screen data is not updated.
In the present embodiment, the screen acquisition processing unit 102 and the screen collation processing unit 103 correspond to the data determination unit 11 and the notification unit 12 described in the first embodiment.
 図6は、本実施の形態に係る監視用PC100の動作例を示すフローチャートである。
 ST101は画面取得処理部102が行う処理であり、ST102は画面照合処理部103が行う処理である。
FIG. 6 is a flowchart showing an operation example of the monitoring PC 100 according to the present embodiment.
ST101 is a process performed by the screen acquisition processing unit 102, and ST102 is a process performed by the screen collation processing unit 103.
 先ず、画面取得処理部102がブラウザ101を用いてWebサーバ300にHTTPリクエストを送信し、Webページを表示する(ステップST1011)。
 更に、画面取得処理部102がブラウザ101を用いてWebサーバ300にHTTPリクエストを送信し、Webページの自動遷移を行い、照合対象のページに遷移する(ステップST1012、ST1014)。
 画面取得処理部102は、遷移した照合対象のページで画面キャプチャを行う(ST1013、ST1015)。
 図6のフローチャートでは、一回の処理で2種類のWebページ画面データを取得する例を示している。
 画面キャプチャでは、画面取得処理部102は、Webページ画面データのスクリーンショットデータを取得してもよいし、Webページ画面データそのものを取得してもよい。
First, the screen acquisition processing unit 102 transmits an HTTP request to the Web server 300 using the browser 101, and displays a Web page (step ST1011).
Furthermore, the screen acquisition processing unit 102 transmits an HTTP request to the web server 300 using the browser 101, performs automatic transition of the web page, and transitions to the page to be verified (steps ST1012 and ST1014).
The screen acquisition processing unit 102 performs screen capture on the transitioned page to be collated (ST1013, ST1015).
The flowchart in FIG. 6 shows an example in which two types of Web page screen data are acquired in a single process.
In screen capture, the screen acquisition processing unit 102 may acquire screen shot data of Web page screen data, or may acquire Web page screen data itself.
 次に、画面照合処理部103が、過去に取得したWebページ画面データを記憶装置902から読み出し、画面照合処理を行う(ステップST1021)。
 画面照合処理部103は、表示が異常である場合、すなわち、Webページ画面データが更新されていない場合(ステップST1022でYES)は、管理者PC200に通知メッセージを送信する(ステップST1023)。
 最後に、画面照合処理部103は、Webページ画面データを記憶装置902に格納する(ステップST1024)。
Next, screen collation processing section 103 reads Web page screen data acquired in the past from storage device 902, and performs screen collation processing (step ST1021).
If the display is abnormal, that is, if the Web page screen data has not been updated (YES in step ST1022), screen collation processing unit 103 transmits a notification message to administrator PC 200 (step ST1023).
Finally, screen collation processing unit 103 stores the Web page screen data in storage device 902 (step ST1024).
 監視用PC100は、この一連の処理を、Webサーバ300でのWebページ画面データの更新タイミングごとに繰り返す。
 例えば、Webサーバ300において1時間ごとにグラフ等が更新される場合は、画面取得処理部102及び画面照合処理部103は1時間ごとに図6の処理を行う。
The monitoring PC 100 repeats this series of processes at every update timing of the Web page screen data on the Web server 300.
For example, when the graph or the like is updated every hour in the Web server 300, the screen acquisition processing unit 102 and the screen collation processing unit 103 perform the process of FIG. 6 every hour.
 図7は、画面照合処理(図6のST1021)の詳細を示すフローチャートである。
 図7のフローチャートでは、2段階の照合処理を行う場合の処理の流れを表している。ST203は、1段階目の照合処理を表しており、ST204は2段階目の照合処理を表している。
 監視用PC100が3段階以上の照合処理を実施する場合は、ST204とST1023の間にST203又はST204と同様の処理を挿入すればよい。
FIG. 7 is a flowchart showing details of the screen matching process (ST1021 in FIG. 6).
The flowchart of FIG. 7 shows the flow of processing when performing a two-stage verification process. ST203 represents the first-stage collation process, and ST204 represents the second-stage collation process.
When monitoring PC 100 performs three or more steps of collation processing, processing similar to ST203 or ST204 may be inserted between ST204 and ST1023.
 照合処理を開始すると、画面取得処理部102は、ステップST201において、ステップST203及びST204での照合に使用する照合領域や閾値等のパラメータを記憶装置902から読み込む。
 パラメータは、ユーザがテキストファイルに記述してもよい。あるいは、パラメータは、GUI(Graphical User Interface)による設定画面から設定してもよい。
When the collation processing is started, the screen acquisition processing unit 102 reads parameters such as a collation area and a threshold used for collation in steps ST203 and ST204 from the storage device 902 in step ST201.
The parameter may be described in a text file by the user. Alternatively, the parameters may be set from a setting screen by GUI (Graphical User Interface).
 ST201でパラメータが読み込まれた後は、画面照合処理部103は、ステップS202において、照合対象のWebページ画面データを記憶装置902から読み込む。 After the parameters are read in ST201, the screen collation processing unit 103 reads the web page screen data to be collated from the storage device 902 in step S202.
 次に、画面照合処理部103は、ステップST2031で1段階目の照合の領域を設定する。また、画面照合処理部103は、ステップST2032で類似度を算出し、ステップST2033で類似度が1段階目の照合の閾値の範囲内に入っているかどうかを判定する。
 類似度が1段目の照合の閾値の範囲内に入っていない場合(ステップST2033でNO)は、画面照合処理部103は、管理者PC200に通知メッセージを送信(ステップST1023)し、照合処理を終了する。
 類似度が1段目の照合の閾値範囲内に入っている場合(ステップST2033でYES)は、画面照合処理部103は、2段階目の照合処理(ステップST204)を実施する。
 2段階目の照合処理(ステップST204)では、1段階目の照合処理(ステップST203)と同様に、画面照合処理部103は、ステップST2041で2段階目の照合の領域を設定し、ステップST2042で類似度を算出する。
 そして、画面照合処理部103は、ST2043で類似度が2段階目の照合の閾値の範囲内に入っているかどうかを判定する。
 類似度が2段階目の照合の閾値の範囲内に入っていない場合(ステップST2043でNO)、画面照合処理部103は、管理者PC200に通知メッセージを送信(ステップST1023)し、照合処理を終了する。
 類似度が2段階目の照合の閾値の範囲内に入っている場合(ステップST2043でYES)は、処理がステップST1024に移行する。
 なお、図7の処理が終了したとき、画面照合処理部103は、更新が正常/異常であるという結果をログファイルとして出力してもよい。
Next, screen collation processing section 103 sets the first collation area in step ST2031. Further, screen collation processing section 103 calculates the similarity in step ST2032, and determines in step ST2033 whether the similarity falls within the range of the first-stage collation threshold.
If the degree of similarity is not within the range of the first-stage collation threshold (NO in step ST2033), screen collation processing unit 103 transmits a notification message to administrator PC 200 (step ST1023), and performs collation processing. finish.
If the similarity is within the threshold range for the first stage collation (YES in step ST2033), screen collation processing unit 103 performs the second stage collation process (step ST204).
In the second-stage collation process (step ST204), similarly to the first-stage collation process (step ST203), the screen collation processing unit 103 sets the second-stage collation area in step ST2041, and in step ST2042 Calculate similarity.
Then, in ST2043, screen collation processing section 103 determines whether or not the similarity is within the range of the second-stage collation threshold.
If the similarity does not fall within the threshold range for the second stage collation (NO in step ST2043), screen collation processing unit 103 transmits a notification message to administrator PC 200 (step ST1023), and ends the collation process. To do.
If the degree of similarity is within the range of the second-stage collation threshold (YES in step ST2043), the process proceeds to step ST1024.
When the process of FIG. 7 ends, the screen matching processing unit 103 may output a result that the update is normal / abnormal as a log file.
 図8は、画面照合処理部103による照合方式例1を表している。
 照合方式例1では、リアルタイムに電力量や気温等のグラフを表示する画面について、画面照合処理部103は、時刻に対応して表示される棒グラフや折れ線グラフ等のグラフが正常に表示されているかを判定する。
 具体的には、画面照合処理部103は、前時刻のWebページ画面データと現在時刻のWebページ画面データを比較し、時刻に対応する箇所が変化しているかどうかを判定する。
 時刻に対応する箇所の類似度が大きい場合は、前時刻のWebページ画面と現在時刻のWebページ画面データとの間で表示が変化しておらず、画面照合処理部103は、異常であると判定する。
 一方、類似度が小さい場合は、前時刻のWebページ画面データと現在時刻のWebページ画面データとの間で表示が変化しているので、画面照合処理部103は正常であると判定する。
 この場合、画面照合処理部103は、時刻に対応する表示箇所を図7のフローチャート内のST2031やST2041の照合領域設定の照合領域として設定し、ST2033やST2043で類似度が閾値内に入っているかどうかで表示が正常/異常であることを判定する。
 例えば、類似度=30%、閾値が0%以上70%以下であった場合は、画面照合処理部103は、表示が正常と判定する。一方、同じ閾値で類似度=90%であった場合は、画面照合処理部103は、表示が異常であると判定する。
 図8において破線の棒グラフは予測値のグラフであり、実線の棒グラフは実測値のグラフである。
 図8(a)のWebページ画面データでは、9:00のグラフは予測値である。
 1時間が経過したときに、図8(b)のWebページ画面データが得られた場合は、9:00のグラフが実測値に更新されている。つまり、図8(a)の9:00のグラフと図8(b)の9:00のグラフは類似度が低い。
 一方、1時間が経過したときに、図8(c)のWebページ画面データが得られた場合は、9:00のグラフが予測値のままで更新されていない。つまり、図8(a)の9:00のグラフと図8(c)の9:00のグラフの類似度が高い。
FIG. 8 illustrates a collation method example 1 by the screen collation processing unit 103.
In collation method example 1, for screens that display graphs such as electric energy and temperature in real time, screen collation processing unit 103 is displaying graphs such as bar graphs and line graphs that are displayed according to time correctly? Determine.
Specifically, the screen collation processing unit 103 compares the Web page screen data at the previous time with the Web page screen data at the current time, and determines whether or not the location corresponding to the time has changed.
When the similarity of the part corresponding to the time is large, the display is not changed between the Web page screen at the previous time and the Web page screen data at the current time, and the screen matching processing unit 103 is abnormal. judge.
On the other hand, when the degree of similarity is small, since the display changes between the Web page screen data at the previous time and the Web page screen data at the current time, the screen collation processing unit 103 determines that it is normal.
In this case, screen collation processing section 103 sets the display location corresponding to the time as the collation area of the collation area setting of ST2031 or ST2041 in the flowchart of FIG. 7, and whether the similarity is within the threshold in ST2033 or ST2043 It is determined whether the display is normal / abnormal.
For example, when the similarity is 30% and the threshold is 0% or more and 70% or less, the screen matching processing unit 103 determines that the display is normal. On the other hand, when the similarity is 90% with the same threshold, the screen matching processing unit 103 determines that the display is abnormal.
In FIG. 8, a broken line bar graph is a predicted value graph, and a solid line bar graph is a measured value graph.
In the Web page screen data of FIG. 8A, the 9:00 graph is a predicted value.
When the Web page screen data of FIG. 8B is obtained when one hour has elapsed, the 9:00 graph is updated to the actual measurement value. That is, the degree of similarity between the 9:00 graph of FIG. 8A and the 9:00 graph of FIG. 8B is low.
On the other hand, when the Web page screen data of FIG. 8C is obtained when one hour has passed, the graph of 9:00 is not updated with the predicted value. That is, the degree of similarity between the 9:00 graph in FIG. 8A and the 9:00 graph in FIG. 8C is high.
 図9は、画面照合処理部103による照合方式例2を表している。
 照合方式例2では、リアルタイムに電力量や気温等のグラフを表示する画面について、画面照合処理部103は、データの読み込み失敗や監視用PC100のブラウザ101の異常により、グラフが全く描画されない表示異常を検知する。
 具体的には、画面照合処理部103は、前時刻のWebページ画面データと現在時刻のWebページ画面データを比較し、グラフが描画されているかどうかを判定する。
 グラフ部分の類似度が小さい場合は、画面照合処理部103は、前時刻のWebページ画面と異なっており、グラフが全く表示されないという表示異常であると判定する。この場合、画面照合処理部103は、グラフ部分を図7のフローチャート内のST2031やST2041の照合領域設定の照合領域として設定し、ST2033やST2043で類似度が閾値内に入っているかどうかで表示が正常/異常であることを判定する。
 例えば、類似度=10%、閾値が70%以上100%以下であった場合は、画面照合処理部103は、表示が異常と判定する。一方、同じ閾値で類似度=90%であった場合は、画面照合処理部103は、表示が正常であると判定する。
FIG. 9 shows a collation method example 2 by the screen collation processing unit 103.
In the collation method example 2, for a screen that displays a graph such as electric energy and temperature in real time, the screen collation processing unit 103 causes a display abnormality in which a graph is not drawn at all due to data reading failure or an abnormality of the browser 101 of the monitoring PC 100 Is detected.
Specifically, the screen collation processing unit 103 compares the Web page screen data at the previous time with the Web page screen data at the current time, and determines whether a graph is drawn.
When the similarity of the graph part is small, the screen collation processing unit 103 determines that the display is abnormal because it is different from the Web page screen at the previous time and the graph is not displayed at all. In this case, the screen collation processing unit 103 sets the graph part as a collation area for the collation area setting of ST2031 and ST2041 in the flowchart of FIG. 7, and whether the similarity is within the threshold in ST2033 or ST2043 is displayed. Determine whether it is normal / abnormal.
For example, when the similarity is 10% and the threshold value is 70% or more and 100% or less, the screen matching processing unit 103 determines that the display is abnormal. On the other hand, when the similarity is 90% at the same threshold, the screen matching processing unit 103 determines that the display is normal.
 画面照合処理部103は、Webページ画像データの組について、(類似度)=(輝度が異なる画素数)/(全体の画素数)×100(%)により類似度を算出してもよい。
 あるいは、画面照合処理部103は、(類似度)=(輝度差分>閾値である画素数)/(全体の画素数)×100(%)により類似度を算出してもよい。
 閾値は、任意の期間に収集した画面データから決定してもよい。
 例えば、1週間の間収集されたWebページ画面データの各々に人手で異常ラベル又は正常ラベルを付加し、画面照合処理部103がラベルと類似度の組から閾値を決定する。
 あるいは、画面照合処理部103が、現在時刻で取得した画面データの特徴量やデータの傾向から判定モデル(閾値)を学習し、モデル(閾値)の自動更新を行ってもよい。
The screen matching processing unit 103 may calculate the similarity of the Web page image data set by (similarity) = (number of pixels having different luminance) / (total number of pixels) × 100 (%).
Alternatively, the screen matching processing unit 103 may calculate the similarity by (similarity) = (luminance difference> number of pixels that are threshold values) / (total number of pixels) × 100 (%).
The threshold value may be determined from screen data collected during an arbitrary period.
For example, an abnormal label or a normal label is manually added to each of the Web page screen data collected for one week, and the screen matching processing unit 103 determines a threshold value from a set of the label and the similarity.
Alternatively, the screen matching processing unit 103 may learn the determination model (threshold value) from the feature amount of the screen data acquired at the current time and the data trend, and automatically update the model (threshold value).
 画面照合処理部103は、例えば、図9の照合方式例2に従ってWebページ画面データの少なくとも一部が更新されているか否かを判定する。そして、Webページ画面データの少なくとも一部が更新されている場合に、画面照合処理部103は、図8の照合方式例1に従ってWebページ画面データが適正に更新されているか否かを判定する。 The screen collation processing unit 103 determines whether at least a part of the web page screen data is updated according to the collation method example 2 of FIG. When at least a part of the web page screen data is updated, the screen collation processing unit 103 determines whether the web page screen data is properly updated according to the collation method example 1 of FIG.
 実施の形態3.
 本実施の形態でも、実施の形態1で説明した動作手順をより具体的に説明する。
 本実施の形態では、ネイティブアプリケーションが、GUI画面照合により、現在時刻のスクリーンショットと過去のスクリーンショットを比較する。そして、ネイティブアプリケーションが、GUI画面が正常に表示されているかを判定し、表示が異常である場合に、管理者PCに通知する。
 本実施の形態では、ネイティブアプリケーションで生成されるGUI画面が描画データの例に相当する。
Embodiment 3 FIG.
Also in the present embodiment, the operation procedure described in the first embodiment will be described more specifically.
In the present embodiment, the native application compares the screen shot at the current time with the past screen shot by GUI screen collation. Then, the native application determines whether the GUI screen is normally displayed, and notifies the administrator PC when the display is abnormal.
In the present embodiment, a GUI screen generated by a native application corresponds to an example of drawing data.
***構成の説明***
 図10は、本実施の形態に係るシステム構成例を示す。
 本実施の形態では、監視用PC110と管理者PC200がLAN40で接続されている。
 管理者PC200とLAN40は、図4に示したものと同じである。
 つまり、管理者PC200は実施の形態1で説明した通知先装置20に相当する。
 なお、本実施の形態では、Webサーバ300に相当する装置は存在しない。
 本実施の形態では、監視用PC110が実施の形態1で説明したデータ処理装置10及びデータ更新装置30に相当する。
*** Explanation of configuration ***
FIG. 10 shows a system configuration example according to the present embodiment.
In the present embodiment, the monitoring PC 110 and the administrator PC 200 are connected via the LAN 40.
The administrator PC 200 and the LAN 40 are the same as those shown in FIG.
That is, the administrator PC 200 corresponds to the notification destination apparatus 20 described in the first embodiment.
In the present embodiment, there is no device corresponding to the Web server 300.
In the present embodiment, the monitoring PC 110 corresponds to the data processing device 10 and the data update device 30 described in the first embodiment.
 図11は、本実施の形態に係る監視用PC110の構成例を示す。
 プロセッサ901、記憶装置902及び通信装置903は、実施の形態1で説明したものと同じである。
FIG. 11 shows a configuration example of the monitoring PC 110 according to the present embodiment.
The processor 901, the storage device 902, and the communication device 903 are the same as those described in the first embodiment.
 監視用PC100は、機能構成として、ネイティブアプリケーション111、画面取得処理部102及び画面照合処理部103を備える。
 画面取得処理部102は、ネイティブアプリケーション111を起動し、イベント送信による操作の自動再生を行い、照合対象の画面データをキャプチャする。
 また、画面取得処理部102は、キャプチャした画面データを記憶装置902に格納する。
 操作の自動再生については、市販又はフリーの操作自動再生ソフトを使用してもよい。
 画面照合処理部103は、画面データの照合処理を行い、画面データにおいて更新が行われていない場合は、管理者PC200に通知メッセージを送信する。
 本実施の形態では、画面取得処理部102及び画面照合処理部103が、実施の形態で説明したデータ判定部11及び通知部12に相当する。
 また、ネイティブアプリケーション111がデータ更新装置30に相当する。
 ネイティブアプリケーション111は、同じネットワーク内に複数配置して、同時に画面照合を行ってもよい。
 例えば、解像度の異なるPC、OS(Operating System)やJava(登録商標)のバージョンが異なるPCについて同時に画面照合を行ってもよい。
The monitoring PC 100 includes a native application 111, a screen acquisition processing unit 102, and a screen collation processing unit 103 as functional configurations.
The screen acquisition processing unit 102 activates the native application 111, automatically reproduces an operation by sending an event, and captures screen data to be verified.
Further, the screen acquisition processing unit 102 stores the captured screen data in the storage device 902.
For automatic operation reproduction, commercially available or free operation automatic reproduction software may be used.
The screen verification processing unit 103 performs a screen data verification process, and transmits a notification message to the administrator PC 200 if the screen data has not been updated.
In the present embodiment, the screen acquisition processing unit 102 and the screen matching processing unit 103 correspond to the data determination unit 11 and the notification unit 12 described in the embodiment.
The native application 111 corresponds to the data update device 30.
A plurality of native applications 111 may be arranged in the same network and screen verification may be performed simultaneously.
For example, screen collation may be performed simultaneously for PCs having different resolutions, and PCs having different versions of OS (Operating System) and Java (registered trademark).
 図12は、本実施の形態に係る監視用PC100の動作例を示すフローチャートである。
 ST301は画面取得処理部102が行う処理であり、ST302は画面照合処理部103が行う処理である。
FIG. 12 is a flowchart showing an operation example of the monitoring PC 100 according to the present embodiment.
ST301 is a process performed by the screen acquisition processing unit 102, and ST302 is a process performed by the screen collation processing unit 103.
 先ず、画面取得処理部102がネイティブアプリケーション111を起動する(ステップST3011)。
 次に、画面取得処理部102がイベント等のコマンドをネイティブアプリケーション111に出力し、操作の自動再生を行い、照合対象の画面データに遷移する(ST3012、ST3014)。
 画面取得処理部102は、遷移した照合対象の画面データで画面キャプチャを行う(ST3013、ST3015)。
 図12のフローチャートでは、一回の処理で2種類の画面データを取得する例を示している。
 画面キャプチャでは、画面取得処理部102は、画面データのスクリーンショットデータを取得してもよいし、画面データそのものを取得してもよい。
First, the screen acquisition processing unit 102 activates the native application 111 (step ST3011).
Next, the screen acquisition processing unit 102 outputs a command such as an event to the native application 111, performs automatic reproduction of the operation, and transitions to screen data to be collated (ST3012, ST3014).
The screen acquisition processing unit 102 performs screen capture with the screen data to be collated (ST3013, ST3015).
The flowchart of FIG. 12 shows an example in which two types of screen data are acquired in a single process.
In the screen capture, the screen acquisition processing unit 102 may acquire screen shot data of the screen data, or may acquire the screen data itself.
 次に、画面照合処理部103が、過去に取得した画面データを記憶装置902から読み出し、画面照合処理を行う(ステップST3021)。
 画面照合処理部103は、表示が異常である場合、すなわち、画面データが更新されていない場合(ステップST3022でYES)は、管理者PC200に通知メッセージを送信する(ステップST3023)。
 最後に、画面照合処理部103は、画面データを記憶装置902に格納する(ステップST3024)。
Next, screen collation processing section 103 reads screen data acquired in the past from storage device 902, and performs screen collation processing (step ST3021).
If the display is abnormal, that is, if the screen data has not been updated (YES in step ST3022), screen collation processing unit 103 transmits a notification message to administrator PC 200 (step ST3023).
Finally, screen collation processing unit 103 stores the screen data in storage device 902 (step ST3024).
 監視用PC100は、この一連の処理を、ネイティブアプリケーション111での画面データの更新タイミングごとに繰り返す。
 例えば、ネイティブアプリケーション111において1時間ごとにグラフ等が更新される場合は、画面取得処理部102及び画面照合処理部103は1時間ごとに図12の処理を行う。
The monitoring PC 100 repeats this series of processing at each screen data update timing in the native application 111.
For example, when the graph or the like is updated every hour in the native application 111, the screen acquisition processing unit 102 and the screen collation processing unit 103 perform the process of FIG. 12 every hour.
 実施の形態3において、照合処理の流れは実施の形態2と同様であり、図7のフローチャートに表している通りである。
 照合方式及び類似度算出方式、閾値の決定方法は、実施の形態1と同様でもよい。
 あるいは、監視用PC100は、解像度が異なる画面、OS又はJava(登録商標)のバージョンが異なる画面について照合を行う場合に、領域の拡大縮小処理を前処理として行ってから類似度を算出してもよい。
 あるいは、監視用PC100は、類似度の算出を局所特徴量により行ってもよい。
 例えば、監視用PC100は、画像の組について、(類似度)=(局所特徴量において対応する点の個数)/(全体の特徴点数)×100(%)により類似度を算出してもよい。
In the third embodiment, the flow of the collation process is the same as that in the second embodiment, as shown in the flowchart of FIG.
The collation method, similarity calculation method, and threshold determination method may be the same as those in the first embodiment.
Alternatively, the monitoring PC 100 may calculate the similarity after performing the area enlargement / reduction process as a pre-process when collating screens with different resolutions or screens with different versions of OS or Java (registered trademark). Good.
Alternatively, the monitoring PC 100 may calculate the similarity based on the local feature amount.
For example, the monitoring PC 100 may calculate the similarity of an image set by (similarity) = (number of corresponding points in the local feature amount) / (total number of feature points) × 100 (%).
 実施の形態3では、監視用PC100は、ネイティブアプリケーション111の異常による表示異常を画面内のグラフ部分の領域についての画面照合により検知し、異常である場合、管理者PC200に例えばメールで通知する。 In the third embodiment, the monitoring PC 100 detects a display abnormality due to the abnormality of the native application 111 by screen collation for the area of the graph portion in the screen, and notifies the administrator PC 200 by e-mail, for example, if it is abnormal.
実施の形態4.
 本実施の形態では、描画異常又は描画の変化点を検出できる構成を説明する。
***構成の説明***
 本実施の形態に係るシステム構成例は、図1に示すとおりである。
 以下では、主に実施の形態1との違いを説明する。以下で説明していない事項は、実施の形態1と同じである。
Embodiment 4 FIG.
In the present embodiment, a configuration capable of detecting a drawing abnormality or a drawing change point will be described.
*** Explanation of configuration ***
A system configuration example according to the present embodiment is as shown in FIG.
Hereinafter, differences from the first embodiment will be mainly described. Matters not described below are the same as those in the first embodiment.
 データ更新装置30は、実施の形態1と同様に、時間の経過に伴って描画データの描画内容を更新する。
 より具体的には、データ更新装置30は、既定の更新タイミングごとに描画データの描画内容を更新する。
As in the first embodiment, the data update device 30 updates the drawing content of the drawing data with the passage of time.
More specifically, the data update device 30 updates the drawing content of the drawing data at every predetermined update timing.
 本実施の形態では、データ処理装置10は、記憶装置902にモデルデータを保持する。モデルデータでは、描画データにおける非定常の描画パターンである非定常パターンが定義されている。非定常パターンは、例えば、描画異常が発生した場合の描画データにおける描画の時間推移である。この場合には、モデルデータには、例えば、図8に示すようなグラフにおいて現在時刻の数値が1つ前の時刻の数値の1/2未満になっている描画パターン又は現在時刻の数値が1つ前の時刻の数値の2倍以上になっている描画パターンが非定常パターンとして定義されている。また、モデルデータに、描画の変化点が示される非定常パターンが定義されていてもよい。この場合には、モデルデータには、例えば、図8に示すようなグラフにおいて現在時刻の数値が1つ前の時刻の数値の2/3以下(但し、1/2以上)になっている描画パターン又は現在時刻の数値が1つ前の時刻の数値の1.5倍以上(但し、2倍未満)になっている描画パターンが非定常パターンとして定義されている。また、モデルデータとして、過去に取得した描画データを用いることも可能である。
 データ処理装置10のユーザは、モデルデータ及び非定常パターンを任意に定義することができる。
 なお、上記の「1/2」、「2/3」、「1.5」倍、「2」倍といった値は例示であり、非定常パターンに用いる値をユーザが任意に定義することができる。
In the present embodiment, the data processing apparatus 10 holds model data in the storage device 902. In the model data, an unsteady pattern that is an unsteady drawing pattern in the drawing data is defined. An unsteady pattern is, for example, a drawing time transition in drawing data when a drawing abnormality occurs. In this case, the model data includes, for example, a drawing pattern whose current time value is less than ½ of the previous time value in the graph shown in FIG. A drawing pattern that is twice or more the numerical value of the previous time is defined as an unsteady pattern. Further, an unsteady pattern in which a drawing change point is indicated may be defined in the model data. In this case, in the model data, for example, in a graph as shown in FIG. 8, the current time value is 2/3 or less (however, 1/2 or more) of the value of the previous time. A drawing pattern in which the numerical value of the pattern or the current time is 1.5 times or more (but less than twice) the numerical value of the previous time is defined as an unsteady pattern. Also, drawing data acquired in the past can be used as model data.
The user of the data processing apparatus 10 can arbitrarily define model data and non-stationary patterns.
Note that the above values such as “1/2”, “2/3”, “1.5” times, and “2” times are examples, and the user can arbitrarily define the values used for the unsteady pattern. .
 そして、本実施の形態では、データ処理装置10において、データ判定部11は、モデルデータと、新規取得データの描画内容とを照合し、新規取得データの描画内容が前記非定常パターンに一致するか否かを判定する。つまり、データ判定部11は、描画データにいて、モデルデータで定義されている描画異常又は描画傾向における変化が生じているか否かを判定する。
 また、通知部12は、データ判定部11により新規取得データの描画内容が非定常パターンに一致すると判定された場合に、既定の通知先である通知先装置20に、新規取得データの描画内容が非定常パターンに一致することを通知する。
In the present embodiment, in the data processing device 10, the data determination unit 11 compares the model data with the drawing content of the newly acquired data, and whether the drawing content of the newly acquired data matches the unsteady pattern. Determine whether or not. That is, the data determination unit 11 determines whether there is a drawing abnormality or a change in drawing tendency defined in the model data in the drawing data.
In addition, when the data determination unit 11 determines that the drawing content of the newly acquired data matches the non-steady pattern, the notification unit 12 displays the drawing content of the newly acquired data in the notification destination device 20 that is the default notification destination. Notify that it matches an unsteady pattern.
***動作の説明***
 次に、図13のフローチャートを参照して、本実施の形態に係るデータ処理装置10の動作例を説明する。
 なお、図13に示す動作手順は、データ処理方法及びデータ処理プログラムの例に相当する。
*** Explanation of operation ***
Next, an operation example of the data processing apparatus 10 according to the present embodiment will be described with reference to the flowchart of FIG.
The operation procedure illustrated in FIG. 13 corresponds to an example of a data processing method and a data processing program.
 先ず、ステップST1301において、データ判定部11は、事前にユーザが設定したタイミングが到来したか否かを判定する。
 データ判定部11は、例えばネットワークコマンドのキャプチャを行い、ユーザが事前に登録したネットワークコマンドをキャプチャした場合にユーザが設定したタイミングが到来したと判定する。
 ユーザが指定したタイミングが到来した場合(ステップST1301でYES)は、ステップST1302において、データ判定部11はデータ更新装置30から描画データを取得する。
 より具体的には、データ判定部11はデータ更新装置30を宛先とする描画データの取得リクエストを生成し、生成した取得リクエストを通信装置903に出力する。
 通信装置903は、取得リクエストをLAN40を介してデータ更新装置30に送信する。
 データ更新装置30は、取得リクエストに対する応答として、描画データをLAN40を介してデータ処理装置10に送信する。
 データ処理装置10では、通信装置903が描画データを受信し、受信した描画データをデータ判定部11に出力する。
 ステップST1302で取得した描画データは新規取得データである。
First, in step ST1301, the data determination unit 11 determines whether or not the timing set in advance by the user has arrived.
For example, the data determination unit 11 captures a network command and determines that the timing set by the user has arrived when the network command registered in advance by the user is captured.
When the timing designated by the user has arrived (YES in step ST1301), the data determination unit 11 acquires drawing data from the data update device 30 in step ST1302.
More specifically, the data determination unit 11 generates a drawing data acquisition request destined for the data update device 30 and outputs the generated acquisition request to the communication device 903.
The communication device 903 transmits an acquisition request to the data update device 30 via the LAN 40.
The data update device 30 transmits drawing data to the data processing device 10 via the LAN 40 as a response to the acquisition request.
In the data processing device 10, the communication device 903 receives the drawing data and outputs the received drawing data to the data determination unit 11.
The drawing data acquired in step ST1302 is newly acquired data.
 次に、ステップST1303において、データ判定部11が記憶装置902からモデルデータを読み出す。
 なお、データ処理装置10のユーザは、モデルデータとして、1つ前の更新タイミングのステップST1302で取得した新規取得データを定義してもよい。
Next, in step ST1303, the data determination unit 11 reads model data from the storage device 902.
Note that the user of the data processing apparatus 10 may define the newly acquired data acquired in step ST1302 at the previous update timing as model data.
 次に、ステップST1304において、データ判定部11は新規取得データとモデルデータを照合する。
 描画データには描画内容が更新される更新対象領域があり、データ判定部11はモデルデータの更新対象領域の描画内容(非定常パターン)と新規取得データの更新対象領域の描画内容とを照合する。
 また、データ判定部11はモデルデータの描画内容と新規取得データの描画内容とを照合して、モデルデータの描画内容と新規取得データの描画内容との類似度を算出する。
Next, in step ST1304, the data determination unit 11 collates newly acquired data with model data.
The drawing data includes an update target area in which the drawing content is updated, and the data determination unit 11 collates the drawing content (unsteady pattern) in the update target area of the model data with the drawing content in the update target area of the newly acquired data. .
Further, the data determination unit 11 collates the drawing contents of the model data with the drawing contents of the newly acquired data, and calculates the similarity between the drawing contents of the model data and the drawing contents of the newly acquired data.
 次に、ステップST1305において、データ判定部11は、算出した類似度を閾値と比較して、新規取得データの描画内容がモデルデータで定義されている非定常パターンに合致するか否かを判定する。すなわち、データ判定部11は、新規取得データにおいて描画異常又は描画傾向における変化が生じているか否かを判定する。
 なお、類似度が閾値以上であれば、データ判定部11は、新規取得データの描画内容がモデルデータで定義されている非定常パターンに合致すると判定する。
Next, in step ST1305, the data determination unit 11 compares the calculated similarity with a threshold value and determines whether or not the drawing content of the newly acquired data matches the unsteady pattern defined in the model data. . That is, the data determination unit 11 determines whether or not there is a drawing abnormality or a change in drawing tendency in the newly acquired data.
If the similarity is greater than or equal to the threshold, the data determination unit 11 determines that the drawing content of the newly acquired data matches the unsteady pattern defined in the model data.
 ステップST1305で新規取得データの描画内容がモデルデータで定義されている非定常パターンに合致していると判定した場合は、ステップST1306において、データ判定部11が通知部12に新規取得データの描画内容がモデルデータで定義されている非定常パターンに合致している旨を通知する。そして、通知部12が通知先装置20に新規取得データの描画内容がモデルデータで定義されている非定常パターンに合致している旨、すなわち、新規取得データにおいて描画異常又は描画傾向における変化が生じている旨を通知する。
 より具体的には、通知部12は、新規取得データにおいて描画異常又は描画傾向における変化が生じている旨を通知する通知メッセージを生成する。
 通知メッセージは、例えば、電子メールメッセージである。
 そして、通知部12は通知メッセージを通信装置903に出力する。
 通信装置903は通知メッセージをLAN40を介して通知先装置20に送信する。
 次に、ステップST1307において、データ判定部11が新規取得データを記憶装置902に格納する。
 なお、前述したように、ここで記憶装置902に格納した新規取得データは、次の更新タイミングのステップS1303でモデルデータとして読み出されてもよい。
If it is determined in step ST1305 that the drawing content of the newly acquired data matches the unsteady pattern defined in the model data, in step ST1306, the data determining unit 11 sends the drawing content of the newly acquired data to the notification unit 12. Is in conformity with the unsteady pattern defined in the model data. Then, the notification unit 12 indicates that the drawing content of the newly acquired data matches the non-stationary pattern defined in the model data in the notification destination device 20, that is, the drawing abnormality or the change in the drawing tendency occurs in the newly acquired data. Notify that
More specifically, the notification unit 12 generates a notification message notifying that a drawing abnormality or a change in drawing tendency has occurred in the newly acquired data.
The notification message is, for example, an e-mail message.
Then, the notification unit 12 outputs a notification message to the communication device 903.
The communication device 903 transmits a notification message to the notification destination device 20 via the LAN 40.
Next, in step ST1307, the data determination unit 11 stores newly acquired data in the storage device 902.
As described above, the newly acquired data stored in the storage device 902 here may be read as model data in step S1303 of the next update timing.
***実施の形態の効果の説明***
 本実施の形態では、過去に取得した描画データ、又は描画異常時又は描画傾向の変化時に想定される画面の描画データについてユーザが定義したモデルデータの描画内容と新規取得データの描画内容とを照合する。そして、新規取得データの描画内容においてモデルデータで定義されている描画異常又は変化が生じているか否かを判定する。このため、本実施の形態によれば、時間の経過に伴って描画内容が更新される描画データの描画内容においてモデルデータで定義されている描画異常又は変化が生じているか否かを判定することができる。
*** Explanation of the effect of the embodiment ***
In this embodiment, the drawing contents of the model data defined by the user and the drawing contents of the newly acquired data are collated with respect to the drawing data acquired in the past or the drawing data of the screen assumed when the drawing abnormality or the drawing tendency changes. To do. Then, it is determined whether or not the drawing abnormality or change defined in the model data has occurred in the drawing content of the newly acquired data. For this reason, according to the present embodiment, it is determined whether or not the drawing abnormality or change defined in the model data has occurred in the drawing contents of the drawing data whose drawing contents are updated as time passes. Can do.
***ハードウェア構成の説明***
 最後に、データ処理装置10、監視用PC100、監視用PC110のハードウェア構成の補足説明を行う。
 プロセッサ901は、プロセッシングを行うIC(Integrated Circuit)である。
 プロセッサ901は、CPU(Central Processing Unit)、DSP(Digital Signal Processor)等である。
 記憶装置902は、RAM(Random Access Memory)、ROM(Read Only Memory)、フラッシュメモリ、HDD(Hard Disk
 Drive)等である。
 通信装置903は、データを受信するレシーバー及びデータを送信するトランスミッターを含む。
 通信装置903は、例えば、通信チップ又はNIC(Network Interface Card)である。
*** Explanation of hardware configuration ***
Finally, a supplementary description of the hardware configuration of the data processing apparatus 10, the monitoring PC 100, and the monitoring PC 110 will be given.
The processor 901 is an IC (Integrated Circuit) that performs processing.
The processor 901 is a CPU (Central Processing Unit), a DSP (Digital Signal Processor), or the like.
The storage device 902 includes a RAM (Random Access Memory), a ROM (Read Only Memory), a flash memory, and an HDD (Hard Disk).
Drive) and the like.
The communication device 903 includes a receiver that receives data and a transmitter that transmits data.
The communication device 903 is, for example, a communication chip or a NIC (Network Interface Card).
 また、記憶装置902には、OS(Operating System)も記憶されている。
 そして、OSの少なくとも一部がプロセッサ901により実行される。
 プロセッサ901はOSの少なくとも一部を実行しながら、データ判定部11、通知部12、画面取得処理部102及び画面照合処理部103(以下、これらをまとめて「部」という)の機能を実現するプログラムを実行する。
 図2等では、1つのプロセッサが図示されているが、データ処理装置10、監視用PC100、監視用PC110が複数のプロセッサを備えていてもよい。
 また、「部」の処理の結果を示す情報やデータや信号値や変数値が、記憶装置902、又は、プロセッサ901内のレジスタ又はキャッシュメモリに記憶される。
 また、「部」の機能を実現するプログラムは、磁気ディスク、フレキシブルディスク、光ディスク、コンパクトディスク、ブルーレイ(登録商標)ディスク、DVD等の可搬記憶媒体に記憶されてもよい。
The storage device 902 also stores an OS (Operating System).
Then, at least a part of the OS is executed by the processor 901.
The processor 901 implements the functions of the data determination unit 11, the notification unit 12, the screen acquisition processing unit 102, and the screen collation processing unit 103 (hereinafter collectively referred to as “unit”) while executing at least a part of the OS. Run the program.
In FIG. 2 and the like, one processor is illustrated, but the data processing device 10, the monitoring PC 100, and the monitoring PC 110 may include a plurality of processors.
In addition, information, data, signal values, and variable values indicating the processing results of “unit” are stored in the storage device 902, a register in the processor 901, or a cache memory.
The program for realizing the function of “unit” may be stored in a portable storage medium such as a magnetic disk, a flexible disk, an optical disk, a compact disk, a Blu-ray (registered trademark) disk, or a DVD.
 また、「部」を、「回路」又は「工程」又は「手順」又は「処理」に読み替えてもよい。
 また、データ処理装置10、監視用PC100、監視用PC110は、ロジックIC(Integrated Circuit)、GA(Gate Array)、ASIC(Application Specific Integrated Circuit)、FPGA(Field-Programmable Gate Array)といった電子回路により実現されてもよい。
 この場合は、「部」は、それぞれ電子回路の一部として実現される。
 なお、プロセッサ及び上記の電子回路を総称してプロセッシングサーキットリーともいう。
In addition, “part” may be read as “circuit” or “process” or “procedure” or “processing”.
Further, the data processing device 10, the monitoring PC 100, and the monitoring PC 110 are composed of a logic IC (Integrated Circuit), a GA (Gate Array), an ASIC (Application Specific Integrated Circuit), and an FPGA (Field-Programmable Gate) electronic circuit circuit. May be.
In this case, each “unit” is realized as part of an electronic circuit.
The processor and the electronic circuit are also collectively referred to as a processing circuit.
***付記***
 以上、本発明の実施の形態について説明したが、これらの実施の形態のうち、2つ以上を組み合わせて実施しても構わない。
 あるいは、これらの実施の形態のうち、1つを部分的に実施しても構わない。
 あるいは、これらの実施の形態のうち、2つ以上を部分的に組み合わせて実施しても構わない。
 なお、本発明は、これらの実施の形態に限定されるものではなく、必要に応じて種々の変更が可能である。
*** Additional notes ***
As mentioned above, although embodiment of this invention was described, you may implement in combination of 2 or more among these embodiment.
Alternatively, one of these embodiments may be partially implemented.
Alternatively, two or more of these embodiments may be partially combined.
In addition, this invention is not limited to these embodiment, A various change is possible as needed.
 実施の形態1~4では、ネットワークの例としてLAN40を説明しているが、LAN40以外のネットワークが用いられていてもよい。 In the first to fourth embodiments, the LAN 40 is described as an example of a network, but a network other than the LAN 40 may be used.
 10 データ処理装置、11 データ判定部、12 通知部、20 通知先装置、30 データ更新装置、40 LAN、100 監視用PC、101 ブラウザ、102 画面取得処理部、103 画面照合処理部、110 監視用PC、111 ネイティブアプリケーション、200 管理者PC、300 Webサーバ。 10 data processing device, 11 data determination unit, 12 notification unit, 20 notification destination device, 30 data update device, 40 LAN, 100 monitoring PC, 101 browser, 102 screen acquisition processing unit, 103 screen verification processing unit, 110 for monitoring PC, 111 native application, 200 administrator PC, 300 Web server.

Claims (10)

  1.  時間の経過に伴って描画データの描画内容を更新するデータ更新装置から過去に取得した描画データである過去取得データの描画内容と、前記データ更新装置から新たに取得した描画データである新規取得データの描画内容とを照合し、前記新規取得データの描画内容が前記過去取得データから更新された描画内容になっているか否かを判定するデータ判定部を有するデータ処理装置。 The drawing content of past acquired data that is drawing data acquired in the past from the data update device that updates the drawing content of drawing data as time passes, and the newly acquired data that is drawing data newly acquired from the data update device A data processing apparatus having a data determination unit that determines whether or not the drawing content of the newly acquired data is the drawing content updated from the past acquired data.
  2.  前記データ処理装置は、更に、
     前記データ判定部により前記新規取得データの描画内容が前記過去取得データから更新された描画内容になっていないと判定された場合に、既定の通知先に、前記新規取得データの描画内容が前記過去取得データから更新された描画内容になっていないことを通知する通知部を有する請求項1に記載のデータ処理装置。
    The data processing device further includes:
    When it is determined by the data determination unit that the drawing content of the newly acquired data is not the drawing content updated from the past acquired data, the drawing content of the newly acquired data is displayed in the past notification destination. The data processing apparatus according to claim 1, further comprising a notification unit that notifies that the drawing content is not updated from the acquired data.
  3.  前記データ更新装置は、既定の更新タイミングごとに描画データの描画内容を更新し、
     前記データ判定部は、
     更新タイミングごとに、現在の更新タイミングの1つ前の更新タイミングで前記データ更新装置から取得した過去取得データの描画内容と、現在の更新タイミングで前記データ更新装置から新たに取得した新規取得データの描画内容とを照合する請求項1に記載のデータ処理装置。
    The data update device updates the drawing content of drawing data at each predetermined update timing,
    The data determination unit
    For each update timing, the drawing contents of the past acquisition data acquired from the data update device at the update timing immediately before the current update timing and the newly acquired data newly acquired from the data update device at the current update timing The data processing apparatus according to claim 1, wherein collation is performed with drawing contents.
  4.  前記データ更新装置は、描画データ内の更新対象領域で描画内容を更新し、
     前記データ判定部は、
     前記過去取得データの前記更新対象領域の描画内容と前記新規取得データの前記更新対象領域の描画内容とを照合する請求項1に記載のデータ処理装置。
    The data update device updates the drawing content in the update target area in the drawing data,
    The data determination unit
    The data processing device according to claim 1, wherein the drawing content of the update target area of the past acquired data is collated with the drawing content of the update target area of the newly acquired data.
  5.  前記データ判定部は、
     前記過去取得データの描画内容と前記新規取得データの描画内容とを照合して、前記過去取得データの描画内容と前記新規取得データの描画内容との類似度を算出し、算出した類似度に基づいて、前記新規取得データの描画内容が前記過去取得データから更新された描画内容になっているか否かを判定する請求項1に記載のデータ処理装置。
    The data determination unit
    The drawing content of the past acquisition data and the drawing content of the new acquisition data are collated to calculate the similarity between the drawing content of the past acquisition data and the drawing content of the new acquisition data, and based on the calculated similarity The data processing apparatus according to claim 1, wherein it is determined whether or not the drawing content of the newly acquired data is a drawing content updated from the past acquired data.
  6.  前記データ判定部は、
     算出した類似度を閾値と比較して、前記新規取得データの描画内容が前記過去取得データから更新された描画内容になっているか否かを判定する請求項5に記載のデータ処理装置。
    The data determination unit
    The data processing apparatus according to claim 5, wherein the calculated similarity is compared with a threshold value to determine whether or not the drawing content of the newly acquired data is a drawing content updated from the past acquired data.
  7.  前記データ判定部は、
     前記描画データにおける非定常の描画パターンである非定常パターンが定義されているモデルデータと、前記新規取得データの描画内容とを照合し、前記新規取得データの描画内容が前記非定常パターンに合致するか否かを判定する請求項1に記載のデータ処理装置。
    The data determination unit
    The model data in which a non-stationary pattern that is an unsteady drawing pattern in the drawing data is defined is compared with the drawing content of the newly acquired data, and the drawing content of the newly acquired data matches the unsteady pattern. The data processing apparatus according to claim 1, which determines whether or not.
  8.  前記データ処理装置は、更に、
     前記データ判定部により前記新規取得データの描画内容が前記非定常パターンに一致すると判定された場合に、既定の通知先に、前記新規取得データの描画内容が前記非定常パターンに合致することを通知する通知部を有する請求項7に記載のデータ処理装置。
    The data processing device further includes:
    When the data determination unit determines that the drawing content of the newly acquired data matches the non-stationary pattern, the default notification destination is notified that the drawing content of the newly acquired data matches the non-stationary pattern. The data processing device according to claim 7, further comprising a notification unit that performs the notification.
  9.  コンピュータが、時間の経過に伴って描画データの描画内容を更新するデータ更新装置から過去に取得した描画データである過去取得データの描画内容と、前記データ更新装置から新たに取得した描画データである新規取得データの描画内容とを照合し、前記新規取得データの描画内容が前記過去取得データから更新された描画内容になっているか否かを判定するデータ処理方法。 The drawing content of past acquired data, which is drawing data acquired in the past from the data update device that updates the drawing content of drawing data as time passes, and the drawing data newly acquired from the data update device A data processing method for collating the drawing contents of the newly acquired data and determining whether or not the drawing contents of the newly acquired data is the drawing contents updated from the past acquired data.
  10.  時間の経過に伴って描画データの描画内容を更新するデータ更新装置から過去に取得した描画データである過去取得データの描画内容と、前記データ更新装置から新たに取得した描画データである新規取得データの描画内容とを照合し、前記新規取得データの描画内容が前記過去取得データから更新された描画内容になっているか否かを判定するデータ判定処理をコンピュータに実行させるデータ処理プログラム。 The drawing content of past acquired data that is drawing data acquired in the past from the data update device that updates the drawing content of drawing data as time passes, and the newly acquired data that is drawing data newly acquired from the data update device A data processing program for causing a computer to execute a data determination process for determining whether or not the drawing content of the newly acquired data is the drawing content updated from the past acquired data.
PCT/JP2016/082640 2015-12-18 2016-11-02 Data processing device, data processing method, and data processing program WO2017104284A1 (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
JP2017556408A JP6440868B2 (en) 2015-12-18 2016-11-02 Data processing apparatus, data processing method, and data processing program
CN201680071574.5A CN108369560A (en) 2015-12-18 2016-11-02 Data processing equipment, data processing method and data processor

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
JP2015-247997 2015-12-18
JP2015247997 2015-12-18

Publications (1)

Publication Number Publication Date
WO2017104284A1 true WO2017104284A1 (en) 2017-06-22

Family

ID=59056037

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/JP2016/082640 WO2017104284A1 (en) 2015-12-18 2016-11-02 Data processing device, data processing method, and data processing program

Country Status (3)

Country Link
JP (1) JP6440868B2 (en)
CN (1) CN108369560A (en)
WO (1) WO2017104284A1 (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108182202A (en) * 2017-12-07 2018-06-19 海南智媒云图科技股份有限公司 Content update notification method, device, electronic equipment and storage medium

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2002236626A (en) * 2000-12-06 2002-08-23 Site Rock Corp Method and system for monitoring site
JP2006285963A (en) * 2005-03-31 2006-10-19 Microsoft Corp System and method for easily creating raw summary for contents selected from various data information sources
JP2012043140A (en) * 2010-08-18 2012-03-01 Fujifilm Corp Web page browsing system and relay server
JP2013206073A (en) * 2012-03-28 2013-10-07 Nec Corp Network management system, network management method, network monitoring system, and network management program
US20150135060A1 (en) * 2012-08-16 2015-05-14 Amazon Technologies, Inc. Automated content update notification

Family Cites Families (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH07321786A (en) * 1994-05-30 1995-12-08 Nec Eng Ltd Abnormal data detection system and information collection distribution equipment
JP2000076570A (en) * 1998-08-28 2000-03-14 Mitsubishi Electric Corp Video alarm display device and video alarm display method
JP4139485B2 (en) * 1998-09-17 2008-08-27 シャープ株式会社 Display image evaluation method and display image evaluation system
JP5272595B2 (en) * 2008-09-05 2013-08-28 沖電気工業株式会社 Display control apparatus, display control system, display control method, and program
JP2012003295A (en) * 2010-06-14 2012-01-05 Mitsubishi Electric Corp Plant system display and control system
CN102779245A (en) * 2011-05-12 2012-11-14 李朝荣 Webpage abnormality detection method based on image processing technology
CN103207874B (en) * 2012-01-17 2017-05-10 腾讯科技(深圳)有限公司 Updated webpage content prompting method and system
CN103678307B (en) * 2012-08-31 2016-07-13 腾讯科技(深圳)有限公司 Page display method and client
CN105843893B (en) * 2012-09-19 2019-09-24 北京奇付通科技有限公司 Monitoring method and device based on the software update information that Web information extracts
US20140189491A1 (en) * 2013-01-03 2014-07-03 Browserbite Oü Visual cross-browser layout testing method and system therefor
CN103544213B (en) * 2013-09-16 2016-10-12 青岛英网资讯股份有限公司 Web site contents updates method of determination and evaluation and system
CN104391953B (en) * 2014-11-27 2017-12-19 北京国双科技有限公司 Detect the method and device of webpage renewal

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2002236626A (en) * 2000-12-06 2002-08-23 Site Rock Corp Method and system for monitoring site
JP2006285963A (en) * 2005-03-31 2006-10-19 Microsoft Corp System and method for easily creating raw summary for contents selected from various data information sources
JP2012043140A (en) * 2010-08-18 2012-03-01 Fujifilm Corp Web page browsing system and relay server
JP2013206073A (en) * 2012-03-28 2013-10-07 Nec Corp Network management system, network management method, network monitoring system, and network management program
US20150135060A1 (en) * 2012-08-16 2015-05-14 Amazon Technologies, Inc. Automated content update notification

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108182202A (en) * 2017-12-07 2018-06-19 海南智媒云图科技股份有限公司 Content update notification method, device, electronic equipment and storage medium
CN108182202B (en) * 2017-12-07 2021-01-05 广东智媒云图科技股份有限公司 Content update notification method, content update notification device, electronic equipment and storage medium

Also Published As

Publication number Publication date
JPWO2017104284A1 (en) 2018-05-24
JP6440868B2 (en) 2018-12-19
CN108369560A (en) 2018-08-03

Similar Documents

Publication Publication Date Title
CN101188656B (en) Information processing apparatus and control method thereof
CN111158767B (en) BMC-based server safe starting method and device
WO2019019628A1 (en) Test method, apparatus, test device and medium for mobile application
CN107395650B (en) Method and device for identifying Trojan back connection based on sandbox detection file
WO2021174837A1 (en) Breakpoint monitoring method and apparatus based on integral service link, and terminal and storage medium
US20150074808A1 (en) Rootkit Detection in a Computer Network
CN114996103A (en) Page abnormity detection method and device, electronic equipment and storage medium
JP6440868B2 (en) Data processing apparatus, data processing method, and data processing program
CN111856257B (en) Method, system, equipment and medium for detecting and protecting CPLD (complex programmable logic device) firmware
CN110598797B (en) Fault detection method and device, storage medium and electronic device
US10176306B2 (en) Information processing apparatus, evaluation method, and storage medium for evaluating application program
JP5606261B2 (en) Debug system and method of acquiring trace data of debug system
JP6574146B2 (en) Service monitoring apparatus and service monitoring method
JP6580279B2 (en) Test apparatus, test method and test program
CN110874280B (en) Startup exception processing method and device, electronic equipment and storage medium
JP2017162182A (en) Test device, test method, and test program
TWI616772B (en) Factory reset protection disarm method and electronic device
JP7184197B2 (en) Abnormality detection device, abnormality detection method and abnormality detection program
CN112468358B (en) Protocol detection method, system, equipment and computer readable storage medium
TWI726469B (en) Method and device for automatically acquiring status information
CN111414334B (en) File fragment uploading method, device, equipment and storage medium based on cloud technology
US11531764B2 (en) Assessing operational stability of computer system by integrity checking of computer program
JP7087277B2 (en) Information processing equipment, information processing system, information processing program and information processing method
KR102628293B1 (en) Integrity verification system, method and apparatus using artifitial intelligence based on cloud
KR101884529B1 (en) System and method for automatic payload signature update for classification of recent network application

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 16875269

Country of ref document: EP

Kind code of ref document: A1

ENP Entry into the national phase

Ref document number: 2017556408

Country of ref document: JP

Kind code of ref document: A

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 16875269

Country of ref document: EP

Kind code of ref document: A1