JP2017033443A - Data processing device, data processing method, and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a technique enabling a user to easily grasp a temporal variation in state of each of a plurality of electric apparatuses to be monitored with respect to a technique representing current consumptions, power consumptions, or temporal variations in electric charge based upon the power consumptions of the plurality of electric apparatuses to be monitored with stacked bar charts.SOLUTION: A data processing device 100 has: a data acquisition part 10 which acquires time-series measurement data of each apparatus which show current consumptions or power consumptions by unit times of the plurality of electric apparatuses to be monitored; and a stacking order determination part 20 which determines, based upon the time-series measurement data of each apparatus, stacking order of a stacked bar chart showing temporal variation in state of each of the plurality of electric apparatuses to be monitored while setting the time on one axis and electric charges based upon the current consumptions, power consumptions or electric charges on the other axis.SELECTED DRAWING: Figure 2

Description

  The present invention relates to a data processing device, a data processing method, and a program.

  Attempts have been made to monitor the operating state (power supply state, power consumption, etc.) of each of a plurality of monitored electrical devices. When the user grasps the operating state of each monitored electrical device, an effect such as energy saving is expected.

  Patent Document 1 discloses a technique for extracting a feature amount from measurement data detected by a measurement sensor installed in the vicinity of a feeder inlet, and estimating an operating state of each of a plurality of electrical devices based on the feature amount. .

  Patent Document 2 discloses a technique for displaying a breakdown of power consumption in a stacked graph. Patent Document 2 discloses that the stacking order may be freely changed.

Japanese Patent No. 3403368 JP 2013-222256 A

  Take time on one axis, current consumption, power consumption, or electricity charges based on power consumption on the other axis, and use stacked graphs to indicate the status (current consumption, power consumption or electricity By displaying the time change of the charge), it is possible to grasp not only the time change of the state of each of the plurality of monitoring target electric devices but also the time change of the state of the plurality of all of the monitoring target electric devices.

  However, if the stacking order of the state of each of the plurality of monitoring target electrical devices in the stacked graph is inappropriate, it is difficult to grasp the time change of the state of each of the plurality of monitoring target electrical devices.

  Patent Document 2 discloses that the stacking order may be freely changed, but no specific means for determining the order is disclosed.

  The present invention relates to a technique for displaying current consumption, power consumption, or time change of an electricity bill based on power consumption of each of a plurality of monitoring target electrical devices in a stacked graph, and relates to the time change of the state of each of the plurality of monitoring target electrical devices. It is an object of the present invention to provide a technology that makes it easy to grasp.

According to the present invention,
Data acquisition means for acquiring time-series measurement data for each device indicating current consumption or power consumption per unit time of each of the plurality of electric appliances to be monitored;
Take time on one axis, take electricity charges based on current consumption, power consumption or power consumption on the other axis, the stacking order in the stacked graph showing the time change of the state of each of the plurality of monitored electrical equipment, A stacking order determination means for determining based on time-series measurement data for each device,
A data processing apparatus is provided.

Moreover, according to the present invention,
Computer
Data acquisition means for acquiring time-series measurement data for each device indicating the current consumption or power consumption per unit time of each of the plurality of electric appliances to be monitored;
Take time on one axis, take electricity charges based on current consumption, power consumption or power consumption on the other axis, the stacking order in the stacked graph showing the time change of the state of each of the plurality of monitored electrical equipment, Means for determining the order of accumulation based on time-series measurement data for each device;
A program is provided that functions as:

Moreover, according to the present invention,
Computer
A data acquisition step of acquiring time-series measurement data for each device indicating current consumption or power consumption per unit time of each of the plurality of electrical devices to be monitored;
Take time on one axis, take electricity charges based on current consumption, power consumption or power consumption on the other axis, the stacking order in the stacked graph showing the time change of the state of each of the plurality of monitored electrical equipment, A stacking order determination step determined based on time-series measurement data for each device;
A data processing method for performing the above is provided.

Moreover, according to the present invention,
A selection means for selecting a rule relating to a stacked graph indicating a time change of a state of each of a plurality of electric appliances to be monitored;
Output means for outputting the stacked graph in which time-series measurement data for each device indicating current consumption or power consumption per unit time of each of the plurality of monitoring target electrical devices is stacked in the stacking order based on the selected rule; ,
A data processing apparatus is provided.

Moreover, according to the present invention,
Computer
A selection means for selecting a rule relating to a stacked graph indicating a time change of a state of each of a plurality of electric appliances to be monitored;
Output means for outputting the stacked graph in which time series measurement data for each device indicating current consumption or power consumption per unit time of each of the plurality of monitoring target electrical devices is stacked in the stacking order based on the selected rule;
A program is provided that functions as:

Moreover, according to the present invention,
Computer
A selection step of selecting a rule relating to a stacked graph indicating a time change of a state of each of a plurality of electric appliances to be monitored;
An output step of outputting the stacked graph in which time series measurement data for each device indicating current consumption or power consumption per unit time of each of the plurality of monitoring target electrical devices is stacked in the stacking order based on the selected rule; ,
A data processing method for performing the above is provided.

  According to the present invention, in the technology for displaying the current consumption of each of the plurality of monitored electrical devices, the power consumption or the time variation of the electricity bill based on the power consumption in a stacked graph, the time variation of the state of each of the plurality of monitored electrical devices Can be easily grasped by the user.

It is a figure which shows notionally an example of the hardware constitutions of the apparatus of this embodiment. It is an example of a functional block diagram of a data processor of this embodiment. It is a figure which shows typically an example of the registration information of the monitoring object electric equipment. It is a figure which shows typically an example of the time series measurement data for every apparatus. It is a figure which shows an example of a stacked graph typically. It is an example of the functional block diagram of the accumulation order determination part of this embodiment. It is a flowchart which shows an example of the flow of a process of the data processor of this embodiment. It is a figure which shows typically an example of the accumulation graph piled up in the accumulation order which the accumulation order determination part determined. It is a figure which shows typically an example of the accumulation graph piled up in the accumulation order which the accumulation order determination part determined. It is an example of a functional block diagram of a data processor of this embodiment. It is an example of a functional block diagram of a data processor of this embodiment. It is a figure which shows typically an example of the registration information of the monitoring object electric equipment. It is a figure which shows typically an example of the teacher data of this embodiment. It is a figure which shows typically the calculation result of the 2nd calculating means of this embodiment. It is a figure for demonstrating the example of application of the data processor of this embodiment. It is an example of the functional block diagram of the accumulation order determination part of this embodiment. It is a figure which shows typically an example of the stacked graph display screen of this embodiment.

  First, an example of the hardware configuration of the apparatus (data processing apparatus) of this embodiment will be described. Each unit included in the apparatus according to the present embodiment is stored in a CPU (Central Processing Unit) of any computer, a memory, a program loaded into the memory, a storage unit such as a hard disk for storing the program (from the stage of shipping the apparatus in advance). It can also store programs downloaded from CDs (Compact Discs) and other storage media, servers on the Internet, etc.), and any combination of hardware and software centering on a network connection interface Realized. It will be understood by those skilled in the art that there are various modifications to the implementation method and apparatus.

  FIG. 1 is a diagram conceptually illustrating an example of a hardware configuration of an apparatus (data processing apparatus) according to the present embodiment. As shown in the figure, the apparatus of this embodiment includes, for example, a CPU 1A, a RAM (Random Access Memory) 2A, a ROM (Read Only Memory) 3A, a communication unit 8A, an auxiliary storage device 9A, and the like that are connected to each other via a bus 10A. Have. Note that the apparatus of the present embodiment may further include a display control unit 4A, a display 5A, an operation reception unit 6A, an operation unit 7A, and the like. Although not shown, the apparatus according to the present embodiment may include other elements such as a microphone and a speaker. In addition, some of the illustrated elements may not be included.

  The CPU 1A controls the entire computer of the apparatus together with each element. The ROM 3A includes an area for storing programs for operating the computer, various application programs, various setting data used when these programs operate. The RAM 2A includes an area for temporarily storing data, such as a work area for operating a program. The auxiliary storage device 9A is an HDD (Hard Disk Drive), for example, and can store a large amount of data.

  The display 5A is, for example, a display device (LED (Light Emitting Diode) display, liquid crystal display, organic EL (Electro Luminescence) display, etc.). The display 5A may be a touch panel display integrated with a touch pad. The display control unit 4A reads data stored in a VRAM (Video RAM), performs predetermined processing on the read data, and then sends the data to the display 5A to display various screens. The operation reception unit 6A receives various operations via the operation unit 7A. The operation unit 7A includes operation keys, operation buttons, switches, a jog dial, a touch panel display, a keyboard, and the like. The communication unit 8A is wired and / or wirelessly connected to a network such as the Internet or a LAN (Local Area Network) and communicates with other electronic devices. Further, the communication unit 8A can directly communicate with another electronic device by wire and / or wireless to perform communication.

  Hereinafter, this embodiment will be described. Note that the functional block diagram used in the following description of the embodiment shows functional unit blocks rather than hardware unit configurations. In these drawings, each device is described as being realized by one device, but the means for realizing it is not limited to this. That is, it may be a physically separated configuration or a logically separated configuration. In addition, the same code | symbol is attached | subjected to the same component and description is abbreviate | omitted suitably.

<First Embodiment>
First, an outline of the present embodiment will be described. When the data processing apparatus of the present embodiment acquires time-series measurement data for each device indicating the current consumption or power consumption for each unit time of each of the plurality of monitoring target electrical devices, the data processing device is based on the acquired time-series measurement data for each device. Take the time on one axis and the electricity rate based on current consumption, power consumption or power consumption on the other axis, and determine the order of stacking in the stacked graph showing the time change of each status of multiple monitored electrical devices To do.

  According to such a data processing apparatus of this embodiment, the stacking order according to the contents of the acquired time-series measurement data for each device, that is, the stacking order suitable for the acquired contents of the time-series measurement data for each device. It is determined.

  Next, the configuration of the data processing apparatus of this embodiment will be described in detail. FIG. 2 shows an example of a functional block diagram of the data processing apparatus 100 of the present embodiment. As illustrated, the data processing apparatus 100 includes a data acquisition unit 10 and a stacking order determination unit 20.

  The data acquisition unit 10 acquires time-series measurement data for each device (for each monitored electrical device) indicating current consumption (Ah) or power consumption (Wh) per unit time of each of the plurality of monitored electrical devices.

  The monitoring target electrical device is a target electrical device that monitors the operating state (power state, power consumption, etc.). For example, as shown in FIG. 3, a plurality of electrical appliances to be monitored are registered in the data processing apparatus 100 in advance. In FIG. 3, the monitoring target electric device ID, the model number, and the device type are associated with each other. The registration content is not limited to that shown in FIG. 3 as long as it can identify each of the plurality of electric appliances to be monitored.

  Next, FIG. 4 schematically illustrates an example of time-series measurement data for each device acquired by the data acquisition unit 10. FIG. 4 is time-series measurement data of the monitoring target electric device whose monitoring target electric device ID is “A32-00001”. In the illustrated time-series measurement data for each device, the date, time (start time and end time of each unit time zone), and power consumption (Wh) of each unit time zone are associated with each other.

  In addition, although the power consumption (Wh) per unit time is shown in the time series measurement for each device in FIG. 4, instead of or in addition to this, the current consumption (Ah) per unit time and the electricity per unit time. At least one of the charges may be included. The electricity bill is calculated by the product of power consumption (Wh) and unit price. The unit price is expressed in units such as yen / Wh, dollar / Wh, and the like.

  Further, the time-series measurement data for each device shown in FIG. 4 is an integrated value of power consumption every 30 seconds, but the unit time is not limited to this. For example, an integrated value every 1 minute, an integrated value every 5 minutes, an integrated value every 15 minutes, an integrated value every 30 minutes, and the like can be used.

  The data acquisition unit 10 acquires time-series measurement data as shown in FIG. 4 for each monitoring target electrical device. For example, a storage device in which time-series measurement data for each device is accumulated may be provided inside the data processing device 100 or in an external device configured to be able to communicate with the data processing device 100. And the data acquisition part 10 may acquire the time series measurement data for every apparatus from the said memory | storage device. In addition, time-series measurement data for each device may be input to the data processing apparatus 100 by any input means. And the data acquisition part 10 may acquire the time series measurement data for every apparatus input in this way.

  The means for measuring the time series measurement data for each device is not particularly limited. An example will be described in the following embodiment.

  Returning to FIG. 2, the stacking order determination unit 20 takes time on one axis, takes an electricity charge based on current consumption, power consumption, or power consumption on the other axis, and sets the status ( The order of accumulation in the accumulation graph showing the time change of current consumption, power consumption, or electricity charges) is determined based on time-series measurement data for each device.

  The stacking order determination unit 20 determines “the stacking order in which the user can easily grasp the temporal change in the state of each of the plurality of monitoring target electrical devices” based on the contents of the time-series measurement data for each device.

  Here, FIG. 5 shows an example of a stacked graph. In the stacked graph shown in the figure, time (date and time) is taken on the horizontal axis, and power consumption (Wh) is taken on the vertical axis, and the time change of the state (power consumption) of the devices 1 to 4 is displayed. The order of stacking is, from the bottom, equipment 1, equipment 2, equipment 3, and equipment 4. This is simply stacked in the order of numbers, not the stacking order determined by the stacking order determination unit 20.

  The stacking order determination unit 20 determines the stacking order in such a stacked graph based on time-series measurement data for each device. As shown in FIG. 6, the stacking order determination unit 20 may include a statistics unit 21 and a determination unit 22.

  The statistical unit 21 performs predetermined statistical processing on the time-series measurement data for each device. The statistical unit 21 can perform statistical processing using the time-series measurement data for each device in the time zone displayed as a graph as the processing target data. In the case of the example in FIG. 5, the time series measurement data from device 1 to device 4 from 0:00 on January 18 to 24:00 on January 20 is the processing target data. In this case, the processing target data is data for 3 days (72 hours).

  As an example of the statistical process, the statistical unit 21 can calculate an operation rate for each monitoring target electrical device. There are various methods for calculating the operating rate, but an example will be described below. For example, the statistics unit 21 identifies a unit time zone in which the current consumption, power consumption, or electricity rate is equal to or greater than a predetermined threshold as the time zone in which the monitored electrical device is operating. Then, the statistical unit 21 calculates a value obtained by dividing the total time specified as being in operation by the total time of the processing target data (72 hours in the example of FIG. 5) as the operation rate. In other words, the operation rate indicates the ratio of the total time specified that the predetermined monitoring target electric device is operating in the total time.

  As another example of the statistical processing, the statistical unit 21 can calculate the variation of the data value (current consumption, power consumption, or electricity bill) for each monitoring target electrical device. Specifically, the “variation” indicates a standard deviation value of the data value calculated by the statistical unit 21, a ratio between the average value and the standard deviation value (a value obtained by dividing the standard deviation value by the average value), or the like.

  As another example of the statistical processing, the statistical unit 21 can calculate the number of times of power ON / OFF switching for each monitored electrical device. The statistics unit 21 may specify the timing at which the current consumption, power consumption, or electricity rate changes from a predetermined threshold value or more to less than a predetermined threshold value as the timing at which the power source is switched from ON to OFF. For example, the data value (current consumption, power consumption, or electricity bill) in the Nth unit time zone included in the processing target data is greater than or equal to a predetermined threshold, and the data value in the (N + 1) th unit time zone is predetermined. If it is less than the threshold value, the statistical unit 21 may specify the timing of the boundary between the Nth unit time zone and the (N + 1) th unit time zone as the timing at which the power supply is switched from ON to OFF.

  The statistics unit 21 may specify the timing at which the current consumption, power consumption, or electricity rate changes from less than a predetermined threshold value to a predetermined threshold value or more as the timing at which the power source is switched from OFF to ON. For example, the data value (current consumption, power consumption, or electricity bill) in the Nth unit time zone included in the processing target data is less than a predetermined threshold, and the data value in the (N + 1) th unit time zone is predetermined. If it is equal to or greater than the threshold value, the statistics unit 21 may specify the timing of the boundary between the Nth unit time zone and the (N + 1) th unit time zone as the timing at which the power supply is switched from OFF to ON. And the statistics part 21 may count the switching timing specified in this way.

  As another example of the statistical processing, the statistical unit 21 may calculate a maximum value, a minimum value, a mode value, an average value, and the like for each monitored electrical device.

  The determination unit 22 determines the stacking order based on the result of statistical processing by the statistical unit 21. For example, the determination unit 22 may determine the order of stacking from the bottom in descending order of availability, or the order of stacking from the bottom in order from the smallest data value variation.

  In addition, the determination unit 22 has a stacking order in which the maximum value is stacked in order from the bottom, a stacking order in which the minimum value is stacked in order from the bottom, a stacking order in which the mode is small in order, and the average value. The order of stacking from the bottom in order from the smallest, the order of stacking from the bottom in order from the one with the smallest number of power ON / OFF switching, etc. may be determined.

  The determination unit 22 may determine the stacking order by combining a plurality of these. For example, the determination unit 22 determines the stacking order based on the operating rate, and when there are a plurality of monitoring target electrical devices having the same operating rate, as the stacking order of the monitoring target electrical devices, the data values vary in ascending order. The order of stacking from the bottom may be determined.

  In addition, the stacking order determination unit 20 may further include a selection unit 23 as illustrated in FIG. In the selection unit 23, a plurality of rules for determining the stacking order (eg, “stacking from the bottom in order of increasing availability”, “stacking from the bottom in order of small variation”, etc.) are registered. Then, the selection unit 23 selects one from the plurality of rules.

  The statistics unit 21 performs statistical processing related to the rule selected by the selection unit 23. Then, the determination unit 22 determines the stacking order according to the rule selected by the selection unit 23 and the statistical result by the statistical unit 21. For example, when the selection unit 23 selects “pile up from the bottom in descending order of operation rate”, the statistics unit 21 calculates the operation rate. And the determination part 22 is piled up from the bottom in order with a big operation rate, and determines the pile up order.

  The selection unit 23 may accept an input for selecting one rule from the user. Then, one rule may be selected according to the user input. For example, the selection unit 23 may accept user input designating one of a plurality of rules via a GUI (graphical user interface) component such as a radio button or a drop-down list. FIG. 17 shows an example of a UI (user interface) screen that accepts a user input for selecting one rule from the drop-down list.

  The effect of having such a stacking order will be described below.

  Next, an example of the processing flow of the data processing apparatus 100 of this embodiment will be described using the flowchart of FIG.

  First, the data acquisition unit 10 acquires time-series measurement data for each device indicating the current consumption or power consumption per unit time of each of the plurality of monitoring target electrical devices (S10).

  Thereafter, the statistics unit 21 of the stacking order determination unit 20 identifies the time zone to be displayed in the stacked graph, and identifies time series measurement data for each device in the identified time zone as the processing target data (S11). For example, the data processing apparatus 100 may be configured to accept an input specifying a time zone to be displayed in a stacked graph from the user. And the stacking order determination part 20 may specify the time slot | zone displayed with a stacked graph based on a user input. FIG. 17 shows an example of a UI screen for designating a time zone (start date / time and end date / time) to be displayed in a graph in a drop-down list. Other GUI parts may be used.

  Thereafter, the statistical unit 21 performs predetermined statistical processing using the processing target data as a processing target (S12). After that, the determination unit 22 of the stacking order determination unit 20 takes time on one axis based on the statistical result of S12, takes an electric charge based on current consumption, power consumption or power consumption on the other axis, The stacking order of the stacked graph indicating the time change of the state of each monitoring target electric device is determined (S13).

  According to the present embodiment described above, the stacking order in the stacked graph can be determined according to the contents of the time-series measurement data for each device. For example, according to the content of the time-series measurement data for each device, it is possible to determine a stacking order that allows the user to easily grasp the time change of the state of each of the plurality of monitored electrical devices.

  As a result, the user who observed the stacked graph displayed in the stacking order determined by the data processing apparatus 100 of the present embodiment can easily grasp the time change of the state of each of the plurality of monitoring target electrical devices.

  By the way, the easiness of grasping the time change of the monitoring target electrical device positioned above in the stacked graph is affected by the data content of the monitoring target electrical device positioned below it. If the fluctuation of the data value of the monitored electrical equipment located below is large, or if the fluctuation of the data value is large, the time change of the monitored electrical equipment located above it will be grasped. It becomes difficult.

  For example, in the example shown in FIG. 5, the power consumption of the device 1 is the timing at which the power ON / OFF is switched, that is, around 8:00 on January 19, around 22:00 on January 19, January It fluctuates greatly around 8:00 on January 20 and around 22:00 on January 20. Further, immediately after the power ON / OFF switching at about 8:00 on January 20, the power consumption fluctuates greatly.

  From FIG. 5, at the timing when a large data value change occurs, the time change of the monitoring target electrical devices (devices 2 to 4) located thereabove (eg, whether the data value is changing or not). In some cases, it is difficult to figure out whether it is increasing or decreasing. Further, it can be seen that the larger the number of times the large data value fluctuates, the more difficult it is to grasp the time change of the monitoring target electrical devices (devices 2 to 4) located above the data value.

  The present embodiment includes means for reducing such inconvenience. In this embodiment, as shown in FIGS. 8 and 9, it is possible to determine the order of stacking from the bottom in order from the largest operating rate.

  A large fluctuation in the data value (electric current consumption, electric power consumption, or electric charge) of an electric device may occur due to switching of power ON / OFF. The present inventor pays attention to a method of use peculiar to a certain kind of electrical equipment, and when switching the order of stacking from the bottom in order from the one with the highest operating rate, switching the power ON / OFF by a relatively simple arithmetic processing It has been found that the order of stacking the electrical devices to be monitored that are less frequently occurring can be determined.

  Some electric devices, such as fixed telephones and refrigerators, are always operating, that is, 365 days, 24 hours. When such an electrical device is included in the monitoring target electrical device, the operation rate is 100%, and the stacking order is lower. There is almost no switching timing of power ON / OFF in an electric device that is always operating. That is, it is unlikely that the power ON / OFF switching timing appears in the time zone displayed in the stacked graph.

  By determining the order of stacking from the bottom in order from the largest operating rate as in this embodiment (see FIGS. 8 and 9), the power ON / OFF switching timing, that is, the data value (see FIGS. 8 and 9). In this case, it is possible to position the monitoring target electrical device having a low possibility that the timing at which the power consumption) fluctuates greatly appears. As a result, the above inconvenience can be reduced.

  Furthermore, as shown in FIG. 9, by determining the stacking order in which the monitoring target electrical devices having the same operation rate (device 2 and device 4: 100%) are stacked from the bottom in order from the smallest data value variation, Effectively, the inconveniences as described above can be reduced.

  In FIG. 8 and FIG. 9, a plurality of monitoring target electric devices are identified by the information of the devices 1 to 4, but in this embodiment, this information is the monitoring target electric device included in the registration information of FIG. It can be replaced with an ID, model number, or device type.

  Further, in the present embodiment, it is possible to determine the order of stacking from the bottom in order from the least number of power ON / OFF switching times. In this case, it is possible to achieve the same effect as the stacking order of stacking from the bottom in order of increasing availability.

  Further, in the present embodiment, the stacking order in which the maximum value of the data values is stacked in order from the bottom, the stacking order in which the minimum value of the data values is stacked in order from the bottom, the stacking order from the bottom in order from the bottom, The order of stacking from the bottom and the order of stacking from the bottom can be determined in order of increasing average data value. In this case, there is a tendency that monitored electric devices having a smaller difference between the data value at the time of power ON (current consumption, power consumption, or electricity charge) and the data value at the time of power OFF are going downward. As a result, it is possible to reduce the difficulty of grasping the temporal change in the state of the monitoring target electrical device located above it.

  Moreover, in this embodiment, it can comprise so that a user can determine a stacking rule. In the case of this configuration, it is possible to display a stacked graph in the stacked order that the user really wants.

<Second Embodiment>
FIG. 10 shows an example of a functional block diagram of the data processing apparatus 100 of the present embodiment. As illustrated, the data processing apparatus 100 according to the present embodiment includes a data acquisition unit 10, a product order determination unit 20, and an output unit 30. The configurations of the data acquisition unit 10 and the stacking order determination unit 20 are the same as those in the first embodiment.

  The output unit 30 outputs a stacked graph in which the states (current consumption, power consumption, or electricity rate data) of each of the plurality of monitoring target electrical devices are stacked in the stacking order determined by the stacking order determination unit 20.

  For example, when the data processing apparatus 100 includes the display control unit 4A and the display 5A illustrated in FIG. 1, the output unit 30 may display a stacked graph as illustrated in FIGS. 8 and 9 via the display 5A. Good.

  In addition, the output unit 30 may transmit data of a stacked graph as illustrated in FIGS. 8 and 9 to the user terminal device. Examples of the user terminal device include, but are not limited to, a personal computer (PC), a smartphone, a tablet, a mobile phone, a dedicated terminal that communicates with the data processing device 100, and the like. The user terminal device that has received the data of the stacked graph from the output unit 30 processes the data and displays the stacked graph on a predetermined display.

  In addition, the output unit 30 may output a stacked graph as illustrated in FIGS. 8 and 9 via another output device such as a printer or a mailer.

  According to the present embodiment described above, the same operational effects as those of the first embodiment can be realized. Further, according to the present embodiment, the stacked graph in the stacking order determined by the stacking order determination unit 20 can be provided to the user via the output unit 30. A user who has viewed such a stacked graph can easily grasp the time change of the state of each of the plurality of monitoring target electrical devices.

<Third Embodiment>
FIG. 11 shows an example of a functional block diagram of the data processing apparatus 100 of the present embodiment. As illustrated, the data processing apparatus 100 according to the present embodiment includes a data acquisition unit 10, a product order determination unit 20, an output unit 30, and an input reception unit 40. The configurations of the data acquisition unit 10 and the output unit 30 are the same as those in the first and second embodiments.

  The input receiving unit 40 receives an input for designating a time zone (hereinafter, “display time zone”) for displaying the state of each of the plurality of monitoring target electrical devices in the stacked graph. That is, the input reception unit 40 receives an input for designating a start time and an end time on the time axis of the stacked graph. In the case of the example of FIGS. 8 and 9, 0:00 on January 18 is the start time of the display time zone, and 24:00 on January 20 is the end time of the display time zone.

  For example, the user may perform an input of designating a display time zone and an operation of transmitting the designated display time zone to the data processing device 100 via the user terminal device. In this case, the input reception unit 40 acquires information indicating the display time zone transmitted from the user terminal device.

  In addition, when the data processing apparatus 100 includes the operation reception unit 6A and the operation unit 7A illustrated in FIG. 1, the input reception unit 40 receives an input of the display time zone via the operation reception unit 6A and the operation unit 7A. Also good.

  As shown in FIGS. 8 and 9, the input receiving unit 40 may receive an input for changing the display time zone while displaying a stacked graph of a certain display time zone via the user terminal device or the display 5 </ b> A. In the case of the example in FIG. 17, an input for changing the display time zone is received from a GUI component (drop-down list corresponding to the graph display time zone start time and end time) provided on the left side of the UI screen. In addition, before displaying the stacked graph via the user terminal device or the display 5A, the input receiving unit 40 may receive an input for designating a display time zone of the stacked graph to be displayed.

  When the input receiving unit 40 receives the input, the stacking order determination unit 20 determines the stacking order based on the time-series measurement data for each device in the specified time zone in response to the input (accepting input). . First, when the input receiving unit 40 receives an input designating a display time zone, the statistics unit 21 of the stacking order determination unit 20 specifies the display time zone. And the statistics part 21 specifies the data (time series measurement data for every apparatus) of the specified display time slot | zone as process target data. Thereafter, the statistical unit 21 performs predetermined statistical processing based on the processing target data. The details of the statistical processing are the same as those in the first and second embodiments.

  Other configurations of the stacking order determination unit 20 are the same as those in the first and second embodiments.

  According to the present embodiment described above, the same operational effects as those of the first and second embodiments can be realized. Moreover, according to this embodiment, the user can display the accumulation data of a desired time slot | zone.

  In addition, when an input for changing the display time zone is made while displaying the stacked graph of a certain display time zone, the stacking order determination unit 20 sets the new display time zone as the processing target data and sets the new stacking order. Can be re-determined. And the output part 30 can output the accumulation graph of the newly designated display time slot | zone in the accumulation order newly determined by the accumulation order determination part 20. FIG. As described above, according to the present embodiment, the stacking order can be redetermined in accordance with the change of the display time zone for displaying the graph, and can be displayed in the stacking order after the redetermination. As a result, even when the display time zone is changed, it is possible to realize display in the optimum stacking order.

<Fourth Embodiment>
The data processing apparatus 100 according to the present embodiment acquires time-series measurement data for each device measured by a measurement unit described below. The measurement means has at least one of a first measurement means and a second measurement means. Note that the data processing apparatus 100 may or may not include a measurement unit.

  The first measurement means has a plurality of measurement sensors corresponding to the plurality of monitoring target electric devices. Each of the plurality of measurement sensors is installed at a position where the current consumption or power consumption of each of the plurality of monitoring target electrical devices can be measured. For example, a smart tap may be installed between a device and an outlet for each monitored electrical device. In addition, you may install a measurement sensor for every apparatus (every branch) in a distribution board. The first measuring means uses such a plurality of measurement sensors to measure time-series data of current consumption or time-series data of power consumption (time-series measurement data for each device) of each of the plurality of monitored electrical devices. can do.

  The first measuring unit may include a first calculating unit that performs a predetermined calculation process on the time-series data of current consumption or the time-series data of power consumption acquired via the measurement sensor. The 1st calculating means may hold | maintain the information which shows a power unit price previously. The unit price of electric power may be a value that varies with time. Then, the first computing means is based on the unit price of power and the time series data of the power consumption of each of the plurality of electric appliances to be monitored measured by the measurement sensor. You may calculate every time series measurement data).

  The second measuring means includes mixed time series measurement data indicating current consumption or power consumption of a plurality of monitoring target electrical devices, and a feature amount of each operating state for each of a plurality of operating states that can be taken by the plurality of monitoring target electrical devices. Based on the associated teacher data, a result (time-series measurement data for each device) of estimating the current consumption or power consumption per unit time of each of the plurality of monitoring target electric devices is calculated.

  The second measurement means has a measurement sensor. A measurement sensor is installed in the position which can measure the consumption current or power consumption of several monitoring object electric equipment. The second measuring unit obtains mixed time series measurement data (waveform data) indicating current consumption or power consumption of the plurality of electric appliances to be monitored from such a measurement sensor. The mixed time series measurement data includes components of a plurality of electric appliances to be monitored.

  The measurement sensor is installed in a distribution board, for example. A measurement sensor may be installed in the position which can measure mixed time series measurement data which shows consumption current or power consumption of the whole electric appliance to be monitored. In addition, a measurement sensor may be installed in the position which can measure mixed time series measurement data which shows consumption current or power consumption of some (a plurality) of electric appliances to be monitored. In the case of the latter example, by acquiring a plurality of mixed time series measurement data using a plurality of measurement sensors, data of all the monitoring target electric devices is acquired.

  The second measuring means includes second calculating means for performing a predetermined calculation process on the time-series data of current consumption or the time-series data of power consumption acquired via the measurement sensor. The second computing means estimates the operating state of each of the plurality of monitoring target electrical devices based on the mixed time series measurement data. The estimation process can be realized by applying any conventional technique (for example, means disclosed in Patent Document 1), and an example will be described below.

  For example, the second calculation means sets a predetermined time zone in the mixed time series measurement data as a processing target, and extracts a predetermined feature amount from the processing target. The second computing means shifts the time zone to be processed, and extracts feature amounts in order from a plurality of processing targets.

  Features extracted from mixed time series measurement data vary, for example, frequency intensity / phase (harmonic component) of current consumption, phase, change in current consumption, average value, peak value, effective value, crest factor, It may be the waveform rate, current change convergence time, energization time, peak position, time difference between the peak position of the power supply voltage and the peak position of the current consumption, power factor, and the like. In addition, it is not limited to the illustration here.

  The second computing means may extract one type of feature amount from the mixed time series measurement data, or may extract a plurality of types of feature amounts.

  Moreover, as shown in FIG. 12, the feature amount of each of the plurality of monitoring target electrical devices is registered in the second calculation means. The feature amount is obtained by quantifying the feature that appears in the mixed time series measurement data when each monitored electric device is in operation. A feature amount for each power consumption or current consumption of each monitoring target electrical device may be registered.

  The second calculation means obtains feature amounts of each of a plurality of operating states that can be taken by the plurality of monitoring target electrical devices based on the feature amounts of each of the monitoring target electrical devices as shown in FIG. The operating states that can be taken by a plurality of monitoring target electrical devices are, for example, “only a fixed phone is in operation”, “a fixed phone, a monitor, and a PC are in operation”, and the like. In addition, when the feature quantity for each power consumption or current consumption of each monitoring target electric device is registered, the operation states that can be taken by the plurality of monitoring target electric devices are, for example, “Fixed phone is operating with XXW” ”,“ Fixed telephone is operating at XXW ”,“ Fixed telephone is operating at XXW, monitor is operating at ΔΔW, and PC is operating at □ W ”. By adding the feature amounts of each of the monitoring target electrical devices as shown in FIG. 12, it is possible to obtain the feature amounts of the operating states that can be taken by the plurality of monitoring target electrical devices as described above.

  In this way, as shown in FIG. 13, teacher data is obtained in which a feature amount of each operating state is associated with each of a plurality of operating states that can be taken by a plurality of monitoring target electrical devices. In FIG. 13, the operation state ID, contents (details of each operation state), and feature quantities are associated with each other.

  The second calculation means generates an estimation model by machine learning using such teacher data, and inputs the feature amount extracted from the mixed time series measurement data to the generated estimation model, so that the estimation result (multiple monitoring The operating state of the target electric device can be obtained. The estimation model can be, for example, one using multiple regression analysis, a neural network, a genetic algorithm, or the like.

  As a result of the estimation process as described above, the result data associating the date and time information (date, time) and the estimation result (operation state ID) as shown in FIG. 14 is obtained. As shown in FIG. 14, the result data is data in which estimation results for each unit time (in the case of the figure, estimation results for every 30 seconds) are arranged in time series.

  Based on the information shown in FIG. 13 and FIG. 14, the second calculating means, as shown in FIG. 4, time-series data of current consumption or time-series data of power consumption (for each device) Time series measurement data) can be calculated. When a plurality of mixed time series measurement data are acquired, the above processing is performed on each mixed time series measurement data, so that the time series data as shown in FIG. Can be acquired.

  The second calculation means may hold information indicating the power unit price in advance. The unit price of electric power may be a value that varies with time. Then, the second calculation means, based on the power unit price and the time series data of the power consumption of each of the plurality of monitoring target electrical equipment measured by the measurement sensor, Time series measurement data) can be calculated.

  According to the present embodiment described above, the same function and effect as those of the first to third embodiments can be realized.

<Fifth Embodiment>
An application example of the data processing apparatus 100 described in the first to fourth embodiments will be described with reference to FIG.

  The power consumer 7 manages the measurement sensor 1, the information collection device 2, the router 3, and the user terminal 4.

  The measurement sensor 1 is one or a plurality of measurement sensors provided in the measurement means (first measurement means, second measurement means) described in the fourth embodiment.

  The information collection device 2 acquires time-series measurement data measured by the measurement sensor 1. The information collection device 2 may include the first calculation unit or the second calculation unit described in the fourth embodiment. Instead of the information collection device 2, the server 5 may include the first calculation unit or the second calculation unit described in the fourth embodiment.

  The information collection device 2 transmits predetermined information to the server 5 via the router 3 and the network 6. For example, the information collection device 2 may transmit time-series measurement data acquired from the measurement sensor 1 or data obtained by calculation processing by the first calculation unit or the second calculation unit to the server 5.

  The data processing apparatus 100 of this embodiment is provided in the information collection apparatus 2 or the server 5. A stacked graph obtained by stacking the states of each of the plurality of monitoring target electrical devices in the stacking order determined by the stacking order determination unit 20 is output via the information collection device 2 or the display of the user terminal 4.

  According to the present embodiment described above, the same function and effect as those of the first to fourth embodiments can be realized.

Hereinafter, examples of the reference form will be added.
1. Data acquisition means for acquiring time-series measurement data for each device indicating current consumption or power consumption per unit time of each of the plurality of electric appliances to be monitored;
Take time on one axis, take electricity charges based on current consumption, power consumption or power consumption on the other axis, the stacking order in the stacked graph showing the time change of the state of each of the plurality of monitored electrical equipment, A stacking order determination means for determining based on time-series measurement data for each device,
A data processing apparatus.
2. In the data processing apparatus according to 1,
A data processing apparatus further comprising: an output unit that outputs the stacked graph in which the states of the plurality of electrical devices to be monitored are stacked in the stacking order determined by the stacking order determination unit.
3. In the data processing apparatus according to 1 or 2,
The stacking order determination means includes
Statistical means for performing predetermined statistical processing on the time-series measurement data for each device;
A determination means for determining the stacking order based on the statistical processing;
A data processing apparatus.
4). In the data processing apparatus according to 3,
The statistical means calculates an operating rate for each monitored electrical device,
The determination means is a data processing device that determines the order of stacking from the bottom in order from the one with the highest operating rate.
5). In the data processing apparatus according to 3 or 4,
The statistical means calculates the variation of the data value for each monitored electrical device,
The determination means is a data processing device that determines the order of stacking from the bottom up in order from the smallest variation.
6). In the data processing device according to any one of 3 to 5,
A selection means for selecting a rule for determining the stacking order;
The statistical means performs statistical processing related to the selected rule,
The determination unit is a data processing device that determines the stacking order based on the selected rule and the statistical processing.
7). In the data processing device according to any one of 1 to 6,
An input receiving means for receiving an input for designating a time zone for displaying the state of each of the plurality of electric appliances to be monitored in the stacked graph;
The stacking order determination unit is a data processing device that determines the stacking order based on time-series measurement data for each device in a specified time zone when the input receiving unit receives the input.
8). In the data processing device according to any one of 1 to 7,
The data acquisition means includes mixed time-series measurement data indicating current consumption or power consumption of the plurality of monitoring target electrical devices, and a plurality of operating states that can be taken by the plurality of monitoring target electrical devices. A data processing apparatus that obtains, as time-series measurement data for each device, a result of estimating current consumption or power consumption for each unit time of each of the plurality of electrical devices to be monitored based on teacher data associated with the amount.
9. Computer
Data acquisition means for acquiring time-series measurement data for each device indicating the current consumption or power consumption per unit time of each of the plurality of electric appliances to be monitored;
Take time on one axis, take electricity charges based on current consumption, power consumption or power consumption on the other axis, the stacking order in the stacked graph showing the time change of the state of each of the plurality of monitored electrical equipment, A stacking order determination means that is determined based on time-series measurement data for each device,
Program to function as.
9-2. In the program described in 9,
A program that causes the computer to further function as an output unit that outputs the stacked graph in which the states of the plurality of electrical devices to be monitored are stacked in the stacking order determined by the stacking order determination unit.
9-3. In the program described in 9 or 9-2,
The rolling order determining means is
Statistical means for performing predetermined statistical processing on the time-series measurement data for each device;
A determining means for determining the stacking order based on the statistical processing;
Program to function as.
9-4. In the program described in 9-3,
The statistical means calculates an operating rate for each monitored electrical device,
The determination means is a program for determining the stacking order of stacking from the bottom in order from the largest operating rate.
9-5. In the program described in 9-3 or 9-4,
The statistical means calculates the variation of the data value for each monitored electrical device,
The determination means is a program for determining the order of stacking from the bottom in order from the one with the smallest variation.
9-6. In the program according to any one of 9-3 to 9-5,
Causing the computer to function as a selection means for selecting a rule for determining the stacking order;
The statistical means performs statistical processing related to the selected rule,
The determination means is a program for determining the stacking order based on the selected rule and the statistical processing.
9-7. In the program according to any one of 9 to 9-6,
Causing the computer to function as an input receiving unit that receives an input for designating a time zone for displaying a state of each of the plurality of electric appliances to be monitored in the stacked graph;
The accumulation order determining means is a program for determining the accumulation order based on time-series measurement data for each of the devices in a designated time zone when the input receiving means accepts the input.
9-8. In the program according to any one of 9 to 9-7,
The data acquisition means includes mixed time-series measurement data indicating current consumption or power consumption of the plurality of monitoring target electrical devices, and a plurality of operating states that can be taken by the plurality of monitoring target electrical devices. A program for obtaining, as time-series measurement data for each device, a result of estimating current consumption or power consumption for each unit time of each of the plurality of electric appliances to be monitored based on teacher data associated with a quantity.
10. Computer
A data acquisition step of acquiring time-series measurement data for each device indicating current consumption or power consumption per unit time of each of the plurality of electrical devices to be monitored;
Take time on one axis, take electricity charges based on current consumption, power consumption or power consumption on the other axis, the stacking order in the stacked graph showing the time change of the state of each of the plurality of monitored electrical equipment, A stacking order determination step determined based on time-series measurement data for each device;
Data processing method to execute.
10-2. 10. The data processing method according to 10,
The data processing method which performs the output process which outputs the said stacked graph which the said computer piled up the state of each of several said monitoring object electric equipment in the said stacking order determined at the said stacking order determination process.
10-3. In the data processing method according to 10 or 10-2,
The stacking order determination step includes
A statistical process for performing predetermined statistical processing on the time-series measurement data for each device;
A determination step of determining the stacking order based on the statistical processing;
A data processing method.
10-4. In the data processing method according to 10-3,
In the statistical process, the operating rate is calculated for each monitored electrical device,
In the determining step, a data processing method for determining the order of stacking from the bottom in order from the one with the highest operating rate.
10-5. In the data processing method according to 10-3 or 10-4,
In the statistical process, the variation of the data value is calculated for each of the monitoring target electrical devices,
In the determining step, a data processing method for determining the stacking order of stacking from the bottom in order from the smallest variation.
10-6. In the data processing method according to any one of 10-3 to 10-5,
The computer performs a selection step of selecting a rule for determining the stacking order;
In the statistical step, statistical processing related to the selected rule is performed,
In the determining step, a data processing method for determining the stacking order based on the selected rule and the statistical processing.
10-7. In the data processing method according to any one of 10 to 10-6,
The computer executes an input receiving step of receiving an input for designating a time zone for displaying a state of each of the plurality of electric appliances to be monitored in the stacked graph,
In the stacking order determination step, a data processing method for determining the stacking order based on time-series measurement data for each device in a specified time zone when the input receiving unit receives the input.
10-8. In the data processing method according to any one of 10 to 10-7,
In the data acquisition step, the mixed time series measurement data indicating the current consumption or power consumption of the plurality of monitoring target electrical devices, and each of the plurality of operating states that can be taken by the plurality of monitoring target electrical devices are characterized by each of the operating states. A data processing method for acquiring, as time-series measurement data for each device, a result of estimating current consumption or power consumption for each unit time of each of the plurality of electric appliances to be monitored based on teacher data associated with the amount.
11. A selection means for selecting a rule relating to a stacked graph indicating a time change of a state of each of a plurality of electric appliances to be monitored;
Output means for outputting the stacked graph in which time-series measurement data for each device indicating current consumption or power consumption per unit time of each of the plurality of monitoring target electrical devices is stacked in the stacking order based on the selected rule;
A data processing apparatus.
12 11. The data processing apparatus according to 11,
An input receiving means for receiving an input for designating a time zone for displaying the state of each of the plurality of electric appliances to be monitored in the stacked graph;
The output means is a data processing device that determines the stacking order based on time-series measurement data for each device in the designated time zone.
13. 11. The data processing apparatus according to 11,
The data processing apparatus, wherein the output means determines the stacking order based on statistical processing corresponding to the selected rule.
14 11. The data processing apparatus according to 11,
The data processing apparatus that determines the stacking order based on a variation in data values of time-series measurement data for each device or an operation rate calculated based on the time-series measurement data for each device.
15. Computer
A selection means for selecting a rule relating to a stacked graph indicating a time change of a state of each of a plurality of electric appliances to be monitored;
Output means for outputting the stacked graph in which time-series measurement data for each device indicating current consumption or power consumption per unit time of each of a plurality of monitored electrical devices is stacked in the stacking order based on the selected rule;
Program to function as.
15-2. In the program described in 15,
Causing the computer to function as an input receiving unit that receives an input for designating a time zone for displaying a state of each of the plurality of electric appliances to be monitored in the stacked graph;
The output means determines a stacking order based on time-series measurement data for each device in the designated time zone.
15-3. In the program described in 15,
The output means determines a stacking order based on a statistical process corresponding to the selected rule.
15-4. In the program described in 15,
The output means is a program for determining the stacking order based on a variation in data values of time-series measurement data for each device or an operation rate calculated based on the time-series measurement data for each device.
16. Computer
A selection step of selecting a rule relating to a stacked graph indicating a time change of a state of each of a plurality of electric appliances to be monitored;
An output step of outputting the stacked graph in which time-series measurement data for each device indicating current consumption or power consumption per unit time of each of the plurality of monitoring target electrical devices is stacked in the stacking order based on the selected rule;
Data processing method to execute.
16-2. 16. The data processing method according to 16,
The computer executes an input receiving step of receiving an input for designating a time zone for displaying a state of each of the plurality of electric appliances to be monitored in the stacked graph,
In the output step, a data processing method for determining the stacking order based on time-series measurement data for each device in the designated time zone.
16-3. 16. The data processing method according to 16,
In the output step, a data processing method for determining the stacking order based on a statistical process corresponding to the selected rule.
16-4. 16. The data processing method according to 16,
A data processing method for determining the stacking order based on a variation in data values of the time-series measurement data for each device or an operating rate calculated based on the time-series measurement data for each device in the output step.

1A CPU
2A RAM
3A ROM
4A Display control unit 5A Display 6A Operation accepting unit 7A Operation unit 8A Communication unit 9A Auxiliary storage device 10A Bus 1 Measurement sensor 2 Information collection device 3 Router 4 User terminal 5 Server 6 Network 7 Power consumer 10 Data acquisition unit 20 Determination unit 21 Statistics unit 22 Determination unit 23 Selection unit 30 Output unit 40 Input reception unit 100 Data processing device

Claims (16)

Data acquisition means for acquiring time-series measurement data for each device indicating current consumption or power consumption per unit time of each of the plurality of electric appliances to be monitored;
Take time on one axis, take electricity charges based on current consumption, power consumption or power consumption on the other axis, the stacking order in the stacked graph showing the time change of the state of each of the plurality of monitored electrical equipment, A stacking order determination means for determining based on time-series measurement data for each device,
A data processing apparatus. The data processing apparatus according to claim 1,
A data processing apparatus further comprising: an output unit that outputs the stacked graph in which the states of the plurality of electrical devices to be monitored are stacked in the stacking order determined by the stacking order determination unit. The data processing apparatus according to claim 1 or 2,
The stacking order determination means includes
Statistical means for performing predetermined statistical processing on the time-series measurement data for each device;
A determination means for determining the stacking order based on the statistical processing;
A data processing apparatus. The data processing apparatus according to claim 3, wherein
The statistical means calculates an operating rate for each monitored electrical device,
The determination means is a data processing device that determines the order of stacking from the bottom in order from the one with the highest operating rate. The data processing device according to claim 3 or 4,
The statistical means calculates the variation of the data value for each monitored electrical device,
The determination means is a data processing device that determines the order of stacking from the bottom up in order from the smallest variation. The data processing apparatus according to any one of claims 3 to 5,
A selection means for selecting a rule for determining the stacking order;
The statistical means performs statistical processing related to the selected rule,
The determination unit is a data processing device that determines the stacking order based on the selected rule and the statistical processing. The data processing apparatus according to any one of claims 1 to 6,
An input receiving means for receiving an input for designating a time zone for displaying the state of each of the plurality of electric appliances to be monitored in the stacked graph;
The stacking order determination unit is a data processing device that determines the stacking order based on time-series measurement data for each device in a specified time zone when the input receiving unit receives the input. The data processing apparatus according to any one of claims 1 to 7,
The data acquisition means includes mixed time-series measurement data indicating current consumption or power consumption of the plurality of monitoring target electrical devices, and a plurality of operating states that can be taken by the plurality of monitoring target electrical devices. A data processing apparatus that obtains, as time-series measurement data for each device, a result of estimating current consumption or power consumption for each unit time of each of the plurality of electrical devices to be monitored based on teacher data associated with the amount. Computer
Data acquisition means for acquiring time-series measurement data for each device indicating the current consumption or power consumption per unit time of each of the plurality of electric appliances to be monitored;
Take time on one axis, take electricity charges based on current consumption, power consumption or power consumption on the other axis, the stacking order in the stacked graph showing the time change of the state of each of the plurality of monitored electrical equipment, A stacking order determination means that is determined based on time-series measurement data for each device,
Program to function as. Computer
A data acquisition step of acquiring time-series measurement data for each device indicating current consumption or power consumption per unit time of each of the plurality of electrical devices to be monitored;
Take time on one axis, take electricity charges based on current consumption, power consumption or power consumption on the other axis, the stacking order in the stacked graph showing the time change of the state of each of the plurality of monitored electrical equipment, A stacking order determination step determined based on time-series measurement data for each device;
Data processing method to execute. A selection means for selecting a rule relating to a stacked graph indicating a time change of a state of each of a plurality of electric appliances to be monitored;
Output means for outputting the stacked graph in which time-series measurement data for each device indicating current consumption or power consumption per unit time of each of the plurality of monitoring target electrical devices is stacked in the stacking order based on the selected rule;
A data processing apparatus. The data processing apparatus according to claim 11, wherein
An input receiving means for receiving an input for designating a time zone for displaying the state of each of the plurality of electric appliances to be monitored in the stacked graph;
The output means is a data processing device that determines the stacking order based on time-series measurement data for each device in the designated time zone. The data processing apparatus according to claim 11, wherein
The data processing apparatus, wherein the output means determines the stacking order based on statistical processing corresponding to the selected rule. The data processing apparatus according to claim 11, wherein
The data processing apparatus that determines the stacking order based on a variation in data values of time-series measurement data for each device or an operation rate calculated based on the time-series measurement data for each device. Computer
A selection means for selecting a rule relating to a stacked graph indicating a time change of a state of each of a plurality of electric appliances to be monitored;
Output means for outputting the stacked graph in which time-series measurement data for each device indicating current consumption or power consumption per unit time of each of a plurality of monitored electrical devices is stacked in the stacking order based on the selected rule;
Program to function as. Computer
A selection step of selecting a rule relating to a stacked graph indicating a time change of a state of each of a plurality of electric appliances to be monitored;
An output step of outputting the stacked graph in which time-series measurement data for each device indicating current consumption or power consumption per unit time of each of the plurality of monitoring target electrical devices is stacked in the stacking order based on the selected rule;
Data processing method to execute.

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