KR101801952B1 - Context-based method and apparatus for reducing standby power consumption - Google Patents

Abstract

Disclosed are a method and an apparatus to reduce standby power of electric devices based on context. The context-based standby power reducing method includes: a step of determining the operation state of each electric device based on the current power consumption level of electric devices consuming power; a step of determining a correlation between the electric devices based on the operation state of two or more electric devices; a step of inferring work in progress based on the operation context of the electric devices and the correlation; and a step of blocking standby power by turning off the electric devices except an electric device participating in the inferred work in progress. The present invention has an excellent standby power saving effect by reducing total standby power of household appliances by controlling a smart plug through context inference. The present invention can reduce standby power adaptively according to changes of context since ontology and a rule set can be updated by actively reflecting operation context where electric devices operate.

Description

TECHNICAL FIELD The present invention relates to a context-based standby power saving method and apparatus,

The present invention relates to a method and apparatus for reducing context-based standby power, and more particularly, to a method and apparatus for reducing context-based standby power by reducing the standby power by determining an operation performed by a user by analyzing operation contexts of various electronic apparatuses, And more particularly to a method and apparatus for achieving the above objects.

Many home appliances consume standby power, which reduces standby power to reduce the total energy consumption of the home. Standby power refers to the power consumed when electronic devices are not performing their primary operations.

Depending on the device, the standby power can be as high as 1W to 30W. In particular, although the standby power seems to be not large for the individual devices, the total standby power consumed by many devices used in each home is very large, so that a technology for reducing standby power is desperately required nationwide. That is, although the standby power loss by a single device is small, the total standby power loss can not be ignored. For example, in California homes, standby power consumption accounts for as much as 26% of total consumption.

Due to the development of the technology, recent devices consume less standby power than conventional devices, but as more and more smart devices are installed in the home as the Internet of Things (IOT) emerges, the standby power consumption of these devices It is too big to be ignored. In addition, this problem can become even more serious because people simply do not replace the devices they use just because they have low standby power.

The most effective way to shut off standby power is simple, which is to unplug the device when not in use. But unplugging all devices is both annoying and inconvenient. In order to overcome this inconvenience, according to the prior art, a smart plug has been proposed for effectively reducing the standby power of the device by monitoring when the device is not in use and turning off the power. A smart plug can be installed between a household outlet and a device to cut off standby power. The smart plug allows the user to remotely power off the device. In addition, the smart plug can be installed in the home to monitor the device and obtain usage patterns. When the smart plug is used, the user can check the current power consumption state of the device and transmit the device to the remote . ≪ / RTI >

In order to use such a smart plug efficiently, it is very important to determine exactly when it is necessary to shut off standby power. In order to control the smart plug automatically, a control technique based on the user's behavior model has recently been proposed, which is based only on the amount of power consumed by the current electronic device.

In this way, reducing the standby power of the device is also a major research area. L. Wang, D. Peng, and T. Zhang, "Design of smart home system based on wifi smart plug ", International Journal of Smart Home, vol. 9, no. 6, pp. 173-182, 2015 (hereinafter referred to as "Non-Patent Document 1"), a feedback method in which a current level of power consumption is notified to a user is proposed. The user can then control the device accordingly to reduce power consumption. Another technique is to propose an automatic standby power saving system that conserves energy by systematically controlling multiple smart plugs by a power management system. However, it does not disclose in detail how smart plug control is a systematic control method.

Generally, a home gateway is used to collect power data and create a behavior model for the device. However, the behavioral model is primarily written using the power usage patterns of individual devices and does not take into account other contexts such as the correlation between devices that work together in a particular user task (e.g. cooking, watching movies, etc.) . For example, a cooking operation includes various operating contexts of mutually related appliances such as a microwave oven and an electric rice cooker, but a smart plug does not take this context into account. Therefore, it is difficult to use the behavioral model to find the overall attribute of the work that represents the intended behavior of the user.

In this way, when the smart plug is used, the user can analyze the usage pattern of the electronic device and can save the standby power by turning off the specific electronic device at the time when it is estimated that it will not be used. The smart plug also provides the time scheduling function In this case, the device may be operated according to time. However, this time scheduling function is not always effective because users do not necessarily repeat the schedule at the correct time. That is, the user does not perform the task in accordance with the correct time, and the time to perform the same task may be changed every day. Therefore, suddenly stopping the operation of the device in accordance with a usual pattern may significantly affect the quality of the operation such as cooking and stopping, and even the completion of the operation may not be possible.

Non-Patent Document 1: L. Wang, D. Peng, and T. Zhang, "Design of smart home system based on wifi smart plug," International Journal of Smart Home, vol. 9, no. 6, pp. 173-182, 2015 Non-Patent Document 2: A. H. Cheetham and J. E. Hazel, "Binary (presence-absence) similarity coefficients," Journal of Paleontology, pp. 1130-1136, 1969.

An object of the present invention is to provide a context-aware standby power reduction scheme (CASPRE) capable of reducing the total standby power of a home appliance by controlling a smart plug through context inference.

Another object of the present invention is to optimize and use a correlation existing between devices when performing a specific task in a home, to allow an in-progress task to be deduced from the context of several devices, And to provide a context-aware standby power saving device capable of turning off non-involved devices.

According to an aspect of the present invention, there is provided a method of controlling an electronic device, the method comprising: determining an operation state of each electronic device based on a current power consumption level of the electronic devices consuming power; Determining a correlation between the electronic devices based on an operating state of the two or more electronic devices; Inferring a current work in progress based on the correlation and the operating context of the electronic devices; And turning off the electronic devices other than the electronic devices participating in the inferred ongoing task to block the standby power. Wherein the determining the operating state of the electronic devices comprises: detecting a current power consumption level of the electronic devices; Comparing the detected power consumption level with a threshold; And determining the operating state of the electronic devices as one of an operating state, a standby state, and a turn-off state according to a result of the comparison of the power consumption level and the threshold value. Wherein the step of determining a correlation between the electronic devices comprises the steps of: collecting power consumption data of the electronic devices; Analyzing the collected power consumption data with respect to time to give a high similarity coefficient to electronic devices operating simultaneously; And determining a correlation between the electronic devices based on the similarity coefficient. Wherein inferring the current ongoing task comprises: receiving in a knowledge repository an ontology and a set of rules associated with the operation of the electronic devices; Applying the received ontology and rule set to the electronic devices having a high correlation; And deducing the ongoing work performed by the electronic devices based on the results of applying the ontology and the rule set. The ontology and the rule set may include the operating state and environment data of the electronic devices, and may be updated according to the operating state of the electronic devices. Further, in the context-based standby power saving method according to the present invention, the current power consumption level of the electronic devices is measured through the smart plug to which the electronic devices are connected, and the step of blocking the standby power is performed by the smart plug .

According to another aspect of the present invention, there is provided a power analyzer comprising: a power analyzer for determining an operation state of each electronic device based on a current power consumption level of power consuming electronic devices; A context manager that determines a correlation between the electronic devices based on an operating state of the two or more electronic devices and deduces an ongoing task based on the correlation and the operation context of the electronic devices; And a central control unit for turning off the electronic devices other than the electronic devices participating in the inferred ongoing task to cut off the standby power. The power analysis unit may be configured to: detect a current power consumption level of the electronic devices, compare the detected power consumption level with a threshold value, and determine an operation state of the electronic devices based on a comparison result of the power consumption level and a threshold value, , A standby state, and a turn-off state. Wherein the context manager collects power consumption data of the electronic devices, analyzes the collected power consumption data with respect to time, and assigns high similarity coefficients to simultaneously operated electronic devices, and based on the similarity coefficient, And to determine a correlation between the devices. The context-based standby power saving apparatus according to the present invention further includes an information repository for storing an ontology and a set of rules related to the operation of the electronic devices, wherein the context manager receives the ontology and a rule set from the knowledge repository , Applying the received ontology and rule set to the electronic devices having a high correlation and further inferring the ongoing work performed by the electronic devices based on the result of applying the ontology and the rule set . The ontology and the rule set may include the operating state and environment data of the electronic devices, and may be updated according to the operating state of the electronic devices. The current power consumption level of the electronic devices is measured through the smart plug to which the electronic devices are connected, and the central control unit interrupts the standby power through the smart plug.

According to the context-based standby power saving method of the present invention, since the smart plug is controlled through context inference, the total standby power of the home appliance can be reduced, so that the standby power saving effect is excellent.

In addition, according to the context-based standby power saving apparatus of the present invention, since the ontology and the rule set can be updated by actively reflecting the operation context in which the electronic devices operate, the standby power can be adaptively reduced according to the context change .

1 is a flow chart schematically illustrating a context-based standby power saving method according to an aspect of the present invention.
2 is a block diagram schematically illustrating an environment in which a context-based standby power saving device according to another aspect of the present invention operates.
FIG. 3 is a graph illustrating usage patterns of electronic devices provided to facilitate understanding of the present invention.
4 is a diagram illustrating the correlation between electronic devices determined by the present invention.
5 is a diagram illustrating an example of an ontology used to determine an ongoing task in the present invention.
6 is a graph showing an energy saving effect of applying the present invention to an existing data set.
7 is a graph showing the energy saving effect of the present invention applied to an actual test environment.

In order to fully understand the present invention, operational advantages of the present invention, and objects achieved by the practice of the present invention, reference should be made to the accompanying drawings and the accompanying drawings which illustrate preferred embodiments of the present invention.

Hereinafter, the present invention will be described in detail with reference to the preferred embodiments of the present invention with reference to the accompanying drawings. However, the present invention can be implemented in various different forms, and is not limited to the embodiments described. In order to clearly describe the present invention, parts that are not related to the description are omitted, and the same reference numerals in the drawings denote the same members.

Hereinafter, the present invention will be described in more detail with reference to Fig.

1 is a flow chart schematically illustrating a method of reducing context-based standby power according to an aspect of the present invention.

The present invention proposes a context-based standby power saving method (CASPRE), which can reduce the standby power of a home appliance through work inference.

Referring to FIG. 1, first, an operation state of each electronic device is determined based on a current power consumption level of electronic devices consuming power (S110). The operation state indicates whether the electronic device is in the standby mode, is turned off and is not consuming power, or is in a normal operation according to the application.

Once the operating state is determined, a correlation between the electronic devices is determined based on the operating state of the two or more electronic devices (S130). In this case, the correlation is determined between the devices in terms of job execution. That is, by analyzing the usage pattern data of the home appliance, it finds the devices that the user operates to perform a specific task. The technique for determining the correlation will be described in detail later using FIG. 2 and FIG.

If the correlation of the electronic devices is determined as described above, the context-based standby power saving method according to the present invention deduces the current work based on the correlation and the operation context of the electronic devices (S150). To infer ongoing work, a set of rules is used that infer an ongoing work based on other context context definitions, such as the user's presence and time, along with the ontology of the work. Techniques for inferring work in progress will be described in detail later.

When the work in progress is determined in this way, the devices having high correlation are switched on from the standby state to the turn-off state to save standby power (S170), instead of turning on the devices until the end of the corresponding operation. That is, the context-based standby power saving method (CASPRE) according to the present invention saves energy by sending a power-off control message to a smart plug of a device not participating in the current operation.

2 is a block diagram that schematically illustrates an environment 200 in which the context-based standby power saving device 280 operates according to another aspect of the present invention.

The context-based standby power saving device 280 of FIG. 2 includes a smart plug 210, a power analysis unit 230, a context manager 240, a central control unit 250, a knowledge repository 260, . The context-based standby power saving device 280 operates in an operating environment 200 that includes electronic devices 201, 203, 205, 209 and an external sensor 290.

In order to reduce standby power, the state of each electronic device (201, 203, 205, 209) must be determined and integrated to deduce the operation. It is necessary to know the current state of each device such as whether it is in a standby state or in operation.

Experiments have shown that standby power consumption varies greatly depending on the state of the device. This power consumption is illustrated in Table 1.

The power analysis unit 230 analyzes the power level of the device to understand that the operation state of the device is changed. That is, the power analysis unit 230 analyzes the state of the target device based on the power consumption data. In this way, the state of the device can be obtained by analyzing the power consumption level. For example, the operating state of the device can be obtained using the following equation:

From here,

to be.

In Equations (1) and (2), w _current is an exponential moving average and w _avg is an exponential moving average. Given the current level of power consumption, an exponential moving average is calculated using the average of any coefficient α and the previously calculated power consumption level avg (w _prev ) . The exponential moving average is used to minimize the effects of noise that was incorrectly monitored by the smart plug. The threshold is selected on a per device basis to determine which device is in operation or standby.

When the operation states of the electronic devices 201, 203, 205, and 209 are determined, the context manager 240 analyzes the context in which the various electronic devices operate, and determines the work in progress.

For convenience of description, reference is made to Fig. 3, which illustrates a usage pattern of electronic devices.

FIG. 3 is a graph illustrating usage patterns of electronic devices provided to facilitate understanding of the present invention.

Figure 3 shows device usage patterns over a 72 hour period in a typical home. It can be seen from FIG. 3 that the TV and the subwoofer living room are often operated together but are not related to the operation of an electric kettle and a kitchen radio (KitchenRadio). Likewise, we can see that the use time of the equipment also varies with the case. For example, a TV turns on every evening, but the time of its operation is very different from day to day. Referring to FIG. 2, it can be seen that the operation time of the living room audio is short when the operation time of the TV is short, which indicates that the TV and the living room audio have a very high correlation. Once an ongoing task is identified, devices that do not participate in this task can be turned off to reduce standby power.

Context manager 240 may, in addition to the context of other devices, utilize context information for the surrounding context generated from smart devices, such as sensors and actuators in the home, to the fullest extent. For example, a presence sensor installed on the ceiling of a door can recognize that the user is returning home, and a sound / light sensor can also detect the surrounding situation. In this way, it is possible to make an optimal decision to control the power of the device when using the context information for the context, such as the user's status, visibility, date, etc., as well as the operational status of other devices.

In the context referenced by the context manager 240, the tasks determined when the attributes of the various home environments are changed may also be varied. Therefore, there is a need for a method for expressing the work resiliently and efficiently. To this end, the context-based standby power saving method according to the present invention utilizes an ontology and a business rule engine to represent and infer work in progress. The ontology and the rule set are preferably stored in the knowledge repository 260 and managed systematically. That is, the ontology can be updated individually to reflect the various contexts that can be obtained from the associated devices and the surrounding context. Rule sets can also be freely replaced with new rule sets.

The context manager 240 is responsible for managing all the context information from various devices. To this end, the context manager 240 loads the ontology and rule set from the knowledge repository 260. As new knowledge is added, it is as described above that the context manager triggers the rule engine and executes the compiled rules so that new ontology work can be inferred.

Further, in addition to triggering the rule engine, the context manager 240 is responsible for updating and managing conventional knowledge. For example, when the TV is turned on, a context information triple pair (TV, hasState, "on") will be added to the context manager. When the TV enters standby mode, the context manager 240 removes this triple pair and adds a new triple pair (TV, hasState, "Standby").

In the present context, context information includes personal static context information such as a user's health status, identity information, hobbies, preferences and the like using the user terminal and dynamic context information about how well the current user follows the provided content. do. In addition, the context information may include static context information related to individual personality and characteristics, information obtained in real time from the status of the user connected to the home network system, and dynamic context information indicating past history data context information. In general, context information refers to information that defines characteristics of a context, such as a person, a place, an object, an object, and a time, which affect interaction between a user and another user, a system, or a device in association with ubiquitous computing. More specifically, the present invention relates to a method and apparatus for controlling a network connection state, a communication bandwidth, and a computing context such as a printer, a display, and a workstation, a user context including a user's profile, Environmental context such as traffic condition, temperature, time context such as time, week, month, and season are all included in the context information. Such context information may be used for reasoning that the system can be grasped and gathered through various sensing devices and applications and used for providing various application services or tied with other context information to obtain a third conclusion.

As described above, the context-based standby power saving method according to the present invention reduces standby power of a home appliance by controlling the smart plug based on a rule set defined for a specific ontology task.

The knowledge repository 260 used in the context-based standby power saving device (CASPRE) according to the present invention comprises an ontology and a rule set. An ontology is used to express a specific task in terms of the correlation between devices. As described above, it is very important to identify electronic devices belonging to the same task, since highly correlated devices have a tendency to be used together, but low correlation devices may not be used together. To compute this important correlation, A. H. Cheetham and J. E. Hazel, "Binary (presence-absence) similarity coefficients," Journal of Paleontology, pp. 1130-1136, 1969. [hereinafter, "Non-Patent Document 2"] can be used. The similarity coefficient is selected by this technique. However, it is needless to say that the present invention is not limited to the above-mentioned documents, and all prior arts disclosed before the present application can be used to select the similarity coefficient.

Figure 4 shows the results of calculating the similarity coefficient for the operating conditions of each device based on the device usage data collected at the test site during one week. As shown in FIG. 4, there is a high similarity coefficient between the TV and the game console (GameConsole), which indicates that they will be operated simultaneously. On the other hand, the similarity between the TV and the dehumidifier is low, indicating that they are likely to work individually.

Devices with high correlations can be grouped to form a single task. For example, TVs and game consoles can be grouped together to perform a 'video game' task, since they have a high similarity coefficient. This relationship between a task and a device is represented in Figure 5 by an ontology.

5 is a diagram illustrating an example of an ontology used to determine an ongoing task in the present invention.

An ontology is used because it can represent things that constitute tasks in various contexts with high fidelity. An ontology can be defined as a formal and explicit specification of shared conceptualization. Often, an ontology can be thought of as a kind of dictionary composed of words and relations, in which words related to a specific domain are hierarchically represented and additionally includes inference rules that can be expanded to include a web-based knowledge processing And knowledge sharing and reuse among application programs. Ontology is the most central concept of semantic web application. Ontology language is a language that defines schema and syntax structure to represent it. Currently, there are DSML + OIL, OWL, Ontolingun and so on. That is, ontologies are used to support common semantic understanding and interoperability between different meanings. And, ontology matching technology is a technology that must be accompanied by inevitably creating an ontology because the semantic web has characteristics of a heterogeneous distributed environment like the web. The generated ontology itself also includes heterogeneous environments. Therefore, the ontology matching method is proceeding in a way to discover the semantic relation between different ontologies.

As described above, in addition to the operating states of the electronic devices 201, 203, 205, and 209, environmental contexts such as whether a user is present, the current time is at what time, May be included in configuring the task. In order to integrate the context-based standby power saving method according to the present invention into a home in which a smart environment has been established without any problems, it is advantageous to express the task as an ontology. For example, 'playing video games' can be supported not only by the operating status of TVs and game machines, but also by the context in which there is a user created by a room sensor installed on the porch.

A set of rules is defined to deduce an action in progress from a collection of contextual information. These rules define the conditions that can be used to determine what the current work is. For example, to deduce that a 'playing video game' is in progress, you must first find out that you have a user, and that devices such as TVs and gaming devices are running. These rules can be expressed as follows.

(? user rdf: type caspre: User)

? (user caspre: locatedIn caspre: Lounge)

? (caspre: TV caspre: hasState caspre: "On")

? (caspre: PlayingVideoGame caspre: supportedBy caspre: TV)

? (caspre: GameConsole caspre: hasState "On")

? (caspre: PlayingVideoGame caspre: supportedBy caspre: GameConsole) -> (caspre: Lounge caspre: ongoingTaskIs caspre: PlayingVideoGame)

Once an ongoing task is inferred, devices that do not participate in this task can now be turned off. For example, microwave ovens and fans can be turned off completely, not in standby while the 'playing video game' operation is in progress. Accordingly, the power analysis unit 230 cuts off the power of the electronic devices 201, 203, 205, and 209 that are not participating in the ongoing work under the control of the central control unit 250. [

If the operating state of a device supporting a work in progress changes, this means that the work in progress is changed. That is, since an ongoing work condition is no longer satisfied, a new work can be determined from these facts.

Ontologies and rule sets can be created experimentally. However, ontologies and rule sets may be created by various techniques such as conditional probability techniques.

The communication unit 270 plays a role of transmitting and receiving context information to other smart devices. The communication unit 270 may implement various protocols to communicate with various devices used in the home. By default, the context-based standby power saving technique (CASPRE) can utilize known messaging patterns. The adoption of this messaging pattern leads to flexibility and scalability. If the message relaying service is running in a particular smart home environment, the context-based standby power saving method (CASPRE) may participate in the existing network as a messaging client. Otherwise, the communication unit 270 can serve as a separate message relay service.

The context-based standby power saving method (CASPRE) may refer to events from the smart plug 210 to accumulate context to infer certain ontology operations, as described above. Upon receiving an event from the smart plug 210, the context information of the corresponding device is generated by the power analysis unit. The context information is then passed to the context manager to update the collection of context information. At this time, it is checked whether the conditions for reasoning the ontology work are satisfied by referring to the conditions according to the rule engine. If an ongoing task is identified, the context-based standby power saving device 280 sends an event message to control the smart plug 210. The topic-based generation-driven messaging pattern is utilized to maximize the exchange of context information. At this time, the central control unit 250 may generate a control event message including a list of names of devices to be turned off and configured with a topic (e.g., "off"). When this control message is received, the smart plug 210 turns off the corresponding devices.

In order to verify the effect of the context-based standby power saving device 280 as described above, the experimental results of applying this technique to the data set and the experimental site were actually compared with the existing methods.

- Experiments on real data sets

The data set includes device level power data for homes in London. In the verification experiment, data were selected for the 19 instruments used in the two homes. Home 1 contains 10 devices, while Home 2 contains 9 devices. The usage patterns of the devices were evaluated over 92 days.

6 and Table 2 show the experimental results of the comparative analysis.

The result of comparing the conventional technique using only the behavioral model with the context-based standby power saving device 280 according to the present invention is shown in FIG. Figure 6 shows the total amount of energy that can be saved for each device. As a result of comparison, it has been found that the technique of the present invention is more efficient than conventional techniques for almost all devices. In the case of KitchenLights, the conventional technique yielded slightly better results, but this is because kitchens and the like are used independently with less relevance to other devices, It is expected that the saving effect of the technique can also be improved.

Thus, overall, the context-based standby power saving method (CASPRE) shows better performance than the prior art in total air energy consumption. The average standby power consumed during the experimental period of the data set is reduced by 73.29% for Assumption 1 and 92.09% for Assumption 2. Compared to the prior art, the average standby power consumption is reduced by 40.69% to 83.72% per household.

- Application experiment on test bed

7 is a graph showing the energy saving effect of the present invention applied to an actual test environment.

In the experiment of FIG. 7, six household appliances of Table 1 were selected.

FIG. 7 shows the average amount of standby power consumed by each device before and after applying the context-based standby power saving method (CASPRE). Before applying, the average standby power consumption was 232.20 watts, and after applying the context-based standby power saving method (CASPRE), the consumption was reduced to 98.23 watts, resulting in a savings of 57.70%.

In the present invention, it is very important to create a rule set corresponding to creating an ontology of a task and a device, in order to reduce standby power. Because it dynamically changes to a smart home environment, these ontologies and rule sets also change flexibly.

As described above, according to the context-based standby power saving method of the present invention, since the total standby power of the home appliance can be reduced by controlling the smart plug through context inference, the standby power saving effect is excellent.

According to the context-aware standby power saving apparatus of the present invention, since the ontology and the rule set can be updated by actively reflecting the operation context in which the electronic devices operate, the standby power can be adaptively reduced according to the context change .

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is evident that many alternatives, modifications and variations will be apparent to those skilled in the art. For example, it is evident that an ontology stored in the knowledge repository 260 can be created using all of the conventional techniques not described herein.

In addition, the method according to the present invention can be embodied as computer-readable code on a computer-readable recording medium. A computer-readable recording medium may include any type of recording device that stores data that can be read by a computer system. Examples of the computer-readable recording medium include a ROM, a RAM, a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like, and may be implemented in the form of a carrier wave (for example, transmission via the Internet) . The computer readable recording medium may also store computer readable code that may be executed in a distributed manner by a distributed computer system connected to the network.

As used herein, the singular " include " should be understood to include a plurality of representations unless the context clearly dictates otherwise, and the terms "comprises & , Parts or combinations thereof, and does not preclude the presence or addition of one or more other features, integers, steps, components, components, or combinations thereof. The terms "part", "unit", "module", "block", and the like described in the specification mean units for processing at least one function or operation, And a combination of software.

Therefore, it should be understood that the present invention and the drawings attached hereto are only a part of the technical idea included in the present invention, and that those skilled in the art will readily understand the technical ideas included in the specification and drawings of the present invention It is obvious that all the variations and concrete examples that can be deduced are included in the scope of the present invention.

The present invention can be applied to effectively reduce standby power of electronic devices.

Claims (12)

As a standby power saving method,
Determining an operating state of each electronic device based on a current power consumption level of the electronic devices consuming power;
Determining a correlation between the electronic devices based on an operating state of the two or more electronic devices;
Inferring a current work in progress based on the correlation and the operating context of the electronic devices; And
And turning off the electronic devices other than the electronic device participating in the inferred ongoing task to interrupt the standby power,
Wherein the step of inferring the current ongoing task comprises:
Receiving an ontology and a set of rules associated with the operation of the electronic devices in a knowledge repository;
Applying the received ontology and rule set to the electronic devices having a high correlation; And
Based on the result of applying the ontology and the rule set, deducing the ongoing work performed by the electronic devices. The method according to claim 1,
Wherein the step of determining an operating state of the electronic devices comprises:
Detecting a current power consumption level of the electronic devices;
Comparing the detected power consumption level with a threshold; And
And determining a state of operation of the electronic devices as one of an operation state, a standby state, and a turn-off state in accordance with a result of comparison between the power consumption level and the threshold value. . 3. The method of claim 2,
Wherein the step of determining a correlation between the electronic devices comprises:
Collecting power consumption data of the electronic devices;
Analyzing the collected power consumption data with respect to time to give a high similarity coefficient to electronic devices operating simultaneously; And
And determining a correlation between the electronic devices based on the similarity coefficient. ≪ Desc / Clms Page number 19 > delete The method according to claim 1,
Wherein the ontology and the rule set comprise operating state and ambient data of the electronic devices and are updated according to an operating state of the electronic devices. The method according to claim 1,
Wherein a current power consumption level of the electronic devices is measured through a smart plug to which the electronic devices are connected,
Wherein the step of blocking the standby power is performed by the smart plug. As a standby power saving device,
A power analyzer for determining an operating state of each electronic device based on a current power consumption level of the electronic devices consuming power;
A context manager that determines a correlation between the electronic devices based on an operating state of the two or more electronic devices and deduces an ongoing task based on the correlation and the operation context of the electronic devices;
A central control unit for turning off the electronic devices other than the electronic devices participating in the inferred ongoing work to interrupt the standby power; And
A knowledge repository for storing an ontology and a set of rules associated with the operation of the electronic devices,
The context manager
Receiving the ontology and a set of rules from the knowledge repository,
Applying the received ontology and rule set to the electronic devices having a high correlation,
Based on the result of applying the ontology and the rule set, deduces the ongoing work performed by the electronic devices. 8. The method of claim 7,
The power analysis unit includes:
Detecting a current power consumption level of the electronic devices,
Compares the detected power consumption level with a threshold value,
Based on the comparison result of the power consumption level and the threshold value, the operation state of the electronic devices as one of an operation state, a standby state, and a turn-off state. 9. The method of claim 8,
The context manager comprising:
Collecting power consumption data of the electronic devices,
Analyzing the collected power consumption data with respect to time, giving a high similarity coefficient to electronic devices operating at the same time,
And to determine a correlation between the electronic devices based on the similarity coefficient. delete 10. The method of claim 9,
Wherein the ontology and the rule set include an operating state and environment data of the electronic devices and are updated according to an operating state of the electronic devices. 8. The method of claim 7,
Wherein a current power consumption level of the electronic devices is measured through a smart plug to which the electronic devices are connected,
Wherein the central control unit cuts off the standby power through the smart plug.

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