CN113412609A - Equipment control method, device, server and storage medium - Google Patents

Equipment control method, device, server and storage medium Download PDF

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Publication number
CN113412609A
CN113412609A CN201980091634.3A CN201980091634A CN113412609A CN 113412609 A CN113412609 A CN 113412609A CN 201980091634 A CN201980091634 A CN 201980091634A CN 113412609 A CN113412609 A CN 113412609A
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data
equipment
household equipment
condition data
control
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CN113412609B (en
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范作
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Guangdong Oppo Mobile Telecommunications Corp Ltd
Shenzhen Huantai Technology Co Ltd
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Guangdong Oppo Mobile Telecommunications Corp Ltd
Shenzhen Huantai Technology Co Ltd
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B15/00—Systems controlled by a computer
    • G05B15/02—Systems controlled by a computer electric
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

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  • General Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Telephonic Communication Services (AREA)
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Abstract

The application discloses a device control method, a device, a server and a storage medium, wherein the device control method comprises the following steps: acquiring current condition data, wherein the current condition data is used for controlling first household equipment; when the current condition data meet a set control trigger condition, calling a trained training model, wherein the training model is obtained by training according to historical condition data and equipment data of the first household equipment when the first household equipment is executed and operated, the historical condition data at least comprises personal data of a user, environment data and state data of second household equipment, and the equipment data at least comprises a control instruction for the first household equipment; inputting the current condition data into the training model to obtain a control instruction for the first household equipment; and controlling the first household equipment according to the control instruction. The method can improve the intelligent degree of the control of the household equipment.

Description

Equipment control method, device, server and storage medium Technical Field
The present application relates to the field of smart home technologies, and in particular, to a device control method, apparatus, server, and storage medium.
Background
With the continuous development of science and technology and the continuous improvement of people's standard of living, intelligent house gradually gets into people's the field of vision. At present, for controlling home devices (such as an intelligent air conditioner, an intelligent television, and the like) in an intelligent home system, a user generally controls the home devices manually on site, or remotely controls the home devices through a mobile terminal.
Disclosure of Invention
In view of the above problems, the present application provides an apparatus control method, an apparatus, an electronic device, and a storage medium, so as to improve the intelligent degree of home device control.
In a first aspect, an embodiment of the present application provides an apparatus control method, where the method includes: acquiring current condition data, wherein the current condition data is used for controlling first household equipment; when the current condition data meet a set triggering condition, calling a trained training model, wherein the training model is obtained by training according to historical condition data and equipment data of the first household equipment when the first household equipment is executed and operated, the condition data at least comprise personal data of a user, environment data and state data of second household equipment, and the equipment data at least comprise a control instruction for the first household equipment; inputting the current condition data into the training model to obtain a control instruction for the first household equipment; and controlling the first household equipment according to the control instruction.
In a second aspect, an embodiment of the present application provides an apparatus for controlling a device, where the apparatus includes: the system comprises a data acquisition module, a model acquisition module, an instruction acquisition module and a control execution module, wherein the data acquisition module is used for acquiring current condition data, and the current condition data is used for controlling first household equipment; the model acquisition module is used for calling a trained training model when the current condition data meet a set triggering condition, the training model is obtained by training according to historical condition data and equipment data when the first household equipment is executed and operated, the condition data at least comprises personal data of a user, environment data and state data of second household equipment, and the equipment data at least comprises a control instruction for the first household equipment; the instruction acquisition module is used for inputting the current condition data into the training model to obtain a control instruction of the first household equipment; the control execution module is used for controlling the first household equipment according to the control instruction.
In a third aspect, an embodiment of the present application provides a server, including: one or more processors; a memory; one or more application programs, wherein the one or more application programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs configured to perform the device control method provided by the first aspect above.
In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, where a program code is stored in the computer-readable storage medium, and the program code may be called by a processor to execute the apparatus control method provided in the first aspect.
According to the scheme provided by the application, the current condition data for controlling the first household equipment is obtained, when the current condition data meets the set control trigger condition, the training model obtained according to the historical condition data and the equipment data training when the first household equipment is operated is called, the historical condition data comprises the personal data, the environment data and the state data of the second household equipment of a user, the equipment data comprises a control instruction for the first household equipment, then the current condition data is input into the training model to obtain the control instruction for the first household equipment, the first household equipment is controlled according to the control instruction, so that the operation instruction for the household equipment is predicted according to the historical operation of the household equipment by the user, the automatic control for the household equipment is realized, the intelligent degree of the household equipment control is improved, and the relevance with the user is high, the user requirements are met, and the user experience is improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 shows a schematic diagram of an application scenario proposed in an embodiment of the present application.
Fig. 2 shows another schematic view of an application scenario proposed in the embodiment of the present application.
FIG. 3 shows a flow chart of a device control method according to one embodiment of the present application.
Fig. 4 shows a flow chart of a device control method according to another embodiment of the present application.
Fig. 5 shows a flow chart of a device control method according to yet another embodiment of the present application.
FIG. 6 shows a block diagram of a device control apparatus according to an embodiment of the present application.
Fig. 7 is a block diagram of an electronic device according to an embodiment of the present application, configured to execute a device control method according to an embodiment of the present application.
Fig. 8 is a storage unit for storing or carrying a program code implementing an apparatus control method according to an embodiment of the present application.
Detailed Description
In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application.
With the progress of the technology level, the smart home goes deep into each family, and is popular among multiple families due to the convenience brought by the smart home. The intelligent home is characterized in that a home is taken as a platform, facilities related to home life are integrated by utilizing a comprehensive wiring technology, a network communication technology, a safety precaution technology, an automatic control technology and an audio and video technology, an efficient management system of home facilities and family schedule affairs is constructed, home safety, convenience, comfortableness and artistry are improved, and an environment-friendly and energy-saving living environment is realized. The intelligent home is connected with various home devices (such as an intelligent air conditioner, an intelligent lamp, an intelligent refrigerator, an intelligent washing machine and the like) in a home through the Internet of things technology, and various controls such as household appliance control, illumination control, telephone remote control, indoor and outdoor remote control, anti-theft alarm, environment monitoring, heating and ventilation control, infrared forwarding, programmable timing control and the like are provided.
In an intelligent home system, a traditional control method for home devices is mostly to perform control on the home devices on site manually by a user, or perform remote control on the home devices through a visual interface on a mobile terminal (e.g., a mobile phone, a tablet, etc.), or perform delay control, or perform control by using a set scene, and certainly, a language control method is also used to perform control on the home devices.
Through long-term research of the inventor, the control modes of the household equipment are numerous, but the user is still required to participate in the control process of the household equipment, the intelligent degree of the household equipment control is not high, and the user experience is not high. In view of the above problems, the inventor proposes a device control method, an apparatus, an electronic device, and a storage medium provided in this embodiment of the present application, where the current condition data is obtained and used to control a first home device, and when the current condition data satisfies a set control trigger condition, a training model obtained according to historical condition data of the first home device when being operated and device data training is called, and then the current condition data is input to the training model to obtain a control instruction for the first home device, and the first home device is controlled according to the control instruction, so as to predict an operation instruction for the home device according to historical operation of a user on the home device, thereby implementing automatic control on the home device, improving the intelligent degree of control of the home device, and having high correlation with the user, and meeting user requirements, the user experience is improved.
An application scenario of the embodiment of the present application is described below with reference to the drawings.
Referring to fig. 1, a schematic diagram of an application scenario of the device control method provided in the embodiment of the present application is shown, where the application scenario includes an intelligent home system, and the intelligent home system may include a server 100, a home device 200, a gateway device 300, and a mobile terminal 400. The gateway device 300 and the mobile terminal 400 may be in communication connection with the server 100, and the home device 200 establishes wireless connection with the gateway device 300, so that the mobile terminal 400 may perform data interaction with the home device 100 through the server 100 and the gateway device 300. Of course, the mobile terminal 400 may also establish a wireless connection with the gateway device 300 to implement data interaction between the mobile terminal 400 and the home device 200.
Referring to fig. 2, another schematic diagram of an application scenario of the device control method provided in the embodiment of the present application is shown, where the smart home system in the application scenario includes a first cloud server 101, a second cloud server 102, a home device 200, a gateway device 300, and a mobile terminal 400. The mobile terminal 400 may be in communication connection with the first cloud server 101, so as to implement data interaction with the first cloud server 101. The home device 200 is in communication connection with the second cloud server 102 through the gateway device 300, so that data interaction between the second cloud server and the second cloud server 102 is realized. In addition, data interaction can be performed between the first cloud server 101 and the second cloud server 102, so that the mobile terminal 400 can implement data interaction with the home equipment 200 through the first cloud server 101, the second cloud server 102 and the gateway device 300.
The following describes the apparatus control method according to the embodiment of the present application in detail.
Referring to fig. 3, an embodiment of the present application provides an apparatus control method, which is applicable to a server, and the apparatus control method may include:
step S110: and acquiring current condition data, wherein the current condition data is used for controlling the household equipment.
In the embodiment of the application, the server may obtain current condition data, and the current condition data is used for controlling the first home equipment. The current condition data is used by the server to input into the setting model so as to obtain data for predicting the control instruction of the user to the first household equipment.
In some embodiments, the current condition data may include personal data of the user, environmental data, status data of the second home device, and the like. The personal data may be information data of the user, and may include current status, sex, taste, temperament, academic calendar, body data of the user, and the like. The current state of the user can be whether the user is working, the mental state of the user, the mood state of the user and the like. Of course, the above-described personal data are merely examples. The environment data may be data of an environment in which the user and/or the first home device is located, for example, the environment data may include location data, time data, weather data, a situation of a person in the home, and the like. The second home device may be another home device, and the state data of the second home device may be data representing a current state of the second home device, for example, whether the second home device is in a working state, a working parameter, and the like. Of course, the specific current condition data may not be limited in this embodiment, and for example, the current condition data may also include an instruction sent by the user through the mobile terminal.
In some embodiments, the server may obtain the current condition data from the mobile terminal of the user, the environment collecting device, the first home device, the second home device, and other servers. The server may communicate with a mobile terminal of a user, the mobile terminal may send the collected condition data to the server, the condition data collected by the mobile terminal may include a located user position, a user state analyzed according to a collected user image, and the like, and the condition data collected by the mobile terminal may not be limited. The environment acquisition device can be the environment acquisition device (for example, camera, various sensors in the family, etc.) in the environment that first house equipment is located, and the server can obtain the environmental data that the environment acquisition device gathered from the environment acquisition device. The server can obtain the detected state data from the first household equipment and the second household equipment. The server may obtain corresponding data in the current condition data from other servers (e.g., third party servers), for example, weather data may be obtained from a server for weather prediction, and a current taste of the user, a current favorite eating time, and the like may also be obtained from a server of the food and drink service. Of course, the way in which the server specifically acquires the current condition data may not be limiting.
In some embodiments, the server may obtain the current condition data for controlling the first home device in real time, or may obtain the current condition data every set time length, where the time length of the interval for obtaining the current condition data may not be limited.
Step S120: and calling a trained training model when the current condition data meets a set triggering condition, wherein the training model is obtained by training according to historical condition data and equipment data of the first household equipment during operation, the condition data at least comprises personal data of a user, environment data and state data of second household equipment, and the equipment data at least comprises a control instruction for the first household equipment.
In the embodiment of the application, after the current condition data for controlling the first household device is acquired, the server may determine whether the current condition data meets a set trigger condition, so as to determine whether to predict a control instruction for controlling the first household device by the user according to the current condition data.
In some embodiments, the server may determine whether data of a setting type in the current condition data coincides with setting data corresponding to the setting type. As an embodiment, the server may obtain data of a setting type in the current condition data and setting data corresponding to the setting type, and then determine whether the data of the setting type is consistent with the setting data, specifically, determine whether fields, byte lengths, byte sizes, and the like of the two data are consistent. For example, it may be determined whether time data in the current condition data is set time data to determine whether the current condition data satisfies the set trigger condition. If the data of the setting type in the current condition data is judged to be consistent with the setting data corresponding to the setting type, the current condition data can be determined to meet the set triggering condition, and if the data of the setting type in the current condition data is judged to be inconsistent with the setting data corresponding to the setting type, the current condition data can be determined to meet the set triggering condition. Of course, the specific setting data is not limited, and the setting data may be a single value, a numerical range including a plurality of values, or the like.
In this embodiment of the application, the trigger condition may be a trigger condition for predicting that the user will operate the smart device, and if the current condition data satisfies the set trigger condition, it may indicate that the user will operate the smart device, and if the current condition data does not satisfy the set trigger condition, it may indicate that the user will not operate the smart device.
Therefore, when the current condition data meet the set triggering condition, the trained training model can be obtained, so that the control instruction of the user for controlling the first household equipment can be predicted according to the current condition data. The trained training model can be stored in a server, and the server can read and call the training model when needing to calculate a control instruction according to the current condition data.
In some embodiments, the trained training model may be trained according to historical condition data of the first household device when the first household device is operated and the device data. The historical condition data may include at least personal data of the user, environmental data, and status data of the second home device, and the device data may include at least control instructions for the first home device. That is, the historical condition data and the current condition data have the same data content, so that the training model can calculate the control command according with the control habit of the first home device except the user according to the current condition data.
Wherein the historical condition data corresponds to the device data. Each of the historical condition data may form a pair of data with each of the device data, the historical condition data being input data to the initial model for training, and the device data being output data to the initial model for training. Therefore, a data set for model training can be constructed according to historical condition data and equipment data of the past user in the control operation of the first household equipment.
In some embodiments, the personal data in the historical condition data may include current status, taste, temperament, academic calendar, physical data of the user, and the like. The environment data may be data of an environment in which the mobile terminal of the user and/or the first home device is located, the environment data may include location data, time data, weather data, and the like, the location data may be specific to a location where the user is frequently located, for example, a location of a home, a location of a work, and the like, and the time data may be specific to a date, a time point, a holiday, and the like, so that a work and rest habit of the user may be reflected. The state data of the other first household devices may be data representing the current state of the second household device, for example, whether the second household device is in a working state, working parameters, and the like. Of course, the specific current condition data and the device data may not be limited in the embodiments of the present application. The device data may include device information, device status, and the like of the device, in addition to the control instruction for the first home device. The historical condition data can be acquired from the mobile terminal, the first household equipment, the second household equipment, the environment acquisition device and a server of a third party, so that the historical condition data which are personally related to a user, related to the environment and related to the second household equipment when the first household equipment is controlled can be acquired, a training model trained according to the historical condition data and the equipment data can better accord with the operation habit of the user, and the training model is more accurate.
Further, the obtained historical condition data may be quantized into an input vector corresponding to the initial model, and the device data may be quantized into an output vector corresponding to the initial model. And quantizing the data set into a vector set corresponding to the initial model, and inputting the vector set into the initial model for training to obtain a trained training model, namely a model for predicting a control instruction for controlling the first household equipment. The initial model may be a neural network model, such as a bp (back propagation) neural network model. Of course, the specific initial model may not be limited, for example, the initial model may also be a decision tree model, or may also be other neural network models.
Step S130: and inputting the current condition data into the training model to obtain a control instruction for the first household equipment.
After the server acquires the trained training model, the server may input the current condition data as input data to the training model, and the training model may calculate a control instruction corresponding to the current condition data, that is, a control instruction for controlling the first home equipment, according to the current condition data.
In some embodiments, when the current condition data is input to the training model, the current condition data may be quantized into a vector corresponding to the training model, that is, a vector that can be used for calculation of the training model, and then the vector corresponding to the current condition data is input to the training model, so as to calculate a control instruction for controlling the first household device.
Step S140: and controlling the first household equipment according to the control instruction.
In the embodiment of the application, after the server obtains the control instruction for controlling the first household device, the server can perform control matched with the control instruction on the first household device according to the control instruction, so that automatic control on the first household device is realized.
In some embodiments, the server may send the control instruction to the first home device through a network, for example, send the control instruction to a router in a network where the first home device is located through the network, the control instruction is forwarded to the gateway device by the router, the gateway device forwards the control instruction to the first home device, and finally the first home device performs a processing operation matched with the control instruction according to the control instruction, so as to control the first home device.
The equipment control method provided by the embodiment of the application obtains the current condition data, the current condition data is used for controlling the first household equipment, when the current condition data meets the set triggering condition, a training model trained according to the historical condition data and the equipment data is utilized to calculate a control instruction matched with the current condition data, then the first household equipment is controlled according to the control instruction, thereby realizing the calculation of the subsequent operation instruction of the user to the household equipment according to the historical data of the operation of the user to the household equipment, thereby realizing automatic control of the household equipment, improving the intelligent degree of the control of the household equipment, and the historical condition data is related to the user, the environment and other household equipment, therefore, the control instruction calculated by the training model accords with the operation habit of the user on the household equipment, meets the user requirement and improves the user experience.
Referring to fig. 4, another embodiment of the present application provides an apparatus control method, which is applicable to a server, and the apparatus control method may include:
step S210: acquiring historical condition data and device data when the first home device is operated, wherein the historical condition data corresponds to the device data.
In this embodiment, the server may obtain historical condition data and device data of the first home device when the first home device is operated, so as to train the initial model according to the historical condition data and the device data. The historical condition data corresponds to the equipment data, and in the multiple pieces of historical condition data and the multiple pieces of equipment data corresponding to the first household equipment, each piece of historical condition data corresponds to each piece of equipment data.
In some embodiments, the historical condition data includes at least personal data of the user, environmental data, and status data of the second home device. The personal data is data related to the user, and may include a physical state, a mood state, a height, a weight, a taste, an occupation, and the like of the user, and the specific personal data may not be limited, and the personal data is used for reflecting habits, preferences, and the like of the user. The environmental data may include time data, weather data, location data, air data, traffic data, etc., the environmental data relating to the environment in which the user is located and/or the environment in which the first household device is located. The second home device may be other home devices except the first home device, and the state data of the second home device may include an open state, a closed state, a working parameter, and the like of the second home device. The device data may at least include a control instruction corresponding to the current condition data, that is, a control instruction when the first home device is operated, and the state data may further include device information, parameters, types, and the like, so that training may be performed for different devices. Of course, the specific historical condition data and device data may not be limiting. In addition, the control instruction may be specific to control of a working parameter of the first household device, for example, the control instruction corresponding to the lamp may be specific to a light-emitting color, a light-emitting brightness, and the like, and the television may be specific to a playing channel, and the like, so that the training model for training may predict the control instruction for specifically controlling the first household device.
In some embodiments, the current condition data and the device data when the first home device is controlled may be obtained from a mobile terminal of the user, an environment acquisition device, the first home device, the second home device, and a server of a third-party platform. Of course, it may also be obtained from a local database. Therefore, data related to the user and the equipment can be acquired when the user controls the first household equipment every time, and the range and the types covered by the data are large, so that an accurate training model can be trained in the subsequent process.
In this embodiment of the application, after the current condition data and the device data are acquired, the server may further filter the historical condition data and the device data and classify the filtered historical condition data and the device data before the initial model is trained according to the current condition data and the device data.
In some embodiments, the server may screen valid data from the historical condition data and the device data according to a set screening rule to remove invalid data, so as to ensure correctness of the data, thereby improving accuracy of the trained training model. For example, the server may filter the number of times of controlling the first home devices, and if the number of times of controlling the first home devices in the same time period is less than the set number of times, it may be determined that the current condition data and the device data are invalid when the first home devices are controlled in the time period. Of course, the specific screening rules are not limited in the embodiments of the present application.
In some embodiments, when the server classifies the current condition data and the device data, the server may classify the current condition data and the device data according to devices and individuals, classify the personal data of the user and the environment data of the environment where the user is located into user-related data, and use the environment data of the environment where the first home device is located, the state data of the second home device, and the device data of the first home device as device-related data. For the data related to the device, the device type may also be divided, for example, into a household appliance class, a gateway class, a sensor class, a smart car class, and the like. Of course, the above classification is merely an example, and for example, a control command in the device data may be classified. By classifying the historical condition data and the equipment data, marking the current condition data and the equipment data according to the classified categories, and subsequently inputting the marked and classified data into the initial model for training, the training model can be more accurate.
Step S220: and inputting the historical condition data and the equipment data into an initial model, and training the initial model to obtain a trained training model.
In some embodiments, the server may construct the initial model, although the initial model may be pre-stored locally. When the initial model is trained, the historical condition data and the equipment data can be input into the initial model, and the initial model is trained. The current condition data and the equipment data are in one-to-one correspondence, the current condition data can be quantized into input vectors, the equipment data can be quantized into output vectors, and then the input vectors and the output vectors which are in one-to-one correspondence are input into the initial model for training to obtain a trained training model, namely a model for predicting a control instruction for controlling the first household equipment. In addition, after the trained training model is obtained, the accuracy of the trained training model can be verified, whether the output information of the trained target detection model based on the input data meets the preset requirement or not is judged, and if the output result of the trained training model based on the input data does not meet the set requirement, a data set formed by the current condition data and the equipment data can be obtained again to train the initial model, or the data set is obtained again to correct the trained training model, which is not limited herein.
In some embodiments, the initial model may be a neural network model or a decision tree model. For example, when the initial model is a neural network model, the neural network model may be trained based on an ssd algorithm, a fast-rcnn algorithm, a yolo algorithm, and the like, which is not described herein again.
Step S230: and acquiring current condition data for controlling the first household equipment.
In the embodiment of the present application, step S230 may refer to the contents of the above embodiments, and is not described herein again.
Step S240: when the current condition data meet a set triggering condition, a trained training model is obtained, the training model is obtained according to historical condition data and equipment data obtained when the first household equipment is executed to operate, the historical condition data at least comprise personal data of a user, environment data and state data of second household equipment, and the equipment data at least comprise a control instruction for the first household equipment.
In this embodiment of the present application, the set triggering condition may include: the time data is at least one of set time data, the position data is set position data, the weather data is set weather data, the second household equipment is in a set state, and the condition data comprises a trigger instruction input by a user.
It can be understood that the trigger condition is used as a trigger condition for determining that the user can operate the smart device, and if the current condition data meets the trigger condition, the current condition data needs to be input into the training model, and a control instruction corresponding to the current condition data is calculated to control the first home equipment. For example, in one scenario, a user usually leaves work at six points, and then the six points may trigger calculation of a control instruction for the smart car, so that the user may experience the in-car environment with the set parameters after getting on the car, and the set parameters correspond to the current condition data. For another example, in a scenario, if the current weather data is weather data corresponding to weather with strong illumination, the calculation of the control instruction for the intelligent window curtain may be triggered, so that the merging degree of the window curtain conforms to the condition corresponding to the current condition data and the control habit of the user. For another example, in one scenario, when the intelligent bathroom heater in the bathroom is turned on, the control instruction for the water heater may be triggered and calculated, so that the operating parameters of the water heater correspond to the current condition data, and the control habit of the user for the water heater is met. Of course, the above scenarios are merely examples.
The condition data includes a trigger instruction input by the user, and the trigger instruction may be input by the user through the mobile terminal, so that the server calculates a control instruction corresponding to the first home device corresponding to the trigger instruction, and subsequently controls the first home device according to the control instruction. When the user manually inputs the trigger instruction, the server may control the first home device according to the control instruction at a time point corresponding to the trigger instruction after calculating the control instruction. For example, the user can send a trigger instruction of "eat at six o ' clock tomorrow" to the server through the mobile terminal, and then the server can calculate a control instruction for the cooking robot according to the current condition data and control the cooking robot according to the control instruction at five o ' clock and half o ' clock tomorrow.
In some embodiments, the trigger conditions may also be used in combination, and may be specifically set according to different devices and scenarios. For example, when the simultaneous time data is the set time data, the position data is the set position data, the weather data is the set weather data, and the second home device is in the set state, it is determined that the current condition data satisfies the trigger condition.
When the current condition data are determined to meet the set triggering conditions, the trained training model can be obtained, and the control instruction for the first household equipment is calculated according to the current condition data.
Step S250: and inputting the current condition data into the training model to obtain a control instruction for the first household equipment.
In the embodiment of the present application, the content of the step S250 may refer to the content of the above embodiment, and is not described herein again.
Step S260: and controlling the first household equipment according to the control instruction.
In this embodiment, after the server obtains the control instruction by using the training model and the current condition data, the server may control the first home device according to the control instruction.
In some embodiments, controlling the first home device according to the control instruction may include:
and sending the control instruction to gateway equipment in a network where the first home equipment is located, wherein the gateway equipment is used for sending the control instruction to the first home equipment, and the control instruction is used for indicating the first home equipment to perform operation corresponding to the control instruction.
It can be understood that, when the first household device communicates with the server through the gateway device, the server may send the control instruction to the gateway device, so that the gateway device may issue the control instruction to the first household device, and the first household device may perform an operation corresponding to the control instruction according to the control instruction, thereby implementing control of the first household device.
In some embodiments, the server may communicate with a vendor server corresponding to the first home device when the server is not the vendor server corresponding to the first home device. The control instruction is sent to the manufacturer server corresponding to the first household equipment, the manufacturer server sends the control instruction to the gateway equipment, and then the gateway equipment sends the control instruction to the first household equipment, so that the first household equipment is controlled.
Of course, the manner in which the server transmits the control instruction to the first home device may not be limited, for example, in some scenarios, if the server can directly communicate with the first home device, the server may also directly send the control instruction to the first home device.
In the embodiment of the application, the server can also continuously correct the training model, so that the control instruction calculated by the training model is more accurate.
In some embodiments, the server corrects the training model, which may include: after controlling the first household equipment according to the control instruction, judging whether the control instruction is wrong; and if the error exists, correcting the training model.
The server can detect whether the control operation of the first household equipment by the user is acquired within a set time length after the first household equipment is controlled; if the control operation of the user on the first home equipment is acquired, determining that the control instruction is wrong; and if the control operation of the user on the first home equipment is not acquired, determining that the control instruction is correct.
It can be understood that, if the control instruction is wrong, the user may know that the control on the first home equipment is wrong, and the user may control the first home equipment. Therefore, after the first home device is controlled according to the control instruction, whether the control of the first home device by the user is obtained within a set time period can be detected, and specifically, whether the first home device or a mobile terminal for controlling the first home device receives the operation of the first home device by the user can be detected. Of course, the specific set time period and the manner of detecting whether the control command is incorrect are not limited, and for example, the set time period may be 5 minutes, or may be 10 minutes.
And correcting the training model when the control command is determined to be wrong. Specifically, a control instruction corresponding to a control operation of the user on the first home device and condition data during the control operation may be acquired, and then the control instruction corresponding to the control operation and the condition data during the control operation are input to the training model to train the training model. The specific training mode is not described herein again. Of course, when it is determined that the control command is correct, the training model is not required to be corrected. In the embodiment of the present application, the manner of correcting the training model may not be limited.
Of course, within a set time length after the first home device is controlled according to the control instruction, if the control operation of the user on the first home device is obtained, a control instruction corresponding to the control operation may be generated, and the first home device is controlled based on the control instruction corresponding to the control operation. Specifically, the first home device is controlled based on the control instruction corresponding to the control operation, and the manner of controlling the first home device may be referred to the control instruction obtained according to the calculation, which is not described herein again. In addition, if the control operation of the user on the first home device is acquired within the set time length after the first home device is controlled according to the control instruction, the first home device is required to stop the operation performed according to the calculated control instruction before the home device is controlled again. Therefore, an operation stop instruction can be sent to the first household equipment to control the first household equipment to stop the previous operation, and the conflict caused by different control instructions is avoided.
The equipment control method provided by the embodiment of the application trains an initial training model by using historical condition data and equipment data when first household equipment is operated to obtain a trained training model, obtains current condition data for controlling the first household equipment, calculates a control instruction matched with the current condition data by using the training model when the current condition data meets a set trigger condition, and controls the first household equipment according to the control instruction, so that the operation instruction of a subsequent user on the first household equipment is calculated according to the historical data of the user on operating the first household equipment, the automatic control on the first household equipment is realized, the intelligent degree of the household equipment control is improved, the historical condition data are related to the user, the environment and other household equipment, and the control instruction calculated by the training model accords with the operation habit of the user on the household equipment, fitting the requirements of users. In addition, the training model is continuously corrected, so that the accuracy of calculating the control command by the training model is improved, and the user experience is improved.
Referring to fig. 5, another embodiment of the present application provides a device control method, which is applicable to a server, and the device control method may include:
step S310: and receiving an automatic control request sent by the mobile terminal.
In this embodiment of the application, the first home device may be in an automatic control mode, and the automatic control mode of the first home device may be selected by a user according to a requirement.
In some embodiments, the server may control whether the automatic control mode of the first home device is turned on according to a request sent by the mobile terminal of the user. The mobile terminal may send an automatic control request or a control close request, where the automatic control request may instruct the server to start an automatic control mode, and the control close request may instruct the server to close the automatic control mode. The mobile terminal can display an interface of an application program for controlling the first home equipment, and the interface can include a setting page of an automatic control mode, so that a user can send an automatic control request or a control closing request to the server through the setting page. And the automatic control mode is used for the server to automatically send a control instruction to the first household equipment according to a corresponding strategy so as to control the first household equipment. When the first household equipment is in the automatic control mode, the first household equipment can execute the corresponding control instruction sent by the server according to the corresponding strategy under the condition that a user does not need to carry out field manual control or remote control is carried out through the mobile terminal, and the control operation corresponding to the control instruction is completed, so that the automatic control of the first household equipment is realized.
In some embodiments, the mode of automatic control of the first home device may be turned on or off by a request or instruction sent by the mobile terminal of the user. When the automatic control mode is started, the server can automatically execute a corresponding strategy and issue a control instruction to the first household equipment. Of course, when the first home device is in the automatic control mode, the first home device may also be manually controlled by the user, for example, the user may still perform control on the site through a key on the first home device, or may also perform control on the first home device through an application program run by the mobile terminal.
Step S320: and responding to the automatic control request, and controlling the first household equipment to be in an automatic control mode.
After receiving an automatic control request sent by a mobile terminal of a user, the server may respond to the automatic control request to control the first home equipment to be in an automatic control mode. And the server continuously collects the condition data to determine whether to calculate the control instruction by using the training model to control the first household equipment under the automatic control mode. And when the first household equipment is not in the automatic control mode, the server does not utilize the condition data and the training model to calculate the control instruction and control the first household equipment.
Step S330: when the first household equipment is in an automatic control mode, obtaining current condition data for controlling the first household equipment.
Step S340: when the current condition data meet a set triggering condition, a trained training model is obtained, the training model is obtained according to historical condition data and equipment data obtained when the first household equipment is executed to operate, the historical condition data at least comprise personal data of a user, environment data and state data of second household equipment, and the equipment data at least comprise a control instruction for the first household equipment.
Step S350: and inputting the current condition data into the training model to obtain a control instruction for the first household equipment.
In the embodiment of the present application, step S330, step S340, and step S350 may refer to the contents of the above embodiments, and are not described herein again.
Step S360: and sending a prompt content to a mobile terminal of a user, wherein the prompt content is used for prompting whether to perform an operation corresponding to the control instruction on the first household equipment.
In the embodiment of the application, after the control instruction for controlling the first household device is calculated by using the training model, the user can be prompted whether to implement control corresponding to the control instruction on the first household device. Specifically, the prompt content may be sent to the mobile terminal of the user, where the prompt content is used to prompt whether to perform an operation corresponding to the control instruction on the first home equipment.
In some embodiments, the server may obtain the number of times of control operations of the first home device by the user within a set time period between current times, to determine whether to send the prompting content to the mobile terminal of the user according to the number of times, so as to prompt the user. The current time is the time when the control instruction is obtained by using the training model. It can be understood that if the number of times of the control operation of the user on the first home device is greater in the set time period between the current times, it indicates that the user controls the first home device more by using the manual control, and at this time, the control instruction calculated by using the training model controls the first home device, which may not meet the requirement of the user.
Further, the server may determine whether the acquired number of times is greater than a set number of times, and if the acquired number of times is greater than the set number of times, the number of times of the control operation of the user on the first home device in the set time period between the current times is greater. If not, the number of times of the control operation of the first home device by the user in the set time period before the current time is not large. Therefore, when the acquired number of times is judged to be larger than the set number of times, the prompting content can be sent to the mobile terminal of the user. The specific number of times and the set time period may not be limited, for example, the number of times may be 5 times, 10 times, or the like, and the set time period may be a time period 2 days before the current time, a time period 3 days before the current time, or the like.
Step S370: and when a determining instruction sent by the mobile terminal is received, controlling the first household equipment according to the control instruction.
In the embodiment of the application, after the prompt content is sent to the mobile terminal of the user, the server may detect whether a determination instruction sent by the mobile terminal is received. And if the determining instruction sent by the mobile terminal is received, the server can control the first household equipment according to the control instruction. Wherein the determination instruction instructs the user to determine that the first home device needs to be controlled according to the control instruction. For example, the determination instruction may be a determination instruction detected by a prompt interface after the mobile terminal receives the prompt content and displays the prompt interface according to the prompt content. And if the server does not receive the determination instruction returned by the mobile terminal, the server does not execute control on the first household equipment according to the control instruction.
The device control method provided by the embodiment of the application, by setting a first home device in an automatic control mode, obtaining current condition data for controlling the first home device for the first home device in the automatic control mode, when the current condition data meets a set trigger condition, calculating a control instruction matched with the current condition data by using a training model trained according to historical condition data and device data, and controlling the first home device according to the control instruction, so that an operation instruction of a subsequent user for the first home device is calculated according to the historical data of the user for operating the first home device, and when the number of times of manual control of the recent user is large, sending a prompt content to a mobile terminal of the user to prompt the user whether to execute an operation corresponding to the control instruction for the first home device, when the determining instruction is received, the first household equipment is controlled according to the control instruction, so that automatic control over the household equipment is achieved, the intelligent degree of control over the household equipment is improved, historical condition data are relevant to the user, the environment and other household equipment, the control instruction calculated by the training model accords with the operation habit of the user on the household equipment, the user requirement is met, and the user experience is improved.
Referring to fig. 6, fig. 6 is a block diagram illustrating a device control apparatus 500 according to an embodiment of the present application. The device control apparatus 500 is applied to a server, and will be explained with respect to the apparatus shown in fig. 6, the device control apparatus 500 includes: a data acquisition module 510, a model acquisition module 520, an instruction acquisition module 530, and a control execution module 540. The data obtaining module 510 is configured to obtain current condition data, where the current condition data is used to control a first home device; the model obtaining module 520 is configured to invoke a trained training model when the current condition data meets a set trigger condition, where the training model is obtained by training according to historical condition data and device data of the first home device when the first home device is operated, the condition data at least includes personal data of a user, environment data, and state data of a second home device, and the device data at least includes a control instruction for the first home device; the instruction obtaining module 530 is configured to input the current condition data into the training model, so as to obtain a control instruction for the first home device; the control execution module 540 is configured to control the first home device according to the control instruction.
In some embodiments, the environmental data includes at least time data, date data, location data, and weather data, and the set triggering condition includes: the time data is at least one of set time data, the date data is set date data, the position data is set position data, the weather data is set weather data, and the second household equipment is in a set state.
In some embodiments, the device control apparatus 500 may further include: and a model training module. The data obtaining module 510 is further configured to obtain historical condition data and device data when the first home device is operated, where the historical condition data corresponds to the device data. And the model training module is used for inputting the historical condition data and the equipment data into an initial model, and training the initial model to obtain the trained training model.
Further, the device control apparatus 500 may further include: the device comprises a data screening module and a data classification module. The data screening module is used for screening the historical condition data and the equipment data; and the data classification module is used for classifying the filtered historical condition data and the filtered equipment data.
In some embodiments, the acquiring historical condition data and device data of the household device when being operated by the data acquiring module 510 may include: historical condition data and equipment data of the first household equipment when the first household equipment is executed are obtained from a mobile terminal, an environment acquisition device, the first household equipment, the second household equipment and a server of a third-party platform.
In some embodiments, the control execution module 540 may be specifically configured to: and sending the control instruction to a gateway device in a network where the first household device is located, wherein the gateway device is used for sending the control instruction to the first household device, and the control instruction is used for indicating the first household device to perform an operation corresponding to the control instruction.
Further, the sending, by the control execution module 540, the control instruction to the gateway device in the network where the home device is located may include: and sending the control instruction to a manufacturer server corresponding to the first household equipment, wherein the manufacturer server is used for sending the control instruction to gateway equipment in a network where the first household equipment is located.
In some embodiments, the device control apparatus 500 may further include: and a model correction module. The model correction module may be to: after the first household equipment is controlled according to the control instruction, whether the control instruction is wrong is judged; and if the error exists, correcting the training model.
Further, the determining, by the model correction module, whether the control command is incorrect may include: detecting whether control operation of a user on the first household equipment is obtained within a set time length after the first household equipment is controlled; and if the control operation of the user on the first household equipment is obtained, determining that the control instruction is wrong.
Further, the model correction module corrects the training model, and may include: acquiring a control instruction corresponding to the control operation and condition data when the control operation is carried out; and inputting a control instruction corresponding to the control operation and condition data during the control operation into the training model, and training the training model.
In some embodiments, the control execution module 550 may be specifically configured to: sending a prompt content to a mobile terminal of a user, wherein the prompt content is used for prompting whether to perform an operation corresponding to the control instruction on the first household equipment; and when a determining instruction sent by the mobile terminal is received, controlling the first household equipment according to the control instruction.
Further, the controlling and executing module 550 may send the prompt content to the mobile terminal of the user, and may include: acquiring the number of times of control operation of a user on the first household equipment within a set time period before the current time, wherein the current time is the time when the control instruction is obtained; and if the times are more than the set times, sending the prompt content to the mobile terminal of the user.
In some embodiments, the device control apparatus 500 may further include a request receiving module and a request responding module. The request receiving module is used for receiving an automatic control request sent by the mobile terminal; and the request response module is used for responding to the automatic control request and controlling the first household equipment to be in an automatic control mode.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described apparatuses and modules may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, the coupling between the modules may be electrical, mechanical or other type of coupling.
In addition, functional modules in the embodiments of the present application may be integrated into one processing module, or each of the modules may exist alone physically, or two or more modules are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode.
In summary, according to the scheme provided by the application, the current condition data for controlling the first home device is acquired, when the current condition data meets the set control trigger condition, the training model obtained according to the historical condition data and the device data training when the first home device is operated is called, the historical condition data comprises the personal data of the user, the environmental data and the state data of the second home device, the device data comprises the control instruction for the first home device, then the current condition data is input into the training model to obtain the control instruction for the first home device, the first home device is controlled according to the control instruction, so that the operation instruction for the home device is predicted according to the historical operation of the user on the home device, the automatic control for the home device is realized, and the intelligent degree of the home device control is improved, and the relevance with the user is high, the user requirement is met, and the user experience is improved.
Referring to fig. 7, a block diagram of a server according to an embodiment of the present disclosure is shown. The server 100 in the present application may include one or more of the following components: a processor 110, a memory 120, and one or more applications, wherein the one or more applications may be stored in the memory 120 and configured to be executed by the one or more processors 110, the one or more programs configured to perform a method as described in the aforementioned method embodiments.
Processor 110 may include one or more processing cores. The processor 110 connects various parts within the overall server 100 using various interfaces and lines, performs various functions of the server 100 and processes data by executing or executing instructions, programs, code sets, or instruction sets stored in the memory 120, and calling data stored in the memory 120. Alternatively, the processor 110 may be implemented in hardware using at least one of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), and Programmable Logic Array (PLA). The processor 110 may integrate one or more of a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), a modem, and the like. Wherein, the CPU mainly processes an operating system, a user interface, an application program and the like; the GPU is used for rendering and drawing display content; the modem is used to handle wireless communications. It is understood that the modem may not be integrated into the processor 110, but may be implemented by a communication chip.
The Memory 120 may include a Random Access Memory (RAM) or a Read-Only Memory (Read-Only Memory). The memory 120 may be used to store instructions, programs, code sets, or instruction sets. The memory 120 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for implementing at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing various method embodiments described below, and the like. The storage data area may also store data created by the terminal 100 in use, such as a phonebook, audio-video data, chat log data, and the like.
Referring to fig. 8, a block diagram of a computer-readable storage medium according to an embodiment of the present application is shown. The computer-readable medium 800 has stored therein a program code that can be called by a processor to execute the method described in the above-described method embodiments.
The computer-readable storage medium 800 may be an electronic memory such as a flash memory, an EEPROM (electrically erasable programmable read only memory), an EPROM, a hard disk, or a ROM. Alternatively, the computer-readable storage medium 800 includes a non-volatile computer-readable storage medium. The computer readable storage medium 800 has storage space for program code 810 to perform any of the method steps of the method described above. The program code can be read from or written to one or more computer program products. The program code 810 may be compressed, for example, in a suitable form.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit the same; although the present application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not necessarily depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.

Claims (20)

  1. An apparatus control method, characterized in that the method comprises:
    acquiring current condition data, wherein the current condition data is used for controlling first household equipment;
    when the current condition data meet a set triggering condition, calling a trained training model, wherein the training model is obtained by training according to historical condition data and equipment data of the first household equipment when the first household equipment is executed and operated, the condition data at least comprise personal data of a user, environment data and state data of second household equipment, and the equipment data at least comprise a control instruction for the first household equipment;
    inputting the current condition data into the training model to obtain a control instruction for the first household equipment;
    and controlling the first household equipment according to the control instruction.
  2. The method of claim 1, wherein the environmental data includes at least time data, location data, and weather data, and the set triggering conditions include:
    the time data is at least one of set time data, the position data is set position data, the weather data is set weather data, the second household equipment is in a set state, and the current condition data comprises a trigger instruction input by a user.
  3. The method of claim 1, wherein before invoking the trained training model when the current condition data satisfies a set trigger condition, the method further comprises:
    acquiring historical condition data and equipment data when the first household equipment is operated, wherein the historical condition data corresponds to the equipment data;
    and inputting the historical condition data and the equipment data into an initial model, and training the initial model to obtain the trained training model.
  4. The method of claim 3, wherein prior to said entering said historical condition data and said device data into an initial model, said method further comprises:
    screening the historical condition data and the equipment data;
    and classifying the filtered historical condition data and the filtered equipment data.
  5. The method of claim 3, wherein obtaining historical condition data and device data of the first home device when operated comprises:
    historical condition data and equipment data of the first household equipment when the first household equipment is executed are obtained from a mobile terminal, an environment acquisition device, the first household equipment, the second household equipment and a server of a third-party platform.
  6. The method according to any one of claims 1 to 5, wherein the controlling the first household device according to the control instruction comprises:
    and sending the control instruction to a gateway device in a network where the first household device is located, wherein the gateway device is used for sending the control instruction to the first household device, and the control instruction is used for indicating the first household device to perform an operation corresponding to the control instruction.
  7. The method according to claim 6, wherein the sending the control instruction to a gateway device in a network where the first home device is located comprises:
    and sending the control instruction to a manufacturer server corresponding to the first household equipment, wherein the manufacturer server is used for sending the control instruction to gateway equipment in a network where the first household equipment is located.
  8. The method according to any one of claims 1-7, further comprising:
    after the first household equipment is controlled according to the control instruction, whether the control instruction is wrong is judged;
    and if the error exists, correcting the training model.
  9. The method of claim 8, wherein said determining whether the control command is erroneous comprises:
    detecting whether control operation of a user on the first household equipment is obtained within a set time length after the first household equipment is controlled;
    and if the control operation of the user on the first household equipment is obtained, determining that the control instruction is wrong.
  10. The method of claim 9, wherein said correcting said training model comprises:
    acquiring a control instruction corresponding to the control operation and condition data when the control operation is carried out;
    and inputting a control instruction corresponding to the control operation and condition data during the control operation into the training model, and training the training model.
  11. The method according to any one of claims 1 to 10, wherein the controlling the first household device according to the control instruction comprises:
    sending a prompt content to a mobile terminal of a user, wherein the prompt content is used for prompting whether to perform an operation corresponding to the control instruction on the first household equipment;
    and when a determining instruction sent by the mobile terminal is received, controlling the first household equipment according to the control instruction.
  12. The method of claim 11, wherein sending the reminder to the mobile terminal of the user comprises:
    acquiring the number of times of control operation of a user on the first household equipment within a set time period before the current time, wherein the current time is the time when the control instruction is obtained;
    and if the times are more than the set times, sending the prompt content to the mobile terminal of the user.
  13. The method of any of claims 1-12, wherein prior to said obtaining current condition data, the method further comprises:
    receiving an automatic control request sent by a mobile terminal;
    and responding to the automatic control request, and controlling the first household equipment to be in an automatic control mode.
  14. An apparatus control device, characterized in that the device comprises: a data acquisition module, a model acquisition module, an instruction acquisition module and a control execution module, wherein,
    the data acquisition module is used for acquiring current condition data, and the current condition data is used for controlling the first household equipment;
    the model acquisition module is used for calling a trained training model when the current condition data meet a set triggering condition, the training model is obtained by training according to historical condition data and equipment data when the first household equipment is executed and operated, the condition data at least comprises personal data of a user, environment data and state data of second household equipment, and the equipment data at least comprises a control instruction for the first household equipment;
    the instruction acquisition module is used for inputting the current condition data into the training model to obtain a control instruction of the first household equipment;
    the control execution module is used for controlling the first household equipment according to the control instruction.
  15. The apparatus of claim 14, wherein the environmental data comprises at least time data, date data, location data, and weather data, and the set triggering condition comprises:
    the time data is at least one of set time data, the position data is set position data, the weather data is set weather data, the second household equipment is in a set state, and the current condition data comprises a trigger instruction input by a user.
  16. The apparatus of claim 14, further comprising: a model training module to:
    when the current condition data meet a set triggering condition and before a trained training model is acquired, acquiring historical condition data and equipment data of the first household equipment when the first household equipment is operated, wherein the historical condition data correspond to the equipment data;
    and inputting the historical condition data and the equipment data into an initial model, and training the initial model to obtain the trained training model.
  17. The apparatus of claim 16, further comprising: a data screening module and a data classification module, wherein,
    the data screening module is used for screening the historical condition data and the equipment data before inputting the historical condition data and the equipment data into an initial model;
    the data classification module is used for classifying the filtered historical condition data and the filtered equipment data.
  18. The apparatus of claim 16, wherein the model training module obtains historical condition data and device data of the first home device when the operation is performed, comprising:
    historical condition data and equipment data of the first household equipment when the first household equipment is executed are obtained from a mobile terminal, an environment acquisition device, the first household equipment, the second household equipment and a server of a third-party platform.
  19. A server, comprising:
    one or more processors;
    a memory;
    one or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, the one or more programs configured to perform the method of any of claims 1-13.
  20. A computer-readable storage medium, having stored thereon program code that can be invoked by a processor to perform the method according to any one of claims 1 to 13.
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