CN110719217A - Control method and system based on affair map, readable storage medium and computer - Google Patents
Control method and system based on affair map, readable storage medium and computer Download PDFInfo
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- CN110719217A CN110719217A CN201910989187.5A CN201910989187A CN110719217A CN 110719217 A CN110719217 A CN 110719217A CN 201910989187 A CN201910989187 A CN 201910989187A CN 110719217 A CN110719217 A CN 110719217A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L12/00—Data switching networks
- H04L12/28—Data switching networks characterised by path configuration, e.g. LAN [Local Area Networks] or WAN [Wide Area Networks]
- H04L12/2803—Home automation networks
- H04L12/2816—Controlling appliance services of a home automation network by calling their functionalities
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- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
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- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
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- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
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- G10L15/26—Speech to text systems
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- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
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- H04L12/28—Data switching networks characterised by path configuration, e.g. LAN [Local Area Networks] or WAN [Wide Area Networks]
- H04L12/2803—Home automation networks
- H04L12/2816—Controlling appliance services of a home automation network by calling their functionalities
- H04L12/282—Controlling appliance services of a home automation network by calling their functionalities based on user interaction within the home
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Abstract
The invention relates to a control method and a control system based on a physical knowledge graph. The control method based on the affair knowledge graph comprises the following steps: acquiring a voice signal in a target area; analyzing the user intention according to the voice signal to obtain an equipment control instruction; finding corresponding equipment in a target scene database according to the equipment control instruction; controlling the corresponding equipment according to the equipment control instruction; inquiring related equipment having a physical logic relation with the corresponding equipment in the target scene database according to the equipment information of the corresponding equipment; if yes, controlling a sensor of the associated equipment to acquire an environmental parameter; judging whether the environmental parameters meet the response conditions of the associated equipment or not according to a preset rule; if so, sending out the voice information of whether to operate the associated equipment. The invention solves the problem of the singleness of the user awakening equipment. The invention realizes the process of awakening the device related to the target scene by the user.
Description
Technical Field
The invention relates to the technical field of Internet of things, in particular to a control method and system based on a physics knowledge graph, a readable storage medium and a computer.
Background
At present, in the field of home internet of things, a user often controls home equipment through voice. Common modes of operation: the user firstly wakes up the voice sound box (such as Alexa, makiteskin and the like) by voice, then speaks the operation dialogues of specific equipment, such as ' turning on light ', ' turning off air conditioner ' and the like, and then the dialogue system of the voice sound box "understands ' the operation dialogues of the user as corresponding control instructions. And then the communication unit issues the control command to the networked home equipment, and the control unit of the home equipment responds to the command, so that the home equipment is controlled by the user through voice.
This mode of operation is currently a purely command control, requiring the user to speak a specific control, such as "turn on light" which only turns on the light. However, there is no need for users to control a series of devices in different life scenarios, such as turning on lights, closing windows, closing doors, turning on air conditioners, turning on water heaters, etc. when users arrive at home from work, common household device operations are performed. In a certain life scenario, a series of device operations may occur. If the user simply controls the equipment through a single voice instruction, the equipment is very non-humanized product experience.
In order to solve the problem, a series of home control is usually realized by presetting scenes in the field of smart home at present. For example, a user may preset a "home scene" in which the user binds a series of device operations such as turning on a light, closing a window, turning on an air conditioner, turning on a water heater, and the like. After this process, the user simply speaks "go home" to trigger a series of device operations.
At present, the processing scheme is quite popular, and the problem of operation of a series of associated equipment by a user is solved to a certain extent.
But there is a problem: various daily life scenes cannot be preset. And the association between the devices is conditional, for example, there is no necessity between the two device operations of "closing the window" and "opening the air conditioner", and under the condition that the outdoor environment is suitable, the user does not need to "open the air conditioner" after "closing the window". The precondition required between the operations of the associated devices makes the scheme of using the preset scene rigid and without generality. In order to solve the problem, the method adopts a dialogue system based on a case-of-affair knowledge graph, encodes the association and association conditions among the devices into the case-of-affair knowledge graph, and intelligently provides the associated device operation for the user by inquiring and reasoning the case-of-affair knowledge graph.
Disclosure of Invention
The present invention is directed to solving at least one of the problems of the prior art or the related art.
To this end, it is an object of the present invention to provide a case-wisdom-based control method that is capable of intelligently providing associated device operations to a user through queries and inferences about a case-wisdom. One situation is that the voice information is sent out by the user, the system starts the equipment by identifying the user requirement, the user requirement comprises a target scene and starting of certain equipment, the target scene comprises a manned state or an unmanned state, a scene in winter or summer and the like, and when one or a series of equipment is started according to the user instruction, the system also provides a suggestion for starting the associated equipment to the user based on the physical logic relationship; another situation is that when a detector in the environment detects a certain action of the user, the system retrieves the inference related device based on the event logic relationship through the action information, and proposes the suggestion of enabling the device to the user.
It is another object of the present invention to provide a control system based on a situational knowledge base, which can provide a series of device activation suggestions to a user in conjunction with the user's needs, and the system can also provide device activation suggestions to the user by detecting user actions through a detector of a target area.
It is a third object of the invention to provide a readable storage medium.
It is a fourth object of the invention to provide a computer.
In order to achieve the above object, the technical solution of the first aspect of the present invention provides a control method based on a physical knowledge graph, including the following steps: acquiring a voice signal in a target area; analyzing the user intention according to the voice signal to obtain an equipment control instruction; finding corresponding equipment in a target scene database according to the equipment control instruction; controlling the corresponding equipment according to the equipment control instruction; meanwhile, according to the equipment information of the corresponding equipment, inquiring related equipment having a physical logic relationship with the corresponding equipment in the target scene database; if not, ending the process; if yes, controlling a sensor of the associated equipment to acquire an environmental parameter; judging whether the environmental parameters meet the response conditions of the associated equipment or not according to a preset rule; if not, ending the process; if so, sending out the voice information of whether to operate the associated equipment.
In the technical scheme, the voice signals sent by the user in the target area according to the requirement of the user are analyzed through the natural language understanding module, the dialogue management module receives the intention of the user, starts the equipment related to the intention of the user, simultaneously retrieves and infers the associated equipment based on the affairs knowledge map by the retrieval and inference engine, issuing related environment query requests to sensors of related equipment according to related conditions, reading related monitoring parameters by the sensors according to the received query requests, then reporting the parameters to a retrieval and inference engine, judging whether the correlation conditions are met according to the reported parameters, when the retrieval and reasoning engine judges that the association condition is satisfied, the associated equipment operation is fed back to a dialogue management module of the dialogue system, the dialogue management inquires whether the relevant equipment operation is executed or not to the user according to the dialogue management, and corresponding execution action is carried out according to the answer of the user.
In the above aspect, it is preferable that the method further includes: compiling the target scene database based on a physical knowledge graph; the target scene database comprises the target scene, equipment information corresponding to the target scene, the equipment control instruction based on the equipment information, the information of the physical logic relationship between the equipment identifications, the information of the preset action of the detector in the target area and the information of the physical logic relationship between the equipment; the speech signal includes instructions of a target scene or device.
In the technical scheme, the database based on the affair knowledge graph is compiled to ensure that different types of voice signals can be effectively executed, the equipment in the target area is based on the affair knowledge logic based on the affair knowledge graph, and meanwhile, the preset action information of the detector in the target area is linked with the equipment. When the voice signal is matched with a preset target scene, the system starts a series of devices in a target area based on the support of a database and the logic execution of a case knowledge graph; when the voice signal is a single device, the device corresponding to the voice signal is started.
In the above technical solution, preferably, before controlling the sensor of the associated device to acquire the environmental parameter, the method further includes the following steps: a detector in the target area detects the occurrence of a preset action; and inquiring and reasoning the operation of the associated equipment in the target scene database according to the information of the preset action.
In the technical scheme, the detector in the target area detects the occurrence of the corresponding preset action, the retrieval and inference engine searches the associated equipment in the database according to the preset action, and the associated equipment enabling suggestion is autonomously provided for a user. The preset action is designed as a detection of the target area based on compilation of the fact knowledge graph by the system, so that the system can make equipment starting suggestions based on actions of the user.
The technical scheme of the second aspect of the invention provides a control system based on a affairs knowledge graph, which comprises the following components: an acquisition module configured to acquire a voice signal within a target region; the analysis module is arranged for analyzing the user intention according to the voice signal to obtain an equipment control instruction; a search module configured to find a corresponding device in a target scene database according to the device control instruction; a control module configured to control the corresponding device according to the device control instruction; meanwhile, a first query module is arranged for querying the associated equipment having a physical and logical relationship with the corresponding equipment in the target scene database according to the equipment information of the corresponding equipment; if not, ending the process; if yes, the sensor module is set to be used for controlling a sensor of the associated equipment to acquire an environmental parameter; the judging module is set for judging whether the environmental parameters meet the response conditions of the associated equipment according to preset rules; if not, ending the process; and if so, the voice prompt module is set to be used for sending out the voice information whether to operate the associated equipment.
In the technical scheme, the voice signals sent by the user in the target area according to the requirement of the user are analyzed through the natural language understanding module, the dialogue management module receives the intention of the user, starts the equipment related to the intention of the user, simultaneously retrieves and infers the associated equipment based on the affairs knowledge map by the retrieval and inference engine, issuing related environment query requests to sensors of related equipment according to related conditions, reading related monitoring parameters by the sensors according to the received query requests, then reporting the parameters to a retrieval and inference engine, judging whether the correlation conditions are met according to the reported parameters, when the retrieval and reasoning engine judges that the association condition is satisfied, the associated equipment operation is fed back to a dialogue management module of the dialogue system, the dialogue management inquires whether the relevant equipment operation is executed or not to the user according to the dialogue management, and corresponding execution action is carried out according to the answer of the user.
In the above technical solution, it is preferable that the method includes: a database arranged to compile the target scene database based on a physical knowledge graph; the target scene database comprises the target scene, equipment information corresponding to the target scene, the equipment control instruction based on the equipment information, the information of the physical logic relationship between the equipment identifications, the information of the preset action of the detector in the target area and the information of the physical logic relationship between the equipment; the speech signal includes instructions of a target scene or device.
In the technical scheme, the database based on the affair knowledge graph is compiled to ensure that different types of voice signals can be effectively executed, the equipment in the target area is based on the affair knowledge logic based on the affair knowledge graph, and meanwhile, the preset action information of the detector in the target area is linked with the equipment. When the voice signal is matched with a preset target scene, the system starts a series of devices in a target area based on the support of a database and the logic execution of a case knowledge graph; when the voice signal is a single device, the device corresponding to the voice signal is started.
In the above technical solution, preferably, the method further includes: the detection module is arranged for detecting the occurrence of a preset action by a detector in the target area; and the second query module is set for querying and reasoning the associated equipment in the target scene database according to the information of the preset action.
According to the technical scheme, the detector in the target area detects the occurrence of the corresponding preset action, the retrieval and inference engine searches the associated equipment in the database according to the preset action, and the associated equipment enabling suggestion is autonomously provided for the user. The preset action is designed as a detection of the target area based on compilation of the fact knowledge graph by the system, so that the system can make equipment starting suggestions based on actions of the user.
A third aspect of the invention is to provide a readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the matter knowledgegraph-based control method.
A fourth aspect of the present invention is to provide a computer comprising a storage medium and a processor; a storage medium for storing a computer program; a processor for executing a computer program to implement the method of control based on a physical knowledge graph.
Drawings
The above-mentioned additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
fig. 1 is a flowchart showing a control method based on a physical knowledge base according to embodiment 1 of the present invention;
FIG. 2 is a flow chart showing another control method based on a physical knowledge graph according to embodiment 2 of the present invention;
FIG. 3 is a flow chart showing a third control method based on a case knowledge graph according to embodiment 3 of the present invention;
FIG. 4 is a block diagram showing a fourth control system based on a physical knowledge base according to embodiment 4 of the present invention;
FIG. 5 is a block diagram showing a fifth control system based on a case knowledge map according to embodiment 5 of the present invention;
fig. 6 is a block diagram showing a sixth control system based on a case knowledge map according to embodiment 6 of the present invention.
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those specifically described herein, and therefore the scope of the present invention is not limited to the specific embodiments disclosed below.
The control method and system based on the affairs knowledge graph, the readable storage medium and the computer are described below with reference to fig. 1 to 6.
As shown in fig. 1, the control method based on the affairs knowledge-graph according to one embodiment of the invention includes the following steps:
s10, acquiring a voice signal in the target area;
s20, analyzing the user intention according to the voice signal to obtain an equipment control instruction;
s30, finding the corresponding equipment in the target scene database according to the equipment control instruction;
s40, controlling the corresponding equipment according to the equipment control instruction;
s50, meanwhile, according to the device information of the corresponding device, inquiring the associated device having a logical relationship with the corresponding device in the target scene database;
if not, ending the process;
s60, if yes, controlling the sensor of the associated equipment to acquire environmental parameters;
s70, judging whether the environmental parameters meet the response conditions of the associated equipment according to preset rules;
if not, ending the process;
and S80, if yes, sending out voice information of whether to operate the associated equipment.
In the technical scheme, the voice signals sent by the user in the target area according to the requirement of the user are analyzed through the natural language understanding module, the dialogue management module receives the intention of the user, starts the equipment related to the intention of the user, simultaneously retrieves and infers the associated equipment based on the affairs knowledge map by the retrieval and inference engine, issuing related environment query requests to sensors of related equipment according to related conditions, reading related monitoring parameters by the sensors according to the received query requests, then reporting the parameters to a retrieval and inference engine, judging whether the correlation conditions are met according to the reported parameters, when the retrieval and reasoning engine judges that the association condition is satisfied, the associated equipment operation is fed back to a dialogue management module of the dialogue system, the dialogue management inquires whether the relevant equipment operation is executed or not to the user according to the dialogue management, and corresponding execution action is carried out according to the answer of the user.
As shown in fig. 2, a control method based on a physical knowledge graph according to another embodiment of the present invention includes:
s90, compiling the target scene database based on the affair knowledge graph;
the target scene database comprises the target scene, equipment information corresponding to the target scene, the equipment control instruction based on the equipment information, the information of the physical logic relationship between the equipment identifications, the information of the preset action of the detector in the target area and the information of the physical logic relationship between the equipment;
the speech signal includes instructions of a target scene or device.
In the technical scheme, the database based on the affair knowledge graph is compiled to ensure that different types of voice signals can be effectively executed, the equipment in the target area is based on the affair knowledge logic based on the affair knowledge graph, and meanwhile, the preset action information of the detector in the target area is linked with the equipment. When the voice signal is matched with a preset target scene, the system starts a series of devices in a target area based on the support of a database and the logic execution of a case knowledge graph; when the voice signal is a single device, the device corresponding to the voice signal is started.
As shown in fig. 3, the control method based on the fact knowledge-graph according to the third embodiment of the present invention further includes the following steps before the sensor controlling the associated device acquires the environmental parameter:
s100, detecting the occurrence of a preset action by a detector in a target area;
and S110, inquiring and reasoning the operation of the associated equipment in the target scene database according to the information of the preset action.
In the technical scheme, the detector in the target area detects the occurrence of the corresponding preset action, the retrieval and inference engine searches the associated equipment in the database according to the preset action, and the associated equipment enabling suggestion is autonomously provided for a user. The preset action is designed as a detection of the target area based on compilation of the fact knowledge graph by the system, so that the system can make equipment starting suggestions based on actions of the user.
As shown in fig. 4, a control system 1000 based on a case-knowledge-map according to a fourth embodiment of the present invention includes:
an obtaining module 10 configured to obtain a voice signal in a target area;
the analysis module 20 is configured to analyze the user intention according to the voice signal to obtain a device control instruction;
a search module 30 configured to find a corresponding device in the target scene database according to the device control instruction;
a control module 40 configured to control the corresponding device according to the device control instruction;
meanwhile, the first query module 50 is configured to query, in the target scene database, associated devices having a physical and logical relationship with the corresponding devices according to the device information of the corresponding devices;
if not, ending the process;
if so, the sensor module 60 is configured to control the sensor of the associated device to acquire the environmental parameter;
a judging module 70 configured to judge whether the environmental parameter satisfies a response condition of the associated device according to a preset rule;
if not, ending the process;
if yes, the voice prompt module 80 is configured to send out a voice message indicating whether to operate the associated device.
In the technical scheme, the voice signal sent by the user in the target area according to the requirement of the user is analyzed through the natural language understanding module, the dialogue management module receives the intention of the user, starts the equipment related to the intention of the user, simultaneously retrieves and infers the associated equipment based on the affairs knowledge map by the retrieval and inference engine, issuing related environment query requests to sensors of related equipment according to related conditions, reading related monitoring parameters by the sensors according to the received query requests, then reporting the parameters to a retrieval and inference engine, judging whether the correlation conditions are met according to the reported parameters, when the retrieval and reasoning engine judges that the association condition is satisfied, the associated equipment operation is fed back to a dialogue management module of the dialogue system, the dialogue management inquires whether the relevant equipment operation is executed or not to the user according to the dialogue management, and corresponding execution action is carried out according to the answer of the user.
As shown in fig. 5, a control system 1000 based on a case-knowledge-map according to a fifth embodiment of the present invention includes:
a database 90 arranged to compile the target scene database based on a physical knowledge graph;
the target scene database comprises the target scene, equipment information corresponding to the target scene, the equipment control instruction based on the equipment information, the information of the physical logic relationship between the equipment identifications, the information of the preset action of the detector in the target area and the information of the physical logic relationship between the equipment;
the speech signal includes instructions of a target scene or device.
In the technical scheme, the database based on the affair knowledge graph is compiled to ensure that different types of voice signals can be effectively executed, the equipment in the target area is based on the affair knowledge logic based on the affair knowledge graph, and meanwhile, the preset action information of the detector in the target area is linked with the equipment. When the voice signal is matched with a preset target scene, the system starts a series of devices in a target area based on the support of a database and the logic execution of a case knowledge graph; when the voice signal is a single device, the device corresponding to the voice signal is started.
As shown in fig. 6, the control system 1000 based on the affairs knowledge-graph according to the sixth embodiment of the invention further includes:
a detection module 100 configured to detect occurrence of a preset action by a detector in a target area;
and a second query module 110 configured to query and infer the associated device in the target scene database according to the information of the preset action.
According to the technical scheme, the detector in the target area detects the occurrence of the corresponding preset action, the retrieval and inference engine searches the associated equipment in the database according to the preset action, and the associated equipment enabling suggestion is autonomously provided for the user. The preset action is designed as a detection of the target area based on compilation of the fact knowledge graph by the system, so that the system can make equipment starting suggestions based on actions of the user.
A third aspect of the invention is to provide a readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the matter knowledgegraph-based control method.
A fourth aspect of the present invention is to provide a computer comprising a storage medium and a processor; a storage medium for storing a computer program; a processor for executing a computer program to implement the method of control based on a physical knowledge graph.
The whole system can be roughly divided into three parts, namely a conversation system, a physical knowledge graph and environment monitoring. The dialogue system can be subdivided into three modules of natural language understanding, dialogue management and natural language generation. The affair knowledge graph can be subdivided into a retrieval and inference engine and a data storage module.
Meanwhile, the user can correspondingly eliminate unnecessary equipment requirements in the system according to the different seasons and scenes according to the needs of the user, for example, when window closing behaviors in autumn are detected by the sensor, voice prompts for starting the air conditioner are not necessary to be provided for the user like summer; meanwhile, the user can also set the preset rule individually according to different target scenes, and can adjust the temperature lower than 30 ℃ to be lower than 25 ℃ and the like.
The preset rules are generally customized according to the requirements of the target scene, including detection of the concentration of a certain substance, detection of the temperature and humidity in the target area, detection of PM2.5 in the target area, and the like.
The fact graph is a graph network which takes events as nodes and relations among the events as edges, and is different from the knowledge graph in that most of the entities and relations are stable, most of the relations in the fact graph are uncertain, and the transfer is carried out with a certain probability. The events are events occurring in human social activities, such as shopping, PM2.5 bursting watch, closing a window and the like, and are linked together through a logical relationship, for example, the window is closed because of the PM2.5 bursting watch, and a causal relationship exists between the event PM2.5 and the event window closing. The event knowledge graph abstracts and generalizes the events, represents the events into a fixed data structure, and stores the fixed data structure in a database. The construction of the affair map is basically consistent with the overall thought of the knowledge map, namely, the nodes and the relations are extracted from the mass information, the knowledge of the fact class is stored in the knowledge base, and the events in the affair map are related with a certain probability, so that the affair map is more suitable for recognition of some subsequent intentions or auxiliary reasoning. Determining the logical relationship of the events in the event graph comprises the following steps: (1) detection and type identification of events: generally related to trigger word recognition; (2) extracting event elements: and classifying and labeling event elements and determining roles. The methods adopted at the same time mainly comprise three methods: (1) pattern matching (2) machine learning (3) a hybrid approach of the two. The pattern matching can be mainly divided into matching of vocabulary-grammar patterns and vocabulary-semantic patterns, and the matching of the vocabulary-grammar patterns by combining semantic roles is common. If the relation between the events does not have the corpus which can be trained, a training set is continuously iterated according to rules, subsequent relation recognition can be directly connected to a model, the events are mainly extracted and converted into classification problems by adopting a machine learning method, and common classification algorithms comprise SVM, ME and the like. Therefore, the control method based on the affair knowledge graph is continuously derived and evolutionary learned, and as time is continuously accumulated, the system gradually forms a set of pointed and personalized affair logic relation by continuously carrying out data statistics on the behaviors of the user.
In the present invention, the terms "first", "second", and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance; the term "plurality" means two or more unless expressly limited otherwise. The terms "mounted," "connected," "fixed," and the like are to be construed broadly, and for example, "connected" may be a fixed connection, a removable connection, or an integral connection; "coupled" may be direct or indirect through an intermediary. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
In the description of the present invention, it is to be understood that the terms "upper", "lower", "left", "right", "front", "rear", and the like indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience of description and simplification of description, but do not indicate or imply that the referred device or unit must have a specific direction, be constructed in a specific orientation, and be operated, and thus, should not be construed as limiting the present invention.
In the description herein, the description of the terms "one embodiment," "some embodiments," "specific embodiments," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. A control method based on a physics knowledge graph is characterized by comprising the following steps:
acquiring a voice signal in a target area;
analyzing the user intention according to the voice signal to obtain an equipment control instruction;
finding corresponding equipment in a target scene database according to the equipment control instruction;
controlling the corresponding equipment according to the equipment control instruction;
meanwhile, according to the equipment information of the corresponding equipment, inquiring related equipment having a physical logic relationship with the corresponding equipment in the target scene database;
if not, ending the process;
if yes, controlling a sensor of the associated equipment to acquire an environmental parameter;
judging whether the environmental parameters meet the response conditions of the associated equipment or not according to a preset rule;
if not, ending the process;
if so, sending out the voice information of whether to operate the associated equipment.
2. The method of claim 1, further comprising:
compiling the target scene database based on a physical knowledge graph;
the target scene database comprises the target scene, equipment information corresponding to the target scene, the equipment control instruction based on the equipment information, the information of the physical logic relationship between the equipment identifications, the information of the preset action of the detector in the target area and the information of the physical logic relationship between the equipment;
the speech signal includes instructions of a target scene or device.
3. A method of situational knowledge-graph-based control according to claim 1, further comprising, prior to controlling sensors of the associated equipment to acquire environmental parameters, the steps of:
a detector in the target area detects the occurrence of a preset action;
and inquiring and reasoning the operation of the associated equipment in the target scene database according to the information of the preset action.
4. A control system based on a situational knowledge map, comprising:
an acquisition module configured to acquire a voice signal within a target region;
the analysis module is arranged for analyzing the user intention according to the voice signal to obtain an equipment control instruction;
a search module configured to find a corresponding device in a target scene database according to the device control instruction;
a control module configured to control the corresponding device according to the device control instruction;
meanwhile, a first query module is arranged for querying the associated equipment having a physical and logical relationship with the corresponding equipment in the target scene database according to the equipment information of the corresponding equipment;
if not, ending the process;
if yes, the sensor module is set to be used for controlling a sensor of the associated equipment to acquire an environmental parameter;
the judging module is set for judging whether the environmental parameters meet the response conditions of the associated equipment according to preset rules;
if not, ending the process;
and if so, the voice prompt module is set to be used for sending out the voice information whether to operate the associated equipment.
5. The event map-based control system of claim 4, wherein:
a database arranged to compile the target scene database based on a physical knowledge graph;
the target scene database comprises the target scene, equipment information corresponding to the target scene, the equipment control instruction based on the equipment information, the information of the physical logic relationship between the equipment identifications, the information of the preset action of the detector in the target area and the information of the physical logic relationship between the equipment;
the speech signal includes instructions of a target scene or device.
6. The event knowledgebase control system of claim 4, further comprising:
the detection module is arranged for detecting the occurrence of a preset action by a detector in the target area;
and the second query module is set for querying and reasoning the associated equipment in the target scene database according to the information of the preset action.
7. A readable storage medium, characterized in that a computer program is stored thereon, which when executed by a processor implements the fact knowledge-graph based control method according to any one of claims 1 to 3.
8. A computer, comprising a storage medium and a processor; a storage medium for storing a computer program; a processor for executing a computer program for implementing the method of control based on a situational knowledge-graph of any one of claims 1 to 3.
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