CN111830842A - Intelligent household non-inductive control system - Google Patents
Intelligent household non-inductive control system Download PDFInfo
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
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Abstract
The invention belongs to the field of intelligent home furnishing, and relates to an intelligent home furnishing non-inductive control system. The three-terminal network architecture of the system comprises a local integration terminal, a server terminal and a mobile terminal. The three-layer management and control architecture comprises a monitoring layer, a decision layer and a control layer, wherein the monitoring layer is located at a server end, the decision layer is located at a local integration end and the server end, and the control layer is located at the local integration end. And modeling the collected user activity information by using a discrete event system theory with a human center, and outputting a corresponding equipment control strategy for top-level control. When the user state is changed, the system equipment automatically adjusts the state in order to create a proper living environment, so that the comfort level and the living convenience of the user are improved. Meanwhile, the household system is subjected to layered decoupling, corresponding strategies are designed for different layers, all household appliances are coordinated and operated comprehensively, people are helped to manage the household system intelligently, and safer, worry-saving and comfortable household service and household experience are provided for people.
Description
Technical Field
The invention belongs to the field of intelligent home furnishing, particularly relates to a discrete event dynamic system theory, logic control and the like, and provides a non-inductive control method meeting the personalized requirements of users, so that the operation amount of regulating and controlling equipment of people is reduced, and the people can enjoy life better.
Background
With the development of emerging technologies such as intelligent sensing, internet of things, big data and cloud computing, the heat of smart homes is continuously increased, and the intelligent level of household appliances is also continuously improved. Although the level of intellectualization of the household appliances reaches a high level nowadays, for the smart home systems, users still need to manually set complex logic rules for the smart devices, and the management and control level of the whole home systems cannot be matched with the complex logic rules. For a complex and flexible home system, all smart home devices need to be set and adjusted by automatically sensing the requirements of users, so that an ideal living and working environment is provided. How to intelligently help people manage a home system and enable all equipment to operate coordinately and comprehensively is a problem to be solved urgently.
Disclosure of Invention
In order to solve the technical problem, the invention provides an intelligent household non-inductive control system.
In order to achieve the purpose, the invention adopts the technical scheme that:
a three-terminal network architecture of the intelligent home non-inductive control system comprises a local integration terminal, a server terminal and a mobile terminal, wherein WebSocket communication is adopted among the three terminals. The three-layer management and control architecture comprises a monitoring layer, a decision layer and a control layer, wherein the monitoring layer is located at a server end, the decision layer is located at a local integration end and the server end, and the control layer is located at the local integration end.
The monitoring layer tracks the state of the office according to the state changes of the sensors and the equipment and instructions sent by the user, and outputs the current state of the office to the decision-making layer. The monitoring layer is realized by adopting a discrete event system theory, for a series of sensors and command events, event information of the system is obtained by a multi-sensor data fusion method, and the current state of the office is estimated according to the established state observer.
The construction method of the monitoring layer of the intelligent home system comprises the following steps:
the office state mainly includes two states of people using and long-time nobody using, depending on d0(door/window sensor), m0～m3(human body sensor), mr(virtual body sensor) can be accurately judged.
Meanwhile, the instructions of rest and report of the user are received by establishing virtual switches 'break' and 'report' at the local end.
the present invention divides the office into four states: dormant state (user leaves office for a long time), working state, resting state and reporting state. And establishing the robot model by defining each state in the office and transition events among the states. The automaton model is a quadruple, as shown by the following equation:
wherein 
Is a set of states; Σ is the event set;
is a transfer function; q. q.s0Is a subset of states, determined by the initial state of the system;
is the set of tagged states of the system.
And step 3: determining an observable event:
defining the process in which each sensor is triggered and outputs state change information as a sensor event SsThe process of sending out each human-computer interaction instruction and receiving the instruction by the office is an instruction event Sd。
When any event sigma in the automaton event set sigma occurs, the sensor event set S is triggered by connectionsAnd instruction event set SdOne or a number of the events in (a),the least events that uniquely determine the state transition among the one or several events are extracted, and the sequence of such one or several least events is called an observable event of event σ. The specific correspondence table is as follows:
wherein the symbols in the table above are illustrated in the following table:
by d0m0I.e. theta1The method comprises the steps that after a door is opened, a person enters a room, so that door and window sensor events and human body sensor events occur, and the door and window sensors and the human body sensors are opened;
i.e. theta4Indicating that a person opens the door and leaves the room, resulting in a door and window sensor event and a body sensor event occurring, the door and window sensors and the body sensor being closed; the RE and RP commands are commands for forcibly switching the room state through the switches of the virtual switch.
And 4, step 4: determining an observable sequence of events:
constructing a state tree containing all possible occurring sensor event sequences in a breadth-first manner can convert sensor and command event sequences into observable event sequences.
Initially, the state tree is in an initial state, when a sensor event arrives, the state tree enters a corresponding branch and arrives at a next state, if the current state is a black mark, a corresponding observable event is formed, and meanwhile, the state tree returns to the initial state to wait for the formation of another observable event; if the current state is a white mark, the next sensor event is continuously waited until the reached state is a black mark state, then a corresponding observable event is generated, and the state tree returns to the initial state to wait for the formation of another observable event. In either the initial state or the white-marked state, upon the occurrence of an instruction event, the state tree reaches the black-marked state and then generates a corresponding one of the observable events, the state tree returning to the initial state awaiting the occurrence of another observable event.
And 5: constructing a state observer:
firstly, all the automaton events in the automaton model G are replaced by corresponding observable events in the observable event set theta, and another uncertain automaton G can be obtainednd:
Gnd＝(Q,Θ,N,q0)
wherein ,
secondly, the uncertain automaton G is processedndConversion into its corresponding deterministic automaton, i.e. its state observation
Device Gobs：
Gobs＝(X,Θ,ξ,x0)＝AC(2Q,Θ,ξ,Q0)
wherein ,
x0＝Q0，
and the decision layer judges the equipment to be regulated according to the output of the monitoring layer, designs a regulation and control sequence and an automatic control logic which meet the user comfort level experience, and sends a control instruction of the corresponding equipment to the control layer.
And the control layer receives subsequent tasks customized by the decision layer and completes control work by changing the state variables of the virtual components.
The invention achieves the following beneficial effects: and by taking the residents as the center, appropriate methods are respectively applied to the monitoring layer, the decision layer and the control layer to make corresponding control strategies, so that the user is free from complex setting work. The intelligent home system can set and adjust all intelligent home devices through automatically sensing the requirements of the user, so that the interaction level between people and the devices is improved, the non-inductive control of the intelligent home is effectively realized, and the user requirements are met.
Drawings
Fig. 1 is an overall layout diagram of an office in an embodiment of the present invention.
Fig. 2 is a sensor distribution diagram of an office in an embodiment of the present invention.
Fig. 3 is an intelligent home management and control system architecture in an embodiment of the present invention.
Fig. 4 is a three-layer control framework of the smart home system in the embodiment of the invention.
Fig. 5 is an automaton of a monitoring layer of an intelligent home system in an embodiment of the present invention.
Fig. 6 is a state observer of a monitoring layer of an intelligent home system in an embodiment of the present invention.
Fig. 7 is a state tree structure model of a monitoring layer of an intelligent home system in an embodiment of the present invention.
Fig. 8 is an overall architecture diagram of office state tracking in an embodiment of the present invention.
Fig. 9 is a flow of office work status decision-making in an embodiment of the present invention.
Detailed Description
The technical solutions provided in the present application will be further described with reference to the following specific embodiments and accompanying drawings. The advantages and features of the present application will become more apparent in conjunction with the following description.
The invention particularly relates to an intelligent household non-inductive control system. The system makes full use of the advantages of different platforms and software, deploys the monitoring layer, the decision layer and the control layer in different places of the intelligent home software system, enables the monitoring layer, the decision layer and the control layer to operate coordinately, and achieves the purpose of non-inductive control. The monitoring layer adopts a discrete event system theory to carry out top-level control, and details the change logic of the office state when a sensor event occurs or a user instruction arrives.
How to realize the non-inductive control of the smart home system according to the technical scheme provided by the invention is described in a specific embodiment. According to the intelligent home system, a normally used personal office is selected, a complete intelligent home system is built, and after a person enters the office, the ceiling lamp of the office area is automatically turned on, so that the system is used for carrying out non-inductive control explanation.
Fig. 1 is an overall layout diagram of an office according to the embodiment, which is divided into an office learning area and a guest resting area. Fig. 2 is a sensor distribution diagram of an office, including a human body sensor, a temperature sensor, a door/window sensor, a light intensity sensor, and the like. The office has four states, respectively: a sleep state, a rest state, a working state and a reporting state. When the office is in a dormant state, no user moves in the office; when the office is in a working state, the user can work at any position of the office; when the office is in a rest state, a user can have a rest at any position in the office; when the office is in a reporting state, the user uses the projector in the office for reporting.
The three-terminal network architecture of the office comprises a local integration terminal, a server terminal and a mobile terminal, wherein Websocket communication is adopted between the three terminals, as shown in figure 3. The three-layer management and control architecture comprises a monitoring layer, a decision-making layer and a control layer, wherein the monitoring layer tracks the state of an office according to the state changes of the sensors and the equipment and an instruction sent by a user and outputs the current state of the office to the decision-making layer; the decision layer judges the equipment to be regulated according to the output of the monitoring layer, designs an automatic control logic and sends a control instruction of the corresponding equipment to the control layer; the control layer controls the device according to the decision made by the decision layer. As shown in fig. 4.
The monitoring layer is implemented in a service layer of the server side. The state of the office is discrete and the transition of the state is triggered by events (sensor events and human-computer interaction events), so the invention utilizes the discrete event dynamic system theory to build a monitoring layer model. When a user moves indoors with various sensors and smart home single products, a series of sensor events can be triggered, meanwhile, the user can trigger a series of instruction events through man-machine interaction, the series of sensor events and the instruction events are converted into an observable event sequence through a state tree structure-based module, and then office state estimation is carried out through the observable events according to an established state observer.
The monitoring layer is constructed by the following steps:
the office state mainly includes two states of people using and no people using for a long time (more than half an hour), depending on d0(door/window sensor), m0～m3(human body sensor), mr(virtual body sensor) can be accurately judged, when m is0～m3When any one sensor is triggered, mrIs triggered and when the non-triggering time of any one sensor is less than 20 minutes, mrKeeping on; when m is0～m3When the non-trigger time of four sensors is more than 20 minutes, mrGo back off, so can be by mrTo determine whether there is a person in the current office.
Meanwhile, the intention of the user to rest and report is received by establishing virtual switches "break" and "report" on the HASS platform. For example, when the break switch is turned on, it indicates that the user wants to take a rest, and vice versa, it indicates that the user wants to end the rest and start work.
the office is divided into four states, namely a dormant state, a working state, a resting state and a reporting state. The states of the automaton are defined as: state 1: a dormant state; state 2: working state; state 3: a rest state; and 4: and reporting the state. The state set of the automaton is:
since the four states of the office are the final states for different cases of the system, the labeled state set of the automaton is:
the automaton's events represent transitions of the office between different states, and are located as follows:
b12office status changes from 1 to 2; b13Office status changes from 1 to 3; b14Office status changes from 1 to 4;
c21office status changes from 2 to 1; c. C23Office status changes from 2 to 3; c. C24Office status changes from 2 to 4;
d31office status changes from 3 to 1; d32Office status changes from 3 to 2; d34Office status changes from 3 to 4;
e42office status changes from 4 to 2; e.g. of the type43Office status changes from 4 to 3;
thus, the set of events:
∑＝{b12,b13,b14,c21,c23,c24,d31,d32,d34,e42,e43}
dynamic transfer process of office state is defined as transfer function
It describes the change of state when an event in the set of events Σ occurs. The transfer function is defined as follows:
(1，b12)＝2；(1，b13)＝3；(1，b14)＝4；
(2，c21)＝1；(2，c23)＝3；(2，c24)＝4；
(3，d31)＝1；(3，d32)＝2；(3，d34)＝4；
(4，e42)＝2；(4，e43)＝3；
since the initial state of the office is uncertain and all states are possible, it is assumed that
The automaton model finally built is shown in fig. 5.
And step 3: determining an observable event:
the sensor events and command events of the present invention are shown in the following table.
Thus, the set of sensor events:
instruction event set:
when any event sigma in the automaton event set sigma occurs, the sensor event set S is triggered by connectionsAnd instruction event set SdThe least events that uniquely determine the state transition in the one or several events are extracted, and the sequence of such one or several least events is called the observable event of event σ.
All robot events and their corresponding sensor and command event sequences and defined observable events are represented by the following table:
therefore, the set of observable events is defined as:
Θ＝{θ1,θ2,θ3,θ4,θ5,θ6}
and 4, step 4: determining an observable sequence of events:
the invention is provided with a wide scopeThe state tree structure model is constructed in a preferential manner. Initial state q of the systemstIndicated in grey, transitional state
Expressed in white, target status
Indicated in black. The state transition diagram of the state tree structure model of the present invention is shown in FIG. 6 below.
Based on the state tree structure model of fig. 6, sensor and command event sequences can be converted into observable event sequences. The office is in a dormant state, the user enters the door and works, and the automaton event occurring in the process is b12The corresponding sequence of sensor events is d0m0. For sequence d0m0When sensor event d0m0On arrival, the state tree generates an observable event θ1And returns to the initial state.
And 5: state observer based office state estimation
Firstly, all the automaton events in the automaton model G are replaced by corresponding observable events in the observable event set theta, and another uncertain automaton G can be obtainednd:
Gnd＝(Q,Θ,N,q0)
wherein ,
secondly, the uncertain automaton G is processedndConversion into its corresponding deterministic automaton, i.e. its state observer Gobs：
Gobs＝(X,Θ,ξ,x0)＝AC(2Q,Θ,ξ,Q0)
wherein ,
x0＝Q0，
according to the method of the state observer shown in step 5, a state observer is established as shown in fig. 7. According to this state observer, the user can determine the state of the office and the trigger condition for the change of the office state. The structural framework of the entire office state tracking problem is shown in fig. 8.
When automaton event b occurs after a person enters the office12That is, the user enters the office to change the office state from the sleep state to the work state, the first occurrence is the door and window sensor event d0What then occurs is a body sensor event m0The last occurrence is a door and window sensor event
However when d occurs0 and m0After the event, a change in office status can be determined.
After receiving the equipment state information transmitted by the local end, the server end judges the office state according to the method by calling the monitoring layer interface due to the occurrence of the event influencing the office state, and at the moment, the office is changed from the dormant state to the working state. And returning the result to the server side, and sending the result to the local integration end HASS by using Websocket communication.
And the decision layer judges the equipment to be regulated according to the output of the monitoring layer, designs a regulation and control sequence and an automatic control logic which meet the user comfort level experience, and sends a control instruction of the corresponding equipment to the control layer. The decision layer is realized in a local integration end, and various component operations during the change of the office state are realized by utilizing a Script in HASS. Script uses an independent Script building means, implemented as an entity. The invention realizes four scripts, namely a dormancy starting state, a working starting state, a rest starting state and a report starting state, which are decision-making layer strategies in four office states.
The decision of the device regulation order needs to satisfy two requirements: first, the logic between devices is to avoid conflicts and conflicts; secondly, because the sudden change of the device state brings discomfort to the user, optimization is required, and good experience is created for the user. Considering that the temperature and the humidity are in an automatic adjusting mode when the office is in working, resting and reporting states and the condition of sudden change does not exist, the invention mainly considers the influence of illumination change on users. Because the illumination of the sofa area is not a main illumination source of an office and is only used as a complementary light source of the sofa area, the influence of switching on and off the floor lamp on the illumination of the office is small, obvious influence can not be brought to a user, and the invention does not take consideration. To sum up, what affects the user experience is mainly the change of the desk area lighting control. The decision layer policy when the office is changed to the working state is shown in fig. 9.
And after the office state is changed into the working state, the decision layer judges that the top lamp of the working area should be turned on and sends the result to the control layer.
The input to the control layer is the output of the decision layer. The purpose of the control layer is to ensure that the device is adjusted in place, so the control layer consists of the actuators of the various components. For the virtual component of the present invention, the controller programmed to implement it performs control actions by changing the values of the variables representing the states in the component. And at the moment, the control layer receives a control instruction for turning on the office area top lamp and controls the office area top lamp to be turned on.
After a person enters an office, the decision layer carries out control decision and sends a control instruction to the control layer through office state estimation of the monitoring layer, so that automatic opening of a top lamp of the office area is realized, both hands of the person are liberated, non-inductive control of the office is realized, and user requirements are met.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.
Claims (5)
1. The utility model provides an intelligence house noninductive control system which characterized in that: the three-terminal network architecture of the system comprises a local integration terminal, a server terminal and a mobile terminal, wherein WebSocket communication is adopted between the three terminals; the three-layer management and control architecture of the system comprises a monitoring layer, a decision layer and a control layer, wherein the monitoring layer is located at a server end, the decision layer is located at a local integration end and the server end, and the control layer is located at the local integration end.
2. The smart home non-inductive control system according to claim 1, characterized in that: the monitoring layer tracks the state of the office according to the state changes of the sensors and the equipment and an instruction sent by a user, and outputs the current state of the office to the decision-making layer; the monitoring layer is realized by adopting a discrete event system theory, for a series of sensors and command events, event information of the system is obtained by a multi-sensor data fusion method, and the current state of the office is estimated according to the established state observer.
3. The smart home non-inductive control system according to claim 2, wherein: the construction method of the monitoring layer comprises the following steps:
step 1, defining sensors and user instructions which influence office states:
the office state is divided into two states of being used by people and being used by no people for a long time, and depends on d0(door/window sensor), m0～m3(human body sensor), mr(virtual body sensor) accurate judgment;
meanwhile, virtual switches 'break' and 'report' are established at a local end to receive rest and report instructions of a user;
step 2, establishing an automaton model:
the office is divided into four states: a sleep state (the user leaves the office for a long time), a working state, a rest state, and a reporting state; establishing an automaton model through the definition of each state and transition events among the states in an office; the automaton model is a quadruple, as shown by the following equation:
G＝(Q,∑,,q0,Qm)
wherein Q is a set of states; Σ is the event set; q x Σ → QIs a transfer function; q. q.s0Is a subset of states, determined by the initial state of the system;
is the set of tagged states of the system;
and step 3: determining an observable event:
defining the process in which each sensor is triggered and outputs state change information as a sensor event SsThe process of sending out each human-computer interaction instruction and receiving the instruction by the office is an instruction event Sd；
When any event sigma in the automaton event set sigma occurs, the sensor event set S is triggered by connectionsAnd instruction event set SdExtracting the least events which can uniquely determine the state transition in the one or more events, and calling the sequence formed by the one or more least events as observable events of the event sigma;
and 4, step 4: determining an observable sequence of events:
constructing a state tree containing all possible sensor event sequences in a breadth-first mode, and converting the sensor and instruction event sequences into observable event sequences;
the state tree is in an initial state, when a sensor event arrives, the state tree enters a corresponding branch and arrives at the next state, if the current state is a black mark, a corresponding observable event is formed, and meanwhile, the state tree returns to the initial state to wait for the formation of another observable event; if the current state is a white mark, continuing to wait for the next sensor event until the reached state is a black mark state, then generating a corresponding observable event, and returning the state tree to the initial state to wait for the formation of another observable event; in either the initial state or the white-marked state, upon occurrence of an instruction event, the state tree reaches the black-marked state and then generates a corresponding observable event, the state tree returning to the initial state waiting for the occurrence of another observable event;
and 5: constructing a state observer:
firstly, all the automaton events in the automaton model G are replaced by corresponding observable events in the observable event set theta, and another uncertain automaton G can be obtainednd:
Gnd＝(Q,Θ,N,q0)
wherein ,
secondly, the uncertain automaton G is processedndConversion into its corresponding deterministic automaton, i.e. its state observer Gobs：
Gobs＝(X,Θ,ξ,x0)＝AC(2Q,Θ,ξ,Q0)
wherein ,
x0＝Q0，
4. the smart home non-inductive control system according to claim 1, characterized in that: and the decision layer judges the equipment to be regulated according to the output of the monitoring layer, designs a regulation and control sequence and an automatic control logic which meet the user comfort level experience, and sends a control instruction of the corresponding equipment to the control layer.
5. The smart home non-inductive control system according to claim 1, characterized in that: and the control layer receives subsequent tasks customized by the decision layer and completes control work by changing the state variables of the virtual components.
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Cited By (3)
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| CN113219925A (en) * | 2021-05-12 | 2021-08-06 | 王耘 | Traditional Chinese medicine intelligent service system and model construction method thereof |
| CN114415539A (en) * | 2022-03-31 | 2022-04-29 | 广州爱瑟菲微智能电子有限公司 | Smart home control method, system, medium and computing device |
| WO2024036804A1 (en) * | 2022-08-18 | 2024-02-22 | 青岛海尔科技有限公司 | Intent instruction determining method and apparatus, storage medium, and electronic device |
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