CN117515652A - Heating equipment intelligent control method and device based on user action induction - Google Patents
Heating equipment intelligent control method and device based on user action induction Download PDFInfo
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- PCTMTFRHKVHKIS-BMFZQQSSSA-N (1s,3r,4e,6e,8e,10e,12e,14e,16e,18s,19r,20r,21s,25r,27r,30r,31r,33s,35r,37s,38r)-3-[(2r,3s,4s,5s,6r)-4-amino-3,5-dihydroxy-6-methyloxan-2-yl]oxy-19,25,27,30,31,33,35,37-octahydroxy-18,20,21-trimethyl-23-oxo-22,39-dioxabicyclo[33.3.1]nonatriaconta-4,6,8,10 Chemical compound C1C=C2C[C@@H](OS(O)(=O)=O)CC[C@]2(C)[C@@H]2[C@@H]1[C@@H]1CC[C@H]([C@H](C)CCCC(C)C)[C@@]1(C)CC2.O[C@H]1[C@@H](N)[C@H](O)[C@@H](C)O[C@H]1O[C@H]1/C=C/C=C/C=C/C=C/C=C/C=C/C=C/[C@H](C)[C@@H](O)[C@@H](C)[C@H](C)OC(=O)C[C@H](O)C[C@H](O)CC[C@@H](O)[C@H](O)C[C@H](O)C[C@](O)(C[C@H](O)[C@H]2C(O)=O)O[C@H]2C1 PCTMTFRHKVHKIS-BMFZQQSSSA-N 0.000 description 1
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24D—DOMESTIC- OR SPACE-HEATING SYSTEMS, e.g. CENTRAL HEATING SYSTEMS; DOMESTIC HOT-WATER SUPPLY SYSTEMS; ELEMENTS OR COMPONENTS THEREFOR
- F24D19/00—Details
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- Central Heating Systems (AREA)
Abstract
The invention discloses a heating equipment intelligent control method and a device based on user action induction, wherein the method comprises the following steps: when detecting that a target user exists in a management and control scene corresponding to heating equipment, acquiring action data of the target user in the management and control scene; analyzing the action data to obtain a plurality of action nodes of the target user in the management and control scene and node information of the target user in each action node; judging whether target nodes meeting preset heating control conditions exist in all the action nodes according to all the node information; when judging that the target nodes meeting the heating control conditions exist in all the action nodes, generating heating control parameters for the heating equipment according to the node information corresponding to the target nodes, and adjusting heating output of the heating equipment according to the heating control parameters. Therefore, by implementing the intelligent heating control method and the intelligent heating control device, the intelligent heating degree can be improved, and the real-time control accuracy of heating can be improved.
Description
Technical Field
The invention relates to the technical field of heating control, in particular to an intelligent control method and device for heating equipment based on user action induction.
Background
With the development and popularization of intelligent technologies, the intelligent technologies start to enter life of users, and one of applications of the intelligent technologies includes smart home. Meanwhile, the application of the intelligent home starts to merge with the personalized demands of the user, and meanwhile, a plurality of subsystems related to home life can be linked, such as security protection, light control, curtain control, intelligent home appliances, indoor heating and the like, so that brand-new home life experience is brought to the user. The indoor heating is to supply heat to the indoor environment to maintain a certain indoor temperature so as to create proper living conditions.
However, in the field of indoor intelligent heating, the degree of intellectualization of heating is not high enough, and only control of heating based on the timing and temperature setting requirements of users is remained. The energy consumption of heating control in actual intelligent control is large, and unnecessary energy waste exists. In addition, this intelligent heating can't adapt to user's real-time adjustment demand, leads to user's intelligent heating experience to feel poor. Therefore, aiming at the problems of low intelligent degree and unadapted user real-time heating requirement of the existing heating, the method for improving the intelligent degree of the heating and the real-time control accuracy of the heating is particularly important.
Disclosure of Invention
The invention aims to solve the technical problem of providing an intelligent control method and device for heating equipment based on user action induction, which can improve the intelligent degree of heating and the accuracy of real-time control of heating.
In order to solve the technical problems, a first aspect of the present invention discloses an intelligent control method for heating equipment based on user action induction, the method comprising:
when detecting that a target user exists in a control scene corresponding to heating equipment, acquiring action data of the target user in the control scene;
analyzing the action data to obtain a plurality of action nodes of the target user in the control scene and node information of the target user in each action node;
judging whether target nodes meeting preset heating control conditions exist in all the action nodes according to all the node information;
and when judging that target nodes meeting the heating control conditions exist in all the action nodes, generating heating control parameters for the heating equipment according to the node information corresponding to the target nodes, and adjusting heating output of the heating equipment according to the heating control parameters.
In a first aspect of the present invention, the analyzing the action data to obtain a plurality of action nodes of the target user in the control scene and node information of the target user in each action node includes:
determining a plurality of action nodes with the stay time of the target user in the control scene exceeding the preset stay time according to the action data, and extracting node data corresponding to each action node from the action data by taking each action node as a reference;
generating a tracking model for the target user by taking the user profile of the target user as a reference, wherein the tracking model comprises a plurality of tracking points corresponding to the user profile;
analyzing each piece of node data by combining the tracking model to obtain model tracking information of the target user at each action node, wherein the model tracking information is used as node information of the target user at each action node;
the model tracking information comprises a model moving track, a model posture and a model stay time of the tracking model at each action node.
In an optional implementation manner, in a first aspect of the present invention, the analyzing each piece of the node data in combination with the tracking model to obtain model tracking information of the target user at each action node includes:
For each action node, determining a model starting position recorded by the tracking model in the action node according to the node data corresponding to the action node;
determining all model movement information of the tracking model at the action node by taking the initial position of the model as a base point; all the model movement information comprises a model movement track, a model stay time and a model posture;
matching the model gesture according to a preset action database to obtain a target action gesture matched with the model gesture in the action database and gesture information corresponding to the target action gesture;
determining the model moving track, the model stay time, the target action gesture and the gesture information corresponding to the target action gesture as model tracking information of the action node;
the model movement tracks corresponding to all the action nodes are determined by the following modes:
for each action node, determining element coordinate movement information of the action node in a unit tracking time by taking a preset tracking element as a unit;
drawing a track graph corresponding to the tracking element according to all the element coordinate movement information to obtain a model movement track serving as the action node;
Wherein the preset tracking elements comprise the whole tracking model or all single tracking points.
In an optional implementation manner, in a first aspect of the present invention, the determining, according to all the node information, whether a target node that meets a preset heating control condition exists in all the action nodes includes:
according to all the node information, determining state information of the target user at each action node, wherein the state information comprises static information and/or dynamic information, the static information comprises the current user state of the target user, and the user state comprises one of a sleep rest state, a leisure and entertainment state, a movement state, a bathing state and a working state; the dynamic information is the information which is recorded correspondingly when the target user switches between two different user states; wherein each user state corresponds to a heating control temperature of the heating equipment;
when the state information comprises the static information, judging whether a target state matched with a preset regulation state required to be subjected to heating control exists in the user state corresponding to each action node of the target user; if yes, determining the action node corresponding to the target state as a target node meeting a preset heating control condition;
Wherein the adjustment state includes the sleep resting state, the movement state, and the bathing state;
when the state information comprises the dynamic information, judging whether temperature difference nodes with the temperature difference larger than a preset temperature difference of the heating control temperatures corresponding to the two user states switched currently exist in all the action nodes; if yes, determining the temperature difference node as a target node meeting a preset heating control condition.
As an optional implementation manner, in a first aspect of the present invention, the generating, according to the node information corresponding to the target node, a heating control parameter for the heating apparatus includes:
when the node information corresponding to the target node only comprises the static information, generating a first control parameter for the heating equipment as a heating control parameter according to a target heating control temperature corresponding to the target state, the acquired current scene temperature of the control scene, the equipment operation parameter of the heating equipment and the heat loss data of the control scene;
when the node information corresponding to the target node comprises the dynamic information, acquiring the temperature before switching of the control scene before the target user switches the user state and the temperature difference corresponding to the two user states currently switched by the target user;
And generating a second control parameter for the heating equipment according to the temperature before switching, the temperature difference, the equipment operation parameter and the heat loss data, and taking the second control parameter as a heating control parameter.
As an optional implementation manner, in the first aspect of the present invention, after the adjusting the heating output of the heating apparatus according to the heating control parameter, the method further includes:
determining action prediction information of the target user according to node information of the target user at each action node and by combining with historical work and rest data of the target user in the control scene, wherein the action prediction information comprises predicted stay time of the target user at the target node, predicted mobile nodes of the target user and predicted user states of the target user;
judging whether the motion prediction information meets the heating control conditions, generating a prediction control parameter for the prediction mobile node according to the motion prediction information when judging that the motion prediction information meets the heating control conditions, and adjusting heating output of the heating equipment according to the prediction control parameter when detecting that the target user moves to the prediction mobile node;
The predicted mobile node is a node with a probability that the target user moves from the target node to a certain node higher than a preset first calculation probability; the predicted user state is a state that the probability of the target user switching from the current user state to a certain user state is higher than a preset second calculation probability.
As an optional implementation manner, in the first aspect of the present invention, the determining whether the motion prediction information meets the heating control condition includes:
determining the heating control temperature corresponding to the predicted mobile node, and recording the heating control temperature as a temperature to be controlled;
calculating a temperature difference between the temperature to be controlled and the acquired temperature of the control scene, and recording the temperature difference as a predicted temperature difference, wherein the temperature of the control scene is the temperature of the control scene after the heating output of the heating equipment is regulated according to the heating control parameter;
determining the corresponding user state when the target user moves to the predicted mobile node according to the work and rest data, and marking the user state as a predicted user state;
when the predicted temperature difference is larger than the preset temperature difference and/or the predicted user state is attributed to the adjustment state, determining that the action prediction information meets the heating control condition;
And generating a predictive control parameter for the predictive mobile node according to the action predictive information, including:
and generating a predictive control parameter for the heating equipment according to the predictive temperature difference, the predictive user state, the detention time and the heat loss data of the control scene of the equipment operation parameter of the heating equipment.
The second aspect of the invention discloses an intelligent control device for heating equipment based on user action induction, which comprises:
the system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring action data of a target user in a control scene corresponding to heating equipment when the target user exists in the control scene;
the analysis module is used for analyzing the action data to obtain a plurality of action nodes of the target user in the control scene and node information of the target user in each action node;
the first judging module is used for judging whether target nodes meeting preset heating control conditions exist in all the action nodes according to all the node information;
the generating module is used for generating heating control parameters for the heating equipment according to the node information corresponding to the target nodes when the first judging module judges that the target nodes meeting the heating control conditions exist in all the action nodes;
And the adjusting module is used for adjusting the heating output of the heating equipment according to the heating control parameters.
In a second aspect of the present invention, the analyzing module analyzes the action data to obtain a plurality of action nodes of the target user in the control scene and node information of the target user in each action node specifically includes:
determining a plurality of action nodes with the stay time of the target user in the control scene exceeding the preset stay time according to the action data, and extracting node data corresponding to each action node from the action data by taking each action node as a reference;
generating a tracking model for the target user by taking the user profile of the target user as a reference, wherein the tracking model comprises a plurality of tracking points corresponding to the user profile;
analyzing each piece of node data by combining the tracking model to obtain model tracking information of the target user at each action node, wherein the model tracking information is used as node information of the target user at each action node;
the model tracking information comprises a model moving track, a model posture and a model stay time of the tracking model at each action node.
In a second aspect of the present invention, the analyzing module analyzes each piece of the node data in combination with the tracking model to obtain model tracking information of the target user at each action node specifically includes:
for each action node, determining a model starting position recorded by the tracking model in the action node according to the node data corresponding to the action node;
determining all model movement information of the tracking model at the action node by taking the initial position of the model as a base point; all the model movement information comprises a model movement track, a model stay time and a model posture;
matching the model gesture according to a preset action database to obtain a target action gesture matched with the model gesture in the action database and gesture information corresponding to the target action gesture;
determining the model moving track, the model stay time, the target action gesture and the gesture information corresponding to the target action gesture as model tracking information of the action node;
the model movement tracks corresponding to all the action nodes are determined by the following modes:
for each action node, determining element coordinate movement information of the action node in a unit tracking time by taking a preset tracking element as a unit;
Drawing a track graph corresponding to the tracking element according to all the element coordinate movement information to obtain a model movement track serving as the action node;
wherein the preset tracking elements comprise the whole tracking model or all single tracking points.
In a second aspect of the present invention, the method for determining whether a target node satisfying a preset heating control condition exists in all the action nodes according to all the node information includes:
according to all the node information, determining state information of the target user at each action node, wherein the state information comprises static information and/or dynamic information, the static information comprises the current user state of the target user, and the user state comprises one of a sleep rest state, a leisure and entertainment state, a movement state, a bathing state and a working state; the dynamic information is the information which is recorded correspondingly when the target user switches between two different user states; wherein each user state corresponds to a heating control temperature of the heating equipment;
When the state information comprises the static information, judging whether a target state matched with a preset regulation state required to be subjected to heating control exists in the user state corresponding to each action node of the target user; if yes, determining the action node corresponding to the target state as a target node meeting a preset heating control condition;
wherein the adjustment state includes the sleep resting state, the movement state, and the bathing state;
when the state information comprises the dynamic information, judging whether temperature difference nodes with the temperature difference larger than a preset temperature difference of the heating control temperatures corresponding to the two user states switched currently exist in all the action nodes; if yes, determining the temperature difference node as a target node meeting a preset heating control condition.
In a second aspect of the present invention, as an optional implementation manner, the generating module generates the heating control parameter for the heating apparatus according to the node information corresponding to the target node specifically includes:
when the node information corresponding to the target node only comprises the static information, generating a first control parameter for the heating equipment as a heating control parameter according to a target heating control temperature corresponding to the target state, the acquired current scene temperature of the control scene, the equipment operation parameter of the heating equipment and the heat loss data of the control scene;
When the node information corresponding to the target node comprises the dynamic information, acquiring the temperature before switching of the control scene before the target user switches the user state and the temperature difference corresponding to the two user states currently switched by the target user;
and generating a second control parameter for the heating equipment according to the temperature before switching, the temperature difference, the equipment operation parameter and the heat loss data, and taking the second control parameter as a heating control parameter.
As an alternative embodiment, in the second aspect of the present invention, the apparatus further includes:
the determining module is used for determining action prediction information of the target user according to node information of the target user at each action node after the adjusting module adjusts heating output of the heating equipment according to the heating control parameters and combining history record operation and rest data of the target user at the control scene, wherein the action prediction information comprises predicted residence time of the target user at the target node, predicted mobile nodes of the target user and predicted user states of the target user;
The second judging module is used for judging whether the action prediction information meets the heating control conditions or not;
the generation module is further configured to generate a prediction control parameter for the predicted mobile node according to the motion prediction information when the second determination module determines that the motion prediction information meets the heating control condition;
the adjusting module is further used for adjusting heating output of the heating equipment according to the prediction control parameter when the target user is detected to move to the prediction mobile node;
the predicted mobile node is a node with a probability that the target user moves from the target node to a certain node higher than a preset first calculation probability; the predicted user state is a state that the probability of the target user switching from the current user state to a certain user state is higher than a preset second calculation probability.
In a second aspect of the present invention, the mode of determining, by the second determining module, whether the motion prediction information meets the heating control condition specifically includes:
determining the heating control temperature corresponding to the predicted mobile node, and recording the heating control temperature as a temperature to be controlled;
Calculating a temperature difference between the temperature to be controlled and the acquired temperature of the control scene, and recording the temperature difference as a predicted temperature difference, wherein the temperature of the control scene is the temperature of the control scene after the heating output of the heating equipment is regulated according to the heating control parameter;
determining the corresponding user state when the target user moves to the predicted mobile node according to the work and rest data, and marking the user state as a predicted user state;
when the predicted temperature difference is larger than the preset temperature difference and/or the predicted user state is attributed to the adjustment state, determining that the action prediction information meets the heating control condition;
and the mode of generating the predicted control parameter for the predicted mobile node by the generating module according to the action prediction information specifically comprises the following steps:
and generating a predictive control parameter for the heating equipment according to the predictive temperature difference, the predictive user state, the detention time and the heat loss data of the control scene of the equipment operation parameter of the heating equipment.
The third aspect of the invention discloses another intelligent control device for heating equipment based on user action induction, which comprises:
A memory storing executable program code;
a processor coupled to the memory;
the processor invokes the executable program codes stored in the memory to execute the intelligent control method of the heating equipment based on user action induction disclosed in the first aspect of the invention.
A fourth aspect of the present invention discloses a computer storage medium, where computer instructions are stored, where the computer instructions are used to execute the intelligent control method for a heating apparatus based on user action sensing disclosed in the first aspect of the present invention when the computer instructions are called.
Compared with the prior art, the embodiment of the invention has the following beneficial effects:
in an embodiment of the invention, an intelligent control method for heating equipment based on user action induction is provided, and the method comprises the following steps: when detecting that a target user exists in a management and control scene corresponding to heating equipment, acquiring action data of the target user in the management and control scene; analyzing the action data to obtain a plurality of action nodes of the target user in the management and control scene and node information of the target user in each action node; judging whether target nodes meeting preset heating control conditions exist in all the action nodes according to all the node information; when judging that the target nodes meeting the heating control conditions exist in all the action nodes, generating heating control parameters for the heating equipment according to the node information corresponding to the target nodes, and adjusting heating output of the heating equipment according to the heating control parameters. Therefore, the intelligent heating control flow based on user action induction is set, when the target user is detected in the scene where the heating equipment is located, the target user can be used as a tracking target, and the action data of the target user in the management and control scene can be automatically acquired and data analysis can be carried out; based on the obtained node information, comparing and judging according to preset heating control conditions, if the node information is determined to meet the heating control conditions, executing corresponding heating control parameter generation and execution; the invention realizes the real-time intelligent regulation and control of the heating equipment through the collection and analysis of the motion data of the target user, improves the control intellectualization of the heating equipment, and simultaneously improves the real-time performance of the control and the suitability and accuracy of the current state (motion data) of the heating control and the target user.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a heating equipment intelligent control method based on user action induction, which is disclosed in the embodiment of the invention;
FIG. 2 is a schematic flow chart of another intelligent control method of heating equipment based on user action sensing according to an embodiment of the present invention;
FIG. 3 is a schematic structural diagram of an intelligent control device for heating equipment based on user action sensing according to an embodiment of the present invention;
FIG. 4 is a schematic structural diagram of another intelligent control device for heating equipment based on user action sensing according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of another intelligent control device for heating equipment based on user action sensing according to an embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The terms first, second and the like in the description and in the claims and in the above-described figures are used for distinguishing between different objects and not necessarily for describing a sequential or chronological order. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, apparatus, article, or article that comprises a list of steps or elements is not limited to only those listed but may optionally include other steps or elements not listed or inherent to such process, method, article, or article.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the invention. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.
The invention discloses an intelligent control method and device for heating equipment based on user action induction, wherein an intelligent heating control flow based on user action induction is set, when a target user is detected in a scene where heating equipment is located, the target user can be used as a tracking target, and action data of the target user in the control scene can be automatically acquired and data analysis can be performed; based on the obtained node information, comparing and judging according to preset heating control conditions, if the node information is determined to meet the heating control conditions, executing corresponding heating control parameter generation and execution; the invention realizes the real-time intelligent regulation and control of the heating equipment through the collection and analysis of the motion data of the target user, improves the control intellectualization of the heating equipment, and simultaneously improves the real-time performance of the control and the suitability and accuracy of the current state (motion data) of the heating control and the target user. The following will describe in detail.
Example 1
Referring to fig. 1, fig. 1 is a flow chart of an intelligent control method for a heating device based on user action sensing according to an embodiment of the present invention. The method for controlling the heating equipment based on the user action induction described in fig. 1 can be applied to the heating equipment intelligent control device based on the user action induction, and the embodiment of the invention is not limited. As shown in fig. 1, the intelligent control method for heating equipment based on user action sensing may include the following operations:
101. when detecting that a target user exists in a management and control scene corresponding to the heating equipment, collecting action data of the target user in the management and control scene.
In the embodiment of the invention, the heating equipment can be provided with a first sensor for scanning/sensing a user, and the first sensor is used for scanning and detecting whether a target user exists in a management and control scene where the heating equipment is located; optionally, the heating device may further be provided with a second sensor, which is used for controlling the second sensor to perform user tracking and data recording on the target user after the first sensor determines that the target user is detected.
In the embodiment of the invention, the first sensor and the second sensor can be the same sensor, that is, the functions of the first sensor and the second sensor are integrated on the same sensor; or two different sensors; the first sensor and the second sensor can be configured on heating equipment or independently installed in a control scene.
When at least one of the first sensor and the second sensor is independently arranged in the management and control scene, a corresponding data interaction link is established between the two sensors and the heating equipment, and the transmission of control instructions and the interaction of data can be carried out.
102. And analyzing the action data to obtain a plurality of action nodes of the target user in the management and control scene and node information of the target user in each action node.
In the embodiment of the invention, the data content of the action data acquired and detected by the sensor is disordered, and classification, analysis, arrangement and the like are required to be performed by a background system. Meanwhile, in the embodiment of the invention, required target data (a plurality of action nodes and node information of each action node) is required to be extracted from complex action data; thereby facilitating the subsequent further analysis and arrangement of data based on each action node.
103. And judging whether target nodes meeting preset heating control conditions exist in all the action nodes according to all the node information.
In the embodiment of the invention, heating control conditions for judging whether heating output adjustment is required for heating equipment or not are set; after the node information is determined, the comparison and judgment whether the heating output adjustment is needed or not is carried out later by taking the heating control condition as a judgment standard.
104. When judging that the target nodes meeting the heating control conditions exist in all the action nodes, generating heating control parameters for the heating equipment according to the node information corresponding to the target nodes, and adjusting heating output of the heating equipment according to the heating control parameters.
Therefore, the intelligent control method of the heating equipment based on the user action induction described in fig. 1 is implemented, an intelligent heating control flow based on the user action induction is set, and when a target user is detected in a scene where the heating equipment is located, the target user can be used as a tracking target, and the action data of the target user in the control scene can be automatically acquired and analyzed; based on the obtained node information, comparing and judging according to preset heating control conditions, if the node information is determined to meet the heating control conditions, executing corresponding heating control parameter generation and execution; the invention realizes the real-time intelligent regulation and control of the heating equipment through the collection and analysis of the motion data of the target user, improves the control intellectualization of the heating equipment, and simultaneously improves the real-time performance of the control and the suitability and accuracy of the current state (motion data) of the heating control and the target user.
In an optional embodiment, step 102 of analyzing the action data to obtain a plurality of action nodes of the target user in the control scene and node information of the target user in each action node specifically includes:
determining a plurality of action nodes with the stay time exceeding the preset stay time of the target user in the management and control scene according to the action data, and extracting node data corresponding to each action node from the action data by taking each action node as a reference;
generating a tracking model aiming at a target user by taking the user profile of the target user as a reference, wherein the tracking model comprises a plurality of tracking points corresponding to the user profile;
analyzing each piece of node data by combining the tracking model to obtain model tracking information of the target user at each action node, wherein the model tracking information is used as node information of the target user at each action node;
the model tracking information comprises a model moving track, a model posture and a model stay time of a tracking model at each action node.
In this optional embodiment, further, the determining, according to the action data, the plurality of action nodes whose stay time of the target user in the management and control scene exceeds the preset stay time specifically includes:
Dividing the control scene into a plurality of sub-scenes, wherein each sub-scene corresponds to a preset action node of a target user;
collecting the stay time of a target user in each sub-scene, wherein the stay time comprises a continuous stay time and/or a discontinuous accumulated stay time;
and determining a plurality of action nodes of which the stay time of the target user in the management and control scene exceeds the preset stay time from the stay time corresponding to all the sub-scenes.
In this alternative embodiment, the duration of stay specifically refers to the duration of stay of the target user in the sub-scene for a unit of detection time (e.g., within 5 minutes), and the target user does not leave the sub-scene during the timer; the accumulated stay time length comprises the sum value of the accumulated stay time length of the target user in the sub-scene and the leaving time length; if the target user stays in sub-scene a for 10 minutes, stays in sub-scene B for 1 minute, and returns to sub-scene a for 20 minutes, the cumulative stay time includes one piece of time information that the target user stays in sub-scene a for 30 minutes and leaves 1 minute at 11 th minute. Further, for the illustrated cumulative residence time, it may be determined that the sub-scenario a is an action node, and at the same time, the residence time of the target user in the sub-scenario B does not exceed the preset residence time (e.g. 5 minutes) for 1 minute, which indicates that the sub-scenario B may not be determined as an action node.
In this optional embodiment, when sorting the action data, the action data may be extracted by using a preset residence time as a sorting standard; specifically, the control scene can be divided into four nodes of ABCD, and each node corresponds to a division range; when finishing the action data, analyzing the action data by taking the stay time of the target user at each node as a reference, for example, setting the preset stay time to be 2 minutes; in an actual scene, if the target user stays at the node A for 10 minutes; then the node B is routed, and the recorded retention time is 10 seconds; then passing through the node C and remaining at the node C for more than 30 minutes, and determining the determined action nodes as the node A and the node C; the selection of the action node is not limited in this alternative embodiment.
In this optional embodiment, when the background system generates the tracking model with the user profile as a reference, a three-dimensional modeling space may be established with the control scene; the tracking model of the target user is a portrait model in the three-dimensional modeling space; the portrait model may be an equal ratio conversion model corresponding to the user profile, or may be a node model composed of a simple few tracking nodes.
Alternatively, when the tracking model is a node model, only a few points of the user profile may be selected as tracking points; if the head selects three tracking points to represent the position of the head of the user; the limbs of the user select 2-4 tracking points to represent the limbs of the user respectively; representing the torso of the user with 4-8 tracking points; therefore, the setting of the tracking points is simplified, so that the data volume required to be processed subsequently is reduced; the number of the tracking points can be increased or decreased along with actual application, and the embodiment of the invention is not limited.
In this optional embodiment, when analyzing the motion data, a plurality of motion nodes are obtained by dividing the motion data with a preset residence time as a reference; the dividing of the action nodes screens partial data which do not meet the conditions (the stay time does not exceed the preset stay time), and is beneficial to reducing the data processing amount and the interference of incoherent data; further, through further analysis of the tracking model duration and information of the target user, node information of the target user at each action node is accurately obtained, and accuracy and reliability of determining the node information are improved.
In this optional embodiment, the method for analyzing each piece of node data in combination with the tracking model to obtain the model tracking information of the target user at each action node specifically includes:
For each action node, determining a model starting position recorded by the tracking model in the action node according to node data corresponding to the action node;
determining all model movement information of the tracking model at the action node by taking the initial position of the model as a base point; all the model movement information comprises a model movement track, a model stay time and a model posture;
matching the model gesture according to a preset action database to obtain a target action gesture matched with the model gesture in the action database and gesture information corresponding to the target action gesture;
determining a model moving track, a model stay time, a target action gesture and gesture information corresponding to the target action gesture as model tracking information of the action node;
the model movement tracks corresponding to all the action nodes are determined by the following modes:
for each action node, determining element coordinate movement information of the action node in unit tracking time by taking a preset tracking element as a unit;
drawing a track diagram corresponding to the tracking element according to the coordinate movement information of all the elements to obtain a model movement track serving as the action node;
the preset tracking elements comprise an integral tracking model or all single tracking points.
As described above, the tracking model may be an integral model corresponding to the contour of the target user, or may be simply split into a plurality of tracking points.
It can be seen that in this alternative embodiment, when node data is actually analyzed in conjunction with the tracking model, its steps are refined to the determination of the record of the starting position of the model, the model movement trajectory, the model dwell time, and the model pose; then, matching the target action gesture and gesture information thereof is carried out through an action database, so that the accuracy and the information richness of the determined model tracking information are improved; in addition, when the determination of the model moving track is carried out, at least two track graphs (an integral tracking model and a single tracking point) can be drawn, so that the track graph drawing means are enriched, the visual track graph drawing is carried out, and the viewing convenience of the moving information of the user is improved.
In another optional embodiment, the step 104 of determining whether the target node satisfying the preset heating control condition exists in all the action nodes according to all the node information specifically includes:
according to all node information, determining state information of a target user at each action node, wherein the state information comprises static information and/or dynamic information, the static information comprises the current user state of the target user, and the user state comprises one of a sleep rest state, a leisure and entertainment state, a movement state, a bathing state and a working state; the dynamic information is the information which is recorded correspondingly when the target user switches between two different user states; wherein each user state corresponds to a heating control temperature of a heating device;
In this optional embodiment, it should be noted that, the sleep resting state may be a state where the user is currently sleeping and resting, may be a rest, may be deep sleep; the leisure and entertainment state comprises watching television, playing games, watching movies, playing mobile phones, and even doing housework and cooking; the motion state is the state corresponding to the current body-building motion of the user; the bathing state may refer to a state in a user's bathing, a state corresponding to 20 minutes after the user's bathing, etc., and embodiments of the present invention are not limited.
In this optional embodiment, when the state information includes static information, it is determined whether a target state matching with a preset adjustment state in which heating management and control needs to be performed exists in a user state corresponding to each action node by the target user; if yes, determining an action node corresponding to the target state as a target node meeting preset heating control conditions;
wherein the regulation state comprises a sleep resting state, a movement state and a bathing state;
when the state information comprises dynamic information, judging whether temperature difference nodes with temperature differences larger than preset temperature differences of heating control temperatures corresponding to two user states switched currently exist in all the action nodes; if yes, determining the temperature difference node as a target node meeting the preset heating control conditions.
In this optional embodiment, a plurality of adjustment states that need to perform heating adjustment, such as a sleep rest state, may be set in advance, where the heating device needs to perform adjustment of heating output, so as to improve sleep experience of a user; other states are similar, when a target user is in a motion state, the body temperature of the target user generally rises, heating equipment can intelligently reduce heating output, and the situation that the body temperature of the user rises and the heating output is unchanged, so that the motion body feeling of the user is not the same is avoided; when the target user is in a state of motion for half an hour or 1 hour, the body temperature of the target user starts to fall back, and accordingly, the heating output which is adjusted down before needs to be intelligently improved. The body temperature of the target user rises and falls due to the bath state and the movement state, and the heating equipment needs to be intelligently adjusted.
In this optional embodiment, when the state information includes dynamic information, the setting of the temperature difference between the two user states refers to the above description about the change of the body temperature of the target user in the movement state, and the embodiments of the present invention are not repeated.
Therefore, in the alternative embodiment, the judging conditions of the static and dynamic information are set, and the detail degree of the heating control condition is improved, so that when the heating control condition is actually taken as a reference for judgment, the adaptive judgment can be performed, the setting accuracy of the judging condition is improved, and meanwhile, the accuracy of the determination of the target node obtained by screening the action node based on the judging condition is improved.
In still another optional embodiment, the method for generating the heating control parameter for the heating device according to the node information corresponding to the target node specifically includes:
when node information corresponding to a target node only comprises static information, generating a first control parameter for heating equipment according to a target heating control temperature corresponding to a target state, the acquired current scene temperature of a management and control scene, equipment operation parameters of the heating equipment and heat loss data of the management and control scene, and taking the first control parameter as a heating control parameter;
when the node information corresponding to the target node comprises dynamic information, acquiring the temperature before switching of a control scene before switching of the user state by the target user and the temperature difference corresponding to the two user states currently switched by the target user;
and generating a second control parameter for the heating equipment according to the temperature before switching, the temperature difference, the equipment operation parameter and the heat loss data as a heating control parameter.
In this optional embodiment, a generation scheme of heating control parameters for different node information is set, which deals with generating heating control parameters of static information and dynamic information, so that a preparation consideration scheme for generating heating control parameters is richer and more accurate; the method is favorable for improving the accuracy and reliability of the generated heating control parameters.
Example two
Referring to fig. 2, fig. 2 is a flow chart of another intelligent control method for a heating apparatus based on user action sensing according to an embodiment of the present invention. The intelligent control method of the heating equipment based on the user action induction described in fig. 2 can be applied to the intelligent control device of the heating equipment based on the user action induction, and the embodiment of the invention is not limited. As shown in fig. 2, the intelligent control method for the heating equipment based on the user action sensing can comprise the following operations:
201. when detecting that a target user exists in a management and control scene corresponding to the heating equipment, collecting action data of the target user in the management and control scene.
202. And analyzing the action data to obtain a plurality of action nodes of the target user in the management and control scene and node information of the target user in each action node.
203. And judging whether target nodes meeting preset heating control conditions exist in all the action nodes according to all the node information.
204. When judging that the target nodes meeting the heating control conditions exist in all the action nodes, generating heating control parameters for the heating equipment according to the node information corresponding to the target nodes, and adjusting heating output of the heating equipment according to the heating control parameters.
In the embodiment of the present invention, the other descriptions of step 201 to step 204 refer to the other specific descriptions of step 101 to step 104 in the first embodiment, and the description of the embodiment of the present invention is omitted.
205. And according to the node information of the target user at each action node, determining the action prediction information of the target user by combining the action information of the target user in the management and control scene of the history record.
In the embodiment of the invention, the action prediction information comprises predicted retention time of the target user in the target node, predicted mobile nodes of the target user and predicted user states of the target user.
206. And judging whether the motion prediction information meets the heating control condition or not, and generating prediction control parameters for predicting the mobile node according to the motion prediction information when the motion prediction information meets the heating control condition.
207. And when the target user is detected to move to the predictive mobile node, adjusting the heating output of the heating equipment according to the predictive control parameter.
In the embodiment of the invention, the predicted mobile node is a node with a probability that a target user moves from the target node to a certain node higher than a preset first calculation probability; the predicted user state is a state in which the probability of the target user switching from the current user state to a certain user state is higher than a preset second calculation probability.
Therefore, implementing the intelligent control method of the heating equipment based on user action induction described in fig. 2 sets a movement prediction mechanism for a target user, and can intelligently combine the work and rest data of the user to extract corresponding action prediction information, thereby realizing comparison judgment of heating control conditions and generation and execution of prediction control parameters after the judgment is passed; the setting of the movement prediction mechanism is favorable for improving the adjustment response speed of the parameter adjustment of the heating equipment to a certain extent.
In an alternative embodiment, the determining, in step 206, whether the motion prediction information meets the heating control condition specifically includes:
determining a heating control temperature corresponding to the predicted mobile node, and recording the heating control temperature as a temperature to be controlled;
calculating the temperature difference between the temperature to be controlled and the acquired temperature of the control scene, and recording the temperature difference as a predicted temperature difference, wherein the temperature of the control scene after the temperature is adjusted according to the heating control parameters and the heating output of the heating equipment;
determining a corresponding user state when a target user moves to a predicted mobile node according to the work and rest data, and marking the user state as a predicted user state;
when the predicted temperature difference is larger than the preset temperature difference and/or the predicted user state is attributed to the adjustment state, determining that the action predicted information meets the heating control condition;
And, the method for generating the prediction control parameter for predicting the mobile node according to the motion prediction information in the step 206 specifically includes:
and generating predictive control parameters for the heating equipment according to the predictive temperature difference, the predictive user state, the residence time and the heat loss data of the equipment operation parameter management and control scene of the heating equipment.
In this optional embodiment, when the generation of the predicted control parameter is performed, the requirement of the heating control condition can be determined by referring to the comparison, and the determination of the temperature to be controlled, the calculation of the predicted temperature difference, and the determination of the predicted user temperature can be performed, so that the comparison with the heating control condition is performed, the accuracy of comparing the motion prediction information of the target user with the heating control condition is improved, and the accuracy and reliability of generating the predicted control parameter subsequently are improved.
Example III
Referring to fig. 3, fig. 3 is a schematic structural diagram of an intelligent control device for a heating apparatus based on user action sensing according to an embodiment of the present invention. The heating equipment intelligent control device based on user action induction can be a heating equipment intelligent control terminal, equipment, a system or a server based on user action induction, wherein the server can be a local server, a remote server or a cloud server (also called cloud server), and when the server is a non-cloud server, the non-cloud server can be in communication connection with the cloud server. As shown in fig. 3, the intelligent control device for heating equipment based on user action sensing may include an acquisition module 301, an analysis module 302, a first judgment module 303, a generation module 304, and an adjustment module 305, where:
The acquisition module 301 is configured to acquire action data of a target user in a management and control scene when detecting that the target user exists in the management and control scene corresponding to the heating device;
the analysis module 302 is configured to analyze the action data to obtain a plurality of action nodes of the target user in the management and control scene and node information of the target user in each action node;
a first judging module 303, configured to judge whether a target node that meets a preset heating control condition exists in all the action nodes according to all the node information;
a generating module 304, configured to generate heating control parameters for the heating apparatus according to node information corresponding to the target node when the first judging module 303 judges that the target node satisfying the heating control condition exists in all the action nodes;
the adjusting module 305 is configured to adjust a heating output of the heating apparatus according to the heating control parameter.
As can be seen, implementing the intelligent control device for heating equipment based on user action induction described in fig. 3 sets an intelligent heating control flow based on user action induction, and when a target user is detected in a scene where the heating equipment is located, the target user can be used as a tracking target, and action data of the target user in the control scene can be automatically collected and analyzed; based on the obtained node information, comparing and judging according to preset heating control conditions, if the node information is determined to meet the heating control conditions, executing corresponding heating control parameter generation and execution; the invention realizes the real-time intelligent regulation and control of the heating equipment through the collection and analysis of the motion data of the target user, improves the control intellectualization of the heating equipment, and simultaneously improves the real-time performance of the control and the suitability and accuracy of the current state (motion data) of the heating control and the target user.
In an optional embodiment, the analysis module 302 analyzes the action data to obtain a plurality of action nodes of the target user in the control scene and node information of the target user in each action node specifically includes:
determining a plurality of action nodes with the stay time exceeding the preset stay time of the target user in the management and control scene according to the action data, and extracting node data corresponding to each action node from the action data by taking each action node as a reference;
generating a tracking model aiming at a target user by taking the user profile of the target user as a reference, wherein the tracking model comprises a plurality of tracking points corresponding to the user profile;
analyzing each piece of node data by combining the tracking model to obtain model tracking information of the target user at each action node, wherein the model tracking information is used as node information of the target user at each action node;
the model tracking information comprises a model moving track, a model posture and a model stay time of a tracking model at each action node.
In this optional embodiment, when analyzing the motion data, a plurality of motion nodes are obtained by dividing the motion data with a preset residence time as a reference; the dividing of the action nodes screens partial data which do not meet the conditions (the stay time does not exceed the preset stay time), and is beneficial to reducing the data processing amount and the interference of incoherent data; further, through further analysis of the tracking model duration and information of the target user, node information of the target user at each action node is accurately obtained, and accuracy and reliability of determining the node information are improved.
In this alternative embodiment, the analysis module 302 analyzes each piece of node data in combination with the tracking model, and the mode for obtaining the model tracking information of the target user at each action node specifically includes:
for each action node, determining a model starting position recorded by the tracking model in the action node according to node data corresponding to the action node;
determining all model movement information of the tracking model at the action node by taking the initial position of the model as a base point; all the model movement information comprises a model movement track, a model stay time and a model posture;
matching the model gesture according to a preset action database to obtain a target action gesture matched with the model gesture in the action database and gesture information corresponding to the target action gesture;
determining a model moving track, a model stay time, a target action gesture and gesture information corresponding to the target action gesture as model tracking information of the action node;
the model movement tracks corresponding to all the action nodes are determined by the following modes:
for each action node, determining element coordinate movement information of the action node in unit tracking time by taking a preset tracking element as a unit;
Drawing a track diagram corresponding to the tracking element according to the coordinate movement information of all the elements to obtain a model movement track serving as the action node;
the preset tracking elements comprise an integral tracking model or all single tracking points.
It can be seen that in this alternative embodiment, when node data is actually analyzed in conjunction with the tracking model, its steps are refined to the determination of the record of the starting position of the model, the model movement trajectory, the model dwell time, and the model pose; then, matching the target action gesture and gesture information thereof is carried out through an action database, so that the accuracy and the information richness of the determined model tracking information are improved; in addition, when the determination of the model moving track is carried out, at least two track graphs (an integral tracking model and a single tracking point) can be drawn, so that the track graph drawing means are enriched, the visual track graph drawing is carried out, and the viewing convenience of the moving information of the user is improved.
In another alternative embodiment, the first determining module 303 determines, according to all node information, whether there is a target node that meets a preset heating control condition in all the action nodes, where the method specifically includes:
According to all node information, determining state information of a target user at each action node, wherein the state information comprises static information and/or dynamic information, the static information comprises the current user state of the target user, and the user state comprises one of a sleep rest state, a leisure and entertainment state, a movement state, a bathing state and a working state; the dynamic information is the information which is recorded correspondingly when the target user switches between two different user states; wherein each user state corresponds to a heating control temperature of a heating device;
when the state information comprises static information, judging whether a target state matched with a preset regulation state required to be subjected to heating control exists in a user state corresponding to each action node of a target user; if yes, determining an action node corresponding to the target state as a target node meeting preset heating control conditions;
wherein the regulation state comprises a sleep resting state, a movement state and a bathing state;
when the state information comprises dynamic information, judging whether temperature difference nodes with temperature differences larger than preset temperature differences of heating control temperatures corresponding to two user states switched currently exist in all the action nodes; if yes, determining the temperature difference node as a target node meeting the preset heating control conditions.
Therefore, in the alternative embodiment, the judging conditions of the static and dynamic information are set, and the detail degree of the heating control condition is improved, so that when the heating control condition is actually taken as a reference for judgment, the adaptive judgment can be performed, the setting accuracy of the judging condition is improved, and meanwhile, the accuracy of the determination of the target node obtained by screening the action node based on the judging condition is improved.
In yet another alternative embodiment, the generating module 304 generates the heating control parameter for the heating apparatus according to the node information corresponding to the target node specifically includes:
when node information corresponding to a target node only comprises static information, generating a first control parameter for heating equipment according to a target heating control temperature corresponding to a target state, the acquired current scene temperature of a management and control scene, equipment operation parameters of the heating equipment and heat loss data of the management and control scene, and taking the first control parameter as a heating control parameter;
when the node information corresponding to the target node comprises dynamic information, acquiring the temperature before switching of a control scene before switching of the user state by the target user and the temperature difference corresponding to the two user states currently switched by the target user;
And generating a second control parameter for the heating equipment according to the temperature before switching, the temperature difference, the equipment operation parameter and the heat loss data as a heating control parameter.
In this optional embodiment, a generation scheme of heating control parameters for different node information is set, which deals with generating heating control parameters of static information and dynamic information, so that a preparation consideration scheme for generating heating control parameters is richer and more accurate; the method is favorable for improving the accuracy and reliability of the generated heating control parameters.
In another alternative embodiment, as shown in fig. 4, the apparatus further includes a determining module 306, and a second judging module 307, where:
a determining module 306, configured to determine, after the adjusting module 305 adjusts the heating output of the heating device according to the heating control parameter, action prediction information of the target user according to node information of the target user at each action node and in combination with operation and rest data of the target user in the management and control scene, where the action prediction information includes a predicted residence time of the target user at the target node, a predicted mobile node of the target user, and a predicted user state of the target user;
A second judging module 307, configured to judge whether the motion prediction information meets a heating control condition;
the generating module 304 is further configured to generate a prediction control parameter for predicting the mobile node according to the motion prediction information when the second judging module 307 judges that the motion prediction information meets the heating control condition;
the adjusting module 305 is further configured to adjust a heating output of the heating apparatus according to the predictive control parameter when it is detected that the target user moves to the predictive mobile node;
the method comprises the steps of predicting a mobile node to be a node with a probability that a target user moves to a certain node from the target node higher than a preset first calculation probability; the predicted user state is a state in which the probability of the target user switching from the current user state to a certain user state is higher than a preset second calculation probability.
In the optional embodiment, a movement prediction mechanism for the target user is set, so that the corresponding action prediction information can be extracted by intelligently combining with the work and rest data of the user, and further comparison judgment of heating control conditions and prediction control parameter generation and execution after the judgment are achieved; the setting of the movement prediction mechanism is favorable for improving the adjustment response speed of the parameter adjustment of the heating equipment to a certain extent.
In yet another alternative embodiment, the second determining module 307 determines whether the motion prediction information meets the heating control condition specifically includes:
determining a heating control temperature corresponding to the predicted mobile node, and recording the heating control temperature as a temperature to be controlled;
calculating the temperature difference between the temperature to be controlled and the acquired temperature of the control scene, and recording the temperature difference as a predicted temperature difference, wherein the temperature of the control scene after the temperature is adjusted according to the heating control parameters and the heating output of the heating equipment;
determining a corresponding user state when a target user moves to a predicted mobile node according to the work and rest data, and marking the user state as a predicted user state;
when the predicted temperature difference is larger than the preset temperature difference and/or the predicted user state is attributed to the adjustment state, determining that the action predicted information meets the heating control condition;
and, the mode of generating the predicted control parameter for the predicted mobile node by the generating module 304 according to the motion prediction information specifically includes:
and generating predictive control parameters for the heating equipment according to the predictive temperature difference, the predictive user state, the residence time and the heat loss data of the equipment operation parameter management and control scene of the heating equipment.
In this optional embodiment, when the generation of the predicted control parameter is performed, the requirement of the heating control condition can be determined by referring to the comparison, and the determination of the temperature to be controlled, the calculation of the predicted temperature difference, and the determination of the predicted user temperature can be performed, so that the comparison with the heating control condition is performed, the accuracy of comparing the motion prediction information of the target user with the heating control condition is improved, and the accuracy and reliability of generating the predicted control parameter subsequently are improved.
Example IV
Referring to fig. 5, fig. 5 is a schematic structural diagram of another intelligent control device for a heating apparatus based on user action sensing according to an embodiment of the present invention. As shown in fig. 5, the intelligent control device for heating equipment based on user action sensing may include:
a memory 401 storing executable program codes;
a processor 402 coupled with the memory 401;
the processor 402 invokes executable program codes stored in the memory 401 to execute the steps in the intelligent control method for heating equipment based on user action sensing described in the first embodiment or the second embodiment of the present invention.
Example five
The embodiment of the invention discloses a computer storage medium which stores computer instructions for executing the steps in the intelligent control method of heating equipment based on user action induction described in the first embodiment or the second embodiment of the invention when the computer instructions are called.
Example six
An embodiment of the present invention discloses a computer program product, which includes a non-transitory computer storage medium storing a computer program, and the computer program is operable to cause a computer to execute the steps in the intelligent control method for heating equipment based on user action sensing described in the first embodiment or the second embodiment.
The apparatus embodiments described above are merely illustrative, in which the modules illustrated as separate components may or may not be physically separate, and the components shown as modules may or may not be physical, i.e., may be located in one place, or may be distributed over multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above detailed description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course by means of hardware. Based on such understanding, the foregoing technical solutions may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer storage medium including Read-Only Memory (ROM), random access Memory (Random Access Memory, RAM), programmable Read-Only Memory (PROM), erasable programmable Read-Only Memory (Erasable Programmable Read Only Memory, EPROM), one-time programmable Read-Only Memory (OTPROM), electrically erasable programmable Read-Only Memory (EEPROM), compact disc Read-Only Memory (Compact Disc Read-Only Memory, CD-ROM) or other optical disc Memory, magnetic disk Memory, tape Memory, or any other medium readable by a computer that can be used to carry or store data.
Finally, it should be noted that: the embodiment of the invention discloses an intelligent control method and device for heating equipment based on user action induction, which are disclosed by the embodiment of the invention only for illustrating the technical scheme of the invention, but not limiting the technical scheme; although the invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art will understand that; the technical scheme recorded in the various embodiments can be modified or part of technical features in the technical scheme can be replaced equivalently; such modifications and substitutions do not depart from the spirit and scope of the corresponding technical solutions.
Claims (10)
1. An intelligent control method of heating equipment based on user action induction is characterized by comprising the following steps:
when detecting that a target user exists in a control scene corresponding to heating equipment, acquiring action data of the target user in the control scene;
analyzing the action data to obtain a plurality of action nodes of the target user in the control scene and node information of the target user in each action node;
judging whether target nodes meeting preset heating control conditions exist in all the action nodes according to all the node information;
And when judging that target nodes meeting the heating control conditions exist in all the action nodes, generating heating control parameters for the heating equipment according to the node information corresponding to the target nodes, and adjusting heating output of the heating equipment according to the heating control parameters.
2. The intelligent control method for heating equipment based on user action induction according to claim 1, wherein the analyzing the action data to obtain a plurality of action nodes of the target user in the control scene and node information of the target user in each action node comprises:
determining a plurality of action nodes with the stay time of the target user in the control scene exceeding the preset stay time according to the action data, and extracting node data corresponding to each action node from the action data by taking each action node as a reference;
generating a tracking model for the target user by taking the user profile of the target user as a reference, wherein the tracking model comprises a plurality of tracking points corresponding to the user profile;
analyzing each piece of node data by combining the tracking model to obtain model tracking information of the target user at each action node, wherein the model tracking information is used as node information of the target user at each action node;
The model tracking information comprises a model moving track, a model posture and a model stay time of the tracking model at each action node.
3. The intelligent control method for heating equipment based on user action induction according to claim 2, wherein the analyzing each piece of node data in combination with the tracking model to obtain model tracking information of the target user at each action node comprises:
for each action node, determining a model starting position recorded by the tracking model in the action node according to the node data corresponding to the action node;
determining all model movement information of the tracking model at the action node by taking the initial position of the model as a base point; all the model movement information comprises a model movement track, a model stay time and a model posture;
matching the model gesture according to a preset action database to obtain a target action gesture matched with the model gesture in the action database and gesture information corresponding to the target action gesture;
determining the model moving track, the model stay time, the target action gesture and the gesture information corresponding to the target action gesture as model tracking information of the action node;
The model movement tracks corresponding to all the action nodes are determined by the following modes:
for each action node, determining element coordinate movement information of the action node in a unit tracking time by taking a preset tracking element as a unit;
drawing a track graph corresponding to the tracking element according to all the element coordinate movement information to obtain a model movement track serving as the action node;
wherein the preset tracking elements comprise the whole tracking model or all single tracking points.
4. A method for intelligently controlling a heating apparatus based on user action sensing according to claim 2 or 3, wherein the determining whether a target node satisfying a preset heating control condition exists in all the action nodes according to all the node information includes:
according to all the node information, determining state information of the target user at each action node, wherein the state information comprises static information and/or dynamic information, the static information comprises the current user state of the target user, and the user state comprises one of a sleep rest state, a leisure and entertainment state, a movement state, a bathing state and a working state; the dynamic information is the information which is recorded correspondingly when the target user switches between two different user states; wherein each user state corresponds to a heating control temperature of the heating equipment;
When the state information comprises the static information, judging whether a target state matched with a preset regulation state required to be subjected to heating control exists in the user state corresponding to each action node of the target user; if yes, determining the action node corresponding to the target state as a target node meeting a preset heating control condition;
wherein the adjustment state includes the sleep resting state, the movement state, and the bathing state;
when the state information comprises the dynamic information, judging whether temperature difference nodes with the temperature difference larger than a preset temperature difference of the heating control temperatures corresponding to the two user states switched currently exist in all the action nodes; if yes, determining the temperature difference node as a target node meeting a preset heating control condition.
5. The intelligent control method for heating equipment based on user action sensing according to claim 4, wherein the generating heating control parameters for the heating equipment according to the node information corresponding to the target node comprises:
when the node information corresponding to the target node only comprises the static information, generating a first control parameter for the heating equipment as a heating control parameter according to a target heating control temperature corresponding to the target state, the acquired current scene temperature of the control scene, the equipment operation parameter of the heating equipment and the heat loss data of the control scene;
When the node information corresponding to the target node comprises the dynamic information, acquiring the temperature before switching of the control scene before the target user switches the user state and the temperature difference corresponding to the two user states currently switched by the target user;
and generating a second control parameter for the heating equipment according to the temperature before switching, the temperature difference, the equipment operation parameter and the heat loss data, and taking the second control parameter as a heating control parameter.
6. The intelligent control method for heating equipment based on user action sensing according to claim 4, wherein after the heating output of the heating equipment is adjusted according to the heating control parameter, the method further comprises:
determining action prediction information of the target user according to node information of the target user at each action node and by combining with historical work and rest data of the target user in the control scene, wherein the action prediction information comprises predicted stay time of the target user at the target node, predicted mobile nodes of the target user and predicted user states of the target user;
Judging whether the motion prediction information meets the heating control conditions, generating a prediction control parameter for the prediction mobile node according to the motion prediction information when judging that the motion prediction information meets the heating control conditions, and adjusting heating output of the heating equipment according to the prediction control parameter when detecting that the target user moves to the prediction mobile node;
the predicted mobile node is a node with a probability that the target user moves from the target node to a certain node higher than a preset first calculation probability; the predicted user state is a state that the probability of the target user switching from the current user state to a certain user state is higher than a preset second calculation probability.
7. The intelligent control method for heating equipment based on user action sensing according to claim 6, wherein the determining whether the action prediction information satisfies the heating control condition comprises:
determining the heating control temperature corresponding to the predicted mobile node, and recording the heating control temperature as a temperature to be controlled;
calculating a temperature difference between the temperature to be controlled and the acquired temperature of the control scene, and recording the temperature difference as a predicted temperature difference, wherein the temperature of the control scene is the temperature of the control scene after the heating output of the heating equipment is regulated according to the heating control parameter;
Determining the corresponding user state when the target user moves to the predicted mobile node according to the work and rest data, and marking the user state as a predicted user state;
when the predicted temperature difference is larger than the preset temperature difference and/or the predicted user state is attributed to the adjustment state, determining that the action prediction information meets the heating control condition;
and generating a predictive control parameter for the predictive mobile node according to the action predictive information, including:
and generating a predictive control parameter for the heating equipment according to the predictive temperature difference, the predictive user state, the detention time and the heat loss data of the control scene of the equipment operation parameter of the heating equipment.
8. Heating equipment intelligence management and control device based on user action response, characterized in that, the device includes:
the system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring action data of a target user in a control scene corresponding to heating equipment when the target user exists in the control scene;
the analysis module is used for analyzing the action data to obtain a plurality of action nodes of the target user in the control scene and node information of the target user in each action node;
The first judging module is used for judging whether target nodes meeting preset heating control conditions exist in all the action nodes according to all the node information;
the generating module is used for generating heating control parameters for the heating equipment according to the node information corresponding to the target nodes when the first judging module judges that the target nodes meeting the heating control conditions exist in all the action nodes;
and the adjusting module is used for adjusting the heating output of the heating equipment according to the heating control parameters.
9. Heating equipment intelligence management and control device based on user action response, characterized in that, the device includes:
a memory storing executable program code;
a processor coupled to the memory;
the processor invokes the executable program code stored in the memory to perform the user action sensing based intelligent management and control method of a heating apparatus as claimed in any one of claims 1 to 7.
10. A computer storage medium storing computer instructions which, when invoked, are adapted to perform the user action sensing based intelligent control method of a heating installation as claimed in any one of claims 1 to 7.
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