An automatic intelligent device scene interaction processing system based on an internet of things

Abstract

This invention relates to the field of smart home control technology and discloses an automated smart device scene interaction processing system based on the Internet of Things (IoT). The system uses an automated process as its core. After responding to a preset trigger event, and provided that optional pre-verification checks pass, it acquires a snapshot of key parameters and information representing the latest state of the device. Based on preset rules, it generates the final target state of the device and calculates individual state items and values ​​sequentially according to a user-defined overall change process. Each calculated state item undergoes manual or automatic verification. If the verification passes, corresponding adjustments are executed; if the verification fails, no corresponding control command is output, but the subsequent calculation process continues. After calculation, the system re-acquires the current key parameters and verifies their consistency with the key parameter snapshot. If the parameters change, the current process terminates, and a new automated process is triggered by the changed parameters. The current process ends when the information representing the latest state of the device matches the final target state.

Description

Technical Field

[0001] This invention relates to the field of smart home control technology, specifically to an automated smart device scene interaction processing system based on the Internet of Things. Background Technology

[0002] With the development of IoT technology, smart home systems are becoming increasingly popular. Existing smart home control systems typically allow users to control individual devices via mobile applications or voice assistants, or set simple scheduled tasks and scene linkages. However, in practical applications, the following significant technical shortcomings still exist: First, the existing system has a single execution method, requiring users to piece together a large number of fragmented trigger-execution rules. This not only has a high configuration threshold, but also makes it difficult to predict the final execution result when multiple rules are executed in parallel, which can easily lead to logical conflicts and equipment malfunctions, making it impossible to form a unified and stable control system.

[0003] Second, the existing system's judgment of the presence of people is limited to a simple binary judgment of whether someone is there or not. It cannot identify the state of the space that a user is about to enter in advance, resulting in a delay in device response. Users need to go through an uncomfortable process of device change from the initial state to the target state, and cannot achieve a smooth experience that can be prepared in advance.

[0004] Third, after users manually modify the device status, the existing system lacks a reasonable takeover and recovery mechanism. Either the automatic system will overwrite the user's manual settings, or the manual operation will lock the entire set of automated logic of the device for a long time, making it impossible to achieve a balance between manual priority and automatic recovery at the single status item level.

[0005] Fourth, for devices that can serve multiple spaces simultaneously, existing systems mostly adopt a management method with fixed room ownership, which can only realize the simple logic of "closing only after all associated spaces are empty". This cannot adapt to the real-world usage scenarios of users moving across spaces, and the device control logic is rigid, with poor energy efficiency and practicality.

[0006] Fifth, existing systems mostly adjust the lighting environment by simple switching and fixed brightness threshold adjustment, lacking accurate calculation of the complex propagation, superposition effect and distance attenuation of multiple light sources in multiple spaces. This makes it impossible to achieve uniform brightness transition and fine control across spaces, resulting in a poor user lighting environment experience.

[0007] Sixth, the existing automated processes are merely simple action execution nodes, lacking continuous iteration, parameter consistency verification, and conflict termination mechanisms. They cannot achieve gradual adjustment of equipment status, and are prone to cyclic execution and control conflicts after parameter changes, resulting in insufficient system stability.

[0008] Therefore, it does not meet the existing needs, so we propose an automated intelligent device scene interaction processing system based on the Internet of Things. Summary of the Invention

[0009] The purpose of this invention is to provide an automated intelligent device scene interaction processing system based on the Internet of Things, in order to solve the problems of existing systems such as single execution mode, lack of reasonable takeover and recovery mechanism, difficulty in smoothing out state changes that may cause user discomfort, and relatively simple system logic.

[0010] To achieve the above objectives, the present invention provides the following technical solution: an automated intelligent device scene interaction processing system based on the Internet of Things, comprising a core control layer, wherein the core control layer serves as the central hub of the system's automated process, and includes: The parameter acquisition unit is used to acquire parameter information related to the target physical space, the target device connected to the Internet of Things, and the user's preset rules in response to a preset trigger event. The device status generation unit is used to generate the final target status of the target device based on the first snapshot of key parameters, information representing the latest status of the device, and user-preset rules. It also calculates the individual status items and their status values ​​that should be adjusted in this instance according to the overall change process defined by the user, forming the intermediate status that the device should achieve. A manual or automatic verification unit is used to verify the manual or automatic parameters corresponding to each individual state item obtained in each calculation, so as to determine whether the intermediate state is allowed to be executed by the automated process. The execution unit is used to output control commands that match the status items to be adjusted in this operation to the target device and drive the device to execute them after the verification passes; if the verification fails, the corresponding control commands are not output. The process control unit is used to update the information representing the latest state of the equipment with the state items and their state values ​​obtained in this calculation after each calculation, and to re-acquire the current key parameters and the snapshot of the key parameters for consistency verification; when the two are consistent, the calculation of subsequent state items continues; when the two are inconsistent, the current automation process is terminated, and a new automation process is triggered again by the changed parameters; when the information representing the latest state of the equipment is consistent with the final target state, the current automation process ends.

[0011] Preferably, in the process control unit, the verification result of the manual or automatic verification unit does not affect the continuous advancement of the calculation main line of the current automated process; If a single status item fails verification, only the output of the control command for that status item will be blocked; the verification, execution, and subsequent calculation processes of other status items will not be blocked.

[0012] Preferably, the automated process further includes a pre-test step, which is performed before the first parameter acquisition; if the pre-test fails, the process terminates directly and does not proceed to the parameter acquisition and subsequent calculation steps; different equipment categories and different automated process categories correspond to preset pre-test logic.

[0013] Preferably, the information representing the latest state of the device includes state information obtained from logical updates, and / or the current state information of the device acquired by the system in real time; Subsequent calculations are based on the device's actual state obtained initially and the logically latest state obtained from each round of calculations. When the system meets the preset conditions for accuracy and timeliness of state acquisition, subsequent calculations are performed based on the latest acquired current real state of the device, or the latest logical state is corrected based on the latest acquired state before continuing.

[0014] Preferably, the user-preset rules include the final target value corresponding to each status item of the target device, and the preset change order of each status item in the overall change process; the process control unit determines the individual status item and its status value to be promoted this time based on the preset change order, the current change stage of the device, and information representing the latest status of the device.

[0015] Preferably, the final target state of the target device is determined by scene parameters, human parameters, and other preset parameters related to the control of the target device; manual or automatic parameters are used to verify whether the corresponding state item is allowed to be executed; the automated process uniformly receives and processes multiple parameters to generate the final target state of the target device under the current process and the intermediate states of each calculation.

[0016] Preferably, it also includes a human perception module, which is used to generate human presence parameters in the target space. The human presence parameters include three states: present, likely to be present, and absent. The "potentially occupied state" refers to the pre-triggered state of the target space when it is currently unoccupied, but a user has already arrived at a preset area where it can be predicted that the user will enter the space. Once in this state, the system can pre-drive the devices in the target space to perform pre-operation actions. The human perception module includes a rest state unit, a feasibility determination unit, and a human result unit. The rest state unit is used to generate rest parameters, including unrest, imminent unrest, and full rest, based on the parameters of the space where rest scenarios are frequently present, the scene parameters, the prediction sensor parameters, and the parameters for determining whether there are people in the space where rest scenarios are frequently present. The feasibility determination unit is used to generate feasibility determination parameters based on the "at home or away" parameter and preset conditions, indicating whether the property is occupied, whether it is likely to be occupied, and whether it is unoccupied. The "person in the result unit" is used to integrate the rest parameters, feasibility judgment parameters, and sensor data, and generate the final person in each space through preset logical operation rules.

[0017] Preferably, it also includes a scene interaction module, which is used to configure variable scene parameters for the physical space with configurable scene parameters, and to set a scene activation unit for each space with configured scene parameters; in this embodiment of the invention, the space with configurable scene parameters includes a constant space and a task space, and the channel space is not configured with independent scene parameters.

[0018] The scene activation unit is used to forcibly trigger the automated process of the associated device after being triggered, without changing the current scene parameters, so that the device in the space is restored to the standard state corresponding to the scene. Once a scene is activated, the manual or automatic parameters of the corresponding status item of the device that belongs to the space and whose automated process is triggered by the scene activation are reset to the pending judgment state.

[0019] Preferably, the parameter acquisition unit also acquires device affiliation-related parameters, which include whether the device can be affiliated to a corresponding non-local space parameter and device affiliation parameters; The system also includes a device affiliation management module, which dynamically adjusts the affiliation relationship between the device's current space and non-current spaces based on the space's human presence parameters, whether the device can be affiliated to a corresponding non-current space parameters, and mandatory affiliation conditions; at any given time, the current affiliation space of a single device is unique; the device affiliation management module includes an affiliation feasibility unit and an affiliation decision unit. The attribution feasibility unit is used to generate parameters to determine whether a device can be attributed to a corresponding non-local space based on the person present in the non-local space, preset attribution conditions, and the device's manual or automatic parameters. The attribution decision unit is used to perform a general attribution decision based on the presence parameter of the current space, the current attribution parameter of the device, and the attribution parameters of all corresponding non-current spaces of the device; it is also used to obtain the priority, target space, and presence parameter of the target space corresponding to all mandatory attribution conditions when the mandatory attribution conditions change, and determine the target space with the highest priority from the candidates that simultaneously meet the mandatory attribution conditions and whose presence parameter of the target space is occupied; when the device is not currently assigned to the target space, the device attribution parameter is adjusted to the target space.

[0020] Preferably, it also includes a manual / automatic determination module, which includes a manual marking unit, a value comparison and determination unit, and an automatic recovery unit; The manual marking unit is used to mark the manual or automatic parameters of the device state and its associated state as manual when a change in the device state triggered by a non-automatic process is detected. The automatic recovery unit is used to reset the manual or automatic parameters to a waiting-for-determination state when it detects that the space where the device is located and all the spaces that can belong to are unoccupied, and the duration exceeds a preset delay time, so that the automated process can take over control again. When the preset forced takeover conditions are met, the system resets the manual or automatic parameters of the corresponding status item to the waiting judgment state and executes the target state generated by the automated process; the forced takeover conditions include scene activation triggering and forced affiliation conditions being met and causing device affiliation adjustment; wherein, the forced affiliation conditions include one or more of user preset conditions, scene change conditions and scene activation conditions.

[0021] Preferably, the parameter acquisition unit also acquires the parameters of the brightness calibration, and the system further includes a brightness calibration and calculation module; The brightness calibration and calculation module includes a spatial brightness sensor, a brightness source classification unit, a basic data unit, a channel propagation calculation unit, and a brightness requirement calculation unit. The spatial brightness sensor is used to acquire brightness measurement data for each physical space. The brightness source classification unit is used to divide the physical space into brightness source space, brightness-dependent space, and channel space according to the space type and scene status. The brightness calibration and calculation module calculates the target brightness value for each space by combining the space type, device light output characteristics, spatial distance relationship, and brightness measurement data. Among them, the brightness value of the brightness source space serves as a reference parameter for the brightness-dependent space and the channel space. The required state of the device in the brightness source space is determined by scene parameters and related control parameters. The required brightness value of the device in the brightness-dependent space is calculated by inverse solving based on the brightness value of the corresponding brightness-dependent space. The required brightness value of the device in the channel space is calculated by inverse solving based on the required brightness value of the corresponding device.

[0022] Preferably, it also includes a space classification module and an equipment classification module; The space classification module is used to divide the physical space into a constant space, a task space, and a passage space. The constant space is the space that the user will use regardless of whether there is a task requirement. The task space is the space that the user will only use when there is a task requirement. The passage space is the space that serves as a passageway. The device classification module is used to classify IoT devices connected to the system into switch devices, status devices, and switch / status devices. Switch devices only support on / off control and have no other adjustable operating states. Status devices only support operating state adjustment and cannot control the overall start / stop of the device. Switch / status devices support both overall start / stop control and operating state adjustment. Based on spatial classification results and equipment classification results, the system matches differentiated automated process branches, triggering rules, pre-verification conditions, and parameter verification logic for different spatial types and different equipment types.

[0023] Preferably, at least some of the parameters output by the functional modules can be used as the basis for parameter verification, updating or automatic process re-triggering of other functional modules, forming a parameter linkage closed loop; the preset trigger events include one or more of the following: scene parameter change, parameter change when a person is present, manual or automatic parameter change, parameter change when at home or away, sensor detection value change, scene activation trigger, and user manual trigger.

[0024] A method for handling scene interaction of automated smart devices based on the Internet of Things includes the following steps: S1: In response to a preset trigger event, perform a preset pre-check. If the check fails, the process terminates. If the check passes, obtain a snapshot of the key parameters that this process depends on, information representing the latest status of the target device, and parameter information related to the target physical space, the target device, and user preset rules. S2: Generate the final target state of the target device based on the snapshot of the key parameters, the information representing the latest state of the device, and the user-preset rules; S3: According to the user-defined overall change process, calculate the individual state items that should be adjusted this time and their state values ​​one by one to form the intermediate state that the device should achieve; S4: For a single state item obtained in this calculation, verify the manual or automatic parameters corresponding to the state item. If the verification passes, output the matching control command to the target device and drive its execution. If the verification fails, do not output the corresponding control command. S5: Update the information representing the latest state of the device with the state items and their state values ​​obtained in this calculation, and re-acquire the current key parameters and the snapshot of the key parameters for consistency verification; when the two are consistent, return to step S3 to continue the calculation of subsequent state items; when the two are inconsistent, terminate the current process and return to step S1 to re-trigger a new automated process with the changed parameters. S6: When the information representing the latest state of the device is consistent with the final target state, end the current automation process.

[0025] An electronic device includes a processor and a memory, wherein the memory stores computer-executable instructions, and when the computer-executable instructions are executed by the processor, the above-described method for handling scene interaction of automated intelligent devices based on the Internet of Things is implemented.

[0026] A computer-readable storage medium storing a computer program, wherein when executed by a processor, the computer program implements the aforementioned method for scene interaction processing of automated intelligent devices based on the Internet of Things (IoT). A computer program product comprising a computer program, wherein when executed by a processor, the computer program implements the aforementioned method for scene interaction processing of automated intelligent devices based on the Internet of Things (IoT).

[0027] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention constructs a unified control architecture based on a parameter system and with automated processes as the core, replacing the traditional fragmented rule splicing mode. By linking multiple system parameters together to generate the target state of the device, it significantly reduces the user configuration threshold, reduces logical conflicts and unpredictable results, and improves the stability and consistency of system control. 2. This invention sets up a state where there may be a person in the middle, and combines multi-level logical operations to accurately determine the state of the person. It can drive the equipment to complete pre-preparation before the user enters the space, eliminating the discomfort caused by the sudden change in the state of the equipment after the user enters the space, and realizing the advance and smoothness of the equipment response.

[0028] 3. This invention achieves manual priority control of a single state item dimension through a refined manual / automatic judgment mechanism. At the same time, through the automatic recovery mechanism in the unattended state and the forced takeover mechanism under specific conditions, it retains the user's manual operation rights while avoiding the problem of manual operation blocking automatic takeover for a long time, thus achieving a balance between manual intervention and automatic control.

[0029] 4. This invention uses a dynamic device attribution mechanism to dynamically adjust the device's assigned space based on the user's status and spatial relationships, replacing the rigid traditional fixed room attribution model. This perfectly adapts to the user's cross-space activity scenarios, making the control logic of multi-space service devices more in line with the user's real usage habits, while also improving the energy efficiency of the devices.

[0030] 5. This invention constructs a cross-spatial brightness calculation system based on spatial type, device light output characteristics, and distance attenuation through a brightness calibration and calculation module. This enables refined calculation and control of multi-source and multi-spatial lighting environments, allowing for natural and smooth transitions between different spaces and significantly improving the user's lighting environment experience.

[0031] 6. This invention uses the automated process as the core control hub of the system. By taking snapshots of key parameters, information representing the latest state of the equipment, advancing individual state items step by step according to the overall change process, consistency verification, and a parameter change termination and restart mechanism, it achieves progressive convergence control of the equipment state and avoids misjudgment and loop execution problems caused by state readback delays, parameter mutations, or control conflicts, thus greatly improving the stability and control accuracy of the system operation. Attached Figure Description

[0032] Figure 1 This is a schematic diagram of the overall system architecture of the present invention; Figure 2 This is a schematic diagram of the main process of the IoT-based automated intelligent device scene interaction processing method of the present invention; Figure 3 This is a schematic diagram of the human parameter determination logic in the result unit of the present invention; Figure 4 This is a general ownership decision flowchart for the device ownership management module of the present invention; Figure 5 This is a flowchart of the manual / automatic determination module of the present invention; Figure 6 This is a flowchart of the recovery process of the manual / automatic determination module of the present invention; Figure 7 This is a flowchart of the brightness calibration and calculation module of the present invention; Figure 8 For the present invention Figure 2 A simplified main process diagram.

[0033] Figure 9 This is a flowchart of the mandatory attribution decision process of the device attribution management module of the present invention. Detailed Implementation

[0034] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0035] To clarify the technical boundaries of this invention, the core terms are first uniformly defined: Scene parameters: These are used to express the user's overall expectations of the spatial environment in a certain scenario. They are not directly equal to the final execution result of the device. The system needs to combine the current status of various parameters with the user's preset rules to further calculate and generate the target state that the device should achieve.

[0036] Scene activation: Without switching scene parameters, the automated process of the relevant device is retried to restore the device state to the standard state corresponding to the current scene. In essence, it is a recalculation and reset of the current scene.

[0037] "Potentially Occupied State": This refers to a pre-triggered state in which a space is currently unoccupied, but a user has already arrived at a preset area where it can be predicted that the user will enter the space. This state allows devices within the space to perform pre-operation actions in advance as expected by the user.

[0038] Device attribution parameters: When a device can serve multiple spaces, the space parameter that is ultimately determined by the system as the primary attribution at the current moment; multiple attributable spaces can be set, but at any given moment, the current attribution space of a single device is unique.

[0039] Manual or Automatic Parameter: This parameter indicates whether the corresponding status item of a device is currently allowed to be modified by the automated process. It includes two core states: manual and waiting for judgment. When marked as manual, the automated process cannot modify the corresponding status item. When marked as waiting for judgment, the automated process can take over control normally.

[0040] Brightness benchmark parameter: The reference parameter value used to achieve uniform brightness distribution of devices in each space. This parameter can be used to calculate the brightness value that devices in the brightness-dependent space and channel space should achieve.

[0041] Non-first iteration: When users have multiple gradual adjustment requirements for the device, after the first state adjustment, the system continues to generate the subsequent iterative calculation process of the device target state based on the previous execution result, the current parameter state, and the step size rules.

[0042] Space Activation or Pending Parameters: These parameters determine whether the corresponding space is currently involved in the "someone may be coming soon" judgment and related subsequent parameter calculations. In the pending activation state, the space does not participate in the advance preparation logic and related calculations. In the activated state, the space can enter the prediction and linkage calculation according to the rules.

[0043] Please see Figures 1 to 9 The first embodiment provided by the present invention: An IoT-based automated intelligent device scene interaction processing system includes a core control layer and a functional module layer. The core control layer constitutes the core control hub of the system, carrying out the full-link execution of the automated process. The output parameters of each module in the functional module layer are connected to the core control layer and jointly participate in the generation and control of the device's target state.

[0044] The core control layer includes a parameter acquisition unit, a device status generation unit, a manual or automatic verification unit, an execution unit, and a process control unit. Each unit works together to execute the complete logic of the automated process, as detailed below: Parameter Acquisition Unit: Responding to a preset trigger event, after passing pre-verification, it acquires snapshots of key parameters dependent on this process, the current status information of the target device, and various parameters related to the target physical space, IoT-connected target devices, and user-preset rules, including but not limited to scene parameters, "person in" parameters, manual or automatic parameters, device affiliation parameters, brightness target parameters, and "on / off" parameters. If the trigger event causes changes to parameters dependent on subsequent processes, a delay time is set after the trigger node to ensure that the parameters are updated before executing the parameter acquisition process. The delay time can be configured by the user and must be greater than the maximum time required for parameter updates.

[0045] The device status generation unit generates the final target status of the target device based on the initial snapshot of key parameters, information representing the latest device status, and user-preset rules. Following the user-defined overall change process and preset change sequence, it calculates the individual status items to be adjusted and their values ​​sequentially, forming the intermediate states the device should achieve. User-preset rules include the final target values ​​for each status item, as well as the preset change sequence, adjustment step size, and iteration cycle for each status item within the overall change process.

[0046] Manual or Automatic Verification Unit: For each calculated single state item, the unit verifies the corresponding manual or automatic parameter. If the manual or automatic parameter is pending judgment, the verification passes and the process proceeds to the execution stage. If the manual or automatic parameter is manual, the verification fails and the process does not proceed to the execution stage. The verification result only affects the execution of the current state item and does not affect the progress of the main calculation line.

[0047] Execution unit: After the verification passes, it outputs a control command that matches the status item to be adjusted to the target device and drives the device to execute it; if the verification fails, it does not output the control command corresponding to the status item.

[0048] Process Control Unit: After each calculation, the information representing the latest state of the equipment is updated with the state items and their state values ​​obtained in this calculation, and the current key parameters are re-acquired and the snapshot of the key parameters obtained in the first acquisition is verified for consistency. When the two are consistent, the calculation of subsequent state items continues. When the two are inconsistent, the current automation process is terminated immediately, and a new automation process is triggered by the changed parameters. When the information representing the latest state of the equipment is consistent with the final target state, the current automation process ends.

[0049] The functional module layer includes a spatial classification module, a device classification module, a scene interaction module, a human perception module, a device ownership management module, a manual / automatic judgment module, and a brightness calibration and calculation module. The specific implementation methods of each module are as follows: The spatial classification module is used to divide the physical space into constant space, task space, and channel space. The specific division rules are as follows: Frequently used spaces: Spaces that users use regardless of whether they have task requirements, such as living rooms and bedrooms; Task space: A space that users only use when they have specific task requirements, such as a kitchen, study, or bathroom; Passageway space: A space that serves only as a passageway, such as a corridor or entryway.

[0050] Among them, the constant space and task space support the configuration of scene parameters, while the channel space has no independent scene parameters. Its device operation status depends on the associated brightness source space for linkage control.

[0051] The device classification module is used to categorize IoT devices connected to the system into switch devices, status devices, and switch / status devices. The specific classification rules are as follows: Switching devices: Devices that can only perform overall start-stop control for opening or closing, without other adjustments to their operating status, such as wall switches and smart sockets; Status-based devices: These devices can only have one or more operating states adjusted and cannot control the start and stop of the entire device, such as electric curtains that are controlled only by the percentage of opening and closing, and fresh air conditioning panels without start and stop switches. Switch-on / off devices: These are devices that support both overall start / stop control and adjustment of one or more operating states. Examples include smart lights that can be switched on and off and have their brightness and color temperature adjusted, and air conditioners that can be switched on and off and have their temperature and fan speed adjusted.

[0052] Based on spatial classification results and equipment classification results, the system matches differentiated automated process branches, triggering rules, pre-verification conditions, and parameter verification logic for different spatial types and different equipment types, ensuring that the control logic is accurately matched with equipment characteristics and spatial attributes.

[0053] The scene interaction module is used to configure variable scene parameters for the constant space and task space. Users can define the names, associated conditions and device control rules of the scene parameters, such as "home scene" and "cinema scene" in the living room, and "sleep scene" and "nighttime scene" in the bedroom.

[0054] The scene interaction module sets a scene activation unit for each space configured with scene parameters. The operation logic of the scene activation unit is as follows: after being triggered, without changing the current scene parameters, it can forcibly trigger the devices that currently belong to the space and will trigger the automation process due to the scene activation, execute the corresponding automation process, and restore the devices to the standard state corresponding to the scene; at the same time, the manual or automatic parameters of the corresponding status items of the above devices are reset to the waiting judgment state, so that the automation process can completely take over the control of all devices.

[0055] Compared to traditional scene switching solutions, this module's scene activation mechanism eliminates the need for users to switch scenes and then switch back. It allows for a one-click reset of the scene's standard state, solving the tedious problem of manually modifying and restoring the device's state. This makes the operation more convenient, and the precise limitation of the reset range avoids unintended impacts on other spatial devices.

[0056] The "Person Presence" module generates presence parameters for each space through multi-level logical operations. These parameters include three states: present, likely to be present, and absent. The module also includes a resting state unit, a feasibility determination unit, and a presence result unit.

[0057] Resting state unit: The trigger condition is a change in any parameter that is already active or pending activation in a space where a resting scene is frequently present, a change in scene parameters, a change in predictive sensor parameters, or a change in parameters indicating whether someone is present in any space where a resting scene is frequently present. The resting parameter generation logic is as follows: If all parameters for rest scenarios that are frequently in the space are set to "pending activation", then the rest parameter should be adjusted to "unlocked". If any parameter that is either enabled or pending to be enabled in a space with a rest scene is enabled, and its scene is not a rest scene, the rest parameter is adjusted to disable rest. If all activated rest scenarios in the frequently used space are in the rest scenario and meet any of the following conditions: the parameter for determining whether there is someone in any non-rest scenario in the frequently used space is "definitely someone", the sensor parameter for predicting whether there is someone in any activated rest scenario in the frequently used space is "someone", or the scenario parameter for any task space is not the space name scenario, then the rest parameter is adjusted to the near solution. If all activated rest scenarios are in a resting state, and simultaneously meet the following conditions: the parameter for whether there is a person in all non-resting scenarios is "uncertain," the sensor parameter for all activated rest scenarios is "unmanned," and the scenario parameter for all task spaces is the space name scenario, then the rest parameter is adjusted to "all rest."

[0058] The rest parameter is used to correct the judgment boundary of people in the rest scene. When the rest parameter is full rest, the system blocks the sensor signals triggered by uncontrollable moving objects such as cats and pets, and does not identify them as people, so as to avoid accidentally triggering equipment actions to disturb users during rest. When the system detects that the user has left the rest scene space, the blocking restriction is temporarily lifted.

[0059] Feasibility determination unit: Used to generate feasibility determination parameters for whether a location can be occupied, whether a location may be occupied soon, and whether a location can be unoccupied. The specific logic is as follows: Whether it can be occupied: When the "at home" or "away from home" parameter is "at home" and all the corresponding preset conditions are met, adjust it to "can be occupied"; when the "at home" or "away from home" parameter is "away from home" or the corresponding preset conditions are not met, adjust it to "cannot be occupied"; when the "rest" parameter is "full rest", the "can be occupied" parameter for the "no rest" scene in the "frequent space", "task space", and "passage space" will be forced to "cannot be occupied". Whether or not someone is about to be present: When the "at home" or "away from home" parameter is "at home", the "space already started" or "to be started" parameter is "started", and all the corresponding preset conditions are met, adjust to "whether or not someone is about to be present"; otherwise, adjust to "whether or not someone is about to be present". When the "rest" parameter is "fully rested", the "whether or not someone is about to be present" parameter for the "whether or not someone is about to be present" in the "frequently in space", "task space", and "passage space" in the "no rest scene" is forced to be "whether or not someone is about to be present". Whether it can be unattended: When the "at home" or "away from home" parameter is "away from home" or "approaching home", or when the "at home" or "away from home" parameter is "at home" and all the corresponding preset conditions are met, adjust it to "can be unattended"; otherwise, adjust it to "cannot be unattended".

[0060] Human presence in the results unit: This unit integrates rest parameters, feasibility assessment parameters, and sensor data to generate the final human presence parameters for each space. See also... Figure 3 The person in the result unit determines whether the target space has a predictive sensor and executes the person parameter determination logic according to different situations.

[0061] When the target space has a prediction sensor, acquire the sensor parameters for people, all prediction sensor parameters, whether it can be a person, whether it can be a person that may be about to be present, and whether it can be an unoccupied person. Then, generate the person parameter according to the following rules: (1) The parameter is adjusted to indicate that someone is present when any of the following conditions are met: 1. Whether the parameter for "someone is present" is "yes", and whether the person is present in the sensor parameter "someone is present"; 2. Whether it can be occupied (parameter: can be occupied), whether it can be likely to be occupied (parameter: cannot be likely to be occupied), and whether it can be unoccupied (parameter: cannot be unoccupied); 3. Whether the parameter can be occupied is yes, and whether the parameter can be unoccupied is no, and the sensor parameter for being occupied is no, while all the predicted sensor parameters are no.

[0062] (2) A person is considered to be likely to be present when the parameters are adjusted to reflect any of the following conditions: 1. Whether the parameter of "there may be someone" is "there may be someone" and the sensor parameter of "no one" is "there is someone" and any prediction sensor parameter of "there is someone" is "there is someone". 2. Whether the parameter can be "there is no one" and whether the parameter can be "there may be someone" and whether the parameter can be "there may be someone" and whether the parameter can be "no one"; 3. Whether the parameter for "can be someone" is "cannot be someone" and whether the parameter for "may be someone" is "may be someone" and whether the sensor parameter for "someone" is "someone" and whether any predictive sensor parameter for "someone" is "someone".

[0063] (3) When any of the following conditions are met, the parameter adjustment will be set to "no one": 1. Whether the parameter can be unmanned is yes, and the sensor parameter is no one, and all predicted sensor parameters are no one; 2. Whether the parameter for "there may be someone" is "no" and the sensor parameter for "no one" is "there is someone"; and whether any prediction sensor parameter for "there is someone". 3. Whether the parameter can be "no one" and whether the parameter can be "possibly someone" and whether the parameter can be "no one" and whether the parameter can be "no one". 4. Whether the parameter for "can be occupied" is "cannot be occupied", and whether the parameter for "can be unoccupied" is "can be unoccupied", and the sensor parameter for "occupied" is "occupied", while all prediction sensor parameters are "unoccupied".

[0064] When the target space lacks a predictive sensor, acquire the sensor parameters indicating whether someone is present, the occupancy status, and the occupancy status, and generate the present-person parameter according to the following rules; in this case, the target space cannot enter a state where someone may be present: (1) The parameter is adjusted to indicate that someone is present when any of the following conditions are met: 1. Whether the parameter for "someone is present" is "yes", and whether the person is present in the sensor parameter "someone is present"; 2. Whether it can be occupied is defined as "Yes, it can be occupied", and whether it can be unoccupied is defined as "No, it cannot be unoccupied".

[0065] (2) The parameter is adjusted to be unmanned when any of the following conditions are met: 1. Whether the parameter can be set to "unmanned" is "yes" and whether the person is present in the sensor parameter is "unmanned"; 2. Whether it can be occupied is determined by whether it can be occupied or unoccupied.

[0066] Among them, the human presence sensor is a sensor installed in the target space to detect whether there is a person in the space, such as a human presence sensor or millimeter-wave radar; the prediction sensor is a sensor installed in the target space entrance, adjacent passage, or other areas to predict whether a user is about to enter the target space, such as a human infrared sensor at the door or a millimeter-wave radar in the corridor.

[0067] Compared to traditional binary human detection solutions, this module adds an intermediate state where a person may be present, enabling the device to prepare in advance and eliminating discomfort caused by sudden changes in the user's state upon entering the space. Through rest parameters and multi-level feasibility assessments, it improves the accuracy of human detection, avoids false triggers, and significantly enhances the user experience.

[0068] The equipment attribution management module dynamically adjusts the attribution relationship between the equipment's current and non-current spaces based on parameters such as the presence of people in the space, whether the equipment can be attributed to a corresponding non-current space, and mandatory attribution conditions. This solves the problem of rigid control logic that can serve equipment in multiple spaces. The equipment attribution management module includes an attribution feasibility unit and an attribution decision unit.

[0069] Feasibility of attribution unit: Triggering conditions include changes in parameters of people not in the corresponding space, changes in preset attributability condition parameters, and changes in manual or automatic equipment parameters. The core determination logic is: When any manual or automatic parameter of the device is set to manual, can the device be assigned to a corresponding non-local space parameter that is adjusted to be assignable? When all manual or automatic parameters of the device are not set to manual, and the parameter corresponding to a person outside the current space is set to "person", and all preset attribution conditions are met, the parameter for whether the device can be attributed to the corresponding non-current space is adjusted to "attributable". When all manual or automatic parameters of the device are not set to manual, and the parameter corresponding to a person not in the current space is set to "no one", the parameter for whether the device can be assigned to the corresponding non-current space should be adjusted to "unassignable". When all manual or automatic parameters of the device are not set to manual, and the parameter corresponding to a person outside the current location is set to "person," and the preset attribution conditions are not met, the device's attribution parameter for the corresponding non-current location will be adjusted to "unattributable."

[0070] The attribution decision-making unit includes general attribution decisions and mandatory attribution decisions.

[0071] General attribution decision: The triggering condition is a change in parameters of the person in the space or a change in parameters regarding whether the equipment can be attributed to a corresponding non-space. The core decision logic is: When the "people are here" parameter of the current space is "people are here", and the current attribute parameter of the device is "not in the current space", and the corresponding parameter of the "not in the current space" of the device is "cannot be attributed", adjust the device's attribute parameter to the current space. When the "people are present" parameter of the current space is not "people are present", and the current "attribute" parameter of the device is not "non-current space", and there is a non-current space to which the device can be attributed, the device's attribute parameter is adjusted to the non-current space that is closest to the current space in terms of physical distance. When the "people are in" parameter of the current space is not "people are in", and the current attribute parameter of the device is "not in the current space", and the corresponding parameter of the current non-current space of the device is "unattributable", and there is still an attributable non-current space besides the current space, the device's attribute parameter is adjusted to the attributable non-current space that is physically closest to the current space. When the "people are in" parameter of the current space is not "people are in", and the current attribute parameter of the device is "not in the current space", and all corresponding non-current space parameters are "unattributable", adjust the device's attribute parameter to the current space. In other cases, the equipment attribution parameters remain unchanged.

[0072] Forced attribution decision: The trigger condition is a change in the forced attribution conditions. The system obtains the priority, target space, and person presence parameter of the target space corresponding to all forced attribution conditions, and filters out candidates that simultaneously meet the forced attribution conditions and have a person presence parameter of "occupied" in the target space; if no candidate exists, the device attribution parameter remains unchanged; if a candidate exists, the target space with the highest priority is determined from the candidates; when the device is not currently assigned to the target space, the device attribution parameter is adjusted to that target space; when the device is already assigned to the target space, the device attribution parameter remains unchanged.

[0073] The mandatory attribution conditions include one or more of the following: user-preset conditions, scene change conditions, and scene activation conditions.

[0074] Compared to traditional fixed room allocation schemes, this module can dynamically adjust device allocation based on the user's activity status across spaces. Users do not need to configure multi-space unattended shutdown linkage rules separately. The device control logic is more in line with the user's actual usage habits, taking into account both practicality and energy saving. At the same time, through the priority forced allocation mechanism, the device allocation can be accurately switched to the target space under specific conditions, further enhancing the system's adaptability to complex usage scenarios.

[0075] The manual / automatic judgment module identifies and records whether the change in device status originates from manual or automatic operation. Upon meeting preset conditions, it resets the manual state to a state that can be taken over by the automated process, achieving a balance between prioritizing manual operation and automatic recovery. The module includes a manual marking unit, a value comparison and judgment unit, and an automatic recovery unit.

[0076] Manual marking unit: The trigger condition is a change in the corresponding switch or state of the device. The core logic is: when the device state change is detected to originate from a non-automatic process, it is determined to be a manual operation by the user; if the user sets the manual or automatic parameter of this state to not be associated with other states, then the manual or automatic parameter of this state is marked as manual; if the user sets the manual or automatic parameter of this state to be associated with other states, then the manual or automatic parameter of this state and all its associated states are marked as manual.

[0077] When the system cannot directly determine the source of the state change, it identifies it through value comparison: Before the automated process is executed, the target state value to be executed is pre-written into the manual or automatic parameters of the corresponding state item; if the state will affect other states and the result of the impact is unpredictable, and other states have manual or automatic parameters set, then the manual or automatic parameters corresponding to the other states are adjusted to empty; after the device state changes, if the changed value is completely consistent with the pre-written target state value, it is determined to be an automated operation and is not marked as manual; otherwise, it is determined to be a manual operation and the corresponding manual or automatic parameter is marked as manual.

[0078] Automatic recovery unit: The trigger condition is a change in parameters of the space where the device is located or any person not located in the space, or a change in the device's corresponding manual or automatic parameter to manual. The automatic recovery execution steps are as follows: S1: In response to the triggering condition, when it is detected that the space where the device is located and all people who can be attributed to other spaces are unoccupied, start the timer with a preset delay time T, where T≥5s; S2: After the delay time T ends, check again whether the space where the device is located and all people who can belong to other spaces are unoccupied; S3: If all spaces are unmanned, and the duration of the unmanned status parameter in each space exceeds T-5s, then adjust the manual or automatic parameters of the corresponding device status to await judgment, so that the automated process can take over control again.

[0079] Meanwhile, this module sets up a forced takeover mechanism: when the preset forced takeover conditions are met, the system will reset the manual or automatic parameters of the corresponding status item to the waiting judgment state and execute the target state generated by the automated process; the forced takeover conditions include scene activation triggering and forced affiliation conditions being met and causing device affiliation adjustment; wherein, the forced affiliation conditions include one or more of user preset conditions, scene change conditions and scene activation conditions.

[0080] Compared with traditional manual lock-up solutions for the entire device, this module prioritizes manual operation at the single-state level. Users can manually intervene in a single state of the device without affecting the automated control of other states. At the same time, through automatic recovery and forced takeover mechanisms, a balance between manual intervention and automatic control is achieved, avoiding the problem of manual operation locking up the automated logic for a long time.

[0081] The brightness calibration and calculation module includes a spatial brightness sensor, a brightness source classification unit, a basic data unit, a channel propagation calculation unit, and a brightness requirement calculation unit. The spatial brightness sensor acquires brightness measurement data for each physical space; the brightness source classification unit divides the physical space into brightness source space, brightness-dependent space, and channel space based on space type and scene status; the brightness calibration and calculation module calculates the target brightness value for each space based on space type, device light output characteristics, spatial distance relationships, and brightness measurement data. The brightness value of the brightness source space serves as a reference for brightness calculations in the brightness-dependent space and channel space. The required brightness of devices in the brightness source space is determined by scene parameters and related control parameters. The required brightness value of devices in the brightness-dependent space is obtained by inverse solving based on the brightness value of the corresponding brightness-dependent space, and the required brightness value of devices in the channel space is obtained by inverse solving based on the required brightness value of the corresponding device.

[0082] Luminance Source Classification Unit: Used to divide the physical space into luminance source space, luminance-dependent space, and channel space according to space type and scene state. The division rules are as follows: Luminance source space: The space that is always present and the task space that is not in a luminance-dependent scenario, used to provide a luminance reference for the whole room; Brightness-dependent space: The task space in a brightness-dependent scene, whose brightness scale value is consistent with the brightness source space it depends on; Channel space: The space where the channel function exists, and the brightness values ​​of the related devices should be calculated based on the associated brightness source or brightness-dependent space and distance relationship.

[0083] Among them, the value of the luminance scale in the luminance source space is used as a luminance reference for the calculation of luminance dependent space and channel space. The luminance source space device does not inversely solve the required luminance of its own space through the value of the luminance scale.

[0084] Basic data unit: used to pre-store the light output contribution values ​​of various devices under different color temperature and brightness combinations, including: the brightness scale value provided by the device at the lowest color temperature and highest brightness, the brightness scale value provided by the device at the lowest intermediate color temperature and lowest brightness, the brightness scale value provided by the device at the intermediate intermediate color temperature and highest brightness, the brightness scale value provided by the device at the highest color temperature and highest brightness, and the direct light brightness scale value of the direct light spatial brightness sensor under each operating condition.

[0085] Channel propagation calculation unit: used to calculate the distance between the device and the luminance source or luminance-dependent space within the channel space, and to perform weighted calculation on the luminance values ​​of the associated space based on the distance, so as to obtain the luminance value L that the device in the channel space should provide.

[0086] The distance calculation method is as follows: For devices within the channel space, if they are directly adjacent to a luminance source or a luminance-dependent space, the distance is set to 1. If the devices are not directly adjacent, the parallel unit distance and vertical unit distance are determined by establishing a baseline straight line and a reference perpendicular line in the channel space. Based on the coordinates of the mapping points of the devices and the directly adjacent devices, the comprehensive distance between the device and the corresponding brightness source or brightness-dependent space is calculated.

[0087] First, obtain the current brightness values ​​provided by all devices that can affect the values ​​measured by the spatial brightness sensor but are not directly exposed to it, denoted as . Their sum is ; The device that acquires the current direct luminance value provided by all direct spatial luminance sensors is denoted as... Their sum is ; ; Where S is the value measured by the spatial brightness sensor.

[0088] The formula for calculating the luminance value L for channel space equipment is as follows: ; in, The i-th associated luminance source space or luminance-dependent space pair channel space device should provide calculation parameters for the luminance target. This refers to the distance between the associated luminance source space or luminance-dependent space and the device.

[0089] Brightness requirement calculation unit: Used to inversely calculate the brightness value that the corresponding device should achieve based on the brightness scale value of the brightness-dependent space, or based on the brightness scale value that the channel space device should provide; the brightness that the brightness source space device should achieve is determined by scene parameters and related control parameters, and is not inversely calculated based on the brightness scale value. The core calculation logic is as follows: Step 1: When the space where the device is located or the current home space is a brightness-dependent space, obtain the brightness index value of the brightness-dependent space; if the corresponding space has a brightness index value F provided by the spatial environment, subtract this value to obtain the total brightness index value that needs to be provided by all devices in the brightness-dependent space; when the space where the device is located or the current home space is a channel space, obtain the brightness index value that the device should provide; if the corresponding space has a brightness index value F provided by the spatial environment, subtract this value to obtain the brightness index value that the device needs to provide.

[0090] Step 2: Based on the color temperature that the device needs to achieve, and combined with the pre-stored device light output characteristic data, calculate the minimum and maximum brightness of the device at the required color temperature and provide the brightness values. Step 3: When the space where the device is located or the current assigned space is a brightness-dependent space, allocate the total brightness target value that needs to be provided by the devices in the brightness-dependent space, obtained in Step 1, according to the proportion of the brightness target value provided by the device at its highest intermediate color temperature to the sum of the brightness target values ​​provided by all devices at their highest intermediate color temperature in the brightness-dependent space. This will yield the brightness target value that a single device needs to achieve. When the space where the device is located or the current assigned space is a channel space, use the brightness target value that the device needs to provide, obtained in Step 1, as the brightness target value that the device needs to achieve. Step 4: Using linear interpolation, based on the brightness target value that the device needs to achieve, the minimum or maximum brightness value that needs to be achieved at the color temperature, and the maximum or minimum brightness value of the device, the brightness value that the device needs to achieve is solved in reverse.

[0091] Compared with traditional fixed threshold brightness control schemes, this module achieves smooth brightness transitions across spaces through spatial classification, distance weighting, and refined light output calculation, avoiding discomfort caused by sudden brightness changes. It can also adapt to complex home space structures, significantly improving the user's lighting environment experience.

[0092] The core automation process of this invention is compatible with three types of devices: switch-type, status-type, and switch-status-type devices, including: Triggering event, pre-test, key parameter snapshot acquisition, final target state generation, sequential calculation of single state items, manual or automatic verification, execution or non-execution, state update and parameter consistency verification, continue iteration or terminate and restart, process end.

[0093] The specific implementation steps are as follows: Triggering event process: When a preset triggering event occurs, the automated process is started; the preset triggering events include one or more of the following: scene parameter change, parameter change when a person is present, manual or automatic parameter change, parameter change when the person is present or away from home, sensor detection value change, scene activation trigger, and user manual trigger.

[0094] Pre-processing inspection: Before the initial parameter acquisition, a preset pre-processing inspection is performed. If the inspection fails, the process terminates directly and does not proceed to subsequent stages. If the inspection passes, the parameter acquisition stage begins. The pre-processing inspection logic is configured differently based on the device category and process category. Scenarios where the inspection fails include the target device being offline, the corresponding scenario or space not being enabled, the current status of being at home or away from home not allowing the automation of this type to continue, and the device's current affiliation not matching.

[0095] Key parameter snapshot acquisition stage: Acquire snapshots of key parameters that this process depends on, the current real state of the target device, and all parameter information related to the target physical space, the target device, and user-preset rules.

[0096] Final target state generation stage: Based on key parameter snapshots, current device status, and user-preset rules, the final target state of the target device is generated; the final target state is a set of targets at the overall device level, determined by scene parameters, human parameters, and other preset parameters related to the control of the target device; manual or automatic parameters are used to verify whether the corresponding state item is allowed to be executed.

[0097] Single-state-item successive calculation stage: According to the user-defined overall change process and preset change sequence, the single state item to be adjusted and its state value are calculated one by one to form the intermediate state that the device should achieve; each calculation generates only the adjustment result of one state item, rather than adjusting multiple state items at the same time in one round.

[0098] Manual or automatic verification and execution / non-execution phase: For each individual status item obtained in this calculation, its corresponding manual or automatic parameters are verified; if the verification passes, the corresponding control command is output and the device is driven to execute; if the verification fails, no control command is output, and the status item is not executed. The verification result does not affect the progress of subsequent calculation processes.

[0099] Status update and parameter consistency verification step: The status items and their status values ​​obtained in this calculation are used to update the information representing the latest status of the device; at the same time, the current key parameters are re-acquired and compared with the first snapshot of the key parameters; when the two are consistent, the calculation of the single status item is returned to the single status item calculation step, and the calculation of the subsequent status items continues; when the two are inconsistent, the current automation process is immediately terminated, and a new automation process is triggered by the changed parameters.

[0100] After the execution and non-first iteration logic verifications pass, the execution unit outputs control commands matching the target state to the target device and drives the device to execute. For device states that require gradual adjustment in steps, the system enters a process of continuing iteration or terminating and restarting: this includes the initial calculation, non-first iterations, iteration cycle, and step size.

[0101] The initial calculation involves generating the first target state and control command based on the current state of the device, and completing the initial execution. Non-first iteration: Based on the previous execution result, the current parameter status, and the user-preset step size rules, generate subsequent target states and control instructions to gradually approach the user-preset final target result; Iteration cycle and step size: Different devices and different status items support the configuration of independent adjustment step size and iteration cycle; the step size of text status items is fixed at 1 and is directly adjusted to the target value; the step size of numeric status items is preset by the user and is adjusted step by step.

[0102] Process termination stage: When the information representing the latest state of the device is consistent with the final target state, the current automation process ends; if the key parameters change, the current iteration process is immediately terminated, and the changed parameter state is used as input to re-trigger the complete automation process to avoid control conflicts and cyclic execution.

[0103] The information representing the latest status of the device supports two implementation methods: Method 1: The system obtains the current real state of the device before the first calculation. In subsequent calculations, the system continues to generate subsequent adjustment results based on the logically latest state obtained from each round of calculation results. This method is suitable for systems where there is a delay in reading back the device status and can effectively reduce the risk of misjudgment. Method 2: When the system can accurately and with low latency obtain the current real state of the device, subsequent calculations continue based on the latest obtained current real state of the device, or the logically latest state is corrected based on the latest obtained state before continuing.

[0104] The second embodiment provided by this invention: User returning home scenario: When a user is away from home, the "already" or "awaiting" activation parameters for the corresponding spaces—entryway, hallway, and living room—are all set to "already," indicating that these spaces are unoccupied. A predictive sensor is installed at the user's door, providing predictive input for the entryway, hallway, and living room. A hallway connects the living room and entryway, and a presence sensor is installed in the hallway. The main light in the living room can simultaneously power the living room, entryway, and hallway; the entryway and hallway serve as passageways, while the living room acts as the light source.

[0105] Triggering and Pre-Check: When a user approaches their front door, the door's predictive sensor detects the user and triggers the automated process; Parameter acquisition: The parameter acquisition unit reads the "at home" or "away from home" parameter and adjusts it to "at home". The "already" or "to be" parameters for the corresponding spaces of the entrance hall, corridor and living room are all "already" and the relevant prediction sensor parameters are "occupied". The parameters for whether the corresponding space is "possibly about to be occupied" are "possibly about to be occupied". Human Parameter Update: The Human Results Unit adjusts the Human Parameters for the entrance hall, corridor, and living room to indicate when someone is likely to be present, based on the parameters. Final target state generation: The device state generation unit combines the scene parameters of the "coming home" scene in the living room and the brightness target parameters to generate the target state of the main light in the living room as "on", with a brightness of 30% and a color temperature of 4000K; at the same time, it generates the pre-on target state of the entryway downlight and the corridor light strip. Manual or automatic verification: All manual or automatic parameters of the relevant devices are set to pending judgment, and the verification is successful. Initial calculation and execution: The execution unit outputs control commands, turning on the living room main light to 30% brightness, and simultaneously turning on the entryway downlights and corridor light strips to the preset brightness, so that users do not have to experience a dark environment when they open the door and enter the house, avoiding the discomfort caused by sudden changes in lighting. State update and consistency check: Update the logically latest state with the result of this calculation, re-acquire key parameters and compare with the snapshot. If they are consistent, continue the subsequent calculation. Dynamic Attribution Adjustment 1: After a user enters the entrance hall, the parameter for the person in the entrance hall changes from "potentially someone" to "someone"; if the parameter for the person in the living room is still not "someone", the attribution feasibility unit detects that the corresponding parameter of the entrance hall meets the attribution conditions, and the attribution decision unit adjusts the attribution parameter of the living room main light to the entrance hall, so that the living room main light prioritizes serving the entrance hall's lighting needs. Dynamic Attribution Adjustment 2: After the user continues to walk through the corridor into the living room, the sensor detects someone in the living room and adjusts the parameter to "someone is there"; at the same time, the parameter of "someone is there" in the entrance hall changes to "no one is there", and the parameter corresponding to the non-local space to which the main light in the living room is currently assigned becomes "unassignable". The attribution decision unit adjusts the attribution parameter of the main light in the living room back to the living room. Re-triggering of the process after parameter changes: The user continues to move and enters the living room. The sensor detects someone in the living room and the parameters for the person in the living room are adjusted to indicate that someone is there. At the same time, the parameters for the person in the entrance hall and the parameters related to the device ownership change. The key parameters that the current process depends on change. The system terminates the current automated process and re-triggers a new automated process with the changed parameters.

[0106] Initial calculation and subsequent iterations: In the newly triggered automated process, the system regenerates the final target state of the living room main light as 80% brightness; the initial calculation first adjusts the brightness of the living room main light from the current 30% to 47%, and then continues to execute two non-initial iterations in this new process, adjusting the brightness to 64% and 80% respectively, with a step size of 17% each time and an interval of 200ms, to achieve smooth brightness increase of the light; after each calculation, parameter consistency verification is performed to ensure stable process progress; Process End: The process ends when the latest logical state matches the final target state.

[0107] In this second embodiment, traditional solutions typically only trigger lights after a user actually enters the relevant space such as the entryway, hallway, or living room and is detected as occupied by the corresponding sensor. Users experience discomfort from darkness and sudden changes in lighting during the entry process. For lights that can serve multiple spaces simultaneously, it's difficult to dynamically switch service priorities as the user moves from the entryway to the hallway and then to the living room. When the living room lights need to gradually transition from a pre-on state to the target brightness, multiple independent rules often need to be configured, which can easily lead to logical conflicts. This embodiment pre-activates relevant devices in the entryway, hallway, and living room in advance when someone is likely to be present. Combined with a dynamic device allocation adjustment mechanism, the main living room light can dynamically switch priority service spaces as the user moves. When key parameters related to the living room change, the system terminates the current process and re-triggers a new automated process with the changed parameters. Through the initial calculation and two subsequent iterations, the main living room light smoothly increases in brightness from 30% to 80%, without requiring complex user rules, significantly improving the user experience and stability.

[0108] The third embodiment provided by the present invention: Bedroom rest scenario: The master bedroom is a frequently used space for rest, and the "already" or "pending" parameter indicates that it is already activated. The second bedroom is in a pending state. The master bedroom is equipped with a presence sensor and a prediction sensor, and other related spaces throughout the house are equipped with presence sensors.

[0109] Scene triggering and pre-testing: When a user switches the master bedroom scene to "sleep scene", the change in scene parameters triggers an automated process; Rest parameter generation: The rest state unit detects that all active rest scenarios are in rest scenarios and no other spaces are confirmed to be occupied, and adjusts the rest parameters to full rest.

[0110] Human presence boundary correction: When the rest parameter is set to "full rest," the feasibility assessment unit restricts the parameters for whether the space, task space, and passageway in the no-rest scenario are occupied and whether they are likely to be occupied to "not." Simultaneously, in the sleep scenario, the master bedroom can be set to "possible for occupancy," "unoccupied," or "unlikely for occupancy," to prevent misjudgment of the master bedroom's occupancy parameter due to a brief period of sensor lapse during sleep. This ensures the master bedroom's occupancy parameter remains consistently set to "occupant." Even if sensors in other spaces show changes in detection due to uncontrollable moving objects like pets, the system will not misjudge the corresponding space as occupied, preventing accidental light triggering that could disturb the user's rest.

[0111] Manual intervention: When the user manually adjusts the brightness of the master bedroom night light from the preset 5% to 10%, the manual marking unit marks the manual or automatic parameter corresponding to the night light brightness as manual. When the system executes the automated process of "sleep scene" later, the manual or automatic verification unit detects that the parameter is manual, does not modify the night light brightness, and only performs automated control on other devices that are in the waiting judgment state, realizing manual priority in a single state item dimension.

[0112] Nighttime Scene Interaction: When a user gets up at night, the pre-detection sensor in the master bedroom detects the user's movement, adjusts the rest parameter to "nearly occupant," and the system removes the "person in rest scene" detection shield. In the bathroom, the "person in bathroom" parameter is adjusted to "possibly someone is about to be there," and the system preemptively turns the bathroom lights to their lowest brightness to avoid glare. After the user completes their short activity and returns to the master bedroom, the pre-detection sensor in the master bedroom resets to "no one" after a preset "no one" delay time. This "no one" delay time can be set by the user to 2 to 3 minutes to cover scenarios where the user briefly leaves the rest space and then returns, such as getting up at night or going to the kitchen for a drink. Subsequently, if all activated rest scene spaces remain in the rest scene state, and no other spaces show signs of occupancy, the rest state unit readjusts the rest parameter to "full rest."

[0113] Automatic recovery: When the user cancels the "sleep scene" or switches the master bedroom to another scene, the relevant feasibility judgment conditions of the master bedroom are restored to "can be unoccupied" and "can be occupied soon". If the space where the device is located and all other spaces that can be assigned to it remain unoccupied, the automatic recovery unit starts a timer. After the unoccupied state reaches the preset delay time of 3 minutes, the previously marked manual or automatic parameters of the night light brightness are reset to the waiting judgment state, so that the automation process can take over control again.

[0114] In this third embodiment, traditional solutions struggle to simultaneously achieve interference shielding from uncontrollable moving objects like pets, stable human presence during sleep, and manual priority control at the single-state level in rest scenarios. When a user manually adjusts the nightlight, either the automated process overwrites the user settings, or the entire system's automation logic is permanently locked. This embodiment corrects the human presence judgment boundary using rest parameters, maintains stable human presence parameters in the master bedroom by constraining human presence in sleep scenarios, and combines manual / automatic judgment and automatic recovery mechanisms for single-state items, thus meeting the user's core needs for quietness, accuracy, and controllability in rest scenarios.

[0115] The fourth embodiment provided by this invention: recovery scenario away from home: When a user leaves home, the "No one is here" parameter is set to "No one is here" in all spaces of the house, triggering an automated process.

[0116] Triggering and Pre-testing: When the "At Home" or "Away From Home" parameter changes to "Away From Home" or the "All People in the House" parameter changes to "No One in the House", the automated process is triggered; after the pre-testing is passed, a snapshot of key parameters and the current status of the device are obtained.

[0117] Final target state generation: The system combines the scene parameters of "away from home", "away from home" parameters, and "person in" parameters to generate the final target state of all non-essential devices as "off".

[0118] Sequential calculation and execution: According to the user-preset change sequence, the shutdown status items of each device are calculated sequentially. After manual or automatic verification, the unit outputs control commands to shut down all unnecessary devices in the house. If the verification of a single device fails, the shutdown command of that device will not be executed, and it will not affect the process of other devices.

[0119] Automatic recovery from manual status: For devices whose space and all other spaces that can be attributed to them remain unoccupied, the automatic recovery unit starts a timer with a preset delay time of 3 minutes. After 3 minutes, if it is confirmed again that the corresponding spaces are still unoccupied and the unoccupied period has exceeded 2 minutes and 55 seconds, the manual or automatic parameters of the corresponding status items that were previously marked as manual will be reset to the pending judgment state.

[0120] Device attribution reset: When all relevant space personnel parameters are unoccupied, according to the attribution decision logic, the non-space parameters corresponding to the devices that were originally assigned to the non-space become unassignable. The attribution decision unit adjusts the device attribution parameters back to the space where the device is located, restoring the system to its initial attribution state.

[0121] Process End: The process ends when the latest logical state of all devices is consistent with the final target state, ensuring that the system control logic will operate normally when the user returns home next time.

[0122] In this fourth embodiment, in the traditional solution, the device status manually adjusted by the user before leaving home remains manually locked. When the user returns home next time, the automated process cannot take over and the user needs to manually reset it. Furthermore, devices belonging to different locations cannot be automatically reset, which can easily lead to abnormal control logic when the user returns home next time. This embodiment perfectly solves the above problems through an automatic recovery and ownership reset mechanism in the unattended state, ensuring that the system can be restored to its initial controllable state every time the user leaves home.

[0123] The fifth embodiment provided by this invention: Scene activation and scene reset: In the "Home Scene" of the living room, the user manually adjusts the brightness of the main living room light from the preset 80% to 30%, turns off the ambient light, and adjusts the air conditioner temperature from 26℃ to 24℃. The manual marking unit marks the manual or automatic parameters of the above devices as manual, and the system automation process no longer modifies these states.

[0124] If users wish to restore the living room to its standard "home scene" state later, they can simply click the scene activation button to trigger the scene activation unit without switching scenes. Scene activation trigger: When a user clicks the scene activation button, the scene activation unit is triggered. After the system performs the pre-verification and passes, the automated process is started.

[0125] Attribution and Parameter Reset: After scene activation is triggered as a mandatory attribution condition, if the corresponding mandatory attribution condition is met and the person in the target space parameter is "person", the attribution decision unit determines the target space according to the mandatory attribution decision. For devices that do not currently belong to the target space, their device attribution parameters are adjusted to the target space, and the manual or automatic parameters of the corresponding status item of the device that triggered the automation process due to the scene activation are reset to the waiting judgment state.

[0126] Process execution and state restoration: The system rereads the scene parameters, human parameters and other relevant data of the "home scene" and generates the standard target state of the device corresponding to the scene; calculates each state item in turn according to the user-preset change sequence. After all manual or automatic verifications pass, the unit outputs control commands to restore the living room main light to 80% brightness, turn on the ambient light, and restore the air conditioner temperature to 26℃, completing the reset of the scene standard state with one click.

[0127] Process End: The process ends when the latest logical state of all devices is consistent with the final target state.

[0128] In this fifth embodiment, in the traditional solution, after a user manually modifies the device status, if they want to restore the standard scene status, they must first switch to another scene and then switch back to the original scene, which is cumbersome. Moreover, switching scenes will cause all associated devices to re-execute the start-stop process, which can easily lead to frequent device actions. This embodiment uses a scene activation mechanism to reset the device with one click without switching scenes, and only adjusts the associated devices whose automated processes are triggered by the scene activation, making the operation more convenient and the control more precise.

[0129] The sixth embodiment provided by this invention: Cross-space dynamic device attribution scenario: The main light in the living room can simultaneously serve three spaces: the living room, the dining room, and the kitchen. The device is originally located in the living room, but can also be preset to be assigned to the dining room or the kitchen, which are not its original spaces.

[0130] Initial state: There are people in the living room, but no one in the dining room or kitchen. The attribution decision unit sets the attribution parameter of the main light in the living room to the space it belongs to (living room), and the main light operates according to the living room scene parameters.

[0131] Initial attribution switch: When a user leaves the living room and enters the dining room, the "person in living room" parameter changes to "no one" and the "person in dining room" parameter changes to "person"; the attribution feasibility unit detects that the "person in dining room" parameter is "person" and the device's manual or automatic parameter is "awaiting judgment," and the preset attribution conditions are met, so it adjusts the device's attribution parameter to "attributable"; the attribution decision unit detects that the "person in living room" parameter is not "person" and there is an attributable space other than the current space, the dining room, so it adjusts the attribution parameter of the main light in the living room to the dining room, and the main light operates according to the dining room scene parameters to provide lighting for the dining room.

[0132] Secondary attribution switching: When a user moves from the restaurant to the kitchen, the parameter changes from "restaurant person" to "no person" and from "kitchen person" to "person". The system uses the same attribution determination logic to switch the main light's attribution to the kitchen, and the main light operates according to the kitchen scene parameters.

[0133] Home assignment switch: When a user returns to the living room, the "living room person" parameter changes to "person", and the current home assignment parameter of the main living room light is "not located in the space". If the parameter corresponding to the non-located space currently assigned to the device is "unassignable", then according to the general home assignment decision logic, the home assignment decision unit adjusts the home assignment parameter of the main living room light to the location (living room) and restores the lighting control of the living room.

[0134] When no one is present in the living room, dining room, and kitchen, the parameters corresponding to all non-spaces to which the main light is currently assigned become unassignable. The assignment decision unit adjusts the main light's assignment parameters back to the living room according to the general assignment decision logic. Subsequently, the system triggers the shutdown process to turn off the main light. No additional configuration of the linkage rule of "turning off the main light only when no one is present in the living room, dining room, and kitchen" is required by the user.

[0135] In this sixth embodiment, the traditional solution uses fixed room assignment, meaning the main light in the living room can only be assigned to the living room. When a user enters the dining room or kitchen, the main light cannot switch control logic accordingly. Typically, users need to configure multi-space linkage rules separately to achieve seamless lighting transitions and shutdown control across different spaces. This embodiment, through a dynamic device assignment mechanism, allows the main light to automatically switch assignments as the user moves between the living room, dining room, and kitchen. When no one is in any of the relevant spaces, it can naturally return to its current location and trigger a shutdown process. The control logic is more aligned with actual user habits, eliminating the need for users to configure separate linkage rules for "turning off the main light only when no one is in the living room, dining room, or kitchen," thus balancing practicality and energy efficiency.

[0136] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. An automated intelligent device scene interaction processing system based on the Internet of Things, characterized in that, It includes a core control layer, which serves as the central hub for the system's automated processes, and comprises: The parameter acquisition unit is used to acquire parameter information related to the target physical space, the target device connected to the Internet of Things, and the user's preset rules in response to a preset trigger event. The device status generation unit is used to generate the final target status of the target device based on the first snapshot of key parameters, information representing the latest status of the device, and user-preset rules. It also calculates the individual status items and their status values ​​that should be adjusted in this instance according to the overall change process defined by the user, forming the intermediate status that the device should achieve. A manual or automatic verification unit is used to verify the manual or automatic parameters corresponding to each individual state item obtained in each calculation, so as to determine whether the intermediate state is allowed to be executed by the automated process. The execution unit is used to output control commands that match the status items to be adjusted in this operation to the target device and drive the device to execute them after the verification passes; if the verification fails, the corresponding control commands are not output. The process control unit is used to update the information representing the latest state of the equipment with the state items and their state values ​​obtained in this calculation after each calculation, and to re-acquire the current key parameters and the snapshot of the key parameters for consistency verification; when the two are consistent, the calculation of subsequent state items continues; when the two are inconsistent, the current automation process is terminated, and a new automation process is triggered again by the changed parameters; when the information representing the latest state of the equipment is consistent with the final target state, the current automation process ends.

2. The IoT-based automated intelligent device scene interaction processing system according to claim 1, characterized in that, In the process control unit, the verification results of the manual or automatic verification unit do not affect the continued advancement of the main calculation line of the current automated process; If a single status item fails verification, only the output of the control command for that status item will be blocked; the verification, execution, and subsequent calculation processes of other status items will not be blocked.

3. The IoT-based automated intelligent device scene interaction processing system according to claim 1, characterized in that, The automated process also includes a pre-test step, which is performed before the initial parameter acquisition; If the preliminary test fails, the process will terminate directly and will not proceed to the parameter acquisition and subsequent calculation stages. Different equipment categories and different automated process categories correspond to preset pre-inspection logic.

4. The IoT-based automated intelligent device scene interaction processing system according to claim 1, characterized in that, The information representing the latest state of the device includes state information obtained from logical updates, and / or the current state information of the device acquired by the system in real time; Subsequent calculations are based on the device's actual state obtained initially and the logically latest state obtained from each round of calculations. When the system meets the preset conditions for accuracy and timeliness of state acquisition, subsequent calculations are performed based on the latest acquired current real state of the device, or the latest logical state is corrected based on the latest acquired state before continuing.

5. The IoT-based automated intelligent device scene interaction processing system according to claim 1, characterized in that, The user-preset rules include the final target value corresponding to each status item of the target device, and the preset change order of each status item in the overall change process; the process control unit determines the individual status item and its status value to be promoted this time based on the preset change order, the current change stage of the device, and information representing the latest status of the device.

6. The IoT-based automated intelligent device scene interaction processing system according to claim 1, characterized in that, The final target state of the target device is determined by scene parameters, human parameters, and other preset parameters related to the control of the target device; manual or automatic parameters are used to verify whether the corresponding state item is allowed to be executed. The automated process uniformly receives and processes multiple parameters to generate the final target state of the target device under the current process and the intermediate states of each calculation.

7. The IoT-based automated intelligent device scene interaction processing system according to claim 1, characterized in that, It also includes a human perception module, which is used to generate human presence parameters in the target space. The human presence parameters include three states: present, likely to be present, and absent. The "potentially occupied state" refers to the pre-triggered state of the target space when the target space is currently unoccupied, but a user has arrived at a preset area where it can be predicted that the user will enter the space. Once in this state, the system can pre-drive devices within the target space to perform pre-operation actions. The human perception module includes a rest state unit, a feasibility determination unit, and a human result unit. The rest state unit is used to generate rest parameters, including unrest, imminent unrest, and full rest, based on the parameters of the space where rest scenarios are frequently present, the scene parameters, the prediction sensor parameters, and the parameters for determining whether there are people in the space where rest scenarios are frequently present. The feasibility determination unit is used to generate feasibility determination parameters based on the "at home or away" parameter and preset conditions, indicating whether the property is occupied, whether it is likely to be occupied, and whether it is unoccupied. The "person in the result unit" is used to integrate the rest parameters, feasibility judgment parameters, and sensor data, and generate the final person in each space through preset logical operation rules.

8. The IoT-based automated intelligent device scene interaction processing system according to claim 1, characterized in that, It also includes a scene interaction module, which is used to configure variable scene parameters for physical spaces with configured scene parameters, and to set a scene activation unit for each space with configured scene parameters. The scene activation unit is used to forcibly trigger the automated process of the associated device after being triggered, without changing the current scene parameters, so that the device in the space is restored to the standard state corresponding to the scene. Once a scene is activated, the manual or automatic parameters of the corresponding status item of the device that belongs to the space and whose automated process is triggered by the scene activation are reset to the pending judgment state.

9. The IoT-based automated intelligent device scene interaction processing system according to claim 1, characterized in that, The parameter acquisition unit also acquires device affiliation-related parameters, including whether the device can be affiliated to a corresponding non-local space parameter and device affiliation parameters. The system also includes a device affiliation management module, which dynamically adjusts the affiliation relationship between the device's current space and non-current spaces based on the space's human presence parameters, whether the device can be affiliated to a corresponding non-current space parameters, and mandatory affiliation conditions; at any given time, the current affiliation space of a single device is unique. The equipment ownership management module includes an ownership feasibility unit and an ownership decision unit; The attribution feasibility unit is used to generate parameters to determine whether a device can be attributed to a corresponding non-local space based on the person present in the non-local space, preset attribution conditions, and the device's manual or automatic parameters. The attribution decision unit is used to perform a general attribution decision based on the presence parameter of the current space, the current attribution parameter of the device, and the attributability parameters of all corresponding non-current spaces of the device. When the presence parameter of the current space indicates that someone is present, and the current attribution parameter of the device is a non-current space, and the corresponding parameter of the non-current space to which the device is currently attributed is unattributable, the device's attribution parameter is adjusted to the current space. When the presence parameter of the current space does not indicate that someone is present, and the current attribution parameter of the device is not a non-current space, and there are attributable non-current spaces, the device's attribution parameter is adjusted to the attributable non-current space that is physically closest to the current space. When the presence parameter of the current space does not indicate that someone is present, and the current attribution parameter of the device is a non-current space, and the corresponding parameter of the non-current space to which the device is currently attributed is unattributable, and there are still attributable non-current spaces besides the current attribution space, the device's attribution parameter is adjusted to the attributable non-current space besides the current attribution space that is physically closest to the current space. When the presence parameter of the current space does not indicate that someone is present, and the current attribution parameter of the device is a non-current space, and the parameters of all corresponding non-current spaces are unattributable, the device's attribution parameter is adjusted to the current space. The attribution decision unit is also used to obtain the priority, target space and person presence parameter of all mandatory attribution conditions when the mandatory attribution conditions change, and determine the target space with the highest priority from the candidates that simultaneously meet the mandatory attribution conditions and whose person presence parameter of the target space is occupied; when the device does not currently belong to the target space, the device attribution parameter is adjusted to the target space.

10. The IoT-based automated intelligent device scene interaction processing system according to claim 1, characterized in that, It also includes a manual / automatic determination module, which includes a manual marking unit, an assignment comparison and determination unit, and an automatic recovery unit; The manual marking unit is used to mark the manual or automatic parameters of the device state and its associated state as manual when a change in the device state triggered by a non-automatic process is detected. The assignment comparison and determination unit is used to pre-write the target state value to be executed into the manual or automatic parameters of the corresponding state item before the state item is adjusted in the automated process; when the device state changes, if the change value is inconsistent with the pre-written target state value, it is determined to be a manual change, and the manual or automatic parameters of the corresponding state item and its associated state item are marked as manual. The automatic recovery unit is used to reset the manual or automatic parameters to a waiting-for-determination state when it detects that the space where the device is located and all the spaces that can belong to are unoccupied, and the duration exceeds a preset delay time, so that the automated process can take over control again. When the preset forced takeover conditions are met, the system will reset the manual or automatic parameters of the corresponding status item to the waiting judgment state and execute the target state generated by the automated process. The forced takeover conditions include scene activation triggering and forced attribution conditions being met and causing device attribution adjustment; wherein, the forced attribution conditions include one or more of user preset conditions, scene change conditions, and scene activation conditions.

11. The IoT-based automated intelligent device scene interaction processing system according to claim 1, characterized in that, The parameter acquisition unit also acquires the parameters of the brightness calibration, and the system further includes a brightness calibration and calculation module; The brightness calibration and calculation module includes a spatial brightness sensor, a brightness source classification unit, a basic data unit, a channel propagation calculation unit, and a brightness demand calculation unit; The brightness source classification unit is used to divide the physical space into brightness source space, brightness-dependent space and channel space according to the space type and scene state. The spatial brightness sensor is used to acquire brightness measurement data for each physical space; The brightness calibration and calculation module combines spatial type, device light output characteristics, spatial distance relationship and brightness measurement data to calculate the target brightness value for each space. The target brightness value of the brightness source space is used as a brightness reference for the brightness calculation of the brightness dependent space and the channel space. Devices in the brightness dependent space calculate the brightness value to be set based on the target brightness value of the corresponding brightness dependent space, and devices in the channel space calculate the brightness value to be set based on the brightness value to be provided by the corresponding device.

12. The IoT-based automated intelligent device scene interaction processing system according to claim 1, characterized in that, It also includes a space classification module and an equipment classification module; The space classification module is used to divide the physical space into a constant space, a task space, and a passage space. The constant space is the space that the user will use regardless of whether there is a task requirement. The task space is the space that the user will only use when there is a task requirement. The passage space is the space that serves as a passageway. The device classification module is used to classify IoT devices connected to the system into switch devices, status devices, and switch / status devices. Switch devices only support on / off control and have no other adjustable operating states. Status devices only support operating state adjustment and cannot control the overall start / stop of the device. Switch / status devices support both overall start / stop control and operating state adjustment. Based on spatial classification results and equipment classification results, the system matches differentiated automated process branches, triggering rules, pre-verification conditions, and parameter verification logic for different spatial types and different equipment types.

13. The IoT-based automated intelligent device scene interaction processing system according to claim 1, characterized in that, At least some of the parameters output by the functional modules can be used as the basis for parameter verification, updating or automatic process re-triggering of other functional modules, forming a parameter linkage closed loop; the preset trigger events include one or more of the following: scene parameter change, parameter change when a person is present, manual or automatic parameter change, parameter change when at home or away, sensor detection value change, scene activation trigger, and user manual trigger.

14. A method for scene interaction processing of automated intelligent devices based on the Internet of Things, characterized in that, Includes the following steps: S1: In response to a preset trigger event, perform a preset pre-check; if the check fails, terminate the process. If the verification passes, obtain snapshots of key parameters that this process depends on, information representing the latest status of the target device, and parameter information related to the target physical space, target device, and user-preset rules; S2: Generate the final target state of the target device based on the snapshot of the key parameters, the information representing the latest state of the device, and the user-preset rules; S3: According to the user-defined overall change process, calculate the individual state items that should be adjusted this time and their state values ​​one by one to form the intermediate state that the device should achieve; S4: For a single state item obtained in this calculation, verify the manual or automatic parameters corresponding to the state item. If the verification passes, output the matching control command to the target device and drive its execution. If the verification fails, do not output the corresponding control command. S5: Update the information representing the latest state of the device with the state items and their state values ​​obtained in this calculation, and re-acquire the current key parameters and the snapshot of the key parameters for consistency verification; when the two are consistent, return to step S3 to continue the calculation of subsequent state items; when the two are inconsistent, terminate the current process and return to step S1 to re-trigger a new automated process with the changed parameters. S6: When the information representing the latest state of the device is consistent with the final target state, end the current automation process.

15. An electronic device, characterized in that, It includes a processor and a memory, wherein the memory stores computer-executable instructions, and when the computer-executable instructions are executed by the processor, they implement the IoT-based automated intelligent device scene interaction processing method as described in claim 14.

16. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the IoT-based automated intelligent device scene interaction processing method as described in claim 14.

17. A computer program product, characterized in that, It includes a computer program, which, when executed by a processor, implements the IoT-based automated intelligent device scene interaction processing method as described in claim 14.

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