Internet of Things-based Smartwatch Control Method and Device

Abstract

This invention relates to the field of IoT control technology, specifically to a smartwatch control method and device based on the Internet of Things (IoT). The method includes: acquiring an initial state model of IoT devices associated with the smartwatch; acquiring first device nodes included in the initial state model, and a first user dependency weight corresponding to each of the first device nodes; the first user dependency weight is used to characterize the importance of the device to the user's daily use; acquiring a first candidate control instruction set associated with the IoT devices; and obtaining a first execution priority based on the first device nodes and the first user dependency weight. This invention dynamically adjusts the control strategy through user dependency weights and device node states, ensuring more intelligent control of IoT devices by the smartwatch. Furthermore, by analyzing changes in user states or device anomalies, the control strategy can be adjusted in real time, enabling the smartwatch to adapt to different user needs and device conditions.

Description

Technical Field

[0001] This invention relates to the field of IoT control technology, specifically to a smartwatch control method and device based on the Internet of Things. Background Technology

[0002] With the development of IoT technology, more and more smart devices (such as home appliances, health monitoring instruments, and home appliances) are being connected to the Internet. Users control these IoT devices through wearable devices such as smartwatches, which is gradually becoming an important part of daily life. However, due to the wide variety of devices and their complex functions, how to control these devices efficiently and intelligently, especially in dynamically changing environments, has become an urgent problem to be solved.

[0003] Currently, traditional methods often fail to consider the user's dependence on different devices or the different frequencies of device use, and do not respond quickly to changes in user or device status. As a result, smartwatches lack personalization when dealing with user needs, cannot prioritize the needs that are more important to the user, and cannot make timely adjustments when the device malfunctions or malfunctions, resulting in a poor user experience.

[0004] Furthermore, traditional smartwatch control methods typically employ preset control strategies, controlling IoT devices in a fixed sequence or according to certain rules, without dynamically adjusting the control strategy based on the user's actual needs, device status, or changes in the user. This results in the control method being unable to adapt flexibly to different environments and situations, potentially leading to inefficient or inappropriate control responses. Summary of the Invention

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] A smartwatch control method based on the Internet of Things (IoT) includes:

[0007] Obtain the initial state model of the IoT devices associated with the smartwatch, obtain the first device nodes included in the initial state model, and the first user dependency weight corresponding to each first device node; the first user dependency weight is used to characterize the importance of the device to the user's daily use;

[0008] A first candidate control instruction set associated with the IoT device is obtained. Based on the first device node and the first weight of user dependency, a first execution priority is obtained for each first candidate instruction included in the first candidate control instruction set. Based on the first execution priority, a target initial instruction is obtained from the first candidate instructions. The instruction set composed of the target initial instruction is the instruction set with the optimal number of instructions and the most comprehensive coverage of user needs.

[0009] Based on the initial instructions of each target, a basic control strategy for the smartwatch is generated; the basic control strategy is used to control the smartwatch's routine operation of IoT devices.

[0010] During the process of the smartwatch controlling the IoT device according to the basic control strategy, if a change in user status or an abnormal device status is detected, the second device node and the second weight of user dependence corresponding to each second device node are obtained.

[0011] Obtain the second candidate control instruction set associated with the IoT device; based on the second device node and the second weight of user dependency, obtain the second execution priority of each second candidate instruction included in the second candidate control instruction set; and based on the second execution priority, obtain the target dynamic instruction from the second candidate instructions.

[0012] The basic control strategy is adjusted according to the target dynamic instruction to obtain a real-time control strategy; the real-time control strategy is used to control the smartwatch's dynamic response to IoT devices to adapt to changes in user status or abnormal device conditions.

[0013] Preferably, based on the first device node and the first weight of user dependency, the first execution priority of each first candidate instruction included in the first candidate control instruction set is obtained, including:

[0014] Obtain the current first candidate instruction and the target first device node that the current first candidate instruction can act on; the current first candidate instruction is any one of the first candidate instructions.

[0015] Based on the first weight of user dependence corresponding to each of the target first device nodes, the first demand satisfaction score corresponding to each of the target first device nodes is obtained;

[0016] Based on the scores for satisfying each of the first requirements, the first execution priority of the current first candidate instruction is obtained.

[0017] Preferably, based on the first weight of user dependency corresponding to each of the target first device nodes, a first demand satisfaction score is obtained for each of the target first device nodes, including:

[0018] Obtain the current first device node and the number of first candidate instructions that can be applied to the current first device node; the current first device node is any one of the first device nodes.

[0019] Based on the quantity and the first weight of user dependence corresponding to the current first device node, the first demand satisfaction score corresponding to the current first device node is obtained.

[0020] Preferably, obtaining the first device nodes included in the initial state model, and the first weight of user dependency corresponding to each first device node, includes:

[0021] Obtain the first device nodes included in the initial state model, as well as the device type label and historical usage frequency corresponding to each first device node;

[0022] Obtain the baseline weights corresponding to each device type label and historical usage frequency; the baseline weights are used to characterize the user dependency baseline values ​​of different types of devices at different usage frequencies.

[0023] The baseline weight corresponding to each of the first device nodes is used as the first weight of user dependence corresponding to each of the first device nodes.

[0024] Preferably, based on the second device node and the second weight of user dependency, the second execution priority of each second candidate instruction included in the second candidate control instruction set is obtained, including:

[0025] Obtain the current second candidate instruction; the current second candidate instruction is any one of the second candidate instructions.

[0026] Based on the second device node and the second weight of user dependency, the second requirement satisfaction score of each second device node corresponding to the current second candidate instruction is obtained;

[0027] The second execution priority of the current second candidate instruction is obtained based on the second requirement satisfaction score of each of the second device nodes corresponding to the current second candidate instruction.

[0028] Preferably, based on the second device node and the second weight of user dependency, a second requirement satisfaction score is obtained for each of the second device nodes corresponding to the current second candidate instruction, including:

[0029] Obtain the executed instructions of the current second device node and the smartwatch during the control process; the current second device node can be any one of the second device nodes.

[0030] Based on the executed instructions and the current second candidate instructions, obtain the control necessity information of the current second device node; the control necessity information is used to characterize whether the device needs additional instruction intervention;

[0031] Based on the second weight of user dependence and the information on the necessity of regulation, the second requirement satisfaction score of the current second device node corresponding to the current second candidate instruction is obtained.

[0032] Preferably, the process of obtaining the second device node and the second weight of user dependency corresponding to each second device node includes:

[0033] Obtain the device nodes associated with the user status change or device abnormal status, and use the newly added device node among the associated device nodes, as well as the first device node other than the newly added device node, as the second device node;

[0034] Set the second weight of user dependency corresponding to the newly added device node as the highest priority weight, and use the first weight corresponding to the first device node other than the newly added device node as the second weight corresponding to the first device node other than the newly added device node.

[0035] Preferably, obtaining the first candidate control instruction set associated with the IoT device includes:

[0036] The device functions in the initial state model are enumerated and sampled to obtain the first candidate control instruction set; the first candidate control instruction set includes device start / stop, parameter adjustment, mode switching and basic instructions.

[0037] Preferably, obtaining the second candidate control instruction set associated with the IoT device includes:

[0038] The executed instructions of the smartwatch during the control process are filtered out from the target initial instructions to obtain a set of unexecuted instructions;

[0039] Enumerate and sample the emergency functions corresponding to the user status changes or device abnormal states to obtain an emergency candidate instruction set;

[0040] The union of the set of unexecuted instructions and the set of emergency candidate instructions is taken as the second candidate control instruction set.

[0041] The IoT-based smartwatch control device, applicable to the aforementioned IoT-based smartwatch control method, includes:

[0042] The state acquisition unit is used to acquire the initial state model of the IoT devices associated with the smartwatch, acquire the first device nodes included in the initial state model, and the first user dependency weight corresponding to each first device node; the first user dependency weight is used to characterize the importance of the device to the user's daily use.

[0043] The first generation unit is configured to obtain a first candidate control instruction set associated with the IoT device, obtain a first execution priority of each first candidate instruction included in the first candidate control instruction set according to the first device node and the first weight of user dependency, and obtain a target initial instruction from the first candidate instructions according to the first execution priority; the instruction set composed of the target initial instruction is the instruction set with the optimal number of instructions and the most comprehensive coverage of user needs;

[0044] A basic control unit is used to generate a basic control strategy for the smartwatch based on the initial instructions of each target; the basic control strategy is used to control the smartwatch's routine operation of IoT devices.

[0045] The status detection unit is used to obtain the second device node and the second weight of user dependence corresponding to each second device node if a change in user status or abnormal device status is detected when the smartwatch controls the IoT device according to the basic control strategy.

[0046] The second generation unit is used to obtain a second candidate control instruction set associated with the IoT device, obtain a second execution priority of each second candidate instruction included in the second candidate control instruction set according to the second device node and the second weight of user dependency, and obtain a target dynamic instruction from the second candidate instructions according to the second execution priority.

[0047] A dynamic control unit is used to adjust the basic control strategy according to the target dynamic command to obtain a real-time control strategy; the real-time control strategy is used to control the smartwatch's dynamic response to IoT devices to adapt to changes in user status or device malfunctions.

[0048] Compared with the prior art, the beneficial effects of the present invention are:

[0049] (1) This invention dynamically adjusts the control strategy by weighting the user’s dependence on the device node and adjusting the control strategy accordingly, so as to make the smartwatch’s control of IoT devices more intelligent. For example, the watch prioritizes the operation that is more important to the user’s needs based on the user’s dependence on the device, thus improving the operation efficiency. Moreover, by analyzing changes in the user’s state or device abnormalities, the control strategy can be adjusted in real time, so that the smartwatch can adapt to different user needs and device conditions. This adaptability improves the user experience and ensures that the watch can make appropriate responses in different usage environments.

[0050] (2) By calculating the dependency and demand satisfaction score of the device nodes, the present invention realizes the intelligent allocation of control command priority, optimizes the order of device control, enables the watch to handle the user's most concerned needs more efficiently, and reduces unnecessary operations; and when the device malfunctions or the user's state changes, the system can generate dynamic control strategies and adjust operation commands in a timely manner, avoiding delayed response in the event of device failure or abnormality, and improving the system's emergency response capability.

[0051] (3) The present invention selects the most suitable set of instructions for the current scenario from a wide range of control instructions by enumeration sampling. This not only ensures the comprehensiveness of the instructions, but also improves the execution efficiency of the instruction set, making the control process more accurate and efficient. Moreover, by considering factors such as device type and historical usage frequency, the method can assign different priority weights to different types of devices, making the control strategy of the watch closer to the actual needs and preferences of users, thereby improving user dependence and satisfaction. Attached Figure Description

[0052] Figure 1 This is a schematic flowchart of the overall method in one embodiment of the present invention;

[0053] Figure 2 This is a schematic diagram of the overall device architecture in one embodiment of the present invention.

[0054] In the diagram: 1. Status acquisition unit; 2. First generation unit; 3. Basic control unit; 4. Status detection unit; 5. Second generation unit; 6. Dynamic control unit. Detailed Implementation

[0055] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0056] Example 1, please refer to Figure 1 This invention provides a technical solution: a smartwatch control method based on the Internet of Things, comprising:

[0057] S1. Obtain the initial state model of the IoT devices associated with the smartwatch, obtain the first device node included in the initial state model, and the first weight of user dependence corresponding to each first device node; the first weight of user dependence is used to characterize the importance of the device to the user's daily use.

[0058] S2. Obtain the first candidate control instruction set associated with the IoT device. Based on the first device node and the first weight of user dependency, obtain the first execution priority of each first candidate instruction included in the first candidate control instruction set. Based on the first execution priority, obtain the target initial instruction from the first candidate instructions. The instruction set composed of the target initial instruction is the instruction set with the optimal number of instructions and the most comprehensive coverage of user needs.

[0059] S3. Generate the basic control strategy for the smartwatch based on the initial instructions of each target; the basic control strategy is used to control the smartwatch's routine operation of IoT devices.

[0060] S4. During the process of the smartwatch controlling IoT devices according to the basic control strategy, if a change in user status or an abnormal device status is detected, the second device node and the second weight of user dependence corresponding to each second device node are obtained.

[0061] S5. Obtain the second candidate control instruction set associated with the IoT device, and based on the second device node and the second weight of user dependency, obtain the second execution priority of each second candidate instruction included in the second candidate control instruction set, and obtain the target dynamic instruction from the second candidate instructions based on the second execution priority.

[0062] S6. Adjust the basic control strategy according to the target dynamic command to obtain the real-time control strategy; the real-time control strategy is used to control the smartwatch's dynamic response to IoT devices to adapt to changes in user status or abnormal device conditions.

[0063] It's important to note that the smartwatch first obtains an initial state model of its associated IoT devices. These devices can be smart home devices, such as smart lights, air conditioners, and door locks. Each device is considered a "device node." Each device node has a "user dependency" weight, representing the importance of the device to the user's daily life; for example, the user dependency of an air conditioner might be high, while that of smart lights might be low. The smartwatch then obtains a set of "first-line candidate control commands" based on the initial state model of the IoT devices. These commands can be device operation instructions (such as "turn on" and "turn off"). Based on the dependency of each device node (the user's importance to the device) and their needs, the system assigns an "execution priority" to each candidate command; for example, if the air conditioner is very important to the user (high dependency), then control commands for the air conditioner will have a higher priority. Finally, the system selects a set of commands that covers the broadest range of user needs and ensures an optimal number of commands. Based on the target initial commands, the smartwatch generates a "basic control strategy." This control strategy determines how the smartwatch routinely controls the IoT devices; for example, if... Users frequently need to adjust the air conditioner temperature, and the control strategy may periodically check and adjust the air conditioner's temperature settings. The smartwatch continuously monitors the device's operation and changes in the user's status. If, during operation, the system detects a change in the user's status (such as the user entering a state of exercise or experiencing an abnormal body temperature) or a device malfunction (such as the air conditioner failing), the system will proceed to the next step. Based on the change in user status or device malfunction, the smartwatch will acquire a new "second candidate control instruction set." This acquired instruction set is a response to dynamic situations and may adjust priorities based on new device nodes or statuses. For example, if an increase in the user's body temperature is detected, the air conditioner may have a higher priority than other devices (such as lights). Each instruction also has an execution priority, and the system will select the most appropriate instruction to execute based on these priorities. The smartwatch adjusts its original control strategy based on the new target dynamic instructions, generating a "real-time control strategy." The purpose of this real-time control strategy is to ensure that the smartwatch can dynamically respond to user status or device malfunctions to adapt to actual changes. For example, if the air conditioner fails to work due to equipment failure, the system may choose to activate other cooling devices or adjust the ambient temperature control strategy.

[0064] In an optional embodiment, based on the first device node and the first weight of user dependency, a first execution priority is obtained for each first candidate instruction included in the first candidate control instruction set, including:

[0065] Obtain the current first candidate instruction and the target first device node that the current first candidate instruction can act on; the current first candidate instruction is any one of the first candidate instructions;

[0066] Based on the first weight of user dependency corresponding to each target first device node, the first demand satisfaction score corresponding to each target first device node is obtained;

[0067] Based on the scores of each first requirement being met, the first execution priority of the current first candidate instruction is obtained.

[0068] It's important to note that a "current first candidate instruction" is selected from the set of candidate control instructions for IoT devices. This instruction is chosen from multiple candidate instructions and can be a device control command, such as "turn on the light" or "adjust the temperature." This instruction needs to act on a specific "target first device node," that is, the device it wants to control, such as smart lights or air conditioners. Each device node (such as air conditioners or lights) has a "user dependency first weight," representing the importance of the device to the user's daily life. This weight is usually a number representing the device's dependency; for example, air conditioners may have a higher dependency on users, while smart lights may have a lower dependency. Based on the dependency weights of these devices, the system calculates a "first requirement satisfaction score" for each device. This score can be seen as an evaluation of the device's performance in completing the current task. For example, a device with a higher dependency will be given a higher requirement satisfaction score. The calculation of the requirement satisfaction score may be based on multiple factors, such as the current state of the device and the urgency of the user's requirement. Based on the requirement satisfaction score of each device, the system will calculate the execution priority of the current first candidate instruction. Instructions with higher execution priority will be executed first. For example, if the air conditioner has a high requirement satisfaction score (because of high user dependency), then the air conditioner's control instruction will also have a higher priority.

[0069] In an optional embodiment, a first demand satisfaction score corresponding to each target first device node is obtained based on a first weight of user dependency corresponding to each target first device node, including:

[0070] Obtain the current first device node and the number of first candidate instructions that can be applied to the current first device node; the current first device node can be any one of the first device nodes.

[0071] Based on the quantity and the first weight of user dependence corresponding to the current first device node, the first demand satisfaction score corresponding to the current first device node is obtained.

[0072] It's important to note that the process begins by selecting a device node, referred to as the "current first device node." This device can be any smart device in the home, such as an air conditioner, lights, or door lock. The system then identifies the number of commands that can be applied to this device. For example, for an air conditioner, commands might include "turn on the air conditioner," "adjust the temperature," and "turn off the air conditioner." For smart lights, commands might include "adjust the brightness," "turn on the light," and "turn off the light." The system calculates the total number of commands that can be applied to this device. Finally, it selects one device node from all available device nodes as the current device node (e.g., air conditioner, lights, door lock). Each device node can have different control commands. Each device node has a user dependency weight, representing its importance to the user's life. For example, an air conditioner might have a high dependency (high weight), while lights might have a lower dependency (low weight). When calculating the demand satisfaction score, the system considers not only the device's dependency weight but also the number of commands that can be applied to it. A higher number of commands indicates greater device operability, allowing the system to make more adjustments based on different needs, thus potentially resulting in a higher demand satisfaction score.

[0073] In an optional embodiment, obtaining the first device nodes included in the initial state model, and the first weight of user dependency corresponding to each first device node, includes:

[0074] Obtain the first device node included in the initial state model, as well as the device type label and historical usage frequency corresponding to each first device node;

[0075] Obtain the baseline weights corresponding to each device type label and historical usage frequency; the baseline weights are used to characterize the user dependency baseline values ​​of different types of devices at different usage frequencies.

[0076] The baseline weight corresponding to each first device node is used as the first weight of user dependence for each first device node.

[0077] It should be noted that, firstly, all device nodes in the initial state model are acquired. These device nodes may be devices in a home, office, or other smart environment. Each device node has a device type label, such as "air conditioner," "lighting," or "door lock," and each device node has a historical usage frequency, indicating how often the device is used; for example, the air conditioner was used 10 times in the past week, and the smart light was used 30 times. A baseline weight is used to characterize the degree of user dependence on the device at different usage frequencies. The baseline value of dependence is related to the device type label and historical usage frequency; for example, for a device like "air conditioner," frequent use may mean that the user depends on it more, so its baseline weight may be larger; and... For less frequently used devices, such as "smart locks," their baseline weight may be smaller. The baseline weight can be set based on device type tags (such as "air conditioner" or "lighting") and historical usage frequency. For example, if an "air conditioner" device was used 10 times in the past week, its baseline weight may be higher because air conditioners are relatively more relied upon. On the other hand, a "lighting" device may have a lower baseline weight because it is used more frequently, but the reliance on it each time may not be as strong as that of an air conditioner. The baseline weight of each device is converted into the first weight of user reliance on that device node, that is, the user reliance on the device node is calculated. This represents the overall degree of user reliance on the device. The higher the weight, the stronger the user's reliance on the device, and vice versa.

[0078] In an optional embodiment, based on the second device node and the second weight of user dependency, a second execution priority is obtained for each second candidate instruction included in the second candidate control instruction set, including:

[0079] Obtain the current second candidate instruction; the current second candidate instruction is any one of the various second candidate instructions.

[0080] Based on the second device node and the second weight of user dependency, the second requirement satisfaction score of each second device node corresponding to the current second candidate instruction is obtained;

[0081] The second execution priority of the current second candidate instruction is obtained based on the second requirement satisfaction score of each second device node corresponding to the current second candidate instruction.

[0082] It should be noted that one of the possible candidate instructions is selected as the "current second candidate instruction." This instruction can be a user command to operate a device, such as turning the device on or off, or adjusting device settings. For example, suppose the system has multiple candidate instructions, such as "turn on the air conditioner," "adjust the light brightness," or "close the door lock." The system selects one of these as the current second candidate instruction, such as "adjust the light brightness." For each device node (second device node), the system calculates a requirement satisfaction score based on the user dependency weight of that device. The second user dependency weight measures the degree of user dependence on the device, and the requirement satisfaction score reflects the ability of the current instruction to meet the device's requirements. The requirement satisfaction score is determined by two factors: the user dependency weight of the device node; and whether the device meets the requirements of the current instruction, which is usually measured through information such as the device's status and functions. For example, suppose... The backup nodes are: air conditioner: dependency weight 8; smart light: dependency weight 5; door lock: dependency weight 3; now select "adjust light brightness" as the instruction: the demand satisfaction score of the air conditioner may be 0, because the air conditioner cannot adjust the brightness; the demand satisfaction score of the smart light is based on its dependency weight (5) and the ability of the device itself to respond, and may get a higher demand satisfaction score (e.g., 5); the demand satisfaction score of the door lock is 0, because the door lock does not involve brightness adjustment; according to the demand satisfaction score of each device node, the system will comprehensively calculate the execution priority of the instruction; the execution priority can be calculated by weighted average, maximum value, etc. of the demand satisfaction scores of all devices, and finally determine the execution order of the instruction; if the demand satisfaction score is high, it means that the instruction is more in line with the user's needs and should have a higher priority; if the demand satisfaction score is low, the priority is low.

[0083] In an optional embodiment, a second requirement satisfaction score for each second device node corresponding to the current second candidate instruction is obtained based on the second device node and the second weight of user dependency, including:

[0084] Obtain the executed instructions of the current second device node and the smartwatch during the control process; the current second device node can be any one of the various second device nodes;

[0085] Based on the executed instructions and the current second candidate instructions, obtain the control necessity information of the current second device node; the control necessity information is used to characterize whether the device needs additional instruction intervention;

[0086] Based on the second weight of user dependence and the information on the necessity of regulation, the second requirement satisfaction score of the current second device node corresponding to the current second candidate instruction is obtained.

[0087] It should be noted that the device node being analyzed by the current system (the second device node) is one of the possible devices in the system; the smartwatch has already executed some instructions during the control process, such as adjusting heart rate monitoring and recording exercise data; the current second device node refers to the target device being considered by a certain device in the system (such as a smart light, air conditioner, smart door lock, etc.); executed instructions refer to instructions that have been sent and executed previously; for example, instructions that the smartwatch may have executed include "start heart rate monitoring" and "start exercise tracking"; for example, suppose the smartwatch (the current device) executed two instructions: "start heart rate monitoring" and "start exercise tracking". "The necessity information for intervention refers to determining whether the current device requires additional instructions. This information is based on the instructions already executed and the instructions currently planned to be executed. If the device has already executed some instructions, and the current instruction overlaps with or is no longer needed, then the device may not require further intervention. For example, suppose the smartwatch has already executed the 'Start motion tracking' instruction, and the current second candidate instruction is 'Record motion data'. If motion tracking is already in progress, no additional instructions may be needed (low necessity for intervention); if the smartwatch has not started motion tracking, then 'Start motion tracking' is required before 'Record data' can be executed." The system executes the "record exercise data" command. The demand satisfaction score is calculated based on the user's dependence weight on the device and the device's regulatory necessity information. This score reflects the effectiveness and necessity of the device executing the current candidate command. The second weight of dependence is an indicator of the user's reliance on the device; for example, a high dependence on a smartwatch means the user has a strong need for its functions. If the device has already executed certain commands as expected, and the current command is related to them, it may mean that no additional command is needed. Combining these two factors yields the demand satisfaction score for the device executing the current candidate command. If the device's regulatory necessity is low (no additional intervention is needed), the demand satisfaction score may be low; conversely, if intervention is needed, the demand satisfaction score may be high. For example, suppose the user's dependence weight on the smartwatch is 8 (high dependence), and the current second candidate command is "record exercise data." The regulatory necessity information indicates that the exercise tracking command has already been executed, therefore no additional intervention is needed. In this case, the demand satisfaction score may be low because the system believes no additional intervention is needed. However, if the regulatory necessity information indicates that the device has not executed the "exercise tracking" command, the system may consider "record exercise data" to require additional intervention, and the demand satisfaction score may be high.

[0088] In an optional embodiment, obtaining the second device node and the second weight of user dependency corresponding to each second device node includes:

[0089] Obtain the device nodes associated with user status changes or device abnormal status, and use the newly added device nodes among the associated device nodes, as well as the first device nodes other than the newly added device nodes, as the second device nodes;

[0090] Set the second weight of user dependency corresponding to the newly added device node as the highest priority weight, and use the first weight corresponding to the first device node other than the newly added device node as the second weight corresponding to the first device node other than the newly added device node.

[0091] It's important to note that when a user's state changes (e.g., a change in health status) or a device malfunctions (e.g., a low battery in a smartwatch, inability to connect), it's necessary to identify the device nodes associated with these state changes. User state changes include: for example, a user's heart rate being too high, excessive exercise, etc. Device malfunctions include: for example, low battery, device failure, etc. For example, suppose a user is wearing a smartwatch, the watch detects a high heart rate, and the connection between the phone and the watch is abnormal; then, the device nodes are the smartwatch and the phone. For device nodes related to user state changes or device malfunctions, first identify newly added device nodes (e.g., a new device or sensor), and designate them as second device nodes. A newly added device node refers to a device added to the device node list, possibly due to user state changes or device malfunctions. For example, suppose a user previously only used a smartwatch to monitor their heart rate, but now, for more accurate monitoring, adds a heart rate monitor as a device; the heart rate monitor is the newly added device. The system prioritizes devices as follows: First, the smartwatch is the primary device node; both the smartwatch and the heart rate monitor are secondary device nodes. Newly added device nodes (such as a new heart rate monitor) require the highest priority weight because they may be more urgent in responding to changes in the user's current state or device malfunctions. To ensure the new device can quickly and effectively handle current anomalies or changes, the system assigns it the highest weight. For example, if a new heart rate monitor provides more accurate monitoring of the user's health, its weight is set to the highest. For instance, the second priority weight for the heart rate monitor is 10. For device nodes other than newly added ones (such as the smartwatch), their original primary weight (e.g., dependency or importance) becomes their secondary weight. This means that although it is not a newly added device node, it still needs to be re-evaluated based on its importance. For example, if the smartwatch's original dependency (primary weight) is 7, its secondary weight will also be set to 7. This indicates that although it is not a newly added device, it still has a high priority.

[0092] In an optional embodiment, obtaining a first candidate set of control instructions associated with an IoT device includes:

[0093] The device functions in the initial state model are enumerated and sampled to obtain the first candidate control instruction set; the first candidate control instruction set includes device start / stop, parameter adjustment, mode switching and basic instructions.

[0094] It should be noted that in the initial state model of the device, various functions of the device are enumerated and sampled to generate a candidate set of control instructions. The control instruction set includes the device's routine control operations, such as: device start / stop: starting or stopping the device; parameter adjustment: adjusting the device's parameters, such as adjusting the temperature and brightness; mode switching: switching between different operating modes, such as switching from "energy-saving mode" to "high-efficiency mode"; basic instructions: some routine device operations, such as turning lights on and off, playing music, etc. For example, assuming the device is a smart home system, the initial state includes smart air conditioners, smart lights, smart speakers, etc. The functions that these devices can perform are: smart air conditioner: start / stop, temperature adjustment, mode switching (cooling / heating); smart lights: start / stop, brightness adjustment, color adjustment; smart speaker: start / stop, volume adjustment, playback mode switching. The first candidate set of control instructions obtained by enumeration and sampling may be: start / stop smart air conditioner, adjust air conditioner temperature, switch air conditioner mode; start / stop smart lights, adjust brightness, adjust color; start / stop smart speaker, adjust volume, switch playback mode.

[0095] In an optional embodiment, obtaining a second candidate control instruction set associated with an IoT device includes:

[0096] The set of unexecuted instructions is obtained by filtering out the executed instructions of the smartwatch during the control process from the initial target instructions;

[0097] Enumerate and sample the emergency functions corresponding to changes in user status or abnormal device status to obtain a set of emergency candidate instructions;

[0098] The union of the set of unexecuted instructions and the set of emergency candidate instructions is taken as the second candidate control instruction set.

[0099] It should be noted that during actual control, the smartwatch may have already executed some commands; for example, the smartwatch may have adjusted the heart rate monitoring mode or switched the display mode. By filtering out these executed commands, what remains is the "set of unexecuted commands." These commands are operations that have not yet been executed and can be considered for execution in subsequent control. For example, suppose the initial target commands include the following operations: adjust the smartwatch brightness; switch the smartwatch display mode; start heart rate monitoring; adjust the heart rate monitoring sensitivity. If the smartwatch has already executed the commands "start heart rate monitoring" and "adjust brightness," then they will no longer appear in the set of unexecuted commands. The remaining set of unexecuted commands is: switching the display mode, adjusting the heart rate monitoring sensitivity; when the user's state changes (e.g., ... When a user experiences a health abnormality or the device malfunctions (e.g., a device crash or disconnection), the device may need to take emergency measures. These emergency measures generate an emergency control instruction set, which typically includes specific instructions for emergency handling. For example, suppose a user's smartwatch detects a health abnormality (such as a high heart rate). The emergency candidate instruction set might include: activating the high heart rate emergency warning mode, immediately notifying the user's emergency contacts, activating the breathing relaxation mode, and activating the emergency rescue mode (e.g., automatically sending a distress signal to nearby medical institutions via GPS location). The second candidate control instruction set is obtained by combining the unexecuted instruction set and the emergency candidate instruction set. In other words, all unexecuted regular and emergency instructions are merged as the next possible control instructions to be executed.

[0100] Example 2, please refer to Figure 2 This invention provides a technical solution: a smartwatch control device based on the Internet of Things (IoT), applicable to the aforementioned smartwatch control method based on the IoT, comprising:

[0101] The state acquisition unit 1 is used to acquire the initial state model of the IoT devices associated with the smartwatch, acquire the first device nodes included in the initial state model, and the first weight of user dependence corresponding to each first device node; the first weight of user dependence is used to characterize the importance of the device to the user's daily use.

[0102] The first generation unit 2 is used to obtain a first candidate control instruction set associated with the Internet of Things device, obtain the first execution priority of each first candidate instruction included in the first candidate control instruction set according to the first device node and the first weight of user dependency, and obtain the target initial instruction from the first candidate instruction according to the first execution priority; the instruction set composed of the target initial instruction is the instruction set with the optimal number of instructions and the most comprehensive coverage of user needs;

[0103] The basic control unit 3 is used to generate the basic control strategy of the smartwatch based on the initial instructions of each target; the basic control strategy is used to control the smartwatch's routine operation of IoT devices.

[0104] The status detection unit 4 is used to obtain the second device node and the second weight of user dependence corresponding to each second device node if a change in user status or abnormal device status is detected when the smartwatch controls the IoT device according to the basic control strategy.

[0105] The second generation unit 5 is used to obtain a second candidate control instruction set associated with the Internet of Things device, obtain a second execution priority of each second candidate instruction included in the second candidate control instruction set according to the second device node and the second weight of user dependency, and obtain the target dynamic instruction from the second candidate instructions according to the second execution priority.

[0106] The dynamic control unit 6 is used to adjust the basic control strategy according to the target dynamic command to obtain the real-time control strategy; the real-time control strategy is used to control the smartwatch's dynamic response to IoT devices to adapt to changes in user status or abnormal device conditions.

[0107] The embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited thereto. Various changes can be made within the scope of knowledge possessed by those skilled in the art without departing from the spirit of the present invention.

Claims

1. A smart watch control method based on Internet of Things, characterized in that, The method comprises the following steps: obtain an initial state model of an Internet of Things device associated with a smart watch, obtain first device nodes included in the initial state model, and first weight of user dependence corresponding to each of the first device nodes; the first weight of user dependence is used to represent the importance of the device to the user's daily use; obtain a first candidate control instruction set associated with the Internet of Things device, obtain first execution priority of each first candidate instruction included in the first candidate control instruction set according to the first device nodes and the first weight of user dependence, and obtain a target initial instruction from the first candidate instruction according to the first execution priority; the instruction set composed of the target initial instruction is an instruction set with optimal number of instructions and covering the most comprehensive user demand; generate a basic control strategy of the smart watch according to each of the target initial instructions; the basic control strategy is used to control the smart watch to perform regular operation on the Internet of Things device; during the process that the smart watch controls the Internet of Things device according to the basic control strategy, if a user state change or a device abnormal state is detected, obtain second device nodes and second weight of user dependence corresponding to each of the second device nodes; obtain a second candidate control instruction set associated with the Internet of Things device, obtain second execution priority of each second candidate instruction included in the second candidate control instruction set according to the second device nodes and the second weight of user dependence, and obtain a target dynamic instruction from the second candidate instruction according to the second execution priority; adjust the basic control strategy according to the target dynamic instruction to obtain a real-time control strategy; the real-time control strategy is used to control the smart watch to perform dynamic response on the Internet of Things device to adapt to the user state change or the device abnormal condition; wherein, according to the second device nodes and the second weight of user dependence, the second execution priority of each second candidate instruction included in the second candidate control instruction set is obtained, which comprises: obtain a current second candidate instruction; the current second candidate instruction is any one of the second candidate instructions; obtain second demand satisfaction scores of each of the second device nodes corresponding to the current second candidate instruction according to the second device nodes and the second weight of user dependence; obtain the second execution priority of the current second candidate instruction according to the second demand satisfaction scores of each of the second device nodes corresponding to the current second candidate instruction. 2.The IoT-based smart watch control method of claim 1, wherein, According to the first device nodes and the first weight of user dependence, the first execution priority of each first candidate instruction included in the first candidate control instruction set is obtained, which comprises: obtain a current first candidate instruction and target first device nodes on which the current first candidate instruction can act; the current first candidate instruction is any one of the first candidate instructions; obtain first demand satisfaction scores of each of the target first device nodes according to the first weight of user dependence corresponding to each of the target first device nodes; obtain the first execution priority of the current first candidate instruction based on each of the first demand satisfaction scores. 3.The IoT-based smart watch control method of claim 2, wherein, According to the user dependency first weight corresponding to each target first device node, a first demand satisfaction score corresponding to each target first device node is obtained, comprising: Obtain the current first device node and the number of first candidate instructions that can act on the current first device node; The current first device node is any one of the first device nodes; According to the number and the user dependency first weight corresponding to the current first device node, a first demand satisfaction score corresponding to the current first device node is obtained. 4.The IoT-based smart watch control method of claim 3, wherein, Obtain the first device node included in the initial state model and the user dependency first weight corresponding to each first device node, comprising: Obtain the first device node included in the initial state model and the device type label and historical use frequency corresponding to each first device node; Obtain the reference weight corresponding to each device type label and historical use frequency; The reference weight is used to represent the user dependency reference value of different types of devices under different use frequencies; The reference weight corresponding to each first device node is used as the user dependency first weight corresponding to each first device node. 5.The IoT-based smart watch control method of claim 4, wherein, According to the second device node and the user dependency second weight, a second demand satisfaction score corresponding to each second device node for the current second candidate instruction is obtained, comprising: Obtain the current second device node and the executed instruction of the smart watch in the control process; The current second device node is any one of the second device nodes; According to the executed instruction and the current second candidate instruction, obtain the regulation and control necessity information of the current second device node; The regulation and control necessity information is used to represent whether the device needs additional instruction intervention; According to the user dependency second weight and the regulation and control necessity information, a second demand satisfaction score corresponding to the current second device node for the current second candidate instruction is obtained. 6.The IoT-based smart watch control method of claim 5, wherein, Obtain the second device node and the user dependency second weight corresponding to each second device node, comprising: Obtain the device node associated with the user state change or the abnormal state of the device, and set the newly added device node in the associated device node and the first device node except the newly added device node as the second device node; The user dependency second weight corresponding to the newly added device node is set as the highest priority weight, and the first weight corresponding to the first device node except the newly added device node is set as the second weight corresponding to the first device node except the newly added device node. 7.The IoT-based smart watch control method of claim 6, wherein, Obtain the first candidate control instruction set associated with the Internet of Things device, comprising: Enumerate and sample the device functions in the initial state model to obtain the first candidate control instruction set; The first candidate control instruction set includes device start-stop, parameter adjustment, mode switching and basic instructions. 8.The IoT-based smart watch control method of claim 7, wherein, Obtain the second candidate control instruction set associated with the Internet of Things device, comprising: From the target initial instruction, the executed instruction of the smart watch in the control process is screened out to obtain a non-executed instruction set; Enumerate and sample emergency functions corresponding to the user state change or device abnormal state, to obtain an emergency candidate instruction set; Take the union between the unexecuted instruction set and the emergency candidate instruction set as the second candidate control instruction set.

9. The smart watch control device based on the Internet of Things, which is suitable for the smart watch control method based on the Internet of Things according to any one of claims 1-8, characterized in that, Comprise: A state acquisition unit is configured to acquire an initial state model of an Internet of Things (IoT) device associated with a smart watch, acquire first device nodes included in the initial state model, and a first weight of user dependence corresponding to each of the first device nodes; the first weight of user dependence is used to represent the importance of the device to the user's daily use; A first generation unit is configured to acquire a first candidate control instruction set associated with the IoT device, obtain a first execution priority of each first candidate instruction included in the first candidate control instruction set according to the first device nodes and the first weight of user dependence, and acquire a target initial instruction from the first candidate instruction according to the first execution priority; the instruction set composed of the target initial instruction is an instruction set with optimal number of instructions and most comprehensive coverage of user demand; A basic control unit is configured to generate a basic control strategy of the smart watch according to each of the target initial instructions; The basic control strategy is used to control the smart watch to perform regular manipulation on the IoT device; A state detection unit is configured to acquire second device nodes and a second weight of user dependence corresponding to each of the second device nodes if a user state change or a device abnormal state is detected during the process in which the smart watch controls the IoT device according to the basic control strategy; A second generation unit is configured to acquire a second candidate control instruction set associated with the IoT device, obtain a second execution priority of each second candidate instruction included in the second candidate control instruction set according to the second device nodes and the second weight of user dependence, and acquire a target dynamic instruction from the second candidate instruction according to the second execution priority; A dynamic control unit is configured to adjust the basic control strategy according to the target dynamic instruction to obtain a real-time control strategy; The real-time control strategy is used to control the smart watch to perform dynamic response on the IoT device to adapt to the user state change or the device abnormal condition.

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