Cooperative operation method of smart home system

Abstract

The invention discloses a cooperative operation method of a smart home system, and relates to the technical field of home cooperation, and the method comprises the steps: enabling a plurality of smart homes to be connected into the smart home system through Wi-Fi, controlling the smart homes to carry out the cooperative operation through a set rule, enabling the smart homes to learn the behavior habits of a user through a machine learning algorithm, and enabling the smart homes to carry out the cooperative operation. The method has the advantages that through cooperative operation of the equipment, a user does not need to manually operate multiple pieces of equipment to meet the requirement of one scene, for example, in a home returning mode, after the user opens a home door, equipment such as an intelligent door lock, an intelligent lamp, an intelligent air conditioner and an intelligent curtain automatically and cooperatively work, light is automatically turned on, the air conditioner is adjusted to the comfortable temperature, and the curtain is pulled open; a warm and comfortable environment is created for the user, the time and energy of opening the equipment one by one by the user are saved, and the smart home system can cooperate according to the habits and preferences of the user.

Description

Technical Field

[0001] The present invention relates to the field of home collaboration technology, and in particular to a collaborative operation method for a smart home system. Background Art

[0002] The rapid development of Internet of Things (IoT) technology has laid a solid foundation for the coordinated operation of smart home systems. Through communication protocols such as Wi-Fi, ZigBee, Z-Wave, and Bluetooth, smart devices can connect to each other and exchange data. For example, the ZigBee protocol has the characteristics of low power consumption, low rate, and short-distance transmission, which is suitable for connecting various sensors and small smart devices, such as smart temperature and humidity sensors, smart door and window sensors, etc.; while the Wi-Fi protocol can provide higher data transmission rates and longer transmission distances, and is used to connect smart cameras, smart refrigerators, and other devices that require large data transmission. These communication protocols enable smart devices to "talk" to each other to achieve information sharing and instruction transmission; In traditional smart home systems, each smart home device usually works independently and lacks the ability to work together, which leads to limitations in the overall performance and user experience of the smart home system. To this end, we propose a collaborative operation method for smart home systems. Summary of the invention

[0003] The purpose of the present invention is to provide a collaborative operation method for a smart home system.

[0004] In order to solve the problems raised in the above background technology, the present invention provides the following technical solutions: a method for the coordinated operation of a smart home system, comprising connecting multiple smart homes to the smart home system using Wi-Fi, controlling the smart homes to operate in a coordinated manner through set rules, and the smart homes using machine learning algorithms to learn the user's behavior habits. The specific operation steps of the method for the coordinated operation of a smart home system are as follows: Step 1: Preliminary preparation: The smart home control center uses the Wi-Fi protocol to enable various smart homes to work together; Step 2: Set rules for collaborative operation. Users manually set the linkage rules between devices through the control software of the smart home system; Step 3: According to the time and sensor data trigger rules, the device collaboration is triggered by the time and data collected by various smart sensors; Step 4: Based on the environment perception automation rules, the smart home system formulates automation rules using the environmental data collected by the smart sensors; Step 5: Use artificial intelligence and machine learning to achieve collaborative operation. The smart home system uses machine learning algorithms to learn users' daily behavior habits, and artificial intelligence optimizes existing rules through user feedback during use; Step 6: Use the smart gateway to achieve communication between devices with different protocols. The smart gateway can automatically discover and connect new devices added to the smart home system.

[0005] As a further solution of the present invention: in the step one, a home Mesh network device that supports dual frequency bands is selected, and the frequency band is automatically switched when the smart home changes its position with the Mesh node. The Mesh nodes are connected via wireless Wi-Fi, and the transmission power is between 17dBm-20dBm and the transmission rate is between 400Mbps-1000Mbps. The Wi-Fi setting of the smart home device is turned on, and the smart home device is connected to the home Mesh network. The Mesh network coordinates and links all smart devices in the house.

[0006] As a further solution of the present invention: in the step 2, the user uses the control software of the smart home system to manually set the rules and set the trigger conditions for the starting point of the rule operation. The trigger conditions are time, device status changes and sensor data. After determining the trigger conditions, it is necessary to set the actions to be performed when the trigger conditions are met. These actions are the collaborative operations of multiple devices. After completing the setting of the trigger conditions and the execution actions, the rules are named and saved.

[0007] As a further solution of the present invention: in the step three, based on the time and temperature collaborative triggering rules, in summer, the time range is set to 9 am to 6 pm. When the temperature sensor detects that the indoor temperature is higher than 28°C, the smart air conditioner turns on the cooling mode and sets the temperature to 24°C-26°C. At the same time, when the humidity sensor detects that the humidity is higher than 70%, the smart dehumidifier works to control the indoor humidity between 45%-65%. Based on the time and light collaborative triggering rules, the time range is set to 7 am to 5 pm. When the light sensor detects that the light intensity is higher than 800Lux, the smart curtains automatically work to control the indoor light intensity between 300Lux-500Lux.

[0008] As a further solution of the present invention: in the step three, based on the time and human body sensor collaborative triggering rules, the time range is set to 10 pm to 6 am the next day. The millimeter wave radar detects human breathing and heartbeat by emitting electromagnetic waves in the millimeter wave frequency band of 30GHz-300GHz. When the user's breathing rate is 12-20 times / min and the heart rate is 10%-30% lower than when awake, the body activity gradually decreases and tends to stabilize, and it is detected that the user has fallen asleep. The smart home system automatically turns off the main light in the bedroom, and the smart air conditioner controls the temperature between 24℃-26℃. When the user gets up at night, the human body sensor detects human activity and the night light automatically lights up.

[0009] As a further solution of the present invention: in the step 4, smart sockets and power sensors are used, and the smart home system monitors the energy consumption of each electrical device in real time. When it is detected that the energy consumption of the electrical device is abnormally increased, the system issues an alarm to remind the user to check the electrical device. According to the energy budget and equipment usage habits set by the user, the system automatically adjusts the operation mode of the electrical device when the energy consumption is close to the budget upper limit to reduce the use of high-energy consumption equipment. The smart home system uses temperature sensors and carbon monoxide sensors to issue fire warnings. When the temperature sensor detects an abnormal increase in temperature and the carbon monoxide sensor detects that the carbon monoxide concentration exceeds 10ppm, the smart home system triggers an alarm, automatically closes the gas valve in the home, cuts off the power supply of the electrical device, and automatically unlocks the smart door lock when a fire occurs. The smart door lock, door and window sensors and cameras work together to form a complete security system. When the door and window sensors detect that the doors and windows are abnormally opened and the smart door locks are violently cracked, the system will trigger an alarm, and the camera will automatically turn on the recording function to record the behavior of suspicious persons and send the video to the APP in real time.

[0010] As a further solution of the present invention: in the step five, the smart home system records a large amount of data through various sensors and device interactions. The smart home system collects the time, frequency and schedule of the user's use of the device, cleans the collected data, removes erroneous data, fills in missing values ​​and removes duplicate data records, analyzes the processed data for differences, and builds a user's habit model. The system automatically generates collaborative operation rules. When the smart home system determines that the user is about to arrive home through mobile phone positioning and smart door lock status, the smart home system turns on the smart lights in the living room in advance according to the user's habits. When the time reaches 10 o'clock in the evening, the system automatically executes the user's accustomed sleep mode.

[0011] As a further solution of the present invention: in step five, the smart home system collects user feedback during scene usage to understand user satisfaction with the scene mode and improvement suggestions. Based on the collected feedback information, the system uses a machine learning algorithm to adjust the parameters and rules of the scene mode. As user living habits change and new devices are added, the smart home system can continuously adapt to and update the scene mode, and provide a mechanism for users to manually adjust and intervene. When the optimization results of the model do not meet user expectations, the user can easily make modifications, and these modification data are fed back to the model for further learning and optimization.

[0012] As a further solution of the present invention: in the step six, the smart gateway monitors the broadcast signals of the devices in the network. When the new device is connected to the home network, it sends the broadcast signal according to the protocol of the device. After receiving the broadcast signal, the smart gateway parses the signal and recognizes that this is a new smart home. The smart gateway sends a connection request to it according to the protocol supported by the device. After receiving the request, the device performs authentication and parameter matching. After the match is successful, the device will establish a connection with the smart gateway. The smart gateway assigns a network address and configures communication parameters to the device according to the type of device and the user's settings, so that the new device can be integrated into the smart home system and work in coordination with other devices.

[0013] By adopting the above technical solution, compared with the prior art, the beneficial effects of the present invention are: The present invention uses the collaborative operation between devices, so users do not need to manually operate multiple devices to meet a scene requirement. For example, in the "return home mode", after the user opens the door, smart door locks, smart lights, smart air conditioners, smart curtains and other devices automatically work together, the lights automatically light up, the air conditioner is adjusted to a comfortable temperature, and the curtains are opened, creating a warm and comfortable environment for the user, saving the user's time and energy to open the devices one by one. The smart home system can collaborate according to the user's habits and preferences, and different users can set different collaboration rules according to their preferences to meet personalized needs; The present invention automatically controls the operating status of equipment according to factors such as environment and time through the smart home system. When there is sufficient light during the day, the system can automatically turn off the indoor lights or dim the light brightness after detecting sufficient light through the light sensor. At the same time, after the user leaves home, the system automatically turns off unnecessary electrical appliances, such as televisions, computers, etc., to avoid standby power consumption. Through coordinated operation, the smart home system can achieve optimal utilization of energy. For example, in high temperatures in summer, the system can coordinate the operation of smart air conditioners and smart fans. When the indoor temperature is high, the fan is turned on first for ventilation to reduce the perceived temperature. If the temperature is still beyond the comfortable range, the air conditioner is turned on again. According to factors such as the indoor and outdoor temperature difference and humidity, the temperature and wind speed of the air conditioner are reasonably set to achieve energy saving. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 Schematic diagram of the collaborative operation steps of the smart home system in an embodiment of the present invention. DETAILED DESCRIPTION

[0015] The specific embodiments of the present invention are further described below in conjunction with the accompanying drawings. It should be noted that the description of these embodiments is used to help understand the present invention, but does not constitute a limitation of the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0016] The present invention provides a method for collaborative operation of a smart home system, including using Wi-Fi to connect multiple smart homes to the smart home system, controlling the smart homes to perform collaborative operation through set rules, and using a machine learning algorithm to learn the user's behavior habits. The specific operation steps of the method for collaborative operation of a smart home system are as follows: Step 1: Preliminary preparation: The smart home control center uses the Wi-Fi protocol to enable various smart homes to work together; Step 2: Set rules for collaborative operation. Users manually set the linkage rules between devices through the control software of the smart home system; Step 3: According to the time and sensor data trigger rules, the device collaboration is triggered by the time and data collected by various smart sensors; Step 4: Based on the environment perception automation rules, the smart home system formulates automation rules using the environmental data collected by the smart sensors; Step 5: Use artificial intelligence and machine learning to achieve collaborative operation. The smart home system uses machine learning algorithms to learn users' daily behavior habits, and artificial intelligence optimizes existing rules through user feedback during use; Step 6: Use the smart gateway to achieve communication between devices with different protocols. The smart gateway can automatically discover and connect new devices added to the smart home system.

[0017] In one embodiment of the present invention: in step one, a home Mesh network device that supports dual frequency bands is selected, and the frequency band is automatically switched when the smart home changes its position with the Mesh node. The Mesh nodes are connected via wireless Wi-Fi, and the transmission power is between 17dBm-20dBm and the transmission rate is between 400Mbps-1000Mbps. The Wi-Fi setting of the smart home device is turned on, and the smart home device is connected to the home Mesh network. The Mesh network coordinates and links all smart devices in the house.

[0018] In one embodiment of the present invention: in step 2, the user uses the control software of the smart home system to manually set the rules and set the trigger conditions for the starting point of the rule operation. The trigger conditions are time, device status changes and sensor data. After determining the trigger conditions, it is necessary to set the actions to be performed when the trigger conditions are met. These actions are the collaborative operations of multiple devices. After completing the setting of the trigger conditions and the execution actions, the rules are named and saved.

[0019] In one embodiment of the present invention: In step three, based on the time and temperature collaborative triggering rules, in summer, the time range is set to 9 am to 6 pm. When the temperature sensor detects that the indoor temperature is higher than 28°C, the smart air conditioner turns on the cooling mode and sets the temperature to 24°C-26°C. At the same time, when the humidity sensor detects that the humidity is higher than 70%, the smart dehumidifier works to control the indoor humidity between 45%-65%. Based on the time and light collaborative triggering rules, the time range is set to 7 am to 5 pm. When the light sensor detects that the light intensity is higher than 800Lux, the smart curtains automatically work to control the indoor light intensity between 300Lux-500Lux.

[0020] In one embodiment of the present invention: In step three, based on the time and human body sensor collaborative triggering rules, the time range is set to 10 pm to 6 am the next day. The millimeter wave radar detects human breathing and heartbeat by emitting electromagnetic waves in the millimeter wave frequency band of 30GHz-300GHz. When the user's breathing rate is 12-20 times / min and the heart rate is 10%-30% lower than when awake, the body activity gradually decreases and tends to stabilize, and it is detected that the user has fallen asleep. The smart home system automatically turns off the main light in the bedroom, and the smart air conditioner controls the temperature between 24℃-26℃. When the user gets up at night, the human body sensor detects human activity and the night light automatically lights up.

[0021] In one embodiment of the present invention: in step 4, smart sockets and power sensors are used, and the smart home system monitors the energy consumption of each electrical device in real time. When it is detected that the energy consumption of the electrical device is abnormally increased, the system issues an alarm to remind the user to check the electrical device. According to the energy budget and equipment usage habits set by the user, the system automatically adjusts the operation mode of the electrical device when the energy consumption is close to the budget upper limit to reduce the use of high-energy consumption equipment. The smart home system uses temperature sensors and carbon monoxide sensors to issue fire warnings. When the temperature sensor detects an abnormal increase in temperature and the carbon monoxide sensor detects that the carbon monoxide concentration exceeds 10ppm, the smart home system triggers an alarm, automatically closes the gas valve in the home, cuts off the power supply of the electrical device, and automatically unlocks the smart door lock when a fire occurs. The smart door lock, door and window sensors, and cameras work together to form a complete security system. When the door and window sensors detect that the doors and windows are abnormally opened or the smart door locks are violently cracked, the system triggers an alarm, and the camera automatically turns on the recording function to record the behavior of suspicious persons and send the video to the APP in real time.

[0022] In one embodiment of the present invention: In step five, the smart home system records a large amount of data through various sensors and device interactions. The smart home system collects the time, frequency and schedule of the user's use of the device, cleans the collected data, removes erroneous data, fills in missing values ​​and removes duplicate data records, analyzes the processed data for differences, and builds a user's habit model. The system automatically generates collaborative operation rules. When the smart home system determines that the user is about to arrive home through mobile phone positioning and smart door lock status, the smart home system turns on the smart lights in the living room in advance according to the user's habits. When the time reaches 10 o'clock in the evening, the system automatically executes the user's accustomed sleep mode.

[0023] In one embodiment of the present invention: In step five, the smart home system collects user feedback during scene usage to understand user satisfaction with the scene mode and improvement suggestions. Based on the collected feedback information, the system uses a machine learning algorithm to adjust the parameters and rules of the scene mode. As user living habits change and new devices are added, the smart home system can continuously adapt to and update the scene mode, and provide a mechanism for users to manually adjust and intervene. When the optimization results of the model do not meet user expectations, the user can easily make modifications, and these modification data are fed back to the model for further learning and optimization.

[0024] In one embodiment of the present invention: in step six, the smart gateway monitors the broadcast signals of devices in the network. When a new device is connected to the home network, it sends a broadcast signal in accordance with the protocol of the device. After receiving the broadcast signal, the smart gateway parses the signal and recognizes that this is a new smart home. The smart gateway sends a connection request to it according to the protocol supported by the device. After receiving the request, the device performs authentication and parameter matching. After a successful match, the device establishes a connection with the smart gateway. The smart gateway assigns a network address and configures communication parameters to the device according to the type of device and the user's settings, so that the new device can be integrated into the smart home system and work in coordination with other devices.

[0025] Embodiment 1: The user manually sets rules including time trigger conditions, device status trigger conditions and sensor data trigger conditions. 7 o'clock every morning is set as the trigger condition. When the time is reached, the alarm clock starts working and the smart curtains are automatically opened. At 10 o'clock every night, the system starts the "sleep mode", the bedroom lights are turned off, and the smart air conditioner adjusts the temperature to 26°C. The smart door lock is set to change from the "locked" state to the "open" state as a trigger condition, automatically turning on the smart lights in the living room, closing the smart curtains, turning off the smart camera, turning on the smart air conditioner, and linking the smart humidifier to adjust the indoor humidity according to the data of the humidity sensor. The data collected by the smart sensor is set as the trigger rule. When the temperature sensor detects that the indoor temperature is higher than 28°C and the infrared sensor recognizes that there are people in the room, the trigger rule allows the smart air conditioner to turn on the cooling mode.

[0026] Embodiment 2: When the user is sleeping, the millimeter-wave radar continuously monitors the user's sleep condition and records the sleep cycle, number of tossing and turning, and number of apnea data. These data can be displayed to the user through the smart home system's APP to help the user understand their sleep quality. If it detects that the user has a high number of apnea episodes at night, the APP reminds the user that there may be a risk of sleep apnea syndrome and recommends medical treatment. If the millimeter-wave radar does not detect human activity for a long time while the user is sleeping, the smart home system can issue an alarm to remind family members to pay attention.

[0027] Embodiment 3: In the sleeping scenario, the system discovers through the temperature sensor and the data of the user's manual adjustment of the air-conditioning temperature that the user has different requirements for the sleeping temperature in different seasons and weather conditions. The system dynamically adjusts the temperature setting of the air-conditioning in the sleeping mode according to environmental factors such as outdoor temperature and humidity and the user's historical adjustment data. For example, on humid summer nights, the temperature is appropriately lowered and the dehumidification function is increased; on dry winter nights, the temperature is slightly increased and the humidifier is turned on.

[0028] As attached Figure 1 As shown in the figure, the home Mesh network device connects multiple smart homes to the smart home system through wireless Wi-Fi. The use of Mesh nodes can enable multiple smart home devices to work together at the same time, without the need for users to operate the smart home separately. The smart home system can automatically learn user behavior habits through artificial intelligence and machine learning, and formulate corresponding automation rules.

[0029] The embodiments of the present invention are described in detail above with reference to the accompanying drawings, but the present invention is not limited to the described embodiments. For those skilled in the art, various changes, modifications, substitutions and variations of these embodiments are made without departing from the principles and spirit of the present invention, and still fall within the scope of protection of the present invention.

[0030] In the description of the specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0031] The above contents are merely examples and explanations of the present invention. Various modifications or additions to the specific embodiments described or replacements in similar ways by technicians in the technical field shall fall within the protection scope of the present invention as long as they do not deviate from the invention or exceed the scope defined by the claims.

[0032] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A method for collaborative operation of a smart home system, comprising connecting multiple smart homes to the smart home system using Wi-Fi, controlling the smart homes to operate collaboratively by set rules, and using a machine learning algorithm to learn user behavior habits, characterized in that: The specific operation steps of the collaborative operation method of the smart home system are as follows: Step 1: Preliminary preparation: The smart home control center uses the Wi-Fi protocol to enable various smart homes to work together; Step 2: Set rules for collaborative operation. Users manually set the linkage rules between devices through the control software of the smart home system; Step 3: According to the time and sensor data trigger rules, the device collaboration is triggered by the time and data collected by various smart sensors; Step 4: Based on the environment perception automation rules, the smart home system formulates automation rules using the environmental data collected by the smart sensors; Step 5: Use artificial intelligence and machine learning to achieve collaborative operation. The smart home system uses machine learning algorithms to learn users' daily behavior habits, and artificial intelligence optimizes existing rules through user feedback during use; Step 6: Use the smart gateway to achieve communication between devices with different protocols. The smart gateway can automatically discover and connect new devices added to the smart home system.

2. The method for cooperative operation of a smart home system according to claim 1, characterized in that: In the step 1, a home Mesh network device that supports dual frequency bands is selected, and the frequency band is automatically switched when the smart home changes its position with the Mesh node. The Mesh nodes are connected via wireless Wi-Fi, with a transmission power between 17dBm-20dBm and a transmission rate between 400Mbps-1000Mbps. The Wi-Fi settings of the smart home device are turned on, and the smart home device is connected to the home Mesh network. The Mesh network coordinates and links all smart devices in the house.

3. The method for cooperative operation of a smart home system according to claim 1, characterized in that: In step 2, the user uses the control software of the smart home system to manually set the rules and set the trigger conditions for the starting point of the rule operation. The trigger conditions are time, device status changes and sensor data. After determining the trigger conditions, it is necessary to set the actions to be performed when the trigger conditions are met. These actions are the collaborative operations of multiple devices. After completing the setting of the trigger conditions and execution actions, the rules are named and saved.

4. The method for cooperative operation of a smart home system according to claim 1, characterized in that: In the step three, based on the time and temperature collaborative triggering rules, in summer, the time range is set to 9 am to 6 pm. When the temperature sensor detects that the indoor temperature is higher than 28°C, the smart air conditioner turns on the cooling mode and sets the temperature to 24°C-26°C. At the same time, when the humidity sensor detects that the humidity is higher than 70%, the smart dehumidifier works to control the indoor humidity between 45%-65%. Based on the time and light collaborative triggering rules, the time range is set to 7 am to 5 pm. When the light sensor detects that the light intensity is higher than 800Lux, the smart curtains automatically work to control the indoor light intensity between 300Lux-500Lux.

5. The method for cooperative operation of a smart home system according to claim 1, characterized in that: In the step three, based on the time and human body sensor collaborative triggering rules, the time range is set to 10 pm to 6 am the next day. The millimeter wave radar detects human breathing and heartbeat by emitting electromagnetic waves in the millimeter wave frequency band of 30GHz-300GHz. When the user's breathing rate is 12-20 times / min and the heart rate is 10%-30% lower than when awake, the body activity gradually decreases and tends to stabilize. It is detected that the user has fallen asleep, and the smart home system automatically turns off the main light in the bedroom, and the smart air conditioner controls the temperature between 24℃-26℃. When the user gets up at night, the human body sensor detects human activity and the night light automatically lights up.

6. The method for cooperative operation of a smart home system according to claim 1, characterized in that: In the step 4, the smart socket and power sensor are used, and the smart home system monitors the energy consumption of each electrical device in real time. When it is detected that the energy consumption of the electrical device is abnormally increased, the system issues an alarm to remind the user to check the electrical device. According to the energy budget and equipment usage habits set by the user, the system automatically adjusts the operation mode of the electrical device when the energy consumption is close to the budget upper limit to reduce the use of high-energy consumption equipment. The smart home system uses temperature sensors and carbon monoxide sensors to issue fire warnings. When the temperature sensor detects an abnormal increase in temperature and the carbon monoxide sensor detects that the carbon monoxide concentration exceeds 10ppm, the smart home system triggers an alarm, automatically closes the gas valve in the home, cuts off the power supply of the electrical device, and automatically unlocks the smart door lock when a fire occurs. The smart door lock, door and window sensors and cameras work together to form a complete security system. When the door and window sensors detect that the doors and windows are abnormally opened or the smart door locks are violently cracked, the system triggers an alarm, and the camera automatically turns on the recording function to record the behavior of suspicious persons and send the video to the APP in real time.

7. The method for cooperative operation of a smart home system according to claim 1, characterized in that: In the step five, the smart home system records a large amount of data through various sensors and device interactions. The smart home system collects the time, frequency and schedule of the user's use of the device, cleans the collected data, removes erroneous data, fills in missing values ​​and removes duplicate data records, analyzes the processed data for differences, and builds a user's habit model. The system automatically generates collaborative operation rules. When the smart home system determines that the user is about to arrive home through mobile phone positioning and smart door lock status, the smart home system turns on the smart lights in the living room in advance according to the user's habits. When the time reaches 10 o'clock in the evening, the system automatically executes the user's accustomed sleep mode.

8. The method for cooperative operation of a smart home system according to claim 1, characterized in that: In step five, the smart home system collects user feedback during scene usage to understand user satisfaction with the scene mode and suggestions for improvement. Based on the collected feedback information, the system uses a machine learning algorithm to adjust the parameters and rules of the scene mode. As user living habits change and new devices are added, the smart home system can continuously adapt to and update the scene mode, and provide a mechanism for users to manually adjust and intervene. When the optimization results of the model do not meet user expectations, users can easily make modifications, and these modification data are fed back to the model for further learning and optimization.

9. The method for cooperative operation of a smart home system according to claim 1, characterized in that: In step six, the smart gateway monitors the broadcast signals of devices in the network. When a new device is connected to the home network, it sends a broadcast signal in accordance with the protocol of the device. After receiving the broadcast signal, the smart gateway parses the signal and recognizes that this is a new smart home. The smart gateway sends a connection request to it according to the protocol supported by the device. After the device receives the request, it performs authentication and parameter matching. After a successful match, the device establishes a connection with the smart gateway. The smart gateway assigns a network address and configures communication parameters to the device according to the type of device and the user's settings, so that the new device can be integrated into the smart home system and work in coordination with other devices.

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