Intelligent home control system based on Internet of Things

Abstract

The invention discloses a smart home control system based on the Internet of Things, and relates to the technical field of smart home, the control system comprises a terminal control module, a high-definition data acquisition module, a data control module and an early warning module, the terminal control module comprises a data storage unit and a data processing unit, the data processing unit is used for storing historical feature data and equipment data, the data storage unit is used for storing historical feature data and equipment data, a network architecture is arranged in the terminal control module, and the equipment data is analyzed by using the network architecture. And then behavior characteristic data needing to be collected next is predicted in advance, and the behavior characteristic data is transmitted to the high-definition data collection module, so that the resource consumption occupied when the high-definition image data collected by the high-definition data collection module is transmitted is reduced.

Description

Technical Field

[0001] The present invention relates to the field of smart home technology, and in particular to a smart home control system based on the Internet of Things. Background Art

[0002] In the development process of modern smart home control systems, voice, as an important means of interaction and control, has gradually exposed many inconveniences. With the increasing variety of smart home devices and the continuous expansion of functions, voice control functions have been widely used to provide users with a convenient operating experience. However, there are a lot of voice inconveniences in actual usage scenarios. For example, in a multi-person home environment, the voice commands of different members may interfere with each other, causing the smart home system to misjudge or fail to accurately identify the commands of specific users. Especially in noisy environments such as family gatherings and entertainment activities, background noise will seriously weaken the accuracy of voice recognition, forcing users to increase the volume and repeat the commands, which not only affects the fluency of the interaction, but may also cause unnecessary noise interference to other family members or neighbors;

[0003] However, the existing smart home control system cannot control the devices in the smart home for some special groups of people and people with hoarse voices, and cannot adjust the transmission speed of the smart home according to the performance of the control device. For this reason, we propose a smart home control system based on the Internet of Things. Summary of the invention

[0004] The purpose of the present invention is to provide a smart home control system based on the Internet of Things.

[0005] To achieve the above object, the present invention provides the following technical solutions: a smart home control system based on the Internet of Things, the control system comprising a terminal control module, a high-definition data acquisition module, a data control module and an early warning module;

[0006] The terminal control module includes a data storage unit and a data processing unit. The data storage unit is used to store historical feature data and device data. A network architecture is set in the terminal control module, and the device data is analyzed using the network architecture. The terminal control module adjusts the working state of the high-definition data acquisition module according to the planning task. The data processing unit is used to analyze device performance and pre-process behavioral feature data. After the data processing unit analyzes the device performance resources, the data processing unit creates a device resource threshold according to the device performance resources. When the device performance resources required by the planning task are ≥ the resource threshold, the terminal control module creates mode adjustment instruction data, transmits the mode adjustment instruction data to the high-definition data acquisition module, and uses the high-definition data acquisition module to transmit the collected module to the terminal control module. Then the terminal control module matches the data collected by the high-definition data acquisition module. When the equipment performance resources required by the planning task are less than the resource threshold, the terminal control module analyzes the historical feature data in the data storage unit, obtains the linkage of the personnel feature data, the home control instructions and the behavioral feature data according to the historical feature data, and transmits the analyzed linkage data and the behavioral feature data to the high-definition data acquisition module. The high-definition data acquisition module matches the behavioral feature data with the linkage, and then obtains the home control instructions, and then transmits the successfully matched home control instructions to the data control module, and the behavioral feature data is combined through the portrait action and the execution action, and then after the portrait action is recognized, the execution action needs to be recognized within 3 seconds to obtain the corresponding home control instruction;

[0007] The high-definition data acquisition module is used to collect indoor portrait data;

[0008] The data control module is used to receive instructions and control different home appliances to work according to the instructions;

[0009] The early warning module is used to perform early warning processing on abnormal devices in the home.

[0010] As a further solution of the present invention: a light supplement unit is set in the terminal control module, and the light supplement unit analyzes the image compensation parameters in different time periods, and transmits the image compensation parameters in different time periods to the high-definition data acquisition module. The high-definition data acquisition module adjusts the parameters of the collected image according to the image compensation parameters, and quickly obtains and analyzes the user image feature data in the image.

[0011] As a further solution of the present invention: the terminal control module also includes a task generation unit and a prediction unit. After the device performance resource ≥ resource threshold in the terminal control module, the prediction unit is used to analyze historical feature data, and analyze the behavioral feature data at different times based on the historical feature data. The task generation unit analyzes the number of task instructions that need to be generated based on the behavioral feature data, and adjusts the priority of task instruction processing based on the user's personal habits in the historical feature data.

[0012] As a further solution of the present invention: the task generation unit analyzes the priority values ​​of different tasks according to a formula, and the specific formula is as follows:

[0013]

[0014] Among them, X i represents the priority value of the i-th task instruction, f i1 represents the personal preference weight coefficient of the i-th task instruction, n represents the maximum threshold number of days, A i1 , A i2 ,……,A in They represent the characteristic data of the i-th task instruction within the threshold number of days, f i2 represents the historical data weight coefficient of the i-th task instruction, W i represents the characteristic data in the historical data of the i-th task instruction, N represents the number of days exceeding the maximum threshold number of days, and then the characteristic data of the threshold number of days in the formula is updated every day.

[0015] As a further solution of the present invention: a user tracking unit is set in the high-definition data acquisition module. After the high-definition data acquisition module identifies the user data, when the user moves to the edge position of the high-definition data acquisition module, the user tracking unit transmits the user data to the terminal control module, and then the terminal control module calls other visuals in the high-definition data acquisition module to identify the user data.

[0016] As a further solution of the present invention: the high-definition data acquisition module includes a high-definition image acquisition unit and a feature matching unit. The high-definition image acquisition unit is used to acquire indoor image data, and then use the high-definition image acquisition unit to obtain the user's behavioral feature data. The feature matching unit monitors the image data in the high-definition image acquisition unit in real time, and matches the behavioral feature data received in the feature matching unit with the behavioral feature data of the user in the image data in real time. After the match is successful, the home control instruction data corresponding to the behavioral feature data is transmitted to the data control module. The data control module controls and adjusts the equipment in the home according to the home control instruction data. When the equipment performance resources are less than the resource threshold, the feature matching unit is not started to work. At the same time, the high-definition acquisition unit transmits the collected data to the terminal control module, and then the data transmitted in the high-definition data acquisition module is processed and identified by the data processing unit, and then the home control instructions corresponding to the behavioral feature data are analyzed, and the home control instruction data is transmitted to the data control module.

[0017] As a further solution of the present invention: a body data analysis unit is set in the terminal control module, and the body data analysis unit is used to analyze the body status data in the high-definition data acquisition module in real time, retrieve the room temperature adjustment data in the data storage unit, analyze the body status data and the indoor environment adjustment data that matches the room temperature adjustment data, transmit the indoor environment adjustment data to the data control module, and then control and adjust the indoor equipment.

[0018] As a further solution of the present invention: a network diagnostic unit is set in the data control module, and the network diagnostic unit is used to monitor the stability of the home network. When the network fluctuation is greater than 100ms, the data control module transmits the fluctuation data to the terminal control module, and then the terminal control module transmits the behavioral feature data analyzed by the prediction unit to the high-definition data acquisition module in advance.

[0019] By adopting the above technical solution, compared with the prior art, the beneficial effects of the present invention are:

[0020] 1. The present invention retrieves historical feature data from the data storage unit through the terminal control module, and the data processing unit analyzes the historical feature data, thereby predicting in advance the behavioral feature data that needs to be collected next, and transmits the behavioral feature data to the high-definition data collection module, thereby reducing the resource consumption occupied by the high-definition image data collected by the high-definition data collection module during transmission;

[0021] 2. The present invention adjusts the processing mode of the data processing unit through the terminal control module through the network architecture, thereby enabling the control system to quickly respond to task requirements;

[0022] 3. The present invention uses the light supplement unit to obtain the parameters of the image that need to be adjusted in different time periods through historical feature data, thereby facilitating the high-definition data acquisition module to quickly obtain the user behavior feature data in the image;

[0023] 4. The present invention uses a task generation unit to adjust the feature sequence recognized by the high-definition data acquisition module according to the user's recent behavior habits and historical behavior habits, so that the control system can respond quickly to different users;

[0024] 5. The present invention connects the image data between the high-definition image acquisition units in series through the user tracking unit, thereby facilitating the tracking and identification of the user's movements.

[0025] Other advantages, objectives and features of the present invention will be set forth in part in the following description and, in part, will be apparent to those skilled in the art based on an examination of the following or may be taught from the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 This is a flow chart of a control system in an embodiment of the present invention;

[0027] Figure 2 This is a flow chart of behavioral feature data analysis by a terminal control module in an embodiment of the present invention;

[0028] Figure 3 This is a flow chart of behavioral feature data that is not analyzed by the terminal control module in an embodiment of the present invention. DETAILED DESCRIPTION

[0029] The specific embodiments of the present invention will be 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.

[0030] 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.

[0031] Embodiment 1:

[0032] Please see attached Figure 1 -Attached Figure 3 The present invention provides a smart home control system based on the Internet of Things, the control system includes a terminal control module, a high-definition data acquisition module, a data control module and an early warning module;

[0033] The terminal control module includes a data storage unit and a data processing unit. The data storage unit is used to store historical feature data and device data. A network architecture is set in the terminal control module, and the device data is analyzed using the network architecture. The terminal control module adjusts the working state of the high-definition data acquisition module according to the planning task. The data processing unit is used to analyze the device performance and pre-process the behavioral feature data. After the data processing unit analyzes the device performance resources, the data processing unit creates a device resource threshold according to the device performance resources. When the device performance resources required by the planning task are ≥ the resource threshold, the terminal control module creates mode adjustment instruction data, transmits the mode adjustment instruction data to the high-definition data acquisition module, and uses the high-definition data acquisition module to transmit the collected module to the terminal control module, and then the terminal The terminal control module matches and processes the data collected by the high-definition data acquisition module. When the equipment performance resources required for the planning task are less than the resource threshold, the terminal control module analyzes the historical feature data in the data storage unit, obtains the linkage of the personnel feature data, the home control instructions and the behavioral feature data according to the historical feature data, and transmits the analyzed linkage data and behavioral feature data to the high-definition data acquisition module. The high-definition data acquisition module matches the behavioral feature data with the linkage, and then obtains the home control instructions, and then transmits the successfully matched home control instructions to the data control module, and the behavioral feature data is combined through the portrait action and the execution action, and then after the portrait action is recognized, the execution action needs to be recognized within 3 seconds to obtain the corresponding home control instruction;

[0034] The high-definition data acquisition module is used to collect indoor portrait data;

[0035] The data control module is used to receive instructions and control different home appliances to work according to the instructions;

[0036] The early warning module is used to provide early warning for abnormal devices in the home.

[0037] Specific workflow: When the user is unwell, has damaged vocal cords, or is overly tired, the control system can be used to control the home. When a planned task is generated, the data processing unit of the terminal control module begins to analyze the equipment performance resources required for the task and compares them with the created equipment resource threshold. If the equipment performance resources required for the planned task ≥ the resource threshold: the terminal control module creates real-time control instruction data and transmits the control instruction data to the high-definition data acquisition module. The high-definition data acquisition module collects indoor portrait data according to the instructions and transmits the collected data back to the terminal control module. The terminal control module matches the data collected by the high-definition data acquisition module to further determine the details of task execution. If the equipment performance resources required for the planning task are less than the resource threshold, the terminal control module deeply analyzes the historical feature data in the data storage unit, obtains the linkage of personnel feature data, home control instructions and behavioral feature data, and transmits the analyzed linkage data and behavioral feature data to the high-definition data acquisition module. The high-definition data acquisition module matches the received behavioral feature data with the linkage to determine the corresponding home control instruction, and transmits the successfully matched home control instruction to the data control module. The data control module receives the instruction from the terminal control module and controls the corresponding home equipment to work according to the instruction, such as controlling the brightness of the light switch, adjusting the temperature of the air conditioner, etc.

[0038] Furthermore, the terminal control module retrieves the historical feature data in the data storage unit, and the data processing unit analyzes the historical feature data to predict in advance the behavioral feature data that needs to be collected next, and transmits the behavioral feature data to the high-definition data collection module, thereby reducing the resource consumption occupied by the high-definition image data collected by the high-definition data collection module during transmission;

[0039] The terminal control module adjusts the processing mode of the data processing unit through the network architecture, so that the control system can respond quickly to task requirements.

[0040] Embodiment 2:

[0041] Based on the first embodiment, please refer to the attached Figure 1 -Attached Figure 3As shown, a light supplement unit is set in the terminal control module, and the light supplement unit analyzes the image compensation parameters in different time periods, and transmits the image compensation parameters in different time periods to the high-definition data acquisition module. The high-definition data acquisition module adjusts the parameters of the collected image according to the image compensation parameters, and quickly obtains and analyzes the user image feature data in the image. The terminal control module also includes a task generation unit and a prediction unit. After the device performance resource in the terminal control module is ≥ the resource threshold, the prediction unit is used to analyze the historical feature data, and analyze the behavioral feature data at different times according to the historical feature data. The task generation unit analyzes the number of task instructions that need to be generated according to the behavioral feature data, and uses the personal habits of the user in the historical feature data to adjust the priority of task instruction processing. The task generation unit analyzes the priority values ​​of different tasks according to the formula. The specific formula is as follows:

[0042]

[0043] Among them, X i represents the priority value of the i-th task instruction, f i1 represents the personal preference weight coefficient of the i-th task instruction, n represents the maximum threshold number of days, A i1 , A i2 ,……,A in They represent the characteristic data of the i-th task instruction within the threshold number of days, f i2 represents the historical data weight coefficient of the i-th task instruction, W i represents the characteristic data in the historical data of the i-th task instruction, N represents the number of days exceeding the maximum threshold number of days, and then the characteristic data of the threshold number of days in the formula is updated every day.

[0044] Specific workflow: a light compensation unit is set in the terminal control module through image compensation parameter analysis and transmission; the light compensation unit analyzes image compensation parameters of different time periods, and transmits the image compensation parameters of different time periods to the high-definition data acquisition module; the high-definition data acquisition module adjusts the parameters of the acquired image according to the received image compensation parameters, and quickly acquires and analyzes the user's image feature data in the image; the terminal control module includes a task generation unit and a prediction unit; when the device performance resources in the terminal control module are ≥ the resource threshold: the prediction unit is used to analyze the historical feature data, and the behavioral feature data at different times is analyzed according to the historical feature data; the task generation unit analyzes the number of task instructions that need to be generated according to the behavioral feature data, and uses the user's personal habits in the historical feature data to adjust the priority of task instruction processing.

[0045] Furthermore, the light supplement unit obtains the parameters of the image that need to be adjusted in different time periods through historical feature data, thereby facilitating the high-definition data acquisition module to quickly obtain the user behavior feature data in the image;

[0046] The task generation unit adjusts the feature sequence recognized by the high-definition data acquisition module according to the user's recent and historical behavior habits, so that the control system can respond quickly to different users.

[0047] Embodiment three:

[0048] Based on the second embodiment, please refer to the attached Figure 1 -Attached Figure 3 As shown, a user tracking unit is set in the high-definition data acquisition module. After the high-definition data acquisition module recognizes the user data, when the user moves to the edge of the high-definition data acquisition module, the user tracking unit transmits the user data to the terminal control module, and then the terminal control module calls other vision in the high-definition data acquisition module to recognize the user data. The high-definition data acquisition module includes a high-definition image acquisition unit and a feature matching unit. The high-definition image acquisition unit is used to collect indoor image data, and then the high-definition image acquisition unit is used to obtain the user's behavioral feature data. The feature matching unit monitors the image data in the high-definition image acquisition unit in real time, and the behavior data received in the feature matching unit is received. The characteristic data is matched with the behavioral characteristic data of the user in the image data in real time. After the match is successful, the home control instruction data corresponding to the behavioral characteristic data is transmitted to the data control module. The data control module controls and adjusts the devices in the home according to the home control instruction data. When the device performance resource is less than the resource threshold, the characteristic matching unit is not started to work. At the same time, the high-definition acquisition unit transmits the collected data to the terminal control module, and then the data transmitted in the high-definition data acquisition module is processed and identified by the data processing unit, and then the home control instruction corresponding to the behavioral characteristic data is analyzed, and the home control instruction data is transmitted to the data control module.

[0049] Specific workflow: Select the home control method based on the device resources in the home through the network architecture, and then adjust the operation mode of the control system as needed.

[0050] Furthermore, the user tracking unit connects the image data between the high-definition image acquisition units in series, thereby facilitating tracking and identifying the user's movements.

[0051] Embodiment 4:

[0052] Based on the third embodiment, please refer to the attached Figure 1 -Attached Figure 3As shown, a body data analysis unit is provided in the terminal control module, and the body data analysis unit is used to analyze the body status data in the high-definition data acquisition module in real time, retrieve the room temperature adjustment data in the data storage unit, analyze the body status data and the indoor environment adjustment data that match the room temperature adjustment data, transmit the indoor environment adjustment data to the data control module, and then control and adjust the indoor equipment. A network diagnosis unit is provided in the data control module, and the network diagnosis unit is used to monitor the stability of the home network. When the network fluctuation is greater than 100ms, the data control module transmits the fluctuation data to the terminal control module, and then the terminal control module transmits the behavioral feature data analyzed by the prediction unit to the high-definition data acquisition module in advance.

[0053] Furthermore, the network diagnosis unit is used to prevent the control system from reacting slowly due to excessive network fluctuations, so that the prediction unit and the data processing unit can transmit the predicted behavioral characteristic data to the high-definition data acquisition module in advance, thereby preventing the control system from being unable to respond in time due to network fluctuations.

[0054] The above shows and describes the basic principles, main features and advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A smart home control system based on the Internet of Things, characterized in that: The control system includes a terminal control module, a high-definition data acquisition module, a data control module and an early warning module; The terminal control module includes a data storage unit and a data processing unit. The data storage unit is used to store historical feature data and device data. A network architecture is set in the terminal control module, and the device data is analyzed using the network architecture. The terminal control module adjusts the working state of the high-definition data acquisition module according to the planning task. The data processing unit is used to analyze device performance and pre-process behavioral feature data. After the data processing unit analyzes the device performance resources, the data processing unit creates a device resource threshold according to the device performance resources. When the device performance resources required by the planning task are ≥ the resource threshold, the terminal control module creates mode adjustment instruction data, transmits the mode adjustment instruction data to the high-definition data acquisition module, and uses the high-definition data acquisition module to transmit the collected module to the terminal control module. Then the terminal control module matches the data collected by the high-definition data acquisition module. When the equipment performance resources required by the planning task are less than the resource threshold, the terminal control module analyzes the historical feature data in the data storage unit, obtains the linkage of the personnel feature data, the home control instructions and the behavioral feature data according to the historical feature data, and transmits the analyzed linkage data and the behavioral feature data to the high-definition data acquisition module. The high-definition data acquisition module matches the behavioral feature data with the linkage, and then obtains the home control instructions, and then transmits the successfully matched home control instructions to the data control module, and the behavioral feature data is combined through the portrait action and the execution action, and then after the portrait action is recognized, the execution action needs to be recognized within 3 seconds to obtain the corresponding home control instruction; The high-definition data acquisition module is used to collect indoor portrait data; The data control module is used to receive instructions and control different home appliances to work according to the instructions; The early warning module is used to perform early warning processing on abnormal devices in the home.

2. The smart home control system based on the Internet of Things according to claim 1, characterized in that: A light supplement unit is set in the terminal control module, and the light supplement unit analyzes the image compensation parameters in different time periods and transmits the image compensation parameters in different time periods to the high-definition data acquisition module. The high-definition data acquisition module adjusts the parameters of the collected image according to the image compensation parameters to quickly obtain and analyze the user image feature data in the image.

3. The smart home control system based on the Internet of Things according to claim 2 is characterized in that: The terminal control module also includes a task generation unit and a prediction unit. When the device performance resource in the terminal control module is ≥ the resource threshold, the prediction unit is used to analyze the historical feature data, and analyze the behavioral feature data at different times based on the historical feature data. The task generation unit analyzes the number of task instructions that need to be generated based on the behavioral feature data, and adjusts the priority of task instruction processing based on the user's personal habits in the historical feature data.

4. The smart home control system based on the Internet of Things according to claim 3 is characterized in that: The task generation unit analyzes the priority values ​​of different tasks according to a formula, and the specific formula is as follows: Among them, X i represents the priority value of the i-th task instruction, f i1 represents the personal preference weight coefficient of the i-th task instruction, n represents the maximum threshold number of days, A i1 , A i2 ,……,A in They represent the characteristic data of the i-th task instruction within the threshold number of days, f i2 represents the historical data weight coefficient of the i-th task instruction, W i represents the characteristic data in the historical data of the i-th task instruction, N represents the number of days exceeding the maximum threshold number of days, and then the characteristic data of the threshold number of days in the formula is updated every day.

5. The smart home control system based on the Internet of Things according to claim 4 is characterized in that: A user tracking unit is set in the high-definition data acquisition module. After the high-definition data acquisition module identifies the user data, when the user moves to the edge position of the high-definition data acquisition module, the user tracking unit transmits the user data to the terminal control module, and then the terminal control module calls other visuals in the high-definition data acquisition module to identify the user data.

6. The smart home control system based on the Internet of Things according to claim 5, characterized in that: The high-definition data acquisition module includes a high-definition image acquisition unit and a feature matching unit. The high-definition image acquisition unit is used to acquire indoor image data, and then use the high-definition image acquisition unit to obtain the user's behavioral feature data. The feature matching unit monitors the image data in the high-definition image acquisition unit in real time, and matches the behavioral feature data received in the feature matching unit with the behavioral feature data of the user in the image data in real time. After the match is successful, the home control instruction data corresponding to the behavioral feature data is transmitted to the data control module. The data control module controls and adjusts the equipment in the home according to the home control instruction data. When the equipment performance resource is less than the resource threshold, the feature matching unit is not started to work. At the same time, the high-definition acquisition unit transmits the collected data to the terminal control module, and then the data transmitted in the high-definition data acquisition module is processed and identified by the data processing unit, and then the home control instruction corresponding to the behavioral feature data is analyzed, and the home control instruction data is transmitted to the data control module.

7. The smart home control system based on the Internet of Things according to claim 6, characterized in that: A body data analysis unit is provided in the terminal control module, which is used to analyze the body status data in the high-definition data acquisition module in real time, retrieve the room temperature adjustment data in the data storage unit, analyze the indoor environment adjustment data that matches the body status data and the room temperature adjustment data, transmit the indoor environment adjustment data to the data control module, and then control and adjust the indoor equipment.

8. The smart home control system based on the Internet of Things according to claim 7, characterized in that: A network diagnostic unit is set in the data control module, and the network diagnostic unit is used to monitor the stability of the home network. When the network fluctuation is greater than 100ms, the data control module transmits the fluctuation data to the terminal control module, and then the terminal control module transmits the behavioral feature data analyzed by the prediction unit to the high-definition data acquisition module in advance.

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