An intelligent home robot control system based on multi-terminal data analysis

Abstract

The present application relates to the technical field of intelligent home robot control, and especially relates to an intelligent home robot control system based on multi-terminal data analysis, which comprises an intelligent internet control center, a home database, a time period state evaluation module, a non-voice control module, a voice control module, a double-control evaluation analysis module and a control management module; the present application preliminarily analyzes from two angles of standby state and execution state of the intelligent home robot to improve the state stability of the intelligent home robot, analyzes the voice control and non-voice control performance from the angles of voice control and non-voice control based on the information feedback mode to improve the voice and non-voice control sensitivity, and adjusts the voice control and non-voice control scheme from the historical control angle through the information progressive mode to improve the single control efficiency and overall control efficiency of the voice control and non-voice control of the intelligent home robot.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent home robot control, and particularly relates to an intelligent home robot control system based on multi-end data analysis. BACKGROUND

[0002] The home appliance system has become a project that the industry focuses on; the intelligent home is a platform based on a residence, uses network communication technology, security protection technology, automatic control technology and the like, integrates devices related to home life, constructs a high-efficiency residential facility and a management system of daily affairs at home, and improves home safety, convenience and comfort; the intelligent robot providing intelligent home service is also generated.

[0003] However, in the prior art, the overall safety of the intelligent home robot cannot be monitored, thereby reducing the operation safety of the intelligent home robot, the intelligent home robot cannot be controlled in a targeted manner according to the control mode of the intelligent home robot, thereby reducing the control effect and stability of the intelligent home robot, and the control scheme of the intelligent home robot cannot be controlled from a historical perspective, thereby affecting the control sensitivity of the intelligent home robot.

[0004] In view of the above technical defects, a solution is proposed. SUMMARY

[0005] The present application aims to provide an intelligent home robot control system based on multi-end data analysis to solve the above technical defects; the present application preliminarily analyzes the standby state and the execution state of the intelligent home robot to improve the state stability of the intelligent home robot, analyzes the voice control and non-voice control performance of the current intelligent home robot from the angles of voice control and non-voice control based on information feedback to improve the voice and non-voice control sensitivity of the current intelligent home robot, and adjusts the single and double control management of the voice control and non-voice control scheme from the historical control angle through information progression to improve the single control efficiency and overall control efficiency of the voice control and non-voice control of the intelligent home robot.

[0006] The purpose of the present application can be achieved by the following technical scheme: an intelligent home robot control system based on multi-end data analysis, comprising an intelligent internet-of-things control center, a home database, a time period state evaluation module, a non-voice control module, a voice control module, a double-control evaluation and analysis module and a control management module.

[0007] The intelligent internet-of-things control center is used to call the state information of the intelligent home robot from the home database and send the state information to the time period state evaluation module.

[0008] The period state evaluation module is used for dynamic and static fusion evaluation feedback analysis on the received state information, and obtains standby evaluation value and dynamic evaluation value according to the state information and analyzes to obtain a safety signal or an alarm signal.

[0009] The non-voice control module is used for responding to the safety signal, collecting smart home robot wisdom internet information, performing non-voice control evaluation feedback analysis on the wisdom internet information, performing discriminant processing on the obtained control obstacle coefficient, and obtaining a normal signal or an abnormal signal.

[0010] The voice control module is used for responding to the safety signal, collecting smart home robot voice control information, and performing voice control multi-angle fusion evaluation analysis on the voice control information, performing discriminant processing on the obtained voice control evaluation coefficient, and obtaining a stable signal or a risk signal.

[0011] The double control evaluation analysis module is used for calling the total number of historical controls of the smart home robot from the home database, performing double control decision quantization progressive analysis on the total number of historical controls, performing discriminant processing on the obtained control demand evaluation value, and obtaining a voice management signal or a non-voice management signal or a double control signal.

[0012] Preferably, the dynamic and static fusion evaluation feedback analysis process is as follows:

[0013] A monitoring period is set and is set as a time threshold, state information of the smart home robot within the time threshold is obtained, the state information includes standby evaluation value and dynamic evaluation value, the standby evaluation value and the dynamic evaluation value are compared and analyzed with preset standby evaluation value threshold and preset dynamic evaluation value threshold, and a safety signal or an alarm signal is obtained.

[0014] The standby evaluation value represents a product value obtained by multiplying the energy consumption value and the internal temperature mean value of the smart home robot in standby state after data normalization processing; and the dynamic evaluation value represents a product value obtained by multiplying the operation trajectory of the smart home robot in execution state and the number and frequency of deviation from the preset operation trajectory after data normalization processing.

[0015] Preferably, the non-voice control evaluation feedback analysis process is as follows:

[0016] The control mode of the smart home robot within the time threshold is obtained, the control mode includes voice control and non-voice control; if the current smart home robot is non-voice control, the wisdom internet information of the smart home robot within the time threshold is obtained, and the wisdom internet information includes state stability index and smooth running coefficient.

[0017] The state stability index and the smooth running coefficient are compared with a preset state stability index threshold and a preset smooth running coefficient threshold, the number of the state stability index and the smooth running coefficient greater than or equal to the preset state stability index threshold and the preset smooth running coefficient threshold is set as a control obstacle coefficient, and the control obstacle coefficient is discriminated to obtain a normal signal or an abnormal signal.

[0018] Preferably, the state stability index represents the number of Internet of Things defect features between the user control end and the smart home robot, and the Internet of Things defect features include interruption and lag; and the smooth running coefficient represents a part of the actual transmission time of the user command code exceeding a preset threshold, and the actual transmission time represents the time length between the sending time of the user command code and the execution time of the smart home robot.

[0019] Preferably, the voice control multi-angle fusion evaluation and analysis process is as follows:

[0020] If the current smart home robot is voice controlled, the voice control information of the smart home robot within a time threshold is obtained, the voice control information includes an obstacle transmission coefficient and an identification evaluation value, and an interference control factor of the smart home robot within the time threshold is also obtained.

[0021] The sum value obtained by adding the values of the obstacle transmission coefficient and the identification evaluation value after data normalization processing is multiplied by the interference control factor to obtain a voice control evaluation coefficient, and the voice control evaluation coefficient is discriminated to obtain a stable signal or a risk signal.

[0022] Preferably, the obstacle transmission coefficient represents the number of obstacle features between the position of the user's voice wake-up and the position of the smart home robot, and the obstacle features include walls and glass; and the identification evaluation value represents the time length between the time when the smart home robot receives the user's voice wake-up and the response time.

[0023] Preferably, the interference control factor is obtained as follows:

[0024] The network quantization coefficient of the smart home robot and the user within a time threshold is obtained, the network quantization coefficient represents the number of network information corresponding values of the smart home robot and the user being lower than a preset threshold, and the network information includes network speed and network throughput; the network quantization coefficient is compared with a preset network quantization coefficient interval, and the interference control factor corresponding to the network quantization coefficient located in the preset network quantization coefficient interval is obtained.

[0025] Preferably, the double-control decision quantization progressive analysis process is as follows:

[0026] The total number of historical controls of the smart home robot within a time threshold is obtained, the total number of voice controls and the total number of non-voice controls in the total number of historical controls are obtained;

[0027] The proportion of the number of times that the user exceeds 2 voice wake-up times in a single voice control process in the total number of voice controls is obtained, and is set as a voice recognition depth; the proportion of the number of times that the user sends instructions encountering feedback problems in a single non-voice control process in the total number of non-voice controls is obtained, and is set as an Internet of Things performance coefficient, the feedback problems including error and delay;

[0028] The voice recognition depth and the Internet of Things performance coefficient are compared and analyzed with a preset voice recognition depth threshold and a preset Internet of Things performance coefficient threshold, the number of times that the voice recognition depth and the Internet of Things performance coefficient are greater than or equal to the preset voice recognition depth threshold and the preset Internet of Things performance coefficient threshold is set as a control demand evaluation value, and the control demand evaluation value is discriminated to obtain a voice management signal or a non-voice management signal or a double control signal.

[0029] The beneficial effects of the present application are as follows:

[0030] The present application preliminarily analyzes from two angles of standby state and execution state of the smart home robot, so as to intuitively understand whether the state risk of the smart home robot is too high, and facilitate reasonable management of the smart home robot, so as to improve the state stability and control safety of the smart home robot.

[0031] The present application performs in-depth analysis from two points of voice control and non-voice control based on the information feedback mode, that is, analyzes the voice control and non-voice control performance of the current smart home robot from the angles of voice control and non-voice control, so as to reasonably manage the current smart home robot, improve the voice and non-voice control sensitivity and stability of the current smart home robot, and help improve the monitoring effect of the current smart home robot.

[0032] The present application performs double control decision quantization progressive analysis on the smart home robot through information progressive mode, that is, performs targeted single and double control management adjustment on the voice control and non-voice control scheme from the historical control angle, so as to improve the single control efficiency and overall control efficiency of the voice control and non-voice control of the smart home robot. BRIEF DESCRIPTION OF DRAWINGS

[0033] The present application will be further described below with reference to the accompanying drawings;

[0034] Figure 1 is a system flowchart of the present application;

[0035] Figure 2 is a local analysis reference diagram of the second embodiment of the present application. DETAILED DESCRIPTION

[0036] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative effort belong to the scope of protection of the present application. Embodiment one

[0037] Please refer to Figure 1 The present application is an intelligent home robot control system based on multi-end data analysis, which comprises an intelligent internet-of-things control center, a home database, a time period state evaluation module, a non-voice control module, a voice control module, a double-control evaluation analysis module and a control management module. The home database is in one-way communication connection with the intelligent internet-of-things control center. The intelligent internet-of-things control center is in two-way communication connection with the time period state evaluation module. The intelligent internet-of-things control center is in one-way communication connection with the non-voice control module and the voice control module. The non-voice control module is in one-way communication connection with the voice control module and the double-control evaluation analysis module. The voice control module is in one-way communication connection with the double-control evaluation analysis module and the control management module. The double-control evaluation analysis module is in one-way communication connection with the control management module.

[0038] The intelligent internet-of-things control center is used to call the state information of the intelligent home robot from the home database and send the state information to the time period state evaluation module.

[0039] The time period state evaluation module is used to perform dynamic and static fusion evaluation feedback analysis on the received state information, that is, to analyze from two angles of standby state and execution state of the intelligent home robot, so as to intuitively understand whether the state risk of the intelligent home robot is too high, so as to reasonably manage the current intelligent home robot, and to improve the state stability and safety of the intelligent home robot. The specific dynamic and static fusion evaluation feedback analysis process is as follows:

[0040] A monitoring time period is set and is set as a time threshold. The state information of the intelligent home robot within the time threshold is obtained. The state information includes standby evaluation value and dynamic evaluation value. The standby evaluation value and the dynamic evaluation value are compared and analyzed with the preset standby evaluation value threshold and the preset dynamic evaluation value threshold.

[0041] If the standby evaluation value is less than the preset standby evaluation value threshold, and the dynamic evaluation value is less than the preset dynamic evaluation value threshold, a safety signal is generated.

[0042] If the standby evaluation value is greater than or equal to the preset standby evaluation value threshold, or the dynamic evaluation value is greater than or equal to the preset dynamic evaluation value threshold, an alarm signal is generated, and the safety signal or the alarm signal is sent to the control management module through the intelligent Internet of Things control center. After receiving the safety signal or the alarm signal, the control management module immediately performs the preset warning operation corresponding to the safety signal or the alarm signal, so as to intuitively understand whether the state risk of the intelligent home robot is too high, and facilitate reasonable management of the current intelligent home robot, thereby improving the state stability and safety of the intelligent home robot.

[0043] In the embodiment of the application, the state of the intelligent home robot is divided into standby state and execution state; the intelligent home robot includes a sweeping robot, a dehumidifying robot, etc.

[0044] In the embodiment of the application, the standby evaluation value is the product of the energy consumption value and the average internal temperature value of the intelligent home robot in standby state after data normalization processing. It should be noted that the greater the standby evaluation value, the greater the risk of abnormal control of the intelligent home robot.

[0045] In the embodiment of the application, the dynamic evaluation value is the product of the operation trajectory of the intelligent home robot in the execution state and the number and frequency of deviation from the preset operation trajectory after data normalization processing. It should be noted that the dynamic evaluation value is an influence parameter reflecting the execution performance of the intelligent home robot. Embodiment two

[0046] As shown in Figure 2 When the safety signal is generated, the non-voice control module is used to respond to the safety signal, and the intelligent Internet of Things information of the intelligent home robot is collected. The intelligent Internet of Things information is analyzed for non-voice control evaluation feedback, that is, the control performance of the current intelligent home robot is evaluated from the perspective of non-voice control, so as to reasonably manage the current intelligent home robot, improve the control sensitivity and stability of the current intelligent home robot, and help improve the monitoring effect of the current intelligent home robot. The specific non-voice control evaluation feedback analysis process is as follows:

[0047] The control mode of the intelligent home robot within the time threshold is obtained, and the control mode includes voice control and non-voice control.

[0048] If the current intelligent home robot is non-voice control, the intelligent Internet of Things information of the intelligent home robot within the time threshold is obtained, and the intelligent Internet of Things information includes a state stability index and a smooth running coefficient.

[0049] In the embodiment of the present application, the state stability index represents the number of user control terminal and smart home robot existence material link defect characteristics, material link defect characteristics include interruption, lagging, etc. It should be noted that the state stability index is an influence parameter reflecting the stability performance of the user control terminal and the smart home robot material link state.

[0050] In the embodiment of the present application, the smooth running coefficient represents the part of the actual transmission time of the user command code exceeding the preset threshold, and the actual transmission time represents the time length between the sending time of the user command code and the execution time of the smart home robot. It should be noted that the greater the value of the smooth running coefficient, the lower the risk of the control sensitivity of the smart home robot.

[0051] The state stability index and the smooth running coefficient are compared and analyzed with the preset state stability index threshold and the preset smooth running coefficient threshold, and the number of the state stability index and the smooth running coefficient greater than or equal to the preset state stability index threshold and the preset smooth running coefficient threshold is set as the control obstacle coefficient, and the control obstacle coefficient is discriminated:

[0052] If the control obstacle coefficient is equal to zero, a normal signal is generated;

[0053] If the control obstacle coefficient is not equal to zero, an abnormal signal is generated, and the normal signal or the abnormal signal is sent to the control management module. After receiving the normal signal or the abnormal signal, the control management module immediately makes the preset warning operation corresponding to the normal signal or the abnormal signal, so as to reasonably manage the current smart home robot, improve the control sensitivity and stability of the current smart home robot, and help to improve the monitoring effect of the current smart home robot.

[0054] When the safety signal is generated, the voice control module is used to respond to the safety signal, and the voice control information of the smart home robot is collected, and the voice control information is subjected to voice control multi-angle fusion evaluation analysis, that is, the voice control performance of the current smart home robot is analyzed from the perspective of voice control, so as to manage the voice control system of the current smart home robot according to the information feedback, and improve the voice control stability of the current smart home robot. The specific voice control multi-angle fusion evaluation analysis process is as follows:

[0055] If the current smart home robot is voice controlled, the voice control information of the smart home robot within the time threshold is obtained, the voice control information includes the obstacle transmission coefficient and the recognition evaluation value, and the interference control factor of the smart home robot voice control within the time threshold is also obtained.

[0056] The sum value obtained by adding the data normalized values of the obstruction transmission coefficient and the identification evaluation value is multiplied by the value calculated by the interference control factor to set the voice control evaluation coefficient, and the voice control evaluation coefficient is subjected to discrimination processing:

[0057] If the voice control evaluation coefficient is less than the preset voice control evaluation coefficient threshold, a stable signal is generated;

[0058] If the voice control evaluation coefficient is greater than or equal to the preset voice control evaluation coefficient threshold, a risk signal is generated, and the stable signal or the risk signal is sent to the control management module, which immediately makes the preset warning operation corresponding to the stable signal or the risk signal after receiving the stable signal or the risk signal, so as to manage the voice control system of the current smart home robot according to the information feedback, thereby improving the voice control stability of the current smart home robot.

[0059] In the embodiment of the application, the obstruction transmission coefficient represents the number of obstacle features existing between the straight-line distance between the user's voice wake-up sending position and the smart home robot position, including walls, glass, etc. It should be noted that the obstruction transmission coefficient is an influence parameter reflecting the voice control recognition of the smart home robot, and the greater the value of the obstruction transmission coefficient, the deeper the recognition interference degree of the smart home robot.

[0060] In the embodiment of the application, the identification evaluation value represents the time length between the time when the smart home robot receives the user's voice wake-up and the response time, and it should be noted that the identification evaluation value is an influence parameter reflecting the voice recognition performance of the smart home robot.

[0061] The interference control factor is obtained as follows:

[0062] The network quantization coefficient of the smart home robot and the user within the time threshold is obtained, the network quantization coefficient represents the number of network information corresponding values of the smart home robot and the user below the preset threshold, the network information includes network speed, network throughput, etc., the network quantization coefficient is compared and analyzed with the preset network quantization coefficient interval, and the interference control factor corresponding to the network quantization coefficient located in the preset network quantization coefficient interval is obtained.

[0063] It should be noted that the preset network quantization coefficient interval includes a first interval, a second interval, a third interval, etc., each preset network quantization coefficient interval is provided with a corresponding interference control factor, the interference control factor is greater than zero, the interference control factor of the first interval < the interference control factor of the second interval < the interference control factor of the third interval. Embodiment three

[0064] The double control evaluation analysis module is used to call the total number of historical controls of the smart home robot from the home database, and to perform double control decision quantization progressive analysis on the total number of historical controls, so as to perform targeted single and double control management adjustment on the voice control and non-voice control schemes from the perspective of historical control, so as to improve the single control efficiency and overall control efficiency of voice control and non-voice control of the smart home robot. The specific double control decision quantization progressive analysis process is as follows:

[0065] The total number of historical controls of the smart home robot within the time threshold is obtained, and the total number of voice controls and the total number of non-voice controls in the total number of historical controls are obtained.

[0066] The proportion of the number of times that the user exceeds 2 voice wake-up times in a single voice control process in the total number of voice controls is obtained, and is set as the voice recognition depth.

[0067] The proportion of the number of times that the user sends instructions to encounter feedback problems in a single non-voice control process in the total number of non-voice controls is obtained, and is set as the Internet of Things performance coefficient. The feedback problems include error, delay, etc.

[0068] The voice recognition depth and the Internet of Things performance coefficient are compared and analyzed with the preset voice recognition depth threshold and the preset Internet of Things performance coefficient threshold. The number of times that the voice recognition depth and the Internet of Things performance coefficient are greater than or equal to the preset voice recognition depth threshold and the preset Internet of Things performance coefficient threshold is set as the control demand evaluation value, and the control demand evaluation value is judged:

[0069] If the control demand evaluation value = 0, no signal is generated;

[0070] If the control demand evaluation value = 1, a single control instruction is generated. When the single control instruction is generated, if the voice recognition depth is greater than or equal to the preset voice recognition depth threshold, a voice management signal is generated, and if the Internet of Things performance coefficient is greater than or equal to the preset Internet of Things performance coefficient threshold, a non-voice management signal is generated;

[0071] If the control demand evaluation value = 2, a double control signal is generated. The voice management signal or the non-voice management signal or the double control signal is sent to the control management module. After receiving the voice management signal or the non-voice management signal or the double control signal, the control management module immediately performs the preset warning operation corresponding to the voice management signal or the non-voice management signal or the double control signal, so as to reasonably and targetedly manage and adjust the current voice control scheme and non-voice control scheme according to the historical control situation of the smart home robot, for example, shorten the voice input period or accelerate the Internet of Things network, so as to improve the single control efficiency and overall control efficiency of voice control and non-voice control of the smart home robot.

[0072] To sum up, the application preliminarily analyzes the standby state and the execution state of the smart home robot, so as to intuitively understand whether the state risk of the smart home robot is too high, facilitate reasonable management of the smart home robot, and improve the state stability and control safety of the smart home robot.

[0073] The information feedback-based mode is analyzed from two aspects of voice control and non-voice control, that is, the voice control and non-voice control performance of the current smart home robot is analyzed from the aspects of voice control and non-voice control, so as to reasonably manage the current smart home robot, improve the voice and non-voice control sensitivity and stability of the current smart home robot, and improve the monitoring effect of the current smart home robot.

[0074] Meanwhile, the double-control decision quantization progressive analysis of the smart home robot is performed through information progressive mode, that is, the voice control and non-voice control scheme is adjusted in single and double control management from the historical control angle, so as to improve the single control efficiency and overall control efficiency of the voice control and non-voice control of the smart home robot.

[0075] The size of the threshold is set for comparison, and the size of the threshold depends on the amount of sample data and the base number set by the person skilled in the art for each group of sample data.

[0076] The above is only the preferred embodiment of the application, but the protection scope of the application is not limited to this, any person skilled in the art can make equivalent replacement or change according to the technical scheme and the inventive concept of the application within the technical range disclosed by the application, which should be covered in the protection scope of the application.

Claims

1. A smart home robot control system based on multi-end data analysis, characterized in that, Intelligent Internet of Things control center, home database, time period state evaluation module, non-voice control module, voice control module, double control evaluation analysis module and control management module are included. The intelligent Internet of Things control center is used for calling state information of the intelligent home robot from the home database and sending the state information to the time period state evaluation module. The time period state evaluation module is used for dynamic and static fusion evaluation feedback analysis on the received state information, obtaining standby evaluation value and dynamic evaluation value according to the state information and analyzing to obtain a safety signal or an alarm signal. The non-voice control module is used for responding to the safety signal, collecting wisdom Internet of Things information of the intelligent home robot, performing non-voice control evaluation feedback analysis on the wisdom Internet of Things information, discriminating a control hindering coefficient obtained to obtain a normal signal or an abnormal signal. The voice control module is used for responding to the safety signal, collecting voice control information of the intelligent home robot and performing voice control multi-angle fusion evaluation analysis on the voice control information, discriminating a voice control evaluation coefficient obtained to obtain a stable signal or a risk signal. The double control evaluation analysis module is used for calling total historical control times of the intelligent home robot from the home database and performing double control decision quantization progressive analysis on the total historical control times. The double control decision quantization progressive analysis process is as follows: Total historical control times of the intelligent home robot within a time threshold are obtained, total voice control times and total non-voice control times in the total historical control times are obtained; A proportion value of corresponding times of a user exceeding voice wake-up for 2 times in a single voice control process in the total voice control times is obtained and is set as voice recognition depth, a proportion value of corresponding times of a user sending an instruction encountering a feedback problem in a single non-voice control process in the total non-voice control times is obtained and is set as Internet of Things performance coefficient, the feedback problem including error and delay; The voice recognition depth and the Internet of Things performance coefficient are compared and analyzed with a preset voice recognition depth threshold and a preset Internet of Things performance coefficient threshold, a number corresponding to the voice recognition depth and the Internet of Things performance coefficient greater than or equal to the preset voice recognition depth threshold and the preset Internet of Things performance coefficient threshold is set as a control demand evaluation value, and the control demand evaluation value is discriminated to obtain a voice management signal or a non-voice management signal or a double control signal; The control management module immediately makes a preset warning operation corresponding to the safety signal or the alarm signal after receiving the safety signal or the alarm signal, immediately makes a preset warning operation corresponding to the normal signal or the abnormal signal after receiving the normal signal or the abnormal signal, and immediately makes a preset warning operation corresponding to the stable signal or the risk signal after receiving the stable signal or the risk signal. The control management module immediately makes a preset warning operation corresponding to the voice management signal or the non-voice management signal or the double control signal after receiving the voice management signal or the non-voice management signal or the double control signal. 2.The smart home robot control system based on multi-end data analysis of claim 1, wherein, The dynamic and static fusion evaluation feedback analysis process is as follows: A monitoring period is set and is set as a time threshold, state information of the smart home robot within the time threshold is acquired, the state information includes standby evaluation values and dynamic evaluation values, the standby evaluation values and the dynamic evaluation values are compared and analyzed with preset standby evaluation value thresholds and preset dynamic evaluation value thresholds, and a safety signal or an alarm signal is obtained; The standby evaluation values represent the product of the energy consumption values and the internal temperature mean values of the smart home robot in the standby state after data normalization processing; and the dynamic evaluation values represent the product of the operation trajectory of the smart home robot in the execution state and the number and frequency of deviation from the preset operation trajectory after data normalization processing. 3.The smart home robot control system based on multi-end data analysis of claim 1, wherein, The non-voice control evaluation feedback analysis process is as follows: The control mode of the smart home robot within the time threshold is acquired, the control mode includes voice control and non-voice control; if the current smart home robot is non-voice control, the smart internet of things information of the smart home robot within the time threshold is acquired, the smart internet of things information includes a state stability index and a smooth running coefficient; The state stability index and the smooth running coefficient are compared and analyzed with preset state stability index thresholds and preset smooth running coefficient thresholds, the number of the state stability index and the smooth running coefficient greater than or equal to the preset state stability index thresholds and the preset smooth running coefficient thresholds is set as a control obstacle coefficient, and the control obstacle coefficient is discriminated to obtain a normal signal or an abnormal signal.

4. The intelligent home robot control system based on multi-end data analysis according to claim 3, characterized in that, The state stability index represents the number of smart internet of things defects between the user control end and the smart home robot, and the smart internet of things defects include interruption and lag; and the smooth running coefficient represents the part of the actual transmission time of the user command code that exceeds the preset threshold, and the actual transmission time represents the time length between the user command code sending time and the smart home robot execution time. 5.The smart home robot control system based on multi-end data analysis of claim 1, wherein, The voice control multi-angle fusion evaluation analysis process is as follows: If the current smart home robot is voice control, the voice control information of the smart home robot within the time threshold is acquired, the voice control information includes an obstacle transmission coefficient and an identification evaluation value, and an interference control factor of the voice control of the smart home robot within the time threshold is also acquired; The sum of the obstacle transmission coefficient and the identification evaluation value after data normalization processing is added, and the value calculated by multiplying the sum by the interference control factor is set as a voice control evaluation coefficient, and the voice control evaluation coefficient is discriminated to obtain a stable signal or a risk signal. 6.The smart home robot control system based on multi-end data analysis of claim 5, wherein, The obstacle transmission coefficient represents the number of obstacle features between the straight-line distance between the user's voice wake-up sending position and the smart home robot position, and the obstacle features include walls and glass; and the identification evaluation value represents the time length between the time when the smart home robot receives the user's voice wake-up and the response time.

7. The intelligent home robot control system based on multi-end data analysis according to claim 6, characterized in that, The interference control factor is acquired as follows: The network quantization coefficient of the smart home robot and the user within the time threshold is acquired, the network quantization coefficient represents the number of corresponding values of the network information of the smart home robot and the user below the preset threshold, the network information includes network speed and network throughput, the network quantization coefficient is compared and analyzed with the preset network quantization coefficient interval, and the interference control factor corresponding to the network quantization coefficient located in the preset network quantization coefficient interval is acquired.

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