CN115801840B - Big data detection system - Google Patents
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Abstract
The application discloses a big data detection system, which relates to the technical field of big data, in particular to an intelligent clock, and comprises a user detection module, a device data acquisition module, an associated data processing module, a cloud service module, a control module and an intelligent timing module, wherein the user detection module is connected with the device data acquisition module through a network shared memory, the device data acquisition module is connected with the associated data processing module through a network long, and information of the position and the time point of a user to be detected is acquired in real time and transmitted to the associated data processing module.
Description
Technical Field
The application relates to the technical field of big data, in particular to a big data detection system.
Background
With the rapid development of society and the continuous development of scientific technology, a large amount of data is exploded along with the information technology, and the data is collected in a large data age in a scientific experiment, physical information and other modes, different data are collected, tidied and processed to obtain new data, and the processed new data are utilized to analyze, predict or control, so that the value of the large data is embodied.
The current big data detection system comprises a data acquisition module, a data detection module and a data control module, wherein the data acquisition module acquires data from the outside of the system through a sensor and transmits the data to an interface in the system, then the data detection module performs data processing to obtain a data result, and the data control module completes control of equipment according to the control result.
Under the background of rapid social development, as various data detection intelligent devices are increased, and particularly intelligent devices such as intelligent refrigerators and air purifiers are added with a plurality of data acquisition and data processing functions to help people living life to improve life quality, various intelligent devices are provided with respective data processing systems to finish data operation, so that the singleness and the stacking property of the intelligent household appliances are obvious, people are required to repeatedly operate and set various intelligent household appliances in daily life, and the operation burden is increased for people.
Disclosure of Invention
In order to overcome the above-mentioned drawbacks of the prior art, an embodiment of the present application provides a big data detection system, which adds a user detection module and an associated data processing module to an intelligent clock, detects the time of a prejudged user entering a home, obtains indoor environment data, controls an intelligent home appliance to achieve the effect of comfort for the user to live, and is used for the user to set the required timing content to control or remind the intelligent home appliance, thereby improving the manner of using the intelligent home appliance by the user and improving the living standard, so as to solve the problems raised in the background art.
In order to achieve the above purpose, the present application provides the following technical solutions: the utility model provides a big data detecting system, relates to intelligent clock, specifically includes user detection module, equipment data acquisition module, associated data processing module, cloud service module, control module and intelligent timing module, user detection module passes through network shared memory with equipment data acquisition module and connects, equipment data acquisition module passes through network long connection with associated data processing module, acquires the position and the time point information transmission of required detection user to associated data processing module in real time, associated data processing module adopts network virtual memory shared connection with cloud service module, will acquire data and data processing result storage to cloud service module, control module adopts network long connection with associated data processing module, control module adopts network long connection with intelligent timing module, realizes intelligent clock humanized control intelligent household electrical appliances.
In a preferred embodiment, the intelligent clock further comprises an intelligent switch, a Gao Qingchu screen display screen, a loudspeaker, a wireless module and an uninterruptible power supply, wherein a user sets timing and timing content in the high-definition touch screen display screen on the premise of the uninterruptible power supply, and the intelligent household appliance connected with the wireless module is reminded or controlled through the loudspeaker in a voice manner when a timing task is achieved, and the intelligent household appliance comprises one or more than two of an air purifier, an intelligent air conditioner, a refrigerator and a washing machine.
In a preferred embodiment, the user detection module includes a face recognition positioning unit and a GPS positioning unit, where the face recognition positioning unit refers to a time point and a position of a user when the cell entrance guard enters and exits the cell through face recognition as an intelligent clock switch on command or an intelligent clock switch off command, the on command or the off command is transmitted to the device acquisition module through a long network connection, the GPS positioning unit refers to a time point and a position of the user obtained through the user detection module when the user is in an intelligent clock sensing range as an intelligent clock switch on command or an intelligent clock switch off command through a mobile phone positioning technology, and the on command or the off command is transmitted to the device acquisition module through the long network connection, so that the user can conveniently use the intelligent household appliance.
In a preferred embodiment, the device data acquisition module includes an environmental data acquisition unit, a food data acquisition unit and a custom setting unit, the environmental data acquisition unit acquires real-time environmental data of an environmental sensor of the intelligent household appliance after obtaining an opening instruction of the user detection module, and transmits the indoor environmental data to the associated data processing module, the indoor environmental data includes formaldehyde, temperature, humidity and wind speed, the food data acquisition unit starts to transmit food status period data in the intelligent refrigerator to the associated data processing module after obtaining the opening instruction of the user detection module, the custom setting unit transmits timing data preset by a user to the associated data processing module after obtaining the opening instruction of the user detection module, the preset timing data includes title content, time period and repetition period set by the user, and the content set by the user is net charge, water-electricity-gas charge timing fee reminding or electric curtain opening and closing time.
In a preferred embodiment, the associated data processing module includes a data prediction unit and a data optimization unit, where the data prediction unit and the data optimization unit denoise acquired data, and then count the number of network nodes of data input and data output, where the number of network nodes of data input and data output is a determined number, the number of nodes between data input and data output is uncertain, and is recorded as the number of hidden data nodes, and the acquired data is processed by a neural network method according to the following rules:wherein Y is the number of hidden data nodes, R is the number of data input nodes, C is the number of data output nodes, T is a number adjustment value, T is 1-10, i is the ith data processing time, and n is the total number of data processing times.
The data optimizing unit obtains values from the data input node and the data output node through a weight matrix clustering algorithm, the values are marked as Q, the threshold vector is marked as X, and the error function W is。
In a preferred embodiment, the cloud service module comprises a data storage unit and an expert unit, wherein the data storage unit collects indoor environment data and food property period data through a virtualization technology and stores the indoor environment data and the food property period data according to daily period records, provides a large amount of data support for the associated data processing module, simultaneously acquires local weather change conditions of a user, provides data basis for intelligent household appliances for the control module, and provides a problem troubleshooting and solving scheme for the user in a remote mode through an intelligent clock, wherein the expert unit comprises an intelligent clock system fault and a data processing problem and provides a targeted solution and opinion for the problem troubleshooting and solving scheme.
In a preferred embodiment, the intelligent clock module performs timely accurate setting by using an integrated circuit mode, automatically checks time by using a wireless network technology, comprises a real-time clock unit, reads information of year, month, day, time, minute, watch, week, lunar calendar and the like in real time, automatically judges leap year, and is used for setting time parameters for timing by a user, and realizing time accuracy point time reporting and alarm clock functions preset by the user.
In a preferred embodiment, the control module comprises an internal control unit and an external control unit, the internal control unit controls the display time of the high-definition touch screen and the running condition of the intelligent household appliance through a single chip and sends out voice prompt through a loudspeaker, and the external control unit detects that a user enters a community or the intelligent clock user detects that the user is about to enter the home through the detection module, controls the air purifier to start an air purification mode and controls the intelligent air conditioner to adjust the indoor temperature, and after the user enters the home, the intelligent clock is connected with the intelligent refrigerator and broadcasts the food character period in the refrigerator through the high-definition touch screen and the loudspeaker, or controls other intelligent household appliances through other data parameters set by the user.
In a preferred embodiment, the specific steps are as follows:
s10, firstly, the user detection module detects the position information of the user through a face recognition positioning technology or a GPS (global positioning system) position positioning technology, converts the position information into an opening instruction and transmits the opening instruction to the equipment data acquisition module;
s20, the equipment data acquisition module receives the instruction of the user detection module, acquires intelligent household appliance data through a network technology, and transmits the acquired data to the cloud service module and the associated data processing module;
s30, the associated data processing module predicts the starting or closing time of the intelligent household appliance through a neural network model based on the acquired data, and transmits a data processing result to the control module;
and S40, finally, the control module performs management control on the intelligent household appliances of the user through a network technology and performs control state display and time early warning display on a display screen of the intelligent clock through long network connection on the basis of the time of the intelligent timing module.
The application has the technical effects and advantages that:
(1) The intelligent household appliance control system is provided with the user detection module, and the intelligent clock of the user detects and pre-judges the time for leaving the user at home, acquires indoor environment data and controls the intelligent household appliance to achieve the comfortable effect and the energy-saving effect of the user.
(2) The intelligent household appliance control system is provided with the associated data processing module, the acquired data is rapidly prejudged by using the neural network model, and the prejudgment result is optimized by using the learning linear regression algorithm, so that the prediction accuracy of the intelligent clock control intelligent household appliance on-off time is improved.
Drawings
Fig. 1 is a block diagram of a system architecture of the present application.
FIG. 2 is a flow chart illustrating the operation of the system method of the present application.
Fig. 3 is a block diagram of a user detection module according to the present application.
Fig. 4 is a block diagram of a device data acquisition module according to the present application.
FIG. 5 is a block diagram of an associated data processing module according to the present application.
Fig. 6 is a block diagram of a cloud service module according to the present application.
Fig. 7 is a block diagram of a control module according to the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Embodiments of the application are operational with numerous other general purpose or special purpose computing system environments or configurations. Examples of well known computing systems, environments, and/or configurations that may be suitable for use with the computer system/server include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, hand-held or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, network personal computers, small computer systems, mainframe computer systems, and distributed cloud computing technology environments that include any of the foregoing, and the like.
A computer system/server may be described in the general context of computer-system-executable instructions, such as program modules, being executed by a computer system. Generally, program modules may include routines, programs, objects, components, logic, data structures, etc., that perform particular tasks or implement particular abstract data types. The computer system/server may be implemented in a distributed cloud computing environment in which tasks are performed by remote processing devices that are linked through a communications network. In a distributed cloud computing environment, program modules may be located in both local and remote computing system storage media including memory storage devices.
Example 1
The embodiment provides a big data detection system as shown in fig. 1, which relates to an intelligent clock, and specifically comprises a user detection module, a device data acquisition module, an associated data processing module, a cloud service module, a control module and an intelligent timing module, wherein the user detection module is connected with the device data acquisition module through a network shared memory, the device data acquisition module is connected with the associated data processing module through a network long, information of the position and the time point of a user to be detected is acquired in real time and transmitted to the associated data processing module, the associated data processing module is connected with the cloud service module through the network virtual memory shared memory, acquired data and data processing results are stored to the cloud service module, the control module is connected with the associated data processing module through the network long, and the control module is connected with the intelligent timing module through the network long, so that intelligent household appliances are controlled by humanization of the intelligent clock.
The difference between the embodiment and the prior art is that the user detection module and the associated data processing module detect the pre-judging user home time by adding the module, acquire the detected indoor environment data, control the intelligent household appliance to achieve the best use effect, and simultaneously are used for setting the needed timing content or controlling or reminding the environment of the intelligent household appliance, so that the living environment of the user is improved, and the living standard is improved.
The intelligent clock further comprises an intelligent switch, a Gao Qingchu screen display screen, a loudspeaker, a wireless module and an uninterrupted power source, timing and timing contents are set in the high-definition touch screen display screen on the premise that the uninterrupted power source is used by a user, and the intelligent household appliance connected with the wireless module is reminded or controlled through the loudspeaker in a voice manner when a timing task is achieved, wherein the intelligent household appliance comprises one or more than two of an air purifier, an intelligent air conditioner, a refrigerator and a washing machine, and the electric curtain is not particularly limited. The user is at home and life and accomplishes a plurality of intelligent household appliances of control through intelligent clock, improves user's life convenience.
Referring to fig. 3, in this embodiment, it needs to be specifically described that the user detection module includes a face recognition positioning unit and a GPS positioning unit, where the face recognition positioning unit refers to a time point and a position of a user when the cell entrance guard enters and exits the cell through face recognition as an intelligent clock switch on command or an off command, the on command or the off command is transmitted to the device acquisition module through a long network connection, and the GPS positioning unit refers to a time point and a position of the user obtained through the user detection module when the user is in an intelligent clock sensing range as an intelligent clock switch on command or an intelligent clock switch off command through a mobile phone positioning technology, and the on command or the off command is transmitted to the device acquisition module through the long network connection, so as to provide convenience for the user to use the intelligent household appliance.
Referring to fig. 4, in this embodiment, it needs to be specifically described that the device data acquisition module includes an environmental data acquisition unit, a food data acquisition unit and a custom setting unit, where the environmental data acquisition unit acquires real-time environmental data of an environmental sensor of an intelligent household appliance after obtaining an opening instruction of a user detection module, and transmits the indoor environmental data to an associated data processing module, where the indoor environmental data includes formaldehyde, temperature, humidity and wind speed, the food data acquisition unit starts to transmit food status cycle data in an intelligent refrigerator to the associated data processing module after obtaining an opening instruction of the user detection module, and the custom setting unit obtains an opening instruction of the user detection module and transmits the opening instruction to the associated data processing module according to timing data preset by a user, where the preset timing data includes a header content, a time period and a repetition period set by the user, and the content set by the user is a net fee, a water and electricity and gas fee timed fee reminder or an electric curtain switching time, and is not specifically limited according to the custom setting of life habits of the user.
Referring to fig. 5, in this embodiment, it is to be specifically described that the associated data processing module includes a data prediction unit and a data optimization unit, and performs denoising on acquired data, then performs statistics on the number of nodes of data input and data output, uses data input network nodes and data output network nodes as determined numbers, uses uncertain numbers of nodes between data input and data output as hidden data nodes, and processes the acquired data according to the following rule by using a neural network method:wherein Y is the number of hidden data nodes, R is the number of data input nodes, C is the number of data output nodes, T is a number adjustment value, the value is 1-10, i is the ith data processing time of data processing, n is the total number of data processing times, the data input comprises the face recognition time point of a user and the position of the user, the acquired data is calculated and analyzed by a neural network method through an associated data processing module, the time of the user to arrive home is predicted, and the intelligent household appliance is controlled through an intelligent clock.
The data optimization unit obtains values from the data input nodes and the data output nodes through a weight matrix clustering algorithm, the values are marked as Q, the threshold vector is marked as X, the error function W is obtained through a linear regression algorithm for the data prediction unit through the data optimization unit, and the prediction accuracy of the intelligent clock control intelligent household appliance on or off time can be improved as the number of times is increased through repeated processing of a large amount of data.
Referring to fig. 6, in this embodiment, it needs to be specifically described that the cloud service module includes a data storage unit and an expert unit, where the data storage unit collects indoor environment data and food property period data through a virtualization technology, records and stores the data according to a daily period, provides a large amount of data support for an associated data processing module, obtains local weather change conditions of a user, and provides data basis for an intelligent household appliance for a control module, and the expert unit is used for an intelligent clock to provide a solution for troubleshooting a problem for the user in a remote manner, including an intelligent clock system fault and a data processing problem, and provides a targeted solution and opinion for the problem.
In this embodiment, it needs to be specifically described that the intelligent clock module performs timely and accurate setting by using an integrated circuit mode, and uses a wireless network technology to automatically calibrate time in a network, where the intelligent clock module includes a real-time clock unit, reads information such as year, month, day, time, minute, table, week, lunar calendar and the like in real time, and automatically determines leap year, and is used for setting time parameters for timing by a user, so as to implement a time standard point time reporting and an alarm clock function preset by the user.
Referring to fig. 7, in this embodiment, it needs to be specifically described that the control module includes an internal control unit and an external control unit, the internal control unit controls the display time of the high-definition touch screen and the operation condition of the intelligent household appliance through a single chip and sends out a voice prompt through a speaker, the external control unit detects that a user enters a community or when the user of the intelligent clock detects that the user is about to enter the home through the detection module, controls the air purifier to start an air purification mode and controls the intelligent air conditioner to adjust the indoor temperature, and after the user enters the home, the intelligent clock is connected with the intelligent refrigerator and broadcasts the food character period in the refrigerator through the high-definition touch screen and the speaker, or controls other intelligent household appliances through other data parameters set by the user.
The embodiment provides an operation method of the big data detection system as shown in fig. 2, which comprises the following specific steps:
s10, firstly, the user detection module detects the position information of the user through a face recognition positioning technology or a GPS (global positioning system) position positioning technology, converts the position information into an opening instruction and transmits the opening instruction to the equipment data acquisition module;
s20, the equipment data acquisition module receives the instruction of the user detection module, acquires intelligent household appliance data through a network technology, and transmits the acquired data to the cloud service module and the associated data processing module;
s30, the associated data processing module predicts the starting or closing time of the intelligent household appliance through a neural network model based on the acquired data, and transmits a data processing result to the control module;
and S40, finally, the control module performs management control on the intelligent household appliances of the user through a network technology and performs control state display and time early warning display on a display screen of the intelligent clock through long network connection on the basis of the time of the intelligent timing module.
Finally: the foregoing description of the preferred embodiments of the application is not intended to limit the application to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and principles of the application are intended to be included within the scope of the application.
Claims (7)
1. A big data detection system, characterized by: the intelligent clock comprises a user detection module, a device data acquisition module, an associated data processing module, a cloud service module, a control module and an intelligent timing module, wherein the user detection module is connected with the device data acquisition module through a network shared memory, the user detection module comprises a face recognition positioning unit and a GPS positioning unit, and the face recognition positioning unit is used for taking the time point and the position of a user when the user enters and exits a cell through face recognition as an intelligent point when the user enters and exits the cell through the face recognition of the cell gate inhibitionThe GPS positioning unit is used for transmitting an opening instruction or a closing instruction of a clock switch to the equipment acquisition module through network long connection, the opening instruction or the closing instruction is used as the opening instruction or the closing instruction of the intelligent clock switch in the range where a user is located through a mobile phone positioning technology, the opening instruction or the closing instruction is transmitted to the equipment acquisition module through network long connection, the position where the user is located and a time point are acquired through the user detection module to open or close the intelligent clock switch, the intelligent household appliance is used by the user, the equipment data acquisition module is connected with the associated data processing module through the network long connection, information of the position where the user is required to be detected and the time point is acquired in real time and is transmitted to the associated data processing module, the associated data processing module is connected with the cloud service module through network virtual memory sharing, acquired data and data processing results are stored to the cloud service module, the associated data processing module comprises a data prediction unit and a data optimization unit, then the number of network nodes for data input and data output is counted, the number of network nodes for determining the number is uncertain, the number of nodes between the data input and the data output is hidden, the data processing rule is processed according to the following neural network processing law, and the data processing law is carried out by the following method:wherein Y is the number of hidden data nodes, R is the number of data input nodes, C is the number of data output nodes, T is a number adjustment value, the value is 1-10, i is the ith data processing time, n is the total number of data processing times, the data optimization unit obtains the values of the data input nodes and the data output nodes through a weight matrix clustering algorithm, the values are marked as Q, the threshold vector is marked as X, and the error function W is the value ofThe control module is connected with the associated data processing module by adopting a network length, and the control module is connected with the intelligent timing module by adopting the network length, so that the intelligent clock can be used for controlling the intelligent household appliance in a humanized manner.
2. A big data detection system according to claim 1, wherein: the intelligent clock also comprises an intelligent switch, a Gao Qingchu screen display screen, a loudspeaker, a wireless module and an uninterrupted power source, wherein a user sets timing and timing content in the high-definition touch screen display screen on the premise of the uninterrupted power source, and the intelligent household appliance connected with the wireless module is reminded or controlled through the loudspeaker in a voice manner when a timing task is achieved, and the intelligent household appliance comprises one or more than two of an air purifier, an intelligent air conditioner, a refrigerator, a washing machine and an electric curtain.
3. A big data detection system according to claim 1, wherein: the equipment data acquisition module comprises an environment data acquisition unit, a food data acquisition unit and a self-defined setting unit, wherein the environment data acquisition unit acquires real-time environment data of an environment sensor of the intelligent household appliance after acquiring an opening instruction of the user detection module, and transmits the indoor environment data to the associated data processing module, the indoor environment data comprises formaldehyde, temperature, humidity and wind speed, the food data acquisition unit starts to transmit food state periodic data in the intelligent refrigerator to the associated data processing module after acquiring the opening instruction of the user detection module, the self-defined equipment unit acquires the opening instruction of the user detection module and transmits the opening instruction to the associated data processing module according to timing data preset by a user, the preset timing data comprises title content, time period and repetition period set by the user, and the content set by the user is network fee, water, electricity and gas fee timing fee reminding or electric curtain opening and closing time.
4. A method of a big data detection system according to claim 1, characterized by: the cloud service module comprises a data storage unit and an expert unit, wherein the data storage unit collects indoor environment data and food property period data through a virtualization technology and stores the indoor environment data and the food property period data according to daily period records, provides a large amount of data support for the associated data processing module, acquires local weather change conditions of a user, provides data basis for the control module to provide intelligent household appliances, and is used for an intelligent clock to provide a problem investigation and solution for the user in a remote mode, wherein the problem investigation and solution comprises an intelligent clock system fault and a data processing problem, and provides a targeted solution and opinion for the problem investigation.
5. A big data detection system according to claim 1, wherein: the intelligent clock module utilizes an integrated circuit mode to conduct timely accurate setting, utilizes a wireless network technology to automatically calibrate time in a network mode, comprises a real-time clock unit, reads information such as year, month, day, time, minute, table, week, lunar calendar and the like in real time, automatically judges leap year, is used for setting time parameter timing by a user, and achieves time accuracy point time reporting and alarm clock functions preset by the user.
6. A big data detection system according to claim 1, wherein: the control module comprises an internal control unit and an external control unit, wherein the internal control unit controls the high-definition touch screen to display time and the running condition of the intelligent household appliance through a single chip and sends out voice prompt through a loudspeaker, and the external control unit detects that a user enters a community or when the user of the intelligent clock detects that the user is about to enter home through a detection module, controls an air purifier to start an air purification mode and controls an intelligent air conditioner to adjust indoor temperature, and after the user enters home, the intelligent clock is connected with the intelligent refrigerator and broadcasts food character periods in the refrigerator through the high-definition touch screen or the loudspeaker, or other data parameters set by the user control other intelligent household appliances.
7. A method of operating a big data detection system according to claims 1-6, characterized in that: the method comprises the following specific steps:
s10, firstly, the user detection module detects the position information of the user through a face recognition positioning technology or a GPS (global positioning system) position positioning technology, converts the position information into an opening instruction and transmits the opening instruction to the equipment data acquisition module;
s20, the equipment data acquisition module receives the instruction of the user detection module, acquires intelligent household appliance data through a network technology, and transmits the acquired data to the cloud service module and the associated data processing module;
s30, the associated data processing module predicts the starting or closing time of the intelligent household appliance through a neural network model based on the acquired data, and transmits a data processing result to the control module;
and S40, finally, the control module performs management control on the intelligent household appliances of the user through a network technology and performs control state display and time early warning display on a display screen of the intelligent clock through long network connection on the basis of the time of the intelligent timing module.
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