CN115801840A - Big data detection system - Google Patents
Big data detection system Download PDFInfo
- Publication number
- CN115801840A CN115801840A CN202211546463.9A CN202211546463A CN115801840A CN 115801840 A CN115801840 A CN 115801840A CN 202211546463 A CN202211546463 A CN 202211546463A CN 115801840 A CN115801840 A CN 115801840A
- Authority
- CN
- China
- Prior art keywords
- data
- module
- user
- intelligent
- time
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000001514 detection method Methods 0.000 title claims abstract description 57
- 238000012545 processing Methods 0.000 claims abstract description 63
- 238000005516 engineering process Methods 0.000 claims description 22
- 230000007613 environmental effect Effects 0.000 claims description 12
- 238000000034 method Methods 0.000 claims description 12
- 238000013024 troubleshooting Methods 0.000 claims description 9
- 230000006870 function Effects 0.000 claims description 8
- 238000005457 optimization Methods 0.000 claims description 8
- 235000021060 food property Nutrition 0.000 claims description 7
- 238000013500 data storage Methods 0.000 claims description 6
- 238000013528 artificial neural network Methods 0.000 claims description 4
- 238000003062 neural network model Methods 0.000 claims description 4
- 238000004887 air purification Methods 0.000 claims description 3
- 230000005540 biological transmission Effects 0.000 claims description 3
- 230000008859 change Effects 0.000 claims description 3
- 238000007726 management method Methods 0.000 claims description 3
- 239000011159 matrix material Substances 0.000 claims description 3
- WSFSSNUMVMOOMR-NJFSPNSNSA-N methanone Chemical compound O=[14CH2] WSFSSNUMVMOOMR-NJFSPNSNSA-N 0.000 claims description 3
- 239000013598 vector Substances 0.000 claims description 3
- 238000005406 washing Methods 0.000 claims description 3
- 230000006399 behavior Effects 0.000 claims description 2
- 230000000737 periodic effect Effects 0.000 claims 2
- 230000005611 electricity Effects 0.000 claims 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims 1
- 238000010586 diagram Methods 0.000 description 6
- 230000000694 effects Effects 0.000 description 4
- 238000011161 development Methods 0.000 description 3
- 238000012937 correction Methods 0.000 description 2
- 238000012417 linear regression Methods 0.000 description 2
- 238000004891 communication Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000004134 energy conservation Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 230000005055 memory storage Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
Images
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Abstract
The invention 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, an equipment data acquisition module, a related data processing module, a cloud service module, a control module and an intelligent timing module, wherein the user detection module is connected with the equipment data acquisition module through a network shared memory, the equipment data acquisition module is connected with the related data processing module through a network length, and information of the position and the time point of a user to be detected is acquired in real time and transmitted to the related data processing module.
Description
Technical Field
The invention 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 increased explosively with the information technology, a big data era is presented, the big data is collected in the modes of scientific experiments, physical information and the like, different data are collected and processed to obtain new data, and the processed new data is used for analyzing, predicting or controlling, so that the value of the big data is embodied.
The existing 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 outside the system through a sensor and transmits the data to an interface inside the system, then the data detection module processes the data to obtain a data result, and the data control module controls equipment according to the control result.
Under the background of rapid social development, various intelligent data detection devices are increased, and especially, a plurality of data acquisition and data processing functions are added to intelligent devices such as an intelligent refrigerator and an air purifier to help living life of people to improve quality of life, however, the existing various intelligent devices have respective data processing systems to complete data operation, so that the unicity and stacking property of repeated functions of the intelligent household appliances are too obvious, and therefore, people need to repeatedly operate and set various intelligent household appliances in daily life, operation burden is increased for people, and therefore, the intelligent household appliances can be connected with various intelligent devices to acquire and detect data, perform data prediction control and improve quality of life of people.
Disclosure of Invention
In order to overcome the above defects in the prior art, embodiments of the present invention provide a big data detection system, in which a user detection module and a related data processing module are added to an intelligent clock, so as to detect and pre-determine user time of entering a home, obtain indoor environment data, and control an intelligent household appliance to achieve a comfortable living effect of the user, and at the same time, the user sets a required timing content to control or remind the intelligent household appliance, thereby improving a way of using the intelligent household appliance by the user, improving a living standard, and solving the problems in the background art.
In order to achieve the purpose, the invention provides the following technical scheme: a big data detection system relates to an intelligent clock and specifically comprises a user detection module, an equipment data acquisition module, a related data processing module, a cloud service module, a control module and an intelligent timing module, wherein the user detection module is connected with the equipment data acquisition module through a network shared memory, the equipment data acquisition module is connected with the related data processing module through a network manager, information of the position and the time point of a user to be detected is acquired in real time and transmitted to the related data processing module, the related data processing module is connected with the cloud service module through a network virtual memory shared memory, acquired data and data processing results are stored in the cloud service module, the control module is connected with the related data processing module through the network manager, and the control module is connected with the intelligent timing module through the network manager, so that the intelligent clock can control intelligent household appliances in a humanized manner.
In a preferred embodiment, the intelligent clock further comprises an intelligent switch, a high-definition touch screen display screen, a loudspeaker, a wireless module and an uninterruptible power supply, timing and timing contents are set in the high-definition touch screen display screen on the premise that a user sets the timing and timing contents through the uninterruptible power supply, the intelligent household appliance connected with the wireless module is reminded or controlled through loudspeaker voice 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 and an electric curtain.
In a preferred embodiment, the user detection module comprises a face recognition positioning unit and a GPS positioning unit, wherein the face recognition positioning unit is used for enabling or disabling a smart clock switch at a time point and a time point when a user enters or exits a cell through face recognition and transmitting the enabling or disabling instruction to the equipment acquisition module through network long connection, the GPS positioning unit is used for enabling or disabling the smart clock switch at the time point and the time point within an intelligent clock sensing range of the user through a mobile phone positioning technology and transmitting the enabling or disabling instruction to the equipment acquisition module through network long connection, and the user detection module is used for enabling or disabling the smart clock switch at the time point and the position of the user, so that the user can conveniently use the smart household appliance.
In a preferred embodiment, the device data acquisition module includes environmental data acquisition unit, food data acquisition unit and custom setting unit, environmental data acquisition unit obtains environmental sensor real-time data acquisition indoor environmental data that begins to gather intelligent household electrical appliances after obtaining user detection module's opening instruction to with indoor environmental data transmission to associated data processing module, indoor environmental data includes formaldehyde, temperature, humidity and wind speed, food data acquisition unit begins to transmit the food state cycle data in the intelligent refrigerator to associated data processing module after obtaining user detection module's opening instruction, custom device unit obtains user detection module's opening instruction after according to the timing data transmission of user preset to associated data processing module, and preset timing data includes title content, time quantum, the repetition period that the user set up, the content that the user set up is net fee, gas cost regularly pays for reminding or electric window curtain switch time.
In a preferred embodiment, the associated data processing module includes a data prediction unit and a data optimization unit, which denoise acquired data, and then count the number of network nodes for data input and data output, where the number of the network nodes for data input and data output is determined, the number of the 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 according to the following rule by a neural network method:
in the formula, 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 adjusting value, T is a value which is more than or equal to 1 and less than or equal to 10, i is the ith time of data processing, and n is the total number of data processing.
The data optimization unit obtains values of the data input nodes and the data output nodes through a weight matrix clustering algorithm, the values are recorded as Q, the threshold vectors are recorded as X, and the error function W is
。
In a preferred embodiment, the cloud service module includes a data storage unit and an expert unit, the data storage unit collects indoor environment data and food property cycle data through a virtualization technology and stores the data according to daily cycle records, a large amount of data support is provided for the associated data processing module, meanwhile, local weather change conditions of a user are obtained, data basis is provided for the control module to provide intelligent household appliances, and the expert unit is used for providing problem troubleshooting and solutions for the user in a remote mode through the intelligent clock, wherein the problem troubleshooting and the solution comprise system faults of the intelligent clock and data processing problems, and targeted solutions and suggestions are provided for the problem troubleshooting and the solutions.
In a preferred embodiment, the intelligent clock module is used for performing timely accurate setting by using an integrated circuit, and automatically performing network time correction by using a wireless network technology, and comprises a real-time clock unit, which is used for reading time information such as year, month, day, hour, minute, watch, week, lunar calendar and the like in real time, automatically judging leap year, and is used for setting time parameters for timing by a user to realize the functions of time accurate point reporting and alarm clock preset by the user.
In a preferred embodiment, control module includes internal control unit and external control unit, internal control unit passes through single chip control high definition touch screen display time, intelligent household electrical appliances behavior and sends the pronunciation through the speaker and reminds, external control unit detects that the user gets into the district or when the intelligent clock user is about to get into the family through detection module detection user, control air purifier and open air purification mode, control intelligent air conditioner regulation indoor temperature, and the user gets into the back at home, and the intelligent clock is connected with intelligent refrigerator to show through high definition touch screen display and speaker and report the interior food property cycle of refrigerator, or other data parameters that the user set for carry out the control of other intelligent household electrical appliances.
In a preferred embodiment, the specific steps are as follows:
s10, firstly, the user detection module detects the position information of a user through a face recognition positioning technology or a GPS (global positioning system) position positioning technology, converts the position information into a starting instruction and transmits the starting instruction to the equipment data acquisition module;
s20, secondly, the equipment data acquisition module receives an 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, predicting the starting or closing time of the intelligent household appliance through a neural network model on the basis of the acquired data by the associated data processing module, and transmitting a data processing result to the control module;
and S40, finally, the control module performs management control on the user intelligent household appliances through a network technology and performs control state display and time early warning display on a display screen of the intelligent clock through network long connection on the basis of the time of the intelligent timing module.
The invention has the technical effects and advantages that:
(1) The intelligent household appliance is provided with the user detection module, the intelligent user clock detects and pre-judges the time when the user leaves the house, obtains indoor environment data, and controls the intelligent household appliance to achieve the effects of comfortable living of the user and energy conservation.
(2) The intelligent clock control intelligent household appliance on-off time prediction method is provided with the associated data processing module, the acquired data is rapidly pre-judged by the module through the neural network model, the pre-judgment result is optimized through the learning linear regression algorithm, and the accuracy of the intelligent clock control intelligent household appliance on-off time prediction is improved.
Drawings
FIG. 1 is a block diagram of the system architecture of the present invention.
FIG. 2 is a flow chart of the method operation of the system of the present invention.
Fig. 3 is a block diagram of a structure of a user detection module according to the present invention.
Fig. 4 is a block diagram of the structure of the device data acquisition module of the present invention.
FIG. 5 is a block diagram of an associated data processing module according to the present invention.
Fig. 6 is a block diagram of a cloud service module structure according to the present invention.
FIG. 7 is a block diagram of a control module according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Embodiments of the application are applicable to computer systems/servers that 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 computer systems/servers 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, networked personal computers, minicomputer systems, mainframe computer systems, distributed cloud computing environments that include any of the above, and the like.
The 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 practiced in distributed cloud computing environments where 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 computer 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, an equipment data acquisition module, a related data processing module, a cloud service module, a control module and an intelligent timing module, wherein the user detection module is connected with the equipment data acquisition module through a network shared memory, the equipment data acquisition module is connected with the related data processing module through a network length, information of the position and the time point of a user to be detected is acquired in real time and transmitted to the related data processing module, the related data processing module is connected with the cloud service module through a network virtual memory in a shared manner, acquired data and a data processing result are stored in the cloud service module, the control module is connected with the related data processing module through the network length, and the control module is connected with the intelligent timing module through the network length, so that the intelligent clock can control intelligent household appliances in a humanized manner.
The difference between the embodiment and the prior art is that the user detection module and the associated data processing module are added, the user entering time is detected and pre-judged, the indoor environment data is obtained, the intelligent household appliance is controlled to achieve the best use effect, and meanwhile, the user setting required timing content or the control or reminding of the environment where the intelligent household appliance appears is performed, 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 high-definition touch screen display screen, a loudspeaker, a wireless module and an uninterruptible power supply, timing and timing contents are set in the high-definition touch screen display screen on the premise that the user passes through the uninterruptible power supply, the intelligent household appliance connected with the wireless module is reminded or controlled through loudspeaker voice when a timing task is achieved, the intelligent household appliance comprises an air purifier, an intelligent air conditioner, a refrigerator and a washing machine, and an electric curtain is one or more than two of the intelligent household appliance and is not specifically limited. The intelligent household appliances are controlled through the intelligent clock when the user lives at home, and the life convenience of the user is improved.
Referring to fig. 3, in this embodiment, it is specifically described that the user detection module includes a face recognition positioning unit and a GPS positioning unit, the face recognition positioning unit is configured to use a time point and a position of a user when the access control of a cell enters or exits the cell through face recognition as an opening instruction or a closing instruction of the smart clock switch, and transmit the opening instruction or the closing instruction to the device acquisition module through long network connection, the GPS positioning unit is configured to use a mobile phone positioning technology to use a range of an intelligent clock switch sensing the user is located as an opening instruction or a closing instruction of the smart clock switch, and transmit the opening instruction or the closing instruction to the device acquisition module through long network connection, and the user detection module is configured to obtain the position and the time point of the user and open or close the smart clock switch, so that convenience is provided for the user to use the smart appliance.
Referring to fig. 4, in this embodiment, it is specifically described that the device data acquiring module includes an environment data acquiring unit, a food data acquiring unit, and a custom setting unit, the environment data acquiring unit starts to acquire real-time data of an environment sensor of the intelligent household appliance to acquire indoor environment data 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 includes formaldehyde, temperature, humidity, and wind speed, the food data acquiring unit starts to transmit food state cycle data in the intelligent refrigerator to the associated data processing module after acquiring the opening instruction of the user detection module, the custom device unit transmits the food state cycle data to the associated data processing module according to timing data preset by the user after acquiring the opening instruction of the user detection module, the preset timing data includes a title content, a time period, and a repetition period set by the user, the content set by the user is network charges, a timed gas charges payment reminder, or an electric curtain opening and closing time, and is not specifically limited herein.
Referring to fig. 5, in this embodiment, it is specifically described that the associated data processing module includes a data prediction unit and a data optimization unit to denoise the acquired data, and then count the number of nodes for data input and data output, where the number of nodes between the data input and the data output is uncertain and is recorded as the number of hidden data nodes, and thus the acquired data is processed according to the following rules by a neural network method:
wherein Y is the number of hidden data nodes and R is the number of data input nodesC is the number of data output nodes, T is a number adjusting value, T is a value which is more than or equal to 1 and less than or equal to 10, i is the ith time of data processing, and n is the total number of data processing, the data input comprises a user face recognition time point and a user position, the obtained data is calculated and analyzed by a neural network method through a related data processing module, the user arrival time is predicted, and the intelligent household appliance is controlled through an intelligent clock.
Specifically, the data optimization unit obtains 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 of the values 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 for controlling the on-off time of the intelligent household appliance can be improved as the times are more through repeated processing of a large amount of data.
Referring to fig. 6, in this embodiment, it is specifically described that the cloud service module includes a data storage unit and an expert unit, the data storage unit collects indoor environment data and food property cycle data through a virtualization technology and stores the data according to daily cycle records, provides a large amount of data support for a related data processing module, and simultaneously obtains a local weather change situation of a user, and provides a data basis for an intelligent appliance for a control module, and the expert unit is used for providing a problem troubleshooting and solution for the user in a remote manner by using an intelligent clock, where the problem troubleshooting and solution include a system failure of the intelligent clock and a data processing problem, and provides a targeted solution and suggestion for the problem troubleshooting and solution.
In this embodiment, it should be specifically described that the intelligent clock module utilizes an integrated circuit to perform timely accurate setting, utilizes a wireless network technology to automatically perform network time correction, and includes a real-time clock unit, which reads time information such as year, month, day, hour, minute, watch, week, and lunar calendar in real time, and automatically determines leap year for a user to set time parameters for timing, so as to implement a function of time accurate time reporting and alarm clock preset by the user.
Referring to fig. 7, in this embodiment, what needs to be specifically described is that the control module includes an internal control unit and an external control unit, the internal control unit controls the high-definition touch screen display time and the operation condition of the intelligent household appliance through a single chip and sends a voice prompt through a speaker, when the external control unit detects that a user enters a cell or a user of the intelligent clock detects that the user is about to enter a home through a detection module, the external control unit controls the air purifier to start an air purification mode and controls the intelligent air conditioner to adjust the indoor temperature, after the user enters the home, the intelligent clock is connected with the intelligent refrigerator, and broadcasts the food property cycle in the refrigerator through the high-definition touch screen display and the speaker, or other data parameters set by the user perform control on other intelligent household appliances.
The embodiment provides an operation method of a big data detection system as shown in fig. 2, which includes the following steps:
s10, firstly, the user detection module detects the position information of a user through a face recognition positioning technology or a GPS (global positioning system) position positioning technology, converts the position information into a starting instruction and transmits the starting instruction to the equipment data acquisition module;
s20, secondly, the equipment data acquisition module receives an 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, predicting the starting or closing time of the intelligent household appliance through a neural network model on the basis of the acquired data by the associated data processing module, and transmitting a data processing result to the control module;
and S40, finally, the control module performs management control on the user intelligent household appliances through a network technology and performs control state display and time early warning display on a display screen of the intelligent clock through network long connection on the basis of the time of the intelligent timing module.
And finally: the above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that are within the spirit and principle of the present invention are intended to be included in the scope of the present invention.
Claims (10)
1. A big data detection system, characterized by: the intelligent clock comprises a user detection module, an equipment 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 equipment data acquisition module through a network shared memory, the equipment data acquisition module is connected with the associated data processing module through a network length, 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 and the cloud service module are connected through the network virtual memory shared memory, acquired data and data processing results are stored in the cloud service module, the control module and the associated data processing module are connected through the network length, the control module and the intelligent timing module are connected through the network length, and the intelligent clock is humanized to control intelligent household appliances.
2. The big data detection system according to claim 1, wherein: the intelligent clock further comprises an intelligent switch, a high-definition touch screen display screen, a loudspeaker, a wireless module and an uninterruptible power supply, a user sets timing and timing content in the high-definition touch screen display screen on the premise of the uninterruptible power supply, the intelligent household appliance connected with the wireless module is reminded or controlled through loudspeaker voice when a timing task is achieved, the intelligent household appliance comprises an air purifier, an intelligent air conditioner, a refrigerator and a washing machine, and an electric curtain is one or more than two of the intelligent household appliance.
3. The big data detection system according to claim 1, wherein: the user detection module comprises a face recognition positioning unit and a GPS positioning unit, wherein the face recognition positioning unit is used for enabling a time point and a position of a user when a cell entrance guard enters and exits a cell through face recognition to serve as an intelligent clock switch opening instruction or closing instruction and transmitting the opening instruction or the closing instruction to the equipment acquisition module through network long connection, the GPS positioning unit is used for enabling the user to be in an intelligent clock switch opening instruction or closing instruction in a sensing range through a mobile phone positioning technology, the opening instruction or the closing instruction is transmitted to the equipment acquisition module through network long connection, and the user detection module is used for enabling the user to conveniently use the intelligent household appliance by acquiring the position and the time point of the user and enabling or closing the intelligent clock switch.
4. The big data detecting system according to claim 1, wherein: the equipment data acquisition module includes that environmental data acquires unit, food data acquisition unit and custom and sets up the unit, environmental data acquisition unit obtains the environmental sensor real-time data that begins to gather intelligent household electrical appliances after user detection module's the instruction of opening and acquires indoor environmental data to transmit indoor environmental data to associated data processing module, indoor environmental data includes formaldehyde, temperature, humidity and wind speed, food data acquisition unit begins to transmit the food state cycle data in the intelligent refrigerator to associated data processing module after obtaining user detection module's the instruction of opening, custom equipment unit obtains the timing data transmission of user's preset after user detection module's the instruction of opening and to associated data processing module, and preset's timing data includes the title content, the time quantum, the repetition period that the user set up, the content that the user set up is net fee, water and electricity gas expense regularly pays for the expense warning or electric window curtain on-off time.
5. The big data detection system according to claim 1, wherein: the associated data processing module comprises a data prediction unit and a data optimization unit, wherein the data prediction unit and the data optimization unit are used for denoising acquired data, then the number of network nodes for data input and data output is counted, the number of the network nodes for data input and data output is determined, the number of the nodes between the data input and the data output is not determined and is recorded as the number of hidden data nodes, and the acquired data are processed according to the following rules through 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, and T is the numberAnd the value of the number adjusting value is that T is more than or equal to 1 and less than or equal to 10, i is the ith time of data processing, and n is the total time of data processing.
6. The big data detection system according to claim 1, wherein: the data optimization unit obtains values of the data input nodes and the data output nodes through a weight matrix clustering algorithm, the values are recorded as Q, the threshold vectors are recorded as X, and the error function W is
。
7. The method of the big data detection system according to claim 1, wherein: the cloud service module comprises a data storage unit and an expert unit, the data storage unit collects indoor environment data and food property periodic data through virtualization technology and stores the indoor environment data and the food property periodic data according to daily period records, a large amount of data support is provided for the associated data processing module, the local weather change condition of a user is obtained at the same time, data basis is provided for the control module to provide intelligent household appliances, the expert unit is used for providing problem troubleshooting and solution schemes for the user through a remote mode, the problem troubleshooting and solution schemes comprise intelligent clock system faults and data processing problems, and specific solutions and suggestions are provided for the problem troubleshooting and solution schemes.
8. The big data detecting system according to claim 1, wherein: the intelligent clock module utilizes the mode of integrated circuit to carry out timely accurate setting, utilizes the automatic network of wireless network technique to proofread the time, and intelligent clock module includes the real-time clock unit, reads time information such as year, month, day, time, minute, table, week and lunar calendar in real time to automatic judgement leap year is used for the user sets up time parameter timing, realizes the accurate point of time that the user predetermines time and alarm clock function.
9. The big data detecting system according to claim 1, wherein: control module includes internal control unit and external control unit, internal control unit touches screen display time, intelligent household electrical appliances behavior and sends voice prompt through the speaker through the single-chip control high definition, external control unit detects that the user gets into the district or when the intelligent clock user is about to get into the family through detection module detection user, control air purifier opens air purification mode, control intelligent air conditioner and adjust indoor temperature, the user gets into the back in the family, the intelligent clock is connected with intelligent refrigerator to show through the touch screen of high definition and the speaker reports food property cycle in the refrigerator, or other data parameters that the user set for carry out the control of other intelligent household electrical appliances.
10. A method of operating a big data detection system according to claims 1-9, characterized by: the method comprises the following specific steps:
s10, firstly, the user detection module detects the position information of a user through a face recognition positioning technology or a GPS (global positioning system) position positioning technology, converts the position information into a starting instruction and transmits the starting instruction to the equipment data acquisition module;
s20, secondly, the equipment data acquisition module receives an 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, then, the associated data processing module predicts the starting or closing time of the intelligent household appliance through a neural network model on the basis of the acquired data and transmits a data processing result to the control module;
and S40, finally, the control module performs management control on the user intelligent household appliances through a network technology and performs control state display and time early warning display on a display screen of the intelligent clock through network long connection on the basis of the time of the intelligent timing module.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211546463.9A CN115801840B (en) | 2022-12-05 | 2022-12-05 | Big data detection system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211546463.9A CN115801840B (en) | 2022-12-05 | 2022-12-05 | Big data detection system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115801840A true CN115801840A (en) | 2023-03-14 |
| CN115801840B CN115801840B (en) | 2023-12-15 |
Family
ID=85445488
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211546463.9A Active CN115801840B (en) | 2022-12-05 | 2022-12-05 | Big data detection system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115801840B (en) |
Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101833286A (en) * | 2009-03-13 | 2010-09-15 | 王俊锋 | Intelligent home controller |
| US20130254663A1 (en) * | 2004-04-01 | 2013-09-26 | Sonos, Inc. | Systems, Methods, Apparatus, and Articles of Manufacture to Provide Guest Access |
| CN103345236A (en) * | 2013-07-30 | 2013-10-09 | 刘品杰 | Open-type intelligent household appliance and control method for same |
| WO2017124267A1 (en) * | 2016-01-18 | 2017-07-27 | 刘建兵 | Method for acquiring data during object position prompting and object container |
| CN107479393A (en) * | 2017-08-17 | 2017-12-15 | 北京天平检验行有限公司 | A kind of intelligent domestic system based on big data |
| CN108536030A (en) * | 2018-06-12 | 2018-09-14 | 昆明理工大学 | A kind of intelligent domestic system and its working method based on ANFIS algorithms |
| CN109752960A (en) * | 2017-11-08 | 2019-05-14 | 中兴通讯股份有限公司 | A kind of smart home inter-linked controlling method and device |
| CN110119093A (en) * | 2019-04-29 | 2019-08-13 | 恒大智慧科技有限公司 | A kind of intelligent home furnishing control method, terminal and storage medium |
| CN110134021A (en) * | 2019-04-29 | 2019-08-16 | 恒大智慧科技有限公司 | A kind of intelligent home control system and control method |
| CN110187645A (en) * | 2019-04-02 | 2019-08-30 | 胡渐佳 | Intelligent home furnishing control method based on mobile terminal |
| CN113419438A (en) * | 2021-07-01 | 2021-09-21 | 丽水市知源科技有限公司 | Intelligent household service robot and intelligent household appliance system |
| CN113593583A (en) * | 2021-08-17 | 2021-11-02 | 深圳云基智能科技有限公司 | Smart phone for realizing cooperative work of household appliances |
| CN113777937A (en) * | 2021-08-31 | 2021-12-10 | 湖州市吴兴区数字经济技术研究院 | Intelligent household appliance control system and method based on 5G network |
| US20220383435A1 (en) * | 2021-05-27 | 2022-12-01 | At&T Intellectual Property I, L.P. | Systems and methods for modular hotel and living space orchestration |
-
2022
- 2022-12-05 CN CN202211546463.9A patent/CN115801840B/en active Active
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130254663A1 (en) * | 2004-04-01 | 2013-09-26 | Sonos, Inc. | Systems, Methods, Apparatus, and Articles of Manufacture to Provide Guest Access |
| CN101833286A (en) * | 2009-03-13 | 2010-09-15 | 王俊锋 | Intelligent home controller |
| CN103345236A (en) * | 2013-07-30 | 2013-10-09 | 刘品杰 | Open-type intelligent household appliance and control method for same |
| WO2017124267A1 (en) * | 2016-01-18 | 2017-07-27 | 刘建兵 | Method for acquiring data during object position prompting and object container |
| CN107479393A (en) * | 2017-08-17 | 2017-12-15 | 北京天平检验行有限公司 | A kind of intelligent domestic system based on big data |
| CN109752960A (en) * | 2017-11-08 | 2019-05-14 | 中兴通讯股份有限公司 | A kind of smart home inter-linked controlling method and device |
| CN108536030A (en) * | 2018-06-12 | 2018-09-14 | 昆明理工大学 | A kind of intelligent domestic system and its working method based on ANFIS algorithms |
| CN110187645A (en) * | 2019-04-02 | 2019-08-30 | 胡渐佳 | Intelligent home furnishing control method based on mobile terminal |
| CN110119093A (en) * | 2019-04-29 | 2019-08-13 | 恒大智慧科技有限公司 | A kind of intelligent home furnishing control method, terminal and storage medium |
| CN110134021A (en) * | 2019-04-29 | 2019-08-16 | 恒大智慧科技有限公司 | A kind of intelligent home control system and control method |
| US20220383435A1 (en) * | 2021-05-27 | 2022-12-01 | At&T Intellectual Property I, L.P. | Systems and methods for modular hotel and living space orchestration |
| CN113419438A (en) * | 2021-07-01 | 2021-09-21 | 丽水市知源科技有限公司 | Intelligent household service robot and intelligent household appliance system |
| CN113593583A (en) * | 2021-08-17 | 2021-11-02 | 深圳云基智能科技有限公司 | Smart phone for realizing cooperative work of household appliances |
| CN113777937A (en) * | 2021-08-31 | 2021-12-10 | 湖州市吴兴区数字经济技术研究院 | Intelligent household appliance control system and method based on 5G network |
Non-Patent Citations (2)
| Title |
|---|
| 邹作岩;陈伟利;: "智能家居系统设计与应用", 计算机产品与流通, no. 11 * |
| 陈惠珊;黄干凯;欧巧儒;吴泳琪;崔健学;周永明;文昊翔;: "电器设备远程智能监控系统设计", 韶关学院学报, no. 06 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115801840B (en) | 2023-12-15 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10697662B2 (en) | Automated adjustment of an HVAC schedule for resource conservation | |
| CN104823121B (en) | It is automatic in the presence of detection and to there is related control in intelligent controller | |
| US9240111B2 (en) | Inferring building metadata from distributed sensors | |
| CN106053103B (en) | Node Dynamic Data Acquiring and propagation | |
| US10002184B2 (en) | Methods and systems for identification and correction of controlled system data | |
| CN103890679B (en) | Intelligent controller | |
| US8751432B2 (en) | Automated facilities management system | |
| US20140316582A1 (en) | Automated Facilities Management System having Occupant Relative Feedback | |
| US20140297001A1 (en) | System and method for adaptive automated resource management and conservation | |
| CN107003924A (en) | The elastic regulation engine of consumer device has been connected for managing | |
| US20120165993A1 (en) | Self-Programming Thermostat System, Method and Computer Program Product | |
| CN102193498B (en) | Method for setting intelligent electronic alarm clock based on applied statistical method and embedded computing | |
| CN107148576A (en) | Intelligent domestic system and method | |
| CN103229116A (en) | Flexible functionality partitioning within intelligent-thermostat-controlled hvac systems | |
| CN108536099A (en) | A kind of information processing method, device and mobile terminal | |
| US10621855B2 (en) | Online occupancy state estimation | |
| CN107567083A (en) | The method and apparatus for carrying out power saving optimization processing | |
| CN110308661A (en) | Smart machine control method and device based on machine learning | |
| Alam et al. | Smart-energy group anomaly based behavioral abnormality detection | |
| CN109236104A (en) | The control method of intelligent door and window, device | |
| CN115801840A (en) | Big data detection system | |
| CN116184851A (en) | Sleep mode adjusting method, device, terminal and storage medium | |
| KR20090050405A (en) | Method and apparatus for classifying user behaviors based on the event log generated from the context aware system environment | |
| CN108900884A (en) | Control method, intelligent remote controller, computer equipment and the storage medium of television set shutdown | |
| Chen | Design and Analysis of Home Control Complex System Based on PLC Technology |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20231122 Address after: Room 1507, 15th Floor, Building 1, No. 59 Gaoliangqiao Xiejie Street, Haidian District, Beijing, 100044 Applicant after: Beijing Jin'andao Big Data Technology Co.,Ltd. Address before: 325000 No. 4, Lane 1, Xingda lane, cangning village, Shacheng street, Wenzhou Economic and Technological Development Zone, Wenzhou City, Zhejiang Province Applicant before: Wenzhou DAPAI Intelligent Technology Co.,Ltd. |
|
| GR01 | Patent grant | ||
| GR01 | Patent grant |