CN212873230U - Intelligent home control system for analyzing user habits based on machine learning - Google Patents
Intelligent home control system for analyzing user habits based on machine learning Download PDFInfo
- Publication number
- CN212873230U CN212873230U CN202022426783.3U CN202022426783U CN212873230U CN 212873230 U CN212873230 U CN 212873230U CN 202022426783 U CN202022426783 U CN 202022426783U CN 212873230 U CN212873230 U CN 212873230U
- Authority
- CN
- China
- Prior art keywords
- intelligent
- intelligent home
- control
- video data
- machine learning
- 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.)
- Active
Links
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]
Landscapes
- Selective Calling Equipment (AREA)
Abstract
The utility model particularly relates to an intelligent house control system based on machine learning analysis user habit, this intelligent house control system includes: the monitoring device is used for acquiring the video data of the service condition of each intelligent home; the intelligent home driving device is connected with each intelligent home and is used for controlling the working state of the corresponding intelligent home; the main control center is used for receiving the video data of the service conditions of the intelligent homes, uploading the video data to the remote terminal, receiving the control instruction sent by the remote terminal and driving the corresponding intelligent home to execute the corresponding control instruction; the remote terminal is used for identifying human behavior actions in the intelligent household use condition video data to form corresponding control instructions and sending the control instructions to the master control center; the utility model discloses a user's operation custom of relatively fixed every day fuses with current scene in gathering each intelligent house in service behavior video data, and the push realizes intelligent house automatic control's function for the more perfect one-key formula control scheme of user.
Description
Technical Field
The utility model belongs to the technical field of intelligent control, concretely relates to intelligent house control system based on machine learning analysis user habit.
Background
At present, China only has hundreds of thousands of families using smart homes, and for this reason, huge cost is required for installing the smart homes, and the smart homes are difficult to bear for common families, so that the smart homes are frequently used in high-grade districts, villas and some special occasions, and the intelligent home-moving speed is influenced. China is a large population country, and common families do not experience convenience and safety brought by smart home at present. Therefore, a low-cost and high-efficiency intelligent home system is established according to actual conditions, and more family experiences and uses are facilitated.
However, the existing smart home can only be controlled through manual remote control, and cannot be fused with the current prediction scene according to the behavior habits of the user, so that more perfect one-button control is pushed to the user.
Therefore, it is necessary to develop a new smart home control system for analyzing user habits based on machine learning to solve the above problems.
SUMMERY OF THE UTILITY MODEL
The utility model aims at providing an intelligent house control system based on machine learning analysis user habit to solve the problem of how to realize that the human behavior action habit of intelligent perception controls intelligent house work.
In order to solve the technical problem, the utility model provides an intelligent house control system based on machine learning analysis user habit, it includes: the monitoring device is arranged indoors and used for acquiring the video data of the use condition of each intelligent home; the intelligent home driving device is connected with each intelligent home and is used for controlling the working state of the corresponding intelligent home; the main control center is electrically connected with the monitoring device and the intelligent home driving device, and is used for receiving the video data of the use condition of each intelligent home collected by the monitoring device, uploading the video data to the remote terminal, and receiving the control instruction sent by the remote terminal, so that the intelligent home driving device drives the corresponding intelligent home to execute the corresponding control instruction; and the remote terminal is used for identifying human behavior actions in the intelligent household service condition video data to form corresponding control instructions and sending the control instructions to the master control center.
Further, the monitoring device includes: a plurality of cameras; each camera is suitable for gathering corresponding intelligent house in service behavior video data to transmit to the key center.
Further, the smart home drive device includes: a plurality of electrical switch control nodes; and each electric appliance switch control node is electrically connected with the corresponding intelligent home to drive the corresponding intelligent home to work.
Further, the appliance switch control node comprises: the electric appliance switch processor, the driving relay and the electric appliance switch communication module are electrically connected with the electric appliance switch processor; the driving relay is connected with a control switch of the corresponding smart home; the electric appliance switch processor receives a corresponding control instruction sent by the main control center through the electric appliance switch communication module, namely the electric appliance switch processor is suitable for controlling the driving relay to drive the control switch of the corresponding intelligent home to execute corresponding operation according to the control instruction.
Further, the key center includes: the system comprises a development board, a camera interface module, a network card and a radio frequency module; the development board is suitable for acquiring corresponding intelligent home use condition video data acquired by each camera through the camera interface module and uploading the intelligent home use condition video data to the remote terminal through the network card; and the development board sends a corresponding control instruction to the intelligent household driving device through the radio frequency module.
Further, the development board is adapted to employ an embedded development board.
Further, the radio frequency module performs signal transmission through a radio frequency chip.
Further, the remote terminal includes: a cloud server; the cloud server is suitable for wirelessly receiving the intelligent home use condition video data sent by the network card, and identifying human behavior actions in the intelligent home use condition video data to form corresponding control instructions and then sending the control instructions to the development board.
The beneficial effects of the utility model are that, the utility model discloses a gather user's operation custom of relatively fixed every day in each intelligent house in service behavior video data to fuse user's action custom and current scene, push gives the more perfect one-key formula control scheme of user, realizes intelligent house automatic control's function, and is more convenient, intelligent.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments or the technical solutions in the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a schematic block diagram of an intelligent home control system for analyzing user habits based on machine learning according to the present invention;
fig. 2 is a schematic block diagram of an electrical switch control node of the present invention;
fig. 3 is a schematic block diagram of the main control center of the present invention.
Detailed Description
To make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and obviously, the described embodiments are some embodiments of the present invention, not all embodiments. Based on the embodiments in the present invention, all other embodiments obtained by a person skilled in the art without creative work belong to the protection scope of the present invention.
Example 1
Fig. 1 is the utility model discloses an intelligent house control system's based on machine learning analysis user's habit functional block diagram.
In this embodiment, as shown in fig. 1, the present embodiment provides an intelligent home control system for analyzing user habits based on machine learning, which includes: the monitoring device is arranged indoors and used for acquiring the video data of the use condition of each intelligent home; the intelligent home driving device is connected with each intelligent home and is used for controlling the working state of the corresponding intelligent home; the main control center is electrically connected with the monitoring device and the intelligent home driving device, and is used for receiving the video data of the use condition of each intelligent home collected by the monitoring device, uploading the video data to the remote terminal, and receiving the control instruction sent by the remote terminal, so that the intelligent home driving device drives the corresponding intelligent home to execute the corresponding control instruction; and the remote terminal is used for identifying human behavior actions in the intelligent household service condition video data to form corresponding control instructions and sending the control instructions to the master control center.
In this embodiment, this embodiment fuses user behavior habit and current scene through the relatively fixed operating habit of user every day in gathering each intelligent house in service behavior video data to the push gives the more perfect one-key control scheme of user, realizes intelligent house automatic control's function, and is more convenient, intelligent.
In this embodiment, the monitoring device includes: a plurality of cameras; each camera is suitable for gathering corresponding intelligent house in service behavior video data to transmit to the key center.
In this embodiment, the camera may be, but is not limited to, a USB camera of a holo-ruin video USB100W07M model, and can simultaneously support the output of the MJPEG compression format, and is compatible with the USB2.0 format, and supports the UVC drive-free protocol, and the acquired image can clearly acquire the indoor video information.
In this embodiment, the smart home driving apparatus includes: a plurality of electrical switch control nodes; and each electric appliance switch control node is electrically connected with the corresponding intelligent home to drive the corresponding intelligent home to work.
Fig. 2 is a schematic block diagram of the electrical switch control node of the present invention.
In this embodiment, as shown in fig. 2, the appliance switch control node includes: the electric appliance switch processor, the driving relay and the electric appliance switch communication module are electrically connected with the electric appliance switch processor; the driving relay is connected with a control switch of the corresponding smart home; the electric appliance switch processor receives a corresponding control instruction sent by the main control center through the electric appliance switch communication module, namely the electric appliance switch processor is suitable for controlling the driving relay to drive the control switch of the corresponding intelligent home to execute corresponding operation according to the control instruction.
In this embodiment, the electrical switch processor may adopt, but is not limited to, an STM32F103C8T6 processing chip.
In the present embodiment, the electrical switch communication module may adopt, but is not limited to, an ESP8266 wireless communication module.
Fig. 3 is a schematic block diagram of the main control center of the present invention.
In this embodiment, as shown in fig. 3, the main control center includes: the system comprises a development board, a camera interface module, a network card and a radio frequency module; the development board is suitable for acquiring corresponding intelligent home use condition video data acquired by each camera through the camera interface module and uploading the intelligent home use condition video data to the remote terminal through the network card; and the development board sends a corresponding control instruction to the intelligent household driving device through the radio frequency module.
In this embodiment, the radio frequency module communicates with the appliance switch communication module to enable data to be transmitted bidirectionally.
In this embodiment, the development board is adapted to employ an embedded development board.
In this embodiment, the development board may be, but is not limited to, a JZ2440 development board, a processor chip used by the JZ2440 development board adopts an ARM architecture s3c2440a processor produced by samsung corporation, and also has a DM9000C network card and a WM8976 sound card hardware resource, the JZ2440 development board has an independent camera interface module, and can support 4096 × 4096 pixel input and 2048 × 2048 pixel input to support scaling at the maximum, which is beneficial to accurate acquisition of video data in monitoring equipment, and a COM port and a JTAG port for debugging and use are provided at the same time, so as to facilitate data transmission.
In this embodiment, the rf module performs signal transmission through an rf chip.
In this embodiment, the rf chip may be, but is not limited to, an nRF905 rf chip, which can provide high-speed data transmission without an expensive high-speed processor for clock coverage and data processing, and reducing the memory requirement of the processor means reducing the cost of the processor, and meanwhile, the nRF905 rf chip has a complete communication protocol built therein, and the processor only needs to simply perform effective control with the nRF 905.
In this embodiment, the remote terminal includes: a cloud server; the cloud server is suitable for wirelessly receiving the intelligent home use condition video data sent by the network card, and identifying human behavior actions in the intelligent home use condition video data to form corresponding control instructions and then sending the control instructions to the development board.
In this embodiment, the cloud server and the network card implement bidirectional signal transmission.
To sum up, the utility model discloses a gather user's operation custom of relatively fixed every day in each intelligent house in service behavior video data to fuse user's action custom and current scene, the push realizes intelligent house automatic control's function, and is more convenient, intelligent for the more perfect one-key control scheme of user.
The components selected for use in the present application (components not illustrated for specific structures) are all common standard components or components known to those skilled in the art, and the structure and principle thereof can be known to those skilled in the art through technical manuals or through routine experimentation. Moreover, the software programs referred to in the present application are all prior art, and the present application does not relate to any improvement of the software programs.
In the description of the embodiments of the present invention, unless explicitly stated or limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in the present invention can be understood in specific cases to those skilled in the art.
In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of description and simplification of description, but do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In light of the foregoing, it will be apparent to those skilled in the art from this disclosure that various changes and modifications can be made without departing from the spirit and scope of the invention. The technical scope of the present invention is not limited to the content of the specification, and must be determined according to the scope of the claims.
Claims (8)
1. The utility model provides an intelligent house control system based on machine learning analysis user habit which characterized in that includes:
the monitoring device is arranged indoors and used for acquiring the video data of the use condition of each intelligent home;
the intelligent home driving device is connected with each intelligent home and is used for controlling the working state of the corresponding intelligent home;
the main control center is electrically connected with the monitoring device and the intelligent home driving device, and is used for receiving the video data of the use condition of each intelligent home collected by the monitoring device, uploading the video data to the remote terminal, and receiving the control instruction sent by the remote terminal, so that the intelligent home driving device drives the corresponding intelligent home to execute the corresponding control instruction;
and the remote terminal is used for identifying human behavior actions in the intelligent household service condition video data to form corresponding control instructions and sending the control instructions to the master control center.
2. The smart home control system for analyzing user habits based on machine learning according to claim 1,
the monitoring device includes: a plurality of cameras;
each camera is suitable for gathering corresponding intelligent house in service behavior video data to transmit to the key center.
3. The smart home control system for analyzing user habits based on machine learning according to claim 1,
the intelligent household driving device comprises: a plurality of electrical switch control nodes;
and each electric appliance switch control node is electrically connected with the corresponding intelligent home to drive the corresponding intelligent home to work.
4. The smart home control system for analyzing user habits based on machine learning according to claim 3,
the appliance switch control node comprises:
the electric appliance switch processor, the driving relay and the electric appliance switch communication module are electrically connected with the electric appliance switch processor;
the driving relay is connected with a control switch of the corresponding smart home;
the electric switch processor receives corresponding control instructions sent by the main control center through the electric switch communication module, namely
The electric appliance switch processor is suitable for controlling the driving relay to drive the control switch of the corresponding intelligent home to execute corresponding operation according to the control instruction.
5. The smart home control system for analyzing user habits based on machine learning according to claim 2,
the master control center includes: the system comprises a development board, a camera interface module, a network card and a radio frequency module;
the development board is suitable for acquiring corresponding intelligent home use condition video data acquired by each camera through the camera interface module and uploading the intelligent home use condition video data to the remote terminal through the network card; and
and the development board sends a corresponding control instruction to the intelligent household driving device through the radio frequency module.
6. The smart home control system for analyzing user habits based on machine learning according to claim 5,
the development board is suitable for adopting an embedded development board.
7. The smart home control system for analyzing user habits based on machine learning according to claim 5,
the radio frequency module carries out signal transmission through a radio frequency chip.
8. The smart home control system for analyzing user habits based on machine learning according to claim 5,
the remote terminal includes: a cloud server;
the cloud server is suitable for wirelessly receiving the intelligent home use condition video data sent by the network card, and identifying human behavior actions in the intelligent home use condition video data to form corresponding control instructions and then sending the control instructions to the development board.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202022426783.3U CN212873230U (en) | 2020-10-28 | 2020-10-28 | Intelligent home control system for analyzing user habits based on machine learning |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202022426783.3U CN212873230U (en) | 2020-10-28 | 2020-10-28 | Intelligent home control system for analyzing user habits based on machine learning |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN212873230U true CN212873230U (en) | 2021-04-02 |
Family
ID=75201521
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202022426783.3U Active CN212873230U (en) | 2020-10-28 | 2020-10-28 | Intelligent home control system for analyzing user habits based on machine learning |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN212873230U (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114740745A (en) * | 2022-04-25 | 2022-07-12 | 深圳市联合同创科技股份有限公司 | Intelligent home control method and terminal |
-
2020
- 2020-10-28 CN CN202022426783.3U patent/CN212873230U/en active Active
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114740745A (en) * | 2022-04-25 | 2022-07-12 | 深圳市联合同创科技股份有限公司 | Intelligent home control method and terminal |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102932695B (en) | A kind of remote control thereof, intelligent terminal and intelligent remote control system | |
| CN104571055A (en) | Intelligent home monitoring system based on internet of things | |
| KR20180018787A (en) | Bluetooth pulse diagnosis bracelet and pulse data transmission method (BLUETOOTH PULSE DIAGNOSIS WRISTBAND AND PULSE DATA TRANSMISSION METHOD) | |
| CN105589337A (en) | Automatic control system of smart home | |
| CN204719436U (en) | The intelligent domestic system of Background control service can be realized | |
| CN205101636U (en) | Faucet system, faucet and water purifier with faucet | |
| CN105933220A (en) | Intelligent home gateway with LTE communication and network camera | |
| CN212873230U (en) | Intelligent home control system for analyzing user habits based on machine learning | |
| CN109407524A (en) | A kind of smart home system management method, device and computer readable storage medium | |
| JP2004304520A (en) | Controller, communication device for control, relay device, control system, control method, control program for realizing the control method, and computer readable recording medium recording the program | |
| CN103926888B (en) | A kind of intelligent wireless camera system supporting multiple short range communication protocols and working method thereof | |
| CN207835496U (en) | Industrial Internet of Things adapter | |
| CN112423073A (en) | Remote control method and system for screen projection equipment | |
| CN104539493A (en) | Intelligent terminal system and method of management and control over intelligent household electric appliances based on USB interface | |
| Yang | Design and implementation of intelligent home wireless gateway based on STM32 | |
| CN111145526A (en) | Communication system and method of meter reading equipment | |
| CN207908884U (en) | Intelligent domestic control device with power-off protection function | |
| CN109921658B (en) | Intelligent power adapter | |
| CN106683393A (en) | Remote infrared meter reading method and remote infrared meter reading device | |
| CN212965824U (en) | Intelligent prompting system for smart home | |
| CN202563661U (en) | Room environment information collector with multi-protocol forwarding function | |
| CN205670375U (en) | A kind of modern house Wireless Networking control system of built-in Linux | |
| JP2005073055A (en) | Network adapter and household electrical appliance connectable to network adapter | |
| CN212322419U (en) | Instrument data remote transmission device based on industrial field bus protocol | |
| JP2012182852A (en) | Remote control device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| GR01 | Patent grant | ||
| GR01 | Patent grant |