CN204733413U - A kind of Intelligent LED lamp control device based on degree of depth study - Google Patents
A kind of Intelligent LED lamp control device based on degree of depth study Download PDFInfo
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- CN204733413U CN204733413U CN201520271519.3U CN201520271519U CN204733413U CN 204733413 U CN204733413 U CN 204733413U CN 201520271519 U CN201520271519 U CN 201520271519U CN 204733413 U CN204733413 U CN 204733413U
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- 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
- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B20/00—Energy efficient lighting technologies, e.g. halogen lamps or gas discharge lamps
- Y02B20/40—Control techniques providing energy savings, e.g. smart controller or presence detection
Abstract
The utility model discloses a kind of based on degree of depth learning algorithm, high flexibility, there is the LED control device of autonomous adaptive capacity, be divided into gateway, Controlling vertex and sensor node three part, connect three kinds of equipment by WIFI network; Adopt autocoder structure, sensing data and user's decision-making being input in degree of depth learning algorithm of timing, thus realize the object of training system.After training, by sensing data, and in conjunction with historical data and user's setting, generate corresponding control table, provide corresponding decision-making.Enable system learn the behavioural habits of people, in conjunction with user's setting, make decision-making accurately, thus greatly improve the flexibility of system, realize self-adapting intelligent and control.
Description
Technical field
The utility model relates to brightness-adjustable LED control device, particularly relates to the self-adapting intelligent LED control device based on degree of depth study.
Background technology
At present, a lot of family is all at use LED control device miscellaneous.But, as things go, these lighting apparatus by as single and independently individuality use, do not have special system to manage.This not only makes user need to require efforts and control these equipment, easily causes the low and irrational brilliance control of energy utilization rate can damage user's naked eyes.
True based on this, the concept of Intelligent LED lamp control device is arisen at the historic moment.Intelligent LED lamp control device is in units of individual residence, by technological means such as technology of Internet of things, network technology, embedded technologys, and in conjunction with the feature of LED high-energy source utilance, domestic lighting is done to reasonably management and controls.In recent years, Intelligent LED lamp control device became a more and more important part in people's life gradually as the part in Smart Home, and it provides increasing personalized service for user, makes the life of people more comfortable, convenient and energy-conservation.Current, the Intelligent LED lamp control device that market occurs is by the Systematical control be embedded into separately in LED mostly, and utilizes wireless communications method and user to carry out alternately.
Summary of the invention
The object of the invention is:
Because Intelligent LED lamp control device is an industry of just having risen, current have many places to require further study.Wherein system underaction, hommization degree is not high, and use with installation difficulty comparatively large, lacking adaptation function etc., is all the problem existing for present stage Intelligent LED lamp control device.The purpose of this utility model is, for the problems referred to above and deficiency, propose a kind of based on degree of deep learning algorithm, high flexibility, there is the LED control device of autonomous adaptive capacity.
Technical scheme:
Based on an Intelligent LED lamp control device for degree of depth study, comprise gateway, Controlling vertex and sensor node three part, connect three kinds of equipment by WIFI network;
Described sensor node being provided with multiple sensors, being placed diverse location in the environment, for gathering ambient data, and the ambient data collected being sent to gateway;
Described gateway, with degree of deep learning algorithm module, adopts autocoder structure, the ambient data collected and user's decision-making being input in degree of deep learning algorithm of timing, thus realizes the object of training system; After training, the ambient data collected by transducer, and in conjunction with historical data and user's setting, generate corresponding control table, provide corresponding decision-making, and send to Controlling vertex; Enable system learn the behavioural habits of people, in conjunction with user's setting, make decision-making accurately, thus greatly improve the flexibility of system, realize self-adapting intelligent and control.
Described Controlling vertex is equipped with the drive circuit of LED, after receiving the decision-making order from gateway, corresponding adjustment is done to LED luminance.
Further, described multiple sensors comprises Temperature Humidity Sensor, light sensor, infrared sensor.Can better perception surrounding environment, improve the accurate of decision-making.
Further, described Controlling vertex regulates LED lamplight brightness by PWM pulse width modulation apparatus.
The utility model has following beneficial effect:
1, device adopts degree of deep learning algorithm module, can learn user behavior, and make different decision-makings according to varying environment parameter, realize the Based Intelligent Control to LED.
2, system has detecting sensor data and is uploaded to the ability of user, the monitoring home environment information enabling user real-time.
3, system can set automatic control to LED brightness according to user.
4, system adopts wireless networking mode, convenient installation and configuration.
5, system adopts star net forming form, facilitates user to the supervision of LED.
Accompanying drawing explanation
Fig. 1 is overall system hardware block diagram;
Fig. 2 is gateway hardware block diagram;
Fig. 3 is LED Controlling vertex hardware block diagram;
Fig. 4 is sensor node hardware block diagram;
Fig. 5 is gateway autonomous learning and the operational flow diagram automatically controlled;
Fig. 6 is sensor node operational flow diagram;
Fig. 7 is LED Controlling vertex operational flow diagram.
Embodiment
Below in conjunction with the drawings and the specific embodiments, the utility model is described in detail.
System is made up of gateway, LED Controlling vertex and sensor node three, concrete signal wiring block diagram, as shown in Figure 1.
1, the design of gateway
What gateway play a part is a hinge and computing, and its connects the node in the user mobile phone end of external network and internal network, and runs ANDROID software thereon.First, in the present system, the mode of Gateway External networking is Ethernet, and inside is then by WIFI and node communication and under being operated in ap mode.Secondly, gateway preserves some configuration informations and data message by flash storage, such as nodal information, configuration information, operational data etc.In addition, the touch-screen of man-machine interaction is needed.As shown in Figure 2, wherein concrete functions of modules is as follows for its hardware module structure:
(1) wireless module.Adopt the BCM4330WIFI chip of ROADCOM as main control chip, and under being operated in ap mode, use high-gain aerial to expand the coverage area simultaneously.
(2) capacitance plate is touched.Adopt the touch TFT screen of 7 cun, facilitate user check data and control LED.
(3) ethernet module.Be connected to internet by Ethernet, thus make user that smart mobile phone can be used to connect Internet access system.
(4) Flash memory module.For storing the control table etc. of relevant sensing data, user's setting, user's decision-making and generation.
(5)SOC。Adopt based on the chip of ARM Cortex A9 as system master, and run ANDROID platform thereon.
Gateway runs ANDROID platform, utilize JAVA language to achieve degree of deep learning algorithm.The concept source of degree of depth study, in artificial neural net, is a kind of perceptron containing many hidden layers.Degree of depth study by feature being carried out being combined to form abstract representation, thus finds the high-level characteristic of data.Native system adopts autocoder structure, sensing data and user's decision-making being input in degree of deep learning algorithm of timing, thus realizes the object of training system.After training, by sensing data, and in conjunction with historical data and user's setting, generate corresponding control table, provide corresponding decision-making.Enable system learn the behavioural habits of people, in conjunction with user's setting, make decision-making accurately, thus greatly improve the flexibility of system, realize self-adapting intelligent and control.Gateway autonomous learning and the operational process automatically controlled, as shown in Figure 5.First complete initialization operation, obtained the IP of all the sensors by udp protocol, and by IP address and node communication, obtain the facility information on it.If this node is sensor node, by a newly-built thread, receives the data from this node, the data received are put into received frame buffering area, recycling Packet analyzing module is resolved data, generates reference format information.Information is put into database, and system takes out information by timing from database, adopts degree of deep learning algorithm training system, after training, provides corresponding decision-making again according to sensing data, generate control table, passes to dress bag module.Again packet is passed through sending module, put into and send buffering area, send to LED Controlling vertex.
2, the design of node (LED Controlling vertex and sensor node)
Because node needs and gateway communication, so have employed WIFI wireless communication module and be linked on the AP of gateway under being operated in STA mode.In addition, node is divided into LED Controlling vertex and sensor node two class.Wherein, LED Controlling vertex provides LED drive singal by PWM, and sensor node then obtains sensing data by corresponding communications protocol.The hardware block diagram of LED Controlling vertex, as shown in Figure 3.The hardware block diagram of sensor node, as shown in Figure 4.Wherein in figure, concrete functions of modules is as follows:
(1)MCU。Wherein the MSP430F2122 that selects of MCU, has the maximum running frequency of 16MHZ, under operational mode 250uA super low-power consumption and support the feature of multiple kinds (as UART, SPI, I2C etc.).The node master control be very suitable for as native system uses.
(2) supply module.Because native system is in order to easy for installation and carried out the optimization of low-power consumption aspect, so have employed the power supply plan of lithium battery.Circuit aspect uses BQ24090 chip to charge to battery, utilizes TPS78030 line style pressurizer to provide stable 3.0V voltage to export.
(3) wireless module.WIFI communication aspect adopts the CC3200 of TI as main control chip, uses patch-type antenna, utilizes FLASH chip store configuration information, realize miniaturization and the low-power consumption of WIFI, utilize UART and MCU communication simultaneously.
(4) sensor assembly.Adopt BH1750 as illuminance sensor, its analog to digital converter of built-in 16, use I2C communications protocol, adopt paster encapsulation volume small and exquisite.
(5) LED drive module.Adopt LM3402 driving LED lamp, use PWM pulse width modulation apparatus to regulate lamplight brightness.
The operational process of node, according to node type, is divided into sensor node operational process as shown in Figure 6, and LED Controlling vertex operational process as shown in Figure 7.Wherein sensor node, first completes the initialization of node.Then node is by the acquisition sensing data of timing, and check data validity, if effectively, by dress bag module generation packet, recycling transmission processing module, sends to gateway.LED Controlling vertex, first completes node initializing.Then the data that will ceaselessly receive from gateway of node, if find that data are effective, then by resolving bag module, become control information by Data Analysis, pass to LED and drive, thus export corresponding PWM ripple, control the brightness of LED.
The above is only the preferred embodiment of the present invention; be noted that for those skilled in the art; under the premise without departing from the principles of the invention, can also make some improvements and modifications, these improvements and modifications also should be considered as protection scope of the present invention.
Claims (3)
1. based on an Intelligent LED lamp control device for degree of depth study, it is characterized in that: comprise gateway, Controlling vertex and sensor node three part, connect three kinds of equipment by WIFI network;
Described sensor node being provided with multiple sensors, being placed diverse location in the environment, for gathering ambient data, and the ambient data collected being sent to gateway;
Described gateway, with degree of deep learning algorithm module, adopts autocoder structure, the ambient data collected and user's decision-making being input in degree of deep learning algorithm of timing, thus realizes the object of training system; After training, the ambient data collected by transducer, and in conjunction with historical data and user's setting, generate corresponding control table, provide corresponding decision-making, and send to Controlling vertex;
Described Controlling vertex is equipped with the drive circuit of LED, after receiving the decision-making order from gateway, corresponding adjustment is done to LED luminance.
2. a kind of Intelligent LED lamp control device based on degree of depth study according to claim 1, is characterized in that: described multiple sensors comprises Temperature Humidity Sensor, light sensor, infrared sensor.
3. a kind of Intelligent LED lamp control device based on degree of depth study according to claim 1, is characterized in that: described Controlling vertex regulates LED lamplight brightness by PWM pulse width modulation apparatus.
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106658821A (en) * | 2016-10-26 | 2017-05-10 | 华南理工大学 | Intelligent LED illumination system based on non-visual photo-biological effect and the control method thereof |
| CN107367840A (en) * | 2017-06-30 | 2017-11-21 | 广东欧珀移动通信有限公司 | Method for information display, device, storage medium and electronic equipment |
| CN108717873A (en) * | 2018-07-20 | 2018-10-30 | 同济大学 | A kind of space luminous environment AI regulating systems based on unsupervised learning technology |
| CN109819552A (en) * | 2019-03-14 | 2019-05-28 | 湖州亿科照明科技有限公司 | A kind of control method of intelligent LED lighting system |
| CN110087368A (en) * | 2018-01-26 | 2019-08-02 | 李娜 | A kind of implementation method of the Intelligent lamp with study and perceptional function |
| CN113157327A (en) * | 2021-04-29 | 2021-07-23 | 上海冠显光电科技有限公司 | Driving system and method capable of adapting to display modules with different sizes based on MCU |
| CN113596765A (en) * | 2018-07-22 | 2021-11-02 | 王铁军 | Multi-mode heterogeneous IOT network |
| CN116600453A (en) * | 2023-05-23 | 2023-08-15 | 深圳市海凌科电子有限公司 | Distributed lamp control system and control method thereof |
-
2015
- 2015-04-29 CN CN201520271519.3U patent/CN204733413U/en not_active Expired - Fee Related
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106658821A (en) * | 2016-10-26 | 2017-05-10 | 华南理工大学 | Intelligent LED illumination system based on non-visual photo-biological effect and the control method thereof |
| CN106658821B (en) * | 2016-10-26 | 2019-04-09 | 华南理工大学 | Intelligent LED lighting system and its control method based on non-vision photo-biological effect |
| CN107367840A (en) * | 2017-06-30 | 2017-11-21 | 广东欧珀移动通信有限公司 | Method for information display, device, storage medium and electronic equipment |
| CN107367840B (en) * | 2017-06-30 | 2020-06-23 | Oppo广东移动通信有限公司 | Information display method, information display device, storage medium and electronic equipment |
| CN110087368A (en) * | 2018-01-26 | 2019-08-02 | 李娜 | A kind of implementation method of the Intelligent lamp with study and perceptional function |
| CN108717873A (en) * | 2018-07-20 | 2018-10-30 | 同济大学 | A kind of space luminous environment AI regulating systems based on unsupervised learning technology |
| CN113596765A (en) * | 2018-07-22 | 2021-11-02 | 王铁军 | Multi-mode heterogeneous IOT network |
| CN109819552A (en) * | 2019-03-14 | 2019-05-28 | 湖州亿科照明科技有限公司 | A kind of control method of intelligent LED lighting system |
| CN109819552B (en) * | 2019-03-14 | 2021-02-23 | 浙江连顿照明科技有限公司 | Control method of intelligent LED lighting system |
| CN113157327A (en) * | 2021-04-29 | 2021-07-23 | 上海冠显光电科技有限公司 | Driving system and method capable of adapting to display modules with different sizes based on MCU |
| CN116600453A (en) * | 2023-05-23 | 2023-08-15 | 深圳市海凌科电子有限公司 | Distributed lamp control system and control method thereof |
| CN116600453B (en) * | 2023-05-23 | 2024-04-09 | 深圳市海凌科电子有限公司 | Distributed lamp control system and control method thereof |
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