KR101649173B1 - The apparatus of home network for using aihonet module - Google Patents

The apparatus of home network for using aihonet module Download PDF

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KR101649173B1
KR101649173B1 KR1020160039977A KR20160039977A KR101649173B1 KR 101649173 B1 KR101649173 B1 KR 101649173B1 KR 1020160039977 A KR1020160039977 A KR 1020160039977A KR 20160039977 A KR20160039977 A KR 20160039977A KR 101649173 B1 KR101649173 B1 KR 101649173B1
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unit
module
aihonet
control
load
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KR1020160039977A
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Korean (ko)
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김천섭
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김천섭
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    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L12/00Data switching networks
    • H04L12/28Data switching networks characterised by path configuration, e.g. local area networks [LAN], wide area networks [WAN]
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00Arrangements for maintenance or administration or management of packet switching networks
    • H04L41/02Arrangements for maintenance or administration or management of packet switching networks involving integration or standardization
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L12/00Data switching networks
    • H04L12/28Data switching networks characterised by path configuration, e.g. local area networks [LAN], wide area networks [WAN]
    • H04L12/2803Home automation networks
    • H04L12/2816Controlling appliance services of a home automation network by calling their functionalities
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L12/00Data switching networks
    • H04L12/28Data switching networks characterised by path configuration, e.g. local area networks [LAN], wide area networks [WAN]
    • H04L12/2803Home automation networks
    • H04L12/2823Reporting information sensed by appliance or service execution status of appliance services in a home automation network
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L29/00Arrangements, apparatus, circuits or systems, not covered by a single one of groups H04L1/00 - H04L27/00
    • H04L29/02Communication control; Communication processing
    • H04L29/06Communication control; Communication processing characterised by a protocol
    • H04L29/08Transmission control procedure, e.g. data link level control procedure
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00Arrangements for maintenance or administration or management of packet switching networks
    • H04L41/16Network management using artificial intelligence
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00Network-specific arrangements or communication protocols supporting networked applications
    • H04L67/16Service discovery or service management, e.g. service location protocol [SLP] or Web services
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W4/00Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02Services making use of location information
    • H04W4/023Services making use of location information using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W4/00Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02Services making use of location information
    • H04W4/029Location-based management or tracking services

Abstract

According to the present invention, in the case of the existing home network system, expensive servers are installed in the complex for remote control from the outside. Therefore, there is a restriction that it is difficult to install in a building that is already built and used. Since the control device of the product, the survival confirmation of the isolator, the fire detection device, the security device for preventing the intrusion of the intruder, and the black box recording device are not integrated, they are individually constructed, and they are fixedly installed with high cost, large volume, The smart sensor 100, the AIHonet module 200, the smart sensor node unit 300, and the ubiquitous sensor network USN formation unit 400, which are expensive to install after moving, , Smart designers and low-cost AIHonet modules are used to lower costs and design and implement artificial intelligent home networks. It is possible to construct a Ubiquitous Sensor Network (USN) network composed of a Zigbee communication network, rather than a wired network, between the sensor node attached to the load device and the AIHonet module, and the AIHonet module having a box- It can be installed easily by removable attachment to the location where the home network is integrated, and it is easy to install even after moving. Based on the Smart Device's location based service (LBS), the AIHonet module (Automatic lighting, automatic CCTV, boiler) can be monitored on one device, AIHonet module, as well as on-line control, off-control, isolation survival confirmation (earthquake or disaster building collapse), interlayer noise detection, fire detection, , On-off control of the handset), confirmation of the front door visitor, opening of the front door, confirmation of the survival of the isolated person (when the building collapses due to earthquake or disaster) , Fire detection, and external intrusion detection function, it is possible to control the home appliance control device of household, which is one of the home network systems, isolation survivor confirmation, fire detection device, external intrusion prevention security device and black box recording device separately Therefore, it is possible to reduce the installation cost by 70% compared with the existing one. And it is possible to input the sensed data from the load device through the artificial intelligence function and to perform integrated analysis And an AIHonet module capable of activating the artificial intelligent home network service market. The object of the present invention is to provide an integrated intelligent security incident detection home network integrated management device.

Description

BACKGROUND OF THE INVENTION Field of the Invention [0001] The present invention relates to an AIHonet module,

In the present invention, the ON / OFF control of load devices (automatic lighting, automatic CCTV, boiler, handset) in the AIHonet module as one device and the safeguarding device are provided for checking entrance visitor, detecting door opening / closing, Fire detection and external intrusion detection function, and it is possible to control the load device by self-analyzing according to the set reference value while learning sensed data from the load device through the artificial intelligence function, And an AIHonet module capable of performing an integrated management function that can be remotely controlled by a fixed or mobile system.

A home network generally refers to home appliances and systems in a home by connecting them with information devices on the Internet or the Internet to allow remote access and control of each device and system and to use contents such as music, video, It is defined as a technology that implements the communication service environment.

Conventional home network system can use the parking control system, unmanned door delivery system, CCTV, unmanned security system and remote meter reading system in the apartment complex with integrated server in the apartment complex. In the household, Control, heating control, cooling control, ventilation control, curtain control, and home appliance control.

All of these functions are available from outside the mobile phone, PDA, and PC.

However, these existing home network systems require expensive servers to be installed in the complex for remote control from the outside.

In the case of a home network system in which an expensive server is installed, since the network infrastructure must be well-equipped, there is a limitation in that it is difficult to install in a building already in use.

Also, if there is a problem with the server, there is a danger that the devices of the household will malfunction, and when the operation is stopped, the devices of the generations can not be accessed from the outside.

In addition, the conventional home network system is not an integrated type of control device for home appliances, an existence of isolator survival, a fire detection device, an external intrusion prevention security device, and a black box recording device for each household. In addition, since it is bulky and heavy and must be fixedly installed, there is a problem that the installation cost is high after the moving, and a new installation is required.

Patent Publication No. 2001-0088971

In order to solve the above problems, the present invention can design and implement an artificial intelligent home network by reducing the cost by using a smart device and an inexpensive AIHonet module, And a smart sensor node attached to the load device and the AIHonet module can be constructed as a ubiquitous sensor network (USN) network made up of a Zigbee communication network rather than a wired network, (Automatic lighting, auto CCTV, boiler, handset) on the AIHonet module, which is one device, can be easily installed on the place where the entrance visitor Checking, opening the front door, confirming the survival of the insulator (when the building collapses due to an earthquake or disaster), interlayer noise , Fire detection, to provide intelligent safety through AIHonet module that allows you to configure the intrusion detection feature detects the home network management apparatus that purpose.

In order to accomplish the above object, an integrated intelligent safety incident detection home network integrated management device through an AIHonet module according to the present invention comprises:

It is connected to AIHonet module and WiFi communication network. It activates load device operation state, home internal image and external intrusion on home screen and activates it on the application screen. A smart device (100) for outputting a control signal for on / off control of driving,

Home It is installed on one side of the internal space, receives the data sensed from the load device, and performs on-off control of the load device (automatic lighting, automatic CCTV, boiler, handset) , AIHonet module (integrated management control of front door opening, isolation survival confirmation (when building collapses due to earthquake or disaster), interlayer noise detection, fire detection, external intrusion detection, and transmission control of image data and sensing data to smart device 200,

It is installed at one side of the load device inside the home and senses the temperature, humidity, load device voltage, current and intrusion detection of the load device, and sends the sensed data to the AIHonet module. 300,

And a Ubiquitous Sensor Network (USN) forming unit 400 that forms a Ubiquitous Sensor Network (USN) network between the AIHonet module and the smart sensor node unit.

As described above, in the present invention,

First, smart devices and inexpensive AIHonet modules can be used to lower costs and design and implement artificial intelligent home networks.

Secondly, it is possible to construct a smart sensor node attached to a load device and an AIHonet module as a Ubiquitous Sensor Network (USN) network composed of a Zigbee communication network rather than a wired communication device. It can be easily installed in a detachable manner at a desired location for integrated management of a home network, and is easy to install even after moving.

Third, based on the Smart Device's location based service (LBS), the AIHonet module can control on-off load devices inside the home at anytime and anywhere, confirm isolation of survivors (when building collapses due to earthquake or disaster) Fire detection and external intrusion detection can be monitored, and the disaster prevention and crime prevention effect can be improved by 80% compared with the existing one.

Fourth, the on-off control of load devices (automatic lighting, auto CCTV, boiler, handset) on one device, AIHonet module, confirmation of front door visitors, opening of front door, confirmation of survivor of isolation (when building collapses due to earthquake or disaster) By configuring noise detection, fire detection, and external intrusion detection function, it is possible to control the household appliance control device, isolator survival confirmation, fire detection device, external intrusion prevention security device, black box recording device Since it is not necessary to have it separately, the installation cost can be reduced by 70% compared with the existing one.

Fifth, the intelligent home network service market can be activated by inputting the sensed data from the load device through the artificial intelligence function and performing the integrated management function to control the load device while performing self-learning analysis according to the set reference value have.

FIG. 1 is a block diagram showing the components of an integrated intelligent security incident detection home network integrated management device 1 through an AIHonet module according to the present invention.
FIG. 2 is a block diagram showing the components of an integrated intelligent safety incident detection home network integrated management device 1 through an AIHonet module according to the present invention.
Figure 3 is a block diagram illustrating components of a smart device in accordance with the present invention;
4 is a block diagram illustrating the components of the AIHonet module according to the present invention;
FIG. 5 is a view illustrating an embedded control module according to an embodiment of the present invention, which is located at one side of an internal space of a module body and includes one or more cores to control overall operation of each device.
FIG. 6 is a perspective view showing external components of the AIHonet module according to the present invention,
7 is an exploded interior perspective view showing the internal components of the AIHonet module according to the present invention,
8 is a block diagram illustrating components of an embedded control module according to the present invention;
FIG. 9 is a view illustrating an embodiment in which the configuration of the embedded control module according to the present invention is configured on one PCB substrate.
10 is a block diagram showing the components of the microprocessor according to the present invention,
11 is a block diagram showing components of a black box unit according to the present invention,
12 is a block diagram illustrating components of a smart sensor node unit according to the present invention.
13 is a block diagram illustrating components of a sensor node control unit according to the present invention.
FIG. 14 is a diagram illustrating an embodiment in which the command signal transmitted from the base station control unit through the actuator control unit according to the present invention is received,
15 is a diagram illustrating an embodiment in which the AIHonet module according to the present invention controls on-off control of a load device in a home connected through a ubiquitous sensor network (USN)
FIG. 16 is a view illustrating a state in which a black box according to an embodiment of the present invention is installed on one side of a refrigerator, self-recognizes that an emergency situation has occurred based on an image of a user who has fallen due to food poisoning through an embedded control module, Server, a management office server,
FIG. 17 is a diagram illustrating an example in which when the interlayer noise exceeds the reference setting range in the upper layer sensed by the noise sensor and the vibration sensor of the smart sensor node according to the present invention, In an embodiment showing notifying to a smart device and a management office server set in advance through a reminders transfer unit,
FIG. 18 is a diagram illustrating a case where a fire detection signal indicating that heat, smoke, or flame is detected from a fire detection sensor installed on one side of a load device or a home interior space in a home according to the present invention is input, After analyzing the learning, an embodiment showing that a fire has occurred is reported to the smart device, the management office server, and the management server, which are set in advance, through the emergency alert transmission unit.

In AIHonet module described in the present invention means an abbreviation of AIHonet AI (A rtificial ntelligence I) HO me NET work.

In addition, the load device described in the present invention includes all of the air conditioner, the heater, the devices required for production (production), the computer, the lighting device, and the life power device in addition to the automatic lighting consuming electricity, the automatic CCTV, the boiler, and the handset.

Hereinafter, preferred embodiments of the present invention will be described with reference to the drawings.

FIG. 1 is a block diagram showing the components of an AIH safety management system 1 according to an embodiment of the present invention. FIG. 2 is a block diagram illustrating an AIHonet module according to an embodiment of the present invention. FIG. 1 is a block diagram illustrating components of an integrated home network management system according to an exemplary embodiment of the present invention. (400).

First, the smart device 100 according to the present invention will be described.

The smart device 100 is connected to the AIHonet module through a WiFi communication network and activates a load device operation state of the home device, a home internal image, and an external invasion on the application screen, Off control of the driving of the load device on the basis of the output signal of the load device.

As shown in FIG. 3, there are an AIHonet control activity unit 110, an image presentation activity unit 120, an AIHonet control intent unit 130, And a pairing access control unit 140.

The AIHonet control activity unit 110 generates an AIHonet control UI on the screen of the smart device, which consists of a view and an event response.

The display activity unit 120 receives the sensing data and the image data from the AIHonet module connected through the AIHonet pairing access controller, and displays the sensing data and the image data on the screen of the smart device.

The AIHonet control intent 130 may be a load device (such as an automatic light, an automatic CCTV, or a digital camera) when the AIHonet control UI is moved to another screen according to the user's touch on the displayed screen. , Door opener mode, door opener mode, isolator survival confirmation (when the building collapses due to an earthquake or disaster), interlayer noise detection mode, fire detection mode, or external intrusion detection mode One of which sends a request command to the event drive control unit so that the selected event is performed.

The AIHonet pairing access controller 140 is connected to the WiFi communication network of the AIHonet module to couple the AIHonet module located in the WiFi communication network based on the location based service (LBS) and to display the paired AIHonet module .

The smart device is configured by selecting one of a smart phone, a smart pad, and a smart TV.

Next, the AIHonet module 200 according to the present invention will be described.

The AIHonet module 200 is installed on one side of a home interior space and receives data sensed from a load device and analyzes the load device (automatic lighting, automatic CCTV, boiler, handset) Control of on / off control, entrance visitor confirmation, opening of the front door, confirmation of survival of an isolated person (when the building collapses due to an earthquake or disaster), interlayer noise detection, fire detection and external intrusion detection, As shown in FIG.

As shown in FIG. 4, the module body 210, the embedded control module 220, the home gateway unit 230, the cam camera unit 240, the black box unit 250, the speaker unit 260, Type power supply unit 270, and a display unit 280.

First, the module body 210 according to the present invention will be described.

The module body 210 has a rectangular box shape, and protects and supports each device from external pressure.

It is made of aluminum alloy material and has excellent heat dissipation and durability.

The module main body is formed at one side of the doorway or wall of the groove.

The module main body is divided into an upper cover and a lower cover.

6 and 7, an embedded control module is formed on one side of the inner space of the top cover, a black box is formed on one side of the embedded control module, a speaker is formed on one side of the black box, A display section is formed on one side of the direction.

Here, in addition to being installed in the space inside the module body, the black box portion is installed at one side of the load device, one side of the entrance of the building, and one side of the roof of the building.

A home gateway part is formed on one side of the inner space of the lower cover, a transformer type power supply part is formed on one side of the home gateway part, and a cam camera part is formed on one side of the transformer type power supply part.

Second, the embedded control module 220 according to the present invention will be described.

As shown in FIG. 5, the embedded control module 220 is located at one side of the inner space of the module body, and is composed of one or more cores to control the overall operation of each device.

8 and 9, it includes a microprocessor unit 221, a main memory unit 222, an input unit 223, and an output unit 224.

The microprocessor unit 221 forms a 1: 1 customized communication protocol according to the loaded equipment of the connected USN network, then calls up the operation program stored in the main memory unit, calculates it according to the operation program, On-off control of load devices formed in the ubiquitous sensor network (USN) network through self-learning analysis, confirmation of entrance visitors, opening of the front door, confirmation of the survival of the insulator (when the building collapses due to earthquake or disaster) , Fire detection, external intrusion detection.

It is composed of one or two or more of 3 ~ 10GHz microprocessors.

More specifically, a 512 MByte DDR3 SDRAM is mounted, a Giga Ethernet module 81-1 is formed, a Wince, a Linux, and an Android OS are formed. Through a UART of 6 to 15 channels, An LED and a switch for debugging through a general-purpose I / O port in the form of an additional sub-board using an expansion connector, a 60Pin LCD connector for driving an LCD monitor window of the display unit is formed, It is equipped with a Real Time Clock (RTC) IC, input voltage is set to DC 5V / 2A, and a key button (Key Button) And includes a Wi-Fi module interface, a ZigBee module interface, an asynchronous RS2332 port, and a synchronous RS232 port.

In the microprocessor unit according to the present invention, the input unit is connected to one input terminal, the sensing data of the smart sensor node unit input from the input unit is input, the cam camera unit is connected to one input terminal, A video device for a black box is connected to one input terminal of the black box, video data taken by a camera for a black box is input, and an output A home gateway unit is connected to one side of the terminal to output a connecting signal for connecting the connection of the smart sensor node unit connected to the home gateway unit and a speaker unit is connected to one side of the other output terminal to transmit an emergency message, And an output signal for outputting a warning sound, and on one side of the other output terminal, And the display output signal for displaying the image data photographed by the cam camera unit on the display unit and the sensing data of the load device is outputted and the breaker is connected to one side of the other output terminal so that the overload or overvoltage A breaker-off signal for turning off the breaker is output, a cut-off temperature signal for turning on the breaker is outputted when the load device detects normal current, a transformer-type power supply is connected to the other output terminal, And to output an emergency power supply signal so as to supply power to each device through a pre-charged auxiliary battery in an emergency situation caused by the emergency battery.

In addition, the microprocessor unit according to the present invention can be used not only as an integrated type but also as an on-off control mode of load devices (automatic lighting, automatic CCTV, boiler, handset), a door visitor confirmation mode, Microprocessor for opening and closing the front door, confirming the survival of the insulator, for confirming the door visitor, for controlling the temperature of the door, by controlling the mode of the building, the interlayer noise detection mode, the fire detection mode and the external intrusion detection mode. Microprocessor, microprocessor for interlayer noise detection, microprocessor for fire suppression suppression, and microprocessor for external intrusion detection.

Here, the microprocessor for fire detection suppression automatically turns on the automatic fire-fighting and water supply automatic valve when a fire is detected, water is supplied by a roll-type water hose, the pressurizing pump (circulation pump) So as to drive the sprinkler.

The microprocessor unit 221 includes a self-learning analysis program engine unit 221a as shown in FIG.

The self-learning analysis program engine unit 221a performs a self-learning analysis through a gradient-descent method that minimizes a sum of squares of errors between a target output value and an output value of an artificial neural network.

This is configured to include a back propagation algorithm.

The back propagation algorithm consists of two steps: forward calculation and backward calculation.

The forward calculation is a process of calculating the output value of an artificial neural network for a given input value. The reverse calculation is a process of reverse propagating the difference between the output value and the target output value obtained by the forward calculation, that is, the error from the output layer to the input layer, It is a process of storing.

The self-learning analysis process by the back propagation algorithm according to the present invention is as follows.

First, after determining the structure of the multilayer perceptron, the connection weights are initialized to any very small value (between -1 and 1).

Next, the following procedure is repeated for all learning patterns in the learning data set.

The input layer uses j, the hidden layer uses k, and the output layer uses i to refer to the output values x of each layer processing element.

First, the forward calculation calculates the output value of each PE (processing element) in the hidden layer and the output layer in the same manner.

This computes the sum (total) of the input values in the processing element (PE), as in Equation (1), where the offset is normally treated as a weight value connected to a virtual processing element whose value is always one.

Figure 112016031506703-pat00001

Then, an output value is determined by using a transfer function as shown in equation (2).

Figure 112016031506703-pat00002

Second, the error is calculated as the backward calculation and the weight is adjusted.

This obtains an error value (ti - xi) between the output value xi of the output layer and the target output value ti.

Then, an error value? I to be used for correcting the weight value connected to the output layer PE is obtained. Assuming a sigmoid transfer function, it is expressed as Equation (3) below.

Figure 112016031506703-pat00003

As shown in Equation (4), an error value for correcting the weight value connected to the hidden layer PE is calculated.

Figure 112016031506703-pat00004

Then, the connection weights are adjusted by the following equations (5) and (6). α represents the learning coefficient.

Figure 112016031506703-pat00005

Figure 112016031506703-pat00006

Finally, when the first and second processes are completed, it is assumed that the learning has been completed once, and the process is repeated until the error in the output layer falls below the threshold value.

In addition, the microprocessor unit 221 according to the present invention includes an emergency alert transmission unit 221b.

That is, the emergency alert transmission unit 221b notifies the smart device and the management office server in advance of the occurrence of the inter-floor noise, the fire detection, the intrusion detection, and the second emergency disaster management server It plays a role.

It consists of WiFi communication network.

The main memory unit 222 stores an operation program and a self-learning analysis firmware program for the overall operation of the artificial intelligent home network integrated management device.

It consists of DDR SDRA and NAND flash.

Here, the DDR SDRAM is constituted by copying an operating program or a kernel for overall operation of the artificial intelligent home network integrated management device, and the NAND flash is configured to store a boot loader, a kernel image, and a self-learning analysis firmware program.

The input unit 223 transmits sensed sensing data from the smart sensor node unit to the microprocessor unit.

It is composed of USB Host 2.0 x 20 Port and USB 2.0 Device 20 Port.

The output unit 224 is connected to the home gateway unit, the cam camera unit, the black box unit, the speaker unit, and the display unit. The output unit 224 includes a home gateway unit, a cam camera unit, a black box unit, To output an output signal.

It consists of a UART selection jumper (UART SELECTION JUMPERS) and a serial connector (Serial connector).

A home gateway unit, a cam camera unit, a black box unit, a speaker unit, and a display unit are connected to the UART selection jumper and the serial connector.

Third, the home gateway unit 230 according to the present invention will be described.

The home gateway unit 230 connects the smart sensor node units installed in one side of the load device in the groove with the 1: N structure.

This is an interconnection or relay between the ubiquitous sensor network and the external communication service. It connects the domestic network of the wired / wireless ubiquitous sensor network with the subscriber access network such as various digital subscriber line (xDSL), cable, fiber to the home (FTTH) .

Fourth, the cam camera unit 240 according to the present invention will be described.

The cam camera unit 240 is provided on one side of the front or back side of the module body, and serves to image a load device, a door visitor, and an intruder inside the groove.

It consists of 90 frames per second video and high definition at 1.3 megapixel (1280 * 960) or higher snapshot resolution.

In addition, through the built-in pixel-plus processor, images are corrected naturally even in motion due to sharp image quality and digital natural motion.

As shown in FIG. 5, the cam camera unit 240 includes an external CCTV cam camera unit and an internal CCTV cam camera unit.

Fifth, the black box unit 250 according to the present invention will be described.

The black box unit 250 is located at one side of the embedded control module or one side of the load device, and serves to backup and store the sensing data of the load device and the image data according to the set reference period.

11, a black box body 251, a black box camera photographing section 252, a black box memory section 253, a USB connection connector section 254, a black box short range wireless communication section 255).

The black box body 251 is formed in a box shape that is easy to carry and move, and protects and supports each device from external pressure.

The black-box camera photographing unit 252 is positioned on the head portion of the black box body, and has a wide angle of 180 ° to 360 ° to shoot a specific object and a load device.

The black box memory unit 253 is formed in the internal space of the black box body to store the sensing data of the load device and the image data in real time.

The USB connector 254 is connected to the output terminal of the smart sensor node unit on the external side of the black box body to transmit the sensing data of the load device sensed by the smart sensor node unit to the data memory unit do.

The black-box short-range wireless communication unit 255 is located at one side of the data memory unit and transmits the sensing data and the video data of the load device stored in the data memory unit to the embedded control module.

It consists of ZigBee communication network.

The black box unit 250 including the black box body 251, the camera photographing unit 252, the black box memory unit 253, the USB connection connector unit 254, and the black box short range wireless communication unit 255, Is easily portable and easy to connect to the smart sensor node unit, and sensing data and image data can be uploaded and recorded in real time through the black box memory unit.

The black box unit according to the present invention is installed at one side of a smart sensor node unit installed in a home or at one side of a refrigerator of load devices.

The reason why the black box portion is installed in one side of the refrigerator of the load device is that the poisoning incident frequently occurs by putting pesticide or toxic substance into the food and there is no image evidence data about the crime scene or the evidence, As shown in FIG. 16, the embedded control module can recognize that an emergency has occurred on the basis of the image of the user who has fallen due to the ingestion of food, Management server, emergency disaster management server, management office server.

In addition to the inside of the home, the black box portion according to the present invention images an outside intruder that is installed at one side of the entrance or exit of the building or one side of the roof of the building to illegally enter the building.

Sixth, the speaker unit 260 according to the present invention will be described.

The speaker unit 260 is driven according to a control signal of the embedded control module to output an emergency situation, a voice message regarding an external intruder, and a warning sound.

Seventh, a transformer-type power supply unit 270 according to the present invention will be described.

The transformer-type power supply unit 270 supplies power to each device through a commercial power supply, and supplies power to each device through an auxiliary battery charged in advance in an emergency due to a power failure.

It is configured to supply power to each device in a dual mode of AC power and auxiliary power through the sun.

Eighth, the display unit 280 according to the present invention will be described.

The display unit 280 is located at one side of the front face of the module main body and displays the image data photographed by the cam camera unit and the sensing data of the load device and controls on / off driving of the load device by touch input .

In addition, the AIHonet module 200 according to the present invention includes a handset 290 on one side of the inner space of the module body.

When the building collapses due to an earthquake or a disaster, the handset 290 is directly connected to the emergency disaster management server set in advance, and performs a phone call connection using a transmission / reception system.

It is configured to be connected to the emergency disaster management server via a telephone line or a WiFi communication network.

Next, the smart sensor node unit 300 according to the present invention will be described.

The smart sensor node unit 300 is detachably installed on one side of a load device inside the home and senses temperature, humidity, voltage, current, interlayer noise and intrusion detection of the load device, And transmits the sensing data to the AIHonet module.

12, the sensor unit 310 includes a sensor node control unit 320, a short range wireless communication unit 330, and a power supply unit 340.

An actuator for turning on / off the driving of the load device when detachably attached to one side of the load device in the home is included.

First, the sensor unit 310 according to the present invention will be described.

The sensor unit 310 senses temperature, humidity, voltage, current, or interlayer noise, fire detection, and intrusion detection of the load device.

It consists of a temperature sensor, a humidity sensor, a current sensor, an infrared sensor, a noise sensor, a vibration sensor and a fire sensor.

The temperature sensor serves to measure the temperature of the load device.

It consists of either a thermocouple thermometer, a temperature measuring resistor thermometer, a thermistor (NTC) thermometer, or a metallic thermometer.

The humidity sensor serves to measure the humidity of the load device installation space.

This is configured to measure the humidity through a change in electrical resistance or capacitance caused by absorption by the porous ceramics or the polymer membrane, or a change in the resonance frequency of the vibrator due to a change in the weight of the absorbing material provided on the vibrator.

The current sensing sensor senses an alternating current and a direct current of the load device.

This is accomplished by using a donor-type magnetic core to measure the primary current by measuring the secondary current by winding the primary and secondary coils around the magnetic core, setting the Hall element in the magnetic field generated by the current, And measures the intensity of the magnetic field, that is, the intensity of the current, by measuring the voltage.

The infrared sensor senses heat generated in the human body by infrared rays.

It senses the movement of a person inside a home when a building collapses due to a dark room, night, earthquake, or disaster.

The infrared sensor according to the present invention is configured to detect infrared rays of 30 m to 50 m.

When the building collapses due to an earthquake or a disaster according to the control signal of the embedded control module, the infrared sensor converts the infrared sensor into a disaster mode. The infrared sensor senses a person located inside the collapsed home and transmits the infrared signal to the embedded control module .

The noise sensor senses noise of a reference setting dB through a microphone.

The vibration sensor senses a vibration impact of the reference vibration set value through a spring source.

The fire detection sensor senses heat, smoke, and flame generated by the load device.

Second, the sensor node control unit 320 according to the present invention will be described.

The sensor node controller 320 changes the command signal received from the AIHonet module to a ZigBee protocol and then turns on and off the operation of the load device by actuating the actuator so that the analog signal output from the sensor unit is converted into a digital signal And transmits the converted digital signal to the short range wireless communication unit.

As shown in FIG. 13, this includes a base station control unit 321, an actuator control unit 322, and an oscilloscope RF control unit 323.

The base station controller 321 changes a command signal received from the AIHonet module to a ZigBee protocol and transmits a command signal to the actuator controller wirelessly.

The actuator control unit 322 receives the command signal transmitted from the base station control unit, operates the actuator formed on the load device, and controls the on / off control of the actuator.

Here, as shown in Fig. 14, the actuator is constituted by an actuator for gas on / off, an actuator for boiler on / off, and an actuator for lighting on / off.

The oscilloscope RF control unit 323 converts an analog signal output from the sensor unit into a digital signal.

Third, the short range wireless communication unit 330 according to the present invention will be described.

The short-range wireless communication unit 330 is a short-range wireless communication network. The short-range wireless communication unit 330 is driven according to a control signal of the sensor node control unit and transmits sensing data converted into a digital signal to the AIHonet module.

It consists of ZigBee wireless communication network.

Here, the ZigBee wireless communication network is a technology that refers to IEEE 802.15.4, which has a slower transmission rate than Bluetooth but has an ad-hoc network configuration, low power consumption, and low chipset price.

Fourth, the power supply unit 340 according to the present invention will be described.

The power supply unit 340 supplies the power supplied from the rechargeable battery to each device.

Next, the ubiquitous sensor network USN formation unit 400 according to the present invention will be described.

The ubiquitous sensor network USN formation unit 400 forms a Ubiquitous Sensor Network (USN) network between the AIHonet module and the smart sensor node unit.

It is assumed that any one of a wireless home networking network made up of Ethernet, PLC, IEEE1394, HomePNA (Home Phoneline Networking Alliance), optical home and wireless home networking including wireless LAN, Bluetooth, WPAN, ZigBee, UWB, .

Since the PLC (Power Line Communication) communicates through a pre-established power line, it has a low construction cost and is easy to expand.

It is characterized by high transmission speeds from 200kbps to 200Mbps, high security and sensitivity to temperature changes.

The UWB (Ultra Wideband) performs a function of transmitting a large amount of information at a low power over a very wide band as compared with a conventional spectrum as a wide area which refers to IEEE802.15.3a.

Bluetooth is a technology referred to as IEEE 802.15.1 that performs bidirectional short-range communication as a short-range wireless communication, which is implemented at a low cost without a complicated cable.

The frequency of use is 2.4GHz and the transmission distance is within 10m.

The ZigBee is a technology that refers to IEEE 802.15.4, which has a slower transmission speed than Bluetooth, but has an easy ad-hoc network configuration, low power consumption, and low chipset price.

The Ubiquitous Sensor Network (USN) forming unit 400 according to the present invention includes a ZigBee network between the AIHonet module and the smart sensor node unit.

Hereinafter, a specific operation of the integrated management system for an AI safety fault detection home network using the AIHonet module according to the present invention will be described.

First, the AIHonet module 200 is installed on one side of the home.

More specifically, it is installed on the side of the interior of the front door.

Next, the smart sensor node unit is detachably attached to one side of the load device inside the home.

Next, a Ubiquitous Sensor Network (USN) network is formed between the AIHonet module and the smart sensor node through the ubiquitous sensor network USN formation unit 400.

Next, a smart device located at a remote location outputs a control signal for on-off controlling the operation of the load device based on the location-based service (LBS).

Next, the AIHonet module receives the sensed data from the load device and performs on-off control of the load device (automatic lighting, automatic CCTV, boiler, handset), confirmation of the entrance visitor, Integrated management control of isolator survival confirmation (when building collapses due to earthquake or disaster), interlayer noise detection, fire detection, and external intrusion detection.

[ON / OFF control mode of load device (boiler)]

For example, as shown in FIG. 15, when a control signal for turning the boiler drive on and off from the smart device is input to the AIHonet module, the AIHonet module generates an AIHonet module After the boiler is connected to the smart sensor node unit installed on the boiler, the boiler on / off actuator of the actuator control unit is on / off controlled.

[Entrance visitor confirmation mode, door opening / closing mode]

As another example, if a visitor to the entrance hall is confirmed through a cam camera installed outside the front door, the door automatic door lock is automatically turned on if the visitor is a frequent visitor through the self-learning analysis of the AIHonet module's embedded control module. Open the front door.

In addition, through the self-learning analysis of the embedded control module of the AIHonet module, if a new visitor is automatically turned off, the automatic door lock of the front door is turned off, and after displaying a voice message "Who are you" It informs the office server in real time of a notification message informing that a new visitor has visited inside the home.

[Confirmation of survivor survival (when building collapses due to earthquake or disaster) mode]

In another embodiment, when a building collapses due to an earthquake or a disaster, the entire home network integrated management apparatus is programmed in a disaster mode under the control of the embedded control module of the AIHonet module, and then the infrared sensor of the smart sensor node unit is driven, Detects a person located inside the home, which is located in the home, by infrared rays, and checks whether or not there is an isolated survivor.

[Layer noise detection mode]

For example, as shown in FIG. 17, when the interlayer noise exceeds the reference setting range in the upper layer, the AIHonet module notifies the occurrence of the interlayer noise after the self-learning analysis through the emergency alert transmission unit Notify the server.

Then, an emergency alert message according to the interstage noise transmitted to the management office server is reported, and the management office employee visits the place where the interlayer noise is generated, and further prevents the interlayer noise from being generated.

[Fire detection mode]

For example, as shown in FIG. 18, when a fire detection signal indicating that heat, smoke, or flame is detected from a fire detection sensor installed on one side of a load device or a home interior space of a home is inputted, After the self-learning analysis in the AIHonet module, it notifies the smart device, the management office server, and the management server 119 that a fire has occurred through the emergency alert transmission unit.

In addition, in the present invention, in addition to the prevention of an accident caused by a fire through a fire detection, in order to enable a user to directly suppress a fire when an actual fire occurs inside a home, A roll-type water hose and an automatic fire-fighting water supply valve are formed on one side of the step side wall between the generations.

Here, the fire-fighting and water supply automatic valve is connected to the embedded control module of the AIHonet module, and is automatically turned on and off according to the control signal of the embedded control module.

That is, when a fire occurs, the embedded control module of the AIHonet module automatically recognizes that a fire has occurred through the fire detection sensor unit, automatically opens and opens the fire-fighting and water supply automatic valve, and then through the cam camera unit and the black box unit The image of the area where the first fire occurred is photographed, and a fire occurrence signal indicating that the fire together with the captured fire image data is transmitted to the smart device, the management office server, and the management server 119.

According to another aspect of the present invention, in the present invention, when a fire occurs under the control of the embedded control module of the AIHonet module, the sprinkler installed in the ceiling is automatically driven to automatically fire the fire.

Here, the sprinkler is configured such that the domestic water is supplied through a pressurizing pump (circulation pump), and the water injection nozzle is driven on and off under the control of the embedded control module of the AIHonet module.

[External intrusion detection mode]

For example, if image data transmitted to the black box unit or the cam camera unit is input to the AIHonet module, the AIHonet module detects an external intruder face, , It notifies the smart device, the management office server, and the police administration server through the emergency alert transmission unit that an external intruder has occurred.

Next, the AIHonet module transmits and controls the image data and sensing data to the smart device.

Finally, it displays the driving status of the load device inside the home, the in-home image, and the outside invasion on the screen of the smart device.

1: Artificial Intelligent Home Network Integrated Management Device 100: Smart Device
200: AIHonet module 300: smart sensor node part
400: Ubiquitous sensor network USN forming part

Claims (7)

  1. It is connected to AIHonet module and WiFi communication network. It activates load device operation state, home internal image and external intrusion on home screen and activates it on the application screen. A smart device (100) for outputting a control signal for on / off control of driving,
    Home It is installed on one side of the internal space, receives the data sensed from the load device, and performs on-off control of the load device (automatic lighting, automatic CCTV, boiler, handset) , AIHonet module (integrated management control of front door opening, isolation survival confirmation (when building collapses due to earthquake or disaster), interlayer noise detection, fire detection, external intrusion detection, and transmission control of image data and sensing data to smart device 200,
    It detects the temperature, humidity, voltage, current, interlayer noise and intrusion detection of the load device, and sends sensed data sensed to the AIHonet module in a detachable manner on one side of the load device inside the home A smart sensor node unit 300,
    And an ubiquitous sensor network (USN) forming unit 400 for forming a Ubiquitous Sensor Network (USN) network between the AIHonet module and the smart sensor node unit. In the apparatus,
    The smart device (100)
    An AIHonet control activity unit 110 for generating an AIHonet control UI on the smart device screen made up of a View and an Event response,
    An image display type activity unit 120 for receiving sensing data and image data from the AIHonet module connected through the AIHonet pairing access control unit and displaying the sensed data and the image data on the smart device screen,
    On-off control mode of the load device (automatic lighting, auto CCTV, boiler, handset), entrance visitor confirmation mode , A door open / close mode, an isolator survival confirmation (when the building collapses due to an earthquake or a disaster) mode, an interlayer noise detection mode, a fire detection mode, and an external intrusion detection mode An AIHonet control intent 130 for sending,
    And an AIHonet pairing access control unit 140 that is connected to the WiFi communication network of the AIHonet module to couple the AIHonet module located in the WiFi communication network based on the location-based service (LBS) and display and connect the paired AIHonet modules. AIHonet module for intelligent safety accident detection home network integrated management device.
  2. delete
  3. The method of claim 1, wherein the AIHonet module (200)
    A module body 210 which is formed in a rectangular box shape and protects and supports each device from external pressure,
    An embedded control module 220 located at one side of the inner space of the module main body and configured by one or more cores to control the overall operation of each device,
    A home gateway unit 230 for connecting the smart sensor node units installed at one side of the load device in the groove with each other in a 1: N structure,
    A cam camera unit 240 provided at one side of the front or back side of the module main body for photographing a load device, a door visitor, and an intruder inside the groove,
    A black box unit 250 installed on one side of the embedded control module or on one side of the load device for storing the sensing data of the load device and the image data in accordance with the set reference period,
    A speaker unit 260 driven according to a control signal of the embedded control module and outputting an emergency situation, a voice message relating to an intruder, and a warning sound,
    A transformer-type power supply unit 270 for supplying power to each device through a commercial power supply and supplying power to each device through an auxiliary battery charged in advance in an emergency due to a power failure,
    And a display unit 280 located on one side of the front face of the module body for displaying the image data photographed by the cam camera unit and the sensing data of the load device and controlling the ON / AIHonet module for intelligent safety accident detection home network integrated management device.
  4. 4. The method of claim 3, wherein the embedded control module (220)
    After establishing a 1: 1 customized communication protocol for the loaded equipment of the connected USN network, it calls up the operating program stored in the memory unit, calculates it according to the operating program and outputs the output signal to the output unit, Integrated on-off control of load devices formed in ubiquitous sensor network (USN) network, confirmation of entrance visitor, opening of front door, confirmation of survival of isolator (when building collapses due to earthquake or disaster), interlayer noise detection, fire detection, A microprocessor unit 221 for performing management control,
    A memory unit 222 for storing an operation program related to the overall operation of the artificial intelligent home network integrated management device, a self-learning analysis firmware program,
    An input unit 223 for transmitting sensed sensing data from the smart sensor node unit to the microprocessor unit,
    The home gateway unit, the cam camera unit, the black box unit, the speaker unit, and the transformer-type power supply unit are connected to the home gateway unit, the cam camera unit, the black box unit, the speaker unit, And an output unit (224) for outputting an output signal to the display unit side.
  5. 5. The apparatus of claim 4, wherein the microprocessor unit (221)
    And a self-learning analysis firmware program engine unit 221a for self-learning through a gradient-descent method that minimizes the sum of squares of errors between the target output value and the output value of the artificial neural network. Integrated intelligent safety incident detection home network integrated management device through module.
  6. delete
  7. delete
KR1020160039977A 2016-04-01 2016-04-01 The apparatus of home network for using aihonet module KR101649173B1 (en)

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PCT/KR2016/012430 WO2017171177A1 (en) 2016-04-01 2016-11-01 Artificial intelligence-type home network integrated management device for detecting accidents through aihonet module

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KR102067994B1 (en) 2019-05-20 2020-01-20 한밭대학교 산학협력단 System for detecting flame of embedded environment using deep learning
KR102097286B1 (en) 2019-08-20 2020-04-09 배덕진 CCTV camera device with alarm signal transmission function using sensor
KR102144493B1 (en) 2019-02-11 2020-08-13 주식회사 에스원 Doorlock Control System by Using AI Speaker and Method thereof

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KR102144493B1 (en) 2019-02-11 2020-08-13 주식회사 에스원 Doorlock Control System by Using AI Speaker and Method thereof
KR102067994B1 (en) 2019-05-20 2020-01-20 한밭대학교 산학협력단 System for detecting flame of embedded environment using deep learning
KR102097286B1 (en) 2019-08-20 2020-04-09 배덕진 CCTV camera device with alarm signal transmission function using sensor

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