KR102319475B1 - AI human life service providing system through AI home appliances - Google Patents

Abstract

An artificial intelligence human life service provision system through AI home appliances is started. The artificial intelligence human life service providing system through the AI home appliance of the present invention is, the user's use pattern data of the home appliance, the sensor data of the home appliance, the operation data of the home appliance, the external environment data, the user's location information data, and the user's sleep pattern a data collection unit for collecting data; a big data calculation unit that analyzes the data collected by the data collection unit through machine learning to calculate user-customized home appliance control information; and a control unit receiving the result calculated from the big data calculation unit and controlling the driving of the home appliance. According to the present invention, after collecting the user's home appliance usage pattern data, the sensor data of the home appliance, the external environment data, the user's location information data, the user's physical condition, etc., it is integrated and analyzed through machine learning to optimize the home appliance By deriving product driving control information and recommending it to users or enabling home appliances to be automatically driven, a home automation system can be built for the actual automatic operation of home appliances incorporating AI and IoT technology.

Description

AI human life service providing system through AI home appliances

The present invention provides a life-tracking service, a smart concierge service, a KIA (Keep eye on, Interface, Act) service, etc. when the user uses home appliances by convergence of IoT and AI technology, so that the user can enjoy a richer and more comfortable daily life It is about an artificial intelligence human life service provision system through AI home appliances that can improve the quality of life so that people can spend time together.

In general, in the case of home appliances, a method of direct manipulation by an indoor user has been used, but recent smart home appliances have developed to a level that can be remotely controlled and the operating state can be monitored even when the user is outdoors.

The home automation service using these smart home appliances remotely controls home security, home appliances, air conditioning, and lighting for crime prevention and disaster prevention, so that even if the user is not in the room, it is possible to adjust the room temperature, prevent gas leakage, or lock the door. can do.

However, even in the case of such home automation service, since the smart home appliance operates by the user's remote control, the user has to manually control various home appliances by operating a smartphone or personal computer or make reservation settings. There is a problem that occurs. That is, the conventional home automation service fails to implement practical automation that can autonomously operate each smart home appliance according to a user's condition, usage pattern, and changes in indoor and outdoor environments.

Republic of Korea Patent Publication No. 10-1772408 (registered on Aug. 23, 2017)

The present invention has been devised to solve the above-mentioned problems of the prior art, and after collecting the user's home appliance usage pattern data, the sensor data of the home appliance, the external environment data, the user's location information data, the user's physical condition, etc., The purpose of this is to provide an artificial intelligence human life service provision system through AI home appliances that can be analyzed through machine learning to derive optimized home appliance driving control information and recommend it to users or automatically drive home appliances. do.

According to one aspect of the present invention, after collecting the usage pattern data of the home appliance user, the sensor data of the home appliance, the operation data of the home appliance, the external environment data, and the location information data of the user, the data is analyzed through machine learning. A service providing system through an AI home appliance that recommends or automatically controls home appliance services to a user, the user's usage pattern data, home appliance sensor data, home appliance operation data, external environment data, and user's location information data And a data collection unit for collecting the user's sleep pattern data; a big data calculation unit that analyzes the data collected by the data collection unit through machine learning to calculate user-customized home appliance control information; and a control unit configured to receive the result calculated from the big data calculation unit and control the driving of the home appliance.

The big data calculation unit may include: a data classification unit for classifying the data collected from the data collection unit based on a preset item range; and a control signal calculation unit for deriving optimized user-customized home appliance control information after extracting characteristics by integrally analyzing the data classified by item through the data classification unit through deep learning.

The data classification unit classifies the data of the data collection unit in real time, and the control signal calculation unit analyzes the classified real-time data to derive user-customized home appliance control information, but by accumulating real-time input data and analyzing the accumulated data. The user-customized home appliance control information may be updated.

The control unit may include a transmitter for transmitting a signal for driving the home appliance to the outside, and the home appliance may include a receiver for receiving a signal transmitted through the transmitter.

According to the artificial intelligence human life service providing system through the AI home appliance of the present invention described above, the user's home appliance usage pattern data, the sensor data of the home appliance, the external environment data, the user's location information data, the user's physical condition, etc. After collecting and analyzing it through machine learning, it is possible to derive optimized home appliance operation control information and recommend it to users or automatically drive home appliances, thereby automatically driving practical home appliances incorporating AI and IoT technology. You can build a home automation system for

In addition, the big data calculation unit accumulates the data collected in real time from the data collection unit and analyzes the accumulated data to calculate the optimal home appliance control information. By variably changing and calculating according to user standards, it is possible to continuously improve the user's convenience in using home appliances.

1 is a diagram schematically showing a sequence for providing an artificial intelligence human life service providing system through an AI home appliance according to an embodiment of the present invention;
2 is a block diagram showing a control relationship of an artificial intelligence human life service providing system through an AI home appliance according to an embodiment of the present invention;
3 is a view specifically showing FIG. 1;
4 is a diagram illustrating a home appliance control relationship according to user location information and ambient temperature/humidity/user life pattern change as an example in an AI human life service providing system through an AI home appliance according to an embodiment of the present invention;
5 and 6 are diagrams illustrating a human life service providing process and results when a specific home appliance is applied in the AI human life service providing system through an AI home appliance according to an embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described in more detail with reference to the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below, but will be implemented in various different forms, and only these embodiments allow the disclosure of the present invention to be complete, and the scope of the invention to those of ordinary skill in the art will be completely It is provided to inform you. In the drawings, like reference numerals refer to like elements.

Artificial intelligence human life service providing system through AI home appliances according to a preferred embodiment of the present invention provides a life tracking service, a smart concierge service, a KIA (Keep eye on, Interface, Act) service, etc. It is a system that can improve the quality of life so that users can spend a richer and more comfortable daily life. Hereinafter, prior to the detailed description, if IoT appliances and AI appliances are briefly defined, IoT appliances are appliances connected using an IoT network and can perform remote control, data transmission and storage, and AI appliances are big appliances stored through IoT. It can be defined as a home appliance that can provide customized services to users based on data.

Hereinafter, the present invention will be described in detail with reference to Examples.

The artificial intelligence human life service providing system through AI home appliances according to an embodiment of the present invention goes beyond the existing IoT technology-based device control method (i.e., IoT convergence home appliance, home appliance driving control using a smartphone), and the user's life pattern, etc. It is a system that can comprehensively analyze and control the driving of home appliances based on the analyzed results through AI.

In other words, the present invention collects user's home appliance usage pattern data, home appliance sensor data, external environment data, and user's location information data and analyzes the data through machine learning to recommend or recommend home appliance services to the user. It adopts the method of automatic control of home appliances.

1 to 4, the artificial intelligence human life service providing system through the AI home appliance according to an embodiment of the present invention includes a data collection unit 100, a big data calculation unit 200 and a control unit 300. include

First, the data collection unit 100 collects the user's home appliance usage pattern data, the sensor data of the home appliance, the external environment data, the user's location information data, and the like. In addition, the data collection unit 100 may collect various information from the Internet or the like through a wired/wireless communication network.

Here, the user's home appliance usage pattern data may include the home appliance use cycle, frequently used time/day, etc., that is, the driving cycle of the home appliance, in which day and time of the week the home appliance is mainly driven, and the driving duration. can

On the other hand, as will be described later, the home appliance receives a signal transmitted through the transmitter 310 of the control unit 300 to form a home automation driving system as a whole while driving is controlled. Contains operational data of the drive system.

The sensor data of home appliances is the sensing value measured from the temperature/humidity sensor, the indoor fine dust concentration sensor, and the user's body temperature/respiration rate/heart rate sensor installed in the home appliance. A communication unit (not shown) for transmitting these sensed values to the outside is provided in the home appliance, and the data collection unit 100 can receive these sensed values through a wireless communication (eg, Wi-Fi, LTE, 5G communication network, etc.) network. have. The user's body temperature/respiration rate/heart rate may be sensed through the wearable device, and the sensed value is transmitted to the outside as well.

The external environment data may include meteorological information (temperature/humidity, precipitation, etc.), external air quality, etc., and may be collected, for example, from a server of the Korea Meteorological Administration or a website through wired/wireless communication.

The user's location information data is the current location information of the user who owns the wireless communication device, and the user's location information collected by the base station may be transmitted through the GPS.

Next, the big data calculation unit 200 calculates user-customized home appliance control information by analyzing the data collected by the data collection unit 100 through machine learning.

Specifically, the big data calculator 200 includes a data classifier 210 for classifying data and a control signal calculator 220 for deriving user-customized home appliance driving information based on the classified data.

The data classification unit 210 classifies the data collected from the data collection unit 100 based on a preset item range, and specifically, 1) the user's home appliance usage pattern data, 2) the sensor data of the home appliance, It is classified by setting items such as 3) external environment data and 4) user location information data. Additionally, the data collection unit 100 may collect the user's sleep pattern data, and the data classification unit 210 classifies the collected data as a separate item for the sleep pattern.

The control signal calculating unit 220 derives optimized user-customized home appliance control information after extracting characteristics by integrally analyzing the data classified by item through the data classification unit 210 through deep learning.

In an embodiment of the present invention, the control signal calculating unit 220 does not derive home appliance driving control information by individually analyzing the collected data classified for each item in the data classifying unit 210 by item, but iteratively and collectively. Analyze and learn to calculate optimized control information.

For example, if the data classified by the data classification unit 210 is "the user drives the smart washing machine mainly on Saturday morning", "it is Friday", "precipitation probability is 70% or more on Saturday morning", etc., The control signal calculation unit 220 analyzes the classified data in an integrated way through machine learning (deep learning), and says, "The smart washing machine will not be operated in the morning on Saturday and the driving time will be extended to a later time." Control information can be derived.

As another example, the data classified by the data classification unit 210 is "about 20 minutes left until the user returns home", "the user's average body temperature is 36.9 degrees", "the user's current sensed body temperature is 35.8 degrees", In the case of "the user usually starts the boiler 30 minutes after returning home", "the temperature around the house is 5 degrees chilly", etc., the control signal calculating unit 220 does not start the boiler after about 50 minutes based on the current time. In consideration of the user's body temperature drop, it is possible to derive the user-customized home appliance control information saying, "The boiler will be driven in advance to raise the temperature of the whole house before returning home. That is, the control signal calculating unit 220 determines the user's expected arrival time, It derives customized control information by complexly analyzing temperature/humidity and user life patterns.

In an embodiment of the present invention, the data classification unit 210 classifies the data of the data collection unit 100 in real time, and the control signal calculating unit 220 analyzes the classified real-time data to generate user-customized home appliance control information. However, by accumulating real-time input data and analyzing the accumulated data, it is possible to update user-customized home appliance control information to provide home appliance driving control information suitable for the user's current state.

For example, the data collected and classified so far are "Users operate the humidifier mainly on weekday evenings", "The duration of operation of the humidifier is about 1 hour", "The external humidity is about 60~65% when the humidifier is running" In the future, if there is a difference between the currently collected/classified data in the humidifier operation time period, driving duration, and whether the humidifier is driven according to external humidity due to a change in the user's state, it is continuously updated to reflect these differences.

Next, the control unit 300 receives the result calculated from the big data calculation unit 200 to recommend a home appliance service to the user or to control the operation of the home appliance.

Specifically, the control unit 300 transmits the user-customized home appliance driving control information to the smart terminal used by the user so that the home appliance is driven according to the user's selection. Based on the results, home appliances can be automatically turned on/off.

To this end, the control unit 300 includes a transmitter 310 that transmits a signal for driving the home appliance to the outside, and the home appliance includes a receiver 410 that receives a signal transmitted through the transmitter 310 .

Hereinafter, the provision of user-customized home appliance control information based on the selected home appliance among various home appliances will be described in detail.

First, as shown in FIG. 5 , when the home appliance is a pet care product, the data collection unit 100 provides the pet's feeding information, movement information, barking information, health information (respiration, heart rate, calorie consumption, sleep amount, etc.) ), collects pet behavior information when the owner goes out. To this end, the pet care product may include a camera, a motion sensor, a sound sensor, a respiration/heart rate sensor, and the like.

The big data calculation unit 200 may calculate user-customized home appliance control information by integrating and analyzing the collected data through a deep learning learning method, and such customized information is the state of the pet (movement information, barking, etc.) It may include providing basic meals, providing toys based on the pet's preferred movement pattern, managing the health of the pet and providing solutions (sleep amount, calorie consumption, respiration, heart rate), pet care information when the owner is absent.

Next, as shown in FIG. 6 , when the home appliance is a user-customized seasoning machine product, the data collection unit 100 controls the user's respiration/blood pressure/heart rate, nutritional analysis information of food materials, seasoning mixture information, holding food materials and hygiene information. , recommended recipes, and device operation information (time, number of times, operation recipes, etc.) are collected.

The big data calculation unit 200 may calculate user-customized home appliance control information by integrating and analyzing the collected data through a deep learning learning method, and this customized information provides a customized recipe for analyzing the user's health condition and usage pattern , providing recipes taking into account materials/sanitary information, providing A/S support services considering device operation/state information, sharing information between users and automatically adding customized recipes and seasonings through expert full advice.

Although the present invention has been described with reference to the accompanying drawings and the above-described preferred embodiments, the present invention is not limited thereto, and is defined by the following claims. Accordingly, those of ordinary skill in the art can variously change and modify the present invention within the scope without departing from the spirit of the claims to be described later.

100: data collection unit 200: big data calculation unit
210: data classification unit 220: control signal calculation unit
300: control unit 310: transmitter
410: receiver

Claims (4)

AI home appliance that recommends or automatically controls home appliance service to users by analyzing the data through machine learning after collecting user's home appliance usage pattern data, home appliance sensor data, external environment data, and user's location information data As a service providing system through
a data collection unit 100 for collecting the user's home appliance usage pattern data, the home appliance sensor data, the external environment data, the user's location information data, and the user's sleep pattern data;
a big data calculation unit 200 that analyzes the data collected in the data collection unit 100 through machine learning to calculate user-customized home appliance control information; and
and a control unit 300 for receiving the result calculated from the big data calculation unit 200 and recommending a home appliance service to the user or controlling the operation of the home appliance,
The user's home appliance usage pattern data collected by the data collection unit 100 includes data of a home appliance use cycle, a driving cycle of the home appliance, and a driving duration collected from the home appliance,
The big data calculation unit 200,
The data collected from the data collection unit 100 is based on a preset item range, that is, the user's home appliance usage pattern data, the home appliance sensor data, external environment data, the user's location information data, and the user's sleep pattern data. a data classification unit 210 for classifying into ; and
and a control signal calculation unit 220 for deriving optimized user-customized home appliance control information after extracting characteristics by integrally analyzing the data classified by item through the data classification unit 210 through deep learning Artificial intelligence human life service provision system through AI home appliances. delete According to claim 1,
The data classification unit 210 classifies the data of the data collection unit 100 in real time,
The control signal calculator 220 derives user-customized home appliance control information by analyzing the classified real-time data, but updates the user-customized home appliance control information by accumulating real-time input data and analyzing the accumulated data Artificial intelligence human life service provision system through AI home appliances. According to claim 1,
The control unit 300 includes a transmitter 310 for transmitting a signal for driving a home appliance to the outside, and the home appliance includes a receiver 410 for receiving a signal transmitted through the transmitter 310 Artificial intelligence human life service provision system through AI home appliances, characterized in that.

Images