KR101260649B1 - System and method for smart refrigerator management based on situation-awareness - Google Patents

Abstract

PURPOSE: A system and a method for managing a situation awareness-based smart refrigerator are provided to map and deduce information on the temperature, humidity, food storage from sensors, and the storage preference of users based on ontology. CONSTITUTION: A system for managing a situation awareness-based smart refrigerator comprises a sensor part(10), a data storage part(20), an environment information recognition part(30), an ontology deduction part(40), and a control part(50). The sensor part detects the environment information of a refrigerator. The data storage part stores critical values from the environment information of the refrigerator and the storage information of stored food. The environment recognition part maps the environment information, the critical value, and the storage information based on ontology; compares the environment information and the critical value; and transfers the compared value to the ontology deduction part. The ontology deduction part deducts based on the information mapped in the environment information recognition part, and transfers a control message to the control part. The control part controls an environment device of the refrigerator by receiving the control message. [Reference numerals] (10) Sensor part; (20) Data storage part; (21) Sensor information storage part; (22) Storage information storage part; (30) Environment information recognition part; (40) Ontology deduction part; (50) Control part; (60) Information setting input part

Description

Smart refrigerator management system and method based on situation awareness {SYSTEM AND METHOD FOR SMART REFRIGERATOR MANAGEMENT BASED ON SITUATION-AWARENESS}

The present invention relates to a smart refrigerator management system and method based on situational awareness, and more particularly, to infer based on ontology on information on storage preferences of foods stored in the refrigerator and storage preferences of users, as well as environmental information provided from sensors. The present invention relates to a smart refrigerator management system and method based on situation recognition capable of performing user-centered intelligent refrigerator management.

The conventional refrigerator has a problem that it is difficult to maintain the freshness of the food stored in the refrigerator due to the uniform temperature setting, in order to solve this problem, Korean Patent No. 10-0214659 (registered May 20, 1999) "Fridge temperature control method using fuzzy inference" is introduced.

The refrigerator temperature control method using the fuzzy inference provides a method for varying the set temperature inside the refrigerator by analyzing and determining the amount and type of various foods put into the refrigerator using fuzzy inference, Accurate analysis of quantity and type is used to store and store in optimum conditions suitable for food, and to control the operation of the compressor by varying the set temperature of the refrigerating chamber and the freezing chamber, thereby minimizing power consumption and heat loss.

However, in the method of controlling a refrigerator temperature using the fuzzy inference, it is inferred whether the sensing value, which is the environmental information of the refrigerator, is obtained at a predetermined time or is controlled based on the accumulated sensing value. There is a problem that the control and management of the refrigerator is not made.

Therefore, an object of the present invention can be mapped and inferred on the basis of ontology-based storage information of food stored in the refrigerator, information on the user's storage taste, as well as sensor information detected from the temperature sensor, humidity sensor, etc. installed in the refrigerator. To provide a situation-based smart refrigerator management system and method that can manage the refrigerator according to the user's taste, and more precisely control the refrigerator.

Smart refrigerator management system based on situation recognition according to an embodiment of the present invention comprises a sensor unit for detecting the environmental information of the refrigerator; A data storage unit for storing the threshold value of the environmental information of the refrigerator and storing the storage information of the stored food stored in the refrigerator; An environment information recognizing unit which maps the environmental information detected by the sensor unit, the threshold value and the storage information stored in the data storage unit on the basis of an ontology, compares the environmental information with the threshold value, and transmits the comparison value to the ontology inference unit; Ontology inference unit that infers according to the rule defined based on the information mapped by the environment information recognition unit, and if a comparison value or storage information received from the environment information recognition unit occurs during inference, delivers a control message to the controller. And a control unit receiving a control message from the ontology inference unit and controlling an environmental device of the refrigerator.

The data storage unit further comprises an information setting input unit for inputting the storage information of the stored food and the environmental information threshold value of the refrigerator.

The data storage unit may further include a sensor information storage unit for storing sensor information of the sensor unit and an environmental information threshold value, and a storage information storage unit for storing stored food storage information.

The ontology inference unit infers according to a rule defined based on the relationship between classes using SWRL.

The environmental information recognizing unit designates a component of the refrigerator as a class of ontology, designates environmental information received through the sensor unit as sensor information individual, and stores environmental information threshold value and stored information of the stored food in the data storage unit. It is specified as the critical information and the archive information, and the value of the sensor information and the critical information, characterized in that the variable is specified.

Smart refrigerator management method based on situation recognition in accordance with an embodiment of the present invention comprises the steps of obtaining the environmental information of the refrigerator by the sensor; Storing, by the environmental information recognizing unit, the environmental information acquired by the sensor unit in a data storage unit; Mapping, by the environment information recognizing unit, environmental information values for each sensor stored in the data storage unit, environmental information threshold values, and storage information to the ontology's individual information, and comparing the environmental information and threshold values; Inferring by the ontology inference unit the information mapped by the environment information recognizing unit according to a defined rule; The ontology inference unit infers according to a rule defined based on the information mapped by the environment information recognition unit, and determines whether there is an abnormality in the comparison value or the storage information received from the environment information recognition unit during inference, and if there is no error, the process Repeating step; If there is an abnormality, the ontology inference unit may include transmitting a control message to a control unit, and the control unit controls an environmental condition adjusting device of the refrigerator to solve an abnormal state of the refrigerator.

The environmental information recognizing unit designates a component of the refrigerator as a class of ontology, designates environmental information received through the sensor unit as sensor information individual, and stores environmental information threshold value and stored information of the stored food in the data storage unit. It is specified as the critical information and the archive information, and the value of the sensor information and the critical information, characterized in that the variable is specified.

Accordingly, the smart refrigerator management system and method based on situation recognition according to the present invention is not only sensor information detected from a temperature sensor, a humidity sensor, etc. installed in the refrigerator, but also the storage information of the food stored in the refrigerator, the storage taste of the user. Information can be mapped and inferred on the basis of ontology, and intelligent and user-oriented autonomous refrigerator management can be performed.

1 is a block diagram of a smart refrigerator management system based on situation awareness according to an embodiment of the present invention
2 is an exemplary view for explaining the ontology inference unit in the smart refrigerator management system based on situational awareness according to an embodiment of the present invention.
3 is an exemplary diagram of modeling a refrigerator component ontology in a situation-aware smart refrigerator management system according to an embodiment of the present invention.
Figure 4 is an illustration of the actual XML-based OWL code of Figure 3
5 is an exemplary diagram in which FIG. 3 is represented by a SWRL rule.
6 and 7 are exemplary diagrams for explaining whether or not a situation is made by loading a SWRL-written rule in an inference engine.
8 is a flowchart of a situation-aware smart refrigerator management method according to an embodiment of the present invention.

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

Referring to FIG. 1, a situation-aware refrigerator management system according to an embodiment of the present invention includes a sensor unit 10, a data storage unit 20, an environmental information recognition unit 30, an ontology inference unit 40, and a controller. And 50.

The sensor unit 10 detects environmental information such as temperature and humidity of the refrigerator.

The data storage unit 20 stores a threshold value for environmental information (appropriate temperature, proper humidity, etc.) of the refrigerator, and stores information (expiration date of food, proper maintenance temperature of food and the like) stored in the refrigerator. Humidity, user's taste, etc.).

The environmental information recognizing unit 30 maps the environmental information detected through the sensor unit 10, the threshold value and the storage information stored in the data storage unit 20 based on the ontology, and maps the environmental information and the threshold value. In comparison, the comparison value is transmitted to the ontology inference unit 30.

The ontology inference unit 40 infers according to a rule defined based on the information mapped by the environment information recognizing unit 30, and an abnormality of the comparison value or storage information received from the environment information recognizing unit 30 during inference. If this occurs, the control unit 50 transmits a control message.

The controller 50 receives a control message from the ontology inference unit 40 and controls an environmental device of a refrigerator such as temperature and humidity.

The data storage unit 20 includes an information setting input unit 60 for inputting the storage information of the stored food and the environmental information threshold of the refrigerator.

The setting information input unit 60 may obtain the storage information by reading the food information barcode or RF tag through a barcode reader or an RF reader installed in the refrigerator, and separate input devices (keyboard, touch pad, keypad, voice recognition and input). Device) can input the food information and environmental information threshold value.

The data storage unit 20 includes a sensor information storage unit 21 for storing sensor information of the sensor unit 10 and an environmental information threshold value, and a storage information storage unit 22 for storing stored food storage information. .

As a result, the threshold value of the environmental information stored in the data storage unit 20, the storage information of the stored food, and the environmental information detected through the sensor unit 10 are based on the ontology in the environmental information recognition unit 30. The mapped information is mapped and the reasoning proceeds according to the rules defined in the ontology inference unit 40.

The defined rule is one of the inference engines, and the ontology inference unit 40 defines an inference rule based on the relationship between classes using SWRL (Semantic Web Rule Language).

The SWRL is described in detail in the "SWRL rule definition system" of the Applicant Patent No. 10-1079795, the detailed description thereof will be omitted.

Based on the sensor information of the sensor unit 10 installed in the refrigerator and the storage information stored in the data storage unit 20 through the inference engine, not only the user-centered intelligent reasoning, but also intelligent monitoring of the stored food Inferred to be transmitted to the user's portable terminal through a communication module (not shown).

Alternatively, the threshold value of the environmental information stored in the data storage unit 20 and the storage information of the stored food and the environmental information detected through the sensor unit 10 are transmitted to a home network server (not shown), and the home network The server maps ontology-based, and the mapped information is inferred from the home network server.

The comparison value detected by the environmental information recognizing unit 30 during the inference in the home network may be transmitted to the communication module to the home network, determine whether there is an abnormality in the refrigerator, and transmit the control message to the control unit 50 to control it.

The ontology mapping and inference can be made in the home network server, so that the user can easily change the ontology model by accessing the home network server, and the inference proceeds according to the changed ontology model.

For example, the Kimchi refrigerator compartment of the refrigerator may be replaced with a fruit compartment, and when the user connects to the home network server and changes it, the home network server applies the changed ontology model to perform ontology mapping and inference. Can be.

In addition, by performing ontology mapping and inference in the home network server, there is an advantage that the ontology can be applied to other home appliances.

The environmental information recognizing unit 30 designates (mappings) a component of the refrigerator as a class of an ontology, designates environmental information received through the sensor unit 10 as sensor information visual, and stores the data storage unit ( 20) The threshold information stored in the environment and the stored information of the stored food are designated as the critical information and the stored information individual, and the values of the sensor information and the critical information individual are designated as variables.

The ontology inference unit 40 may perform inference when an individual corresponding to the class has a value corresponding to an inference rule, and the value required for the inference rule stores environmental information and data of the sensor unit 10. The storage information of the stored food stored in the unit 20.

Ontology is a data model that represents a specific domain, and is defined as a set of formal vocabulary describing concepts that belong to a specific domain and the relationships between the concepts.

For example, the ontology can be called an ontology by describing the relationship between species and species between living organisms classified as subclasses (biological classifications) and relationships between English words in a formal vocabulary.

Ontology, which is a set of vocabulary described in the formal language, is used for reasoning and inference.

This ontology is largely composed of Class, Individual, Object, and Property.

Therefore, in order to formalize the environmental components of the refrigerator ontology, the freezer compartment and the refrigerating compartment are designated as classes, and the kimchi refrigerating compartment, fruit box, ice box, etc. included in the refrigerating compartment are designated as auxiliary classes.

For example, as shown in FIG. 2, the first refrigerator compartment (storeroom_A), which is an object of the kimchi refrigerator compartment, is an individual of the Kimchi refrigerator compartment class, and is detected by a temperature sensor (Temperature Sensor_A), a threshold temperature, an event, The control message (NeedToStart cooler) is an individual.

In addition, the temperature detected at the individual (36.5 ° C) and the critical temperature (20 ° C) are set as variables.

The definition of this information and relationships is ontology, and the refrigerator can be managed through a standard reasoning engine using SWRL.

Inference rules can be defined based on the relationship between the classes, and when the individual corresponding to the class has a value corresponding to the inference rules, inference can be performed.

At this time, the values necessary for inference of ontology are the variables (environmental information (sensor value), threshold value, storage information).

The smart refrigerator system based on situation recognition according to the present invention may be ontology modeled as shown in FIG. 3.

As shown in FIG. 3, if the refrigerating compartment is a class, the kimchi refrigerating compartment, which is a part of the refrigerator, is an auxiliary class of the refrigerating compartment class.

In addition, if there is a property called hasParts, the refrigerator class can have a property called hasParts, and within this attribute there are component classes such as doors, chillers and sensors.

In this case, the block A refrigerator compartment, an object of the kimchi refrigerator compartment, is an indie visual of the kimchi refrigerator compartment.

The Kimchi Refrigerator can include the attributes of the Block A Refrigerator through the hasinformationHasparts property, and can include the attributes of the Block A Refrigeration Room by including the temperature sensor and humidity sensor.

Inference can be performed through this ontology modeling.

The ontology modeling is represented in FIG. 4 by the actual XML-based OWL code.

OWL (Web Ontology Language) is a language designed to be used not only to display information to people but also to implement applications that can directly process the content of information.

The OWL is rich in vocabulary and formal semantics and thus outperforms XML, RDF and RDF Schema (RDF-S) for authoring machine-interpretable web content.

OWL consists of three sub-languages with different expressive powers: OWL Lite, OWL DL, and OWL Full. The latter is more expressive.

If both classes and attributes are defined through the OWL, a rule for determining a situation according to the temperature and humidity of the refrigerating compartment is defined based on the classes and attributes.

The rules for determining the proper temperature and humidity of the kimchi refrigerator of FIG. 4 are written in SWRL as shown in FIG. 5, and the critical temperature and the critical humidity suitable for storing kimchi are defined in the information class, and determined according to the defined values. Write a rule to do it.

The written rule can recognize the situation by judging whether the storage temperature and humidity is high and low, and if the ontology model according to the present invention is loaded on an inference engine for inference of actual situation, it is as follows.

Define a storage temperature of 4 ° C and a humidity of 90% in the Information class, and if a temperature is higher or lower than the storage temperature of 4 ° C, a temperature problem event will occur, and if the humidity is higher or lower than 90%, a humidity event. Generates.

Figure 6 is an example of determining the situation that the problem occurs because the temperature is higher than the storage temperature 4 ℃ using the inference engine, Figure 7 is defined as the humidity by 88% using the inference engine, problems caused by low humidity Is an example of judging the situation that is occurring.

Referring to the situation-based smart refrigerator management method according to an embodiment of the present invention.

First, the environmental information threshold value of the sensor unit 10 and the storage information for each food are input through the setting information input unit 60 installed in the refrigerator.

The setting information input unit 60 may obtain food information through a bar code or an RF reader installed in the refrigerator, and food information and environmental information through separate input devices (keyboard, touch pad, keypad, voice recognition and input device). The threshold value may be input from the user.

The storage information is information such as the expiration date of the food, the storage preference of the user.

Referring to FIG. 8, the sensor unit 10 obtains environmental information (temperature, humidity, etc.) of the refrigerator (S10).

The environmental information recognizing unit 30 stores the environmental information acquired by the sensor unit 10 in the data storage unit 20 (S20).

The environmental information recognizing unit 30 maps the environmental information value of each sensor stored in the data storage unit 20, the environmental information threshold value, and the storage information to the ontology's visual (S30), and the ontology inference unit 40 The information mapped by the environment information recognizing unit 30 is inferred according to a defined rule, and the environment information is compared with a threshold value (S40).

The ontology inference unit 40 determines whether there is an abnormality of the comparison value or the storage information of the environmental information and the environmental information threshold value during inference, and if there is no abnormality, repeats the steps S10 to S50 (S50).

If there is an abnormality in the step S50, the ontology inference unit 40 transmits a control message to the control unit 50 (S60), the control unit 50 controls the environmental state control device of the refrigerator abnormality of the refrigerator Control the situation (S70).

In step S40, the environmental information recognition unit 30 designates a component of the refrigerator as an ontology class, designates environmental information received through the sensor unit 10 as sensor information visual, and stores the data. The environmental information threshold stored in the unit 20 and the storage information of the stored food are designated as the critical information individual and the storage information individual, and the values of the sensor information individual and the critical information individual are designated as variables.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is clearly understood that the same is by way of illustration and example only and is not to be construed as limiting the scope of the invention as defined by the appended claims. It will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the present invention.

10: Sensor unit
20: data storage
30: Environmental Information Recognition Department
40: Ontology Inference Unit
50: control unit

Claims (7)

A sensor unit detecting environmental information of the refrigerator;
A data storage unit for storing the threshold value of the environmental information of the refrigerator and storing the storage information of the stored food stored in the refrigerator;
An environment information recognizing unit which maps the environmental information detected by the sensor unit, the threshold value and the storage information stored in the data storage unit on the basis of an ontology, compares the environmental information with the threshold value, and transmits the comparison value to the ontology inference unit;
Ontology inference unit that infers according to the rule defined based on the information mapped by the environment information recognition unit, and if a comparison value or storage information received from the environment information recognition unit occurs during inference, delivers a control message to the controller. And
Smart refrigerator management system based on situation awareness, characterized in that it comprises a control unit for receiving a control message from the ontology inference unit to control the environmental apparatus of the refrigerator.
The method of claim 1,
The smart refrigerator management system based on situation awareness, characterized in that it further comprises an information setting input unit for inputting the storage information of the stored food and the environmental information threshold value of the refrigerator to the data storage unit.
The method of claim 1,
The data storage unit further includes a sensor information storage unit for storing sensor information and environmental information threshold values of the sensor unit, and a storage information storage unit for storing stored food storage information.
The method of claim 1,
The ontology inference unit is based on the situation awareness smart refrigerator management system, characterized in that inference according to the rules defined based on the relationship between the classes using the SWRL.
The method of claim 1,
The environmental information recognizing unit designates a component of the refrigerator as a class of ontology, designates environmental information received through the sensor unit as sensor information individual, and stores environmental information threshold value and stored information of the stored food in the data storage unit. It is specified by the critical information and the storage information, and the situation-aware smart refrigerator management system, characterized in that the value of the sensor information and the critical information individual to specify as a variable.
Acquiring, by the sensor unit, environmental information of the refrigerator (S10);
Storing, by the environmental information recognizing unit, the environmental information acquired by the sensor unit in a data storage unit (S20);
Mapping, by the environmental information recognizing unit, the environmental information value of each sensor stored in the data storage unit, the environmental information threshold value and the storage information to the individual ontology, and comparing the environmental information and the threshold value (S30);
An ontology inference unit inferring information mapped by the environment information recognizing unit according to a defined rule (S40);
The ontology inference unit infers according to a rule defined based on the information mapped by the environment information recognition unit, and determines whether there is an abnormality in the comparison value or the storage information transmitted from the environment information recognition unit during inference, and if there is no error, the S10. Repeating step S50 to step S50;
If there is an error in step S50, the ontology inference unit transmits a control message to the control unit (S60) and
Smart controller management method based on situation awareness, characterized in that the control unit controls the environmental condition control device of the refrigerator to solve the abnormal situation of the refrigerator (S70).
The method according to claim 6,
In step S40, the environmental information recognizing unit designates a component of the refrigerator as a class of ontology, and the environmental information received through the sensor unit as sensor information individual, and the environmental information threshold value stored in the data storage unit. A method for managing smart refrigerators based on situational awareness, wherein the stored information of the stored food is designated as the critical information individual and the stored information individual, and the value of the sensor information individual and the critical information individual is designated as a variable.

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