WO2013100683A1 - System and method for monitoring status of food based on ontology - Google Patents

System and method for monitoring status of food based on ontology Download PDF

Info

Publication number
WO2013100683A1
WO2013100683A1 PCT/KR2012/011687 KR2012011687W WO2013100683A1 WO 2013100683 A1 WO2013100683 A1 WO 2013100683A1 KR 2012011687 W KR2012011687 W KR 2012011687W WO 2013100683 A1 WO2013100683 A1 WO 2013100683A1
Authority
WO
WIPO (PCT)
Prior art keywords
food
information
storage
sensing
ontology
Prior art date
Application number
PCT/KR2012/011687
Other languages
French (fr)
Korean (ko)
Inventor
김병삼
김지영
Original Assignee
한국식품연구원
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 한국식품연구원 filed Critical 한국식품연구원
Publication of WO2013100683A1 publication Critical patent/WO2013100683A1/en

Links

Images

Classifications

    • A—HUMAN NECESSITIES
    • A23—FOODS OR FOODSTUFFS; TREATMENT THEREOF, NOT COVERED BY OTHER CLASSES
    • A23L—FOODS, FOODSTUFFS, OR NON-ALCOHOLIC BEVERAGES, NOT COVERED BY SUBCLASSES A21D OR A23B-A23J; THEIR PREPARATION OR TREATMENT, e.g. COOKING, MODIFICATION OF NUTRITIVE QUALITIES, PHYSICAL TREATMENT; PRESERVATION OF FOODS OR FOODSTUFFS, IN GENERAL
    • A23L3/00—Preservation of foods or foodstuffs, in general, e.g. pasteurising, sterilising, specially adapted for foods or foodstuffs
    • A23L3/003—Control or safety devices for sterilisation or pasteurisation systems
    • A—HUMAN NECESSITIES
    • A23—FOODS OR FOODSTUFFS; TREATMENT THEREOF, NOT COVERED BY OTHER CLASSES
    • A23L—FOODS, FOODSTUFFS, OR NON-ALCOHOLIC BEVERAGES, NOT COVERED BY SUBCLASSES A21D OR A23B-A23J; THEIR PREPARATION OR TREATMENT, e.g. COOKING, MODIFICATION OF NUTRITIVE QUALITIES, PHYSICAL TREATMENT; PRESERVATION OF FOODS OR FOODSTUFFS, IN GENERAL
    • A23L3/00—Preservation of foods or foodstuffs, in general, e.g. pasteurising, sterilising, specially adapted for foods or foodstuffs
    • A23L3/36—Freezing; Subsequent thawing; Cooling
    • A—HUMAN NECESSITIES
    • A23—FOODS OR FOODSTUFFS; TREATMENT THEREOF, NOT COVERED BY OTHER CLASSES
    • A23L—FOODS, FOODSTUFFS, OR NON-ALCOHOLIC BEVERAGES, NOT COVERED BY SUBCLASSES A21D OR A23B-A23J; THEIR PREPARATION OR TREATMENT, e.g. COOKING, MODIFICATION OF NUTRITIVE QUALITIES, PHYSICAL TREATMENT; PRESERVATION OF FOODS OR FOODSTUFFS, IN GENERAL
    • A23L3/00—Preservation of foods or foodstuffs, in general, e.g. pasteurising, sterilising, specially adapted for foods or foodstuffs
    • A—HUMAN NECESSITIES
    • A23—FOODS OR FOODSTUFFS; TREATMENT THEREOF, NOT COVERED BY OTHER CLASSES
    • A23L—FOODS, FOODSTUFFS, OR NON-ALCOHOLIC BEVERAGES, NOT COVERED BY SUBCLASSES A21D OR A23B-A23J; THEIR PREPARATION OR TREATMENT, e.g. COOKING, MODIFICATION OF NUTRITIVE QUALITIES, PHYSICAL TREATMENT; PRESERVATION OF FOODS OR FOODSTUFFS, IN GENERAL
    • A23L3/00—Preservation of foods or foodstuffs, in general, e.g. pasteurising, sterilising, specially adapted for foods or foodstuffs
    • A23L3/34—Preservation of foods or foodstuffs, in general, e.g. pasteurising, sterilising, specially adapted for foods or foodstuffs by treatment with chemicals
    • A23L3/3409—Preservation of foods or foodstuffs, in general, e.g. pasteurising, sterilising, specially adapted for foods or foodstuffs by treatment with chemicals in the form of gases, e.g. fumigation; Compositions or apparatus therefor
    • A—HUMAN NECESSITIES
    • A23—FOODS OR FOODSTUFFS; TREATMENT THEREOF, NOT COVERED BY OTHER CLASSES
    • A23L—FOODS, FOODSTUFFS, OR NON-ALCOHOLIC BEVERAGES, NOT COVERED BY SUBCLASSES A21D OR A23B-A23J; THEIR PREPARATION OR TREATMENT, e.g. COOKING, MODIFICATION OF NUTRITIVE QUALITIES, PHYSICAL TREATMENT; PRESERVATION OF FOODS OR FOODSTUFFS, IN GENERAL
    • A23L3/00—Preservation of foods or foodstuffs, in general, e.g. pasteurising, sterilising, specially adapted for foods or foodstuffs
    • A23L3/34—Preservation of foods or foodstuffs, in general, e.g. pasteurising, sterilising, specially adapted for foods or foodstuffs by treatment with chemicals
    • A23L3/3409—Preservation of foods or foodstuffs, in general, e.g. pasteurising, sterilising, specially adapted for foods or foodstuffs by treatment with chemicals in the form of gases, e.g. fumigation; Compositions or apparatus therefor
    • A23L3/3445—Preservation of foods or foodstuffs, in general, e.g. pasteurising, sterilising, specially adapted for foods or foodstuffs by treatment with chemicals in the form of gases, e.g. fumigation; Compositions or apparatus therefor in a controlled atmosphere comprising other gases in addition to CO2, N2, O2 or H2O

Definitions

  • the present invention relates to ontology modeling and situational awareness method and system for intelligent food storage management, and more specifically, to the storage by applying sensing information, storage operation information, food storage information, food attribute information to inference rules
  • the present invention relates to a food condition monitoring system and method for calculating food corruption, fresh grade, and freshness retention period.
  • a storage room is a facility for storing agricultural products such as grain, and means a storage building or a warehouse having good shielding from outside air. In such a storage, it is important to control temperature and humidity as grains and the like are stored.
  • the reservoir may be equipped with a sensing sensor such as a temperature sensor and a humidity sensor, and a warm air fan, a cold fan, a dehumidifier, and an environmental condition adjusting device for adjusting the environmental condition of the reservoir.
  • control system for controlling the environmental conditioning device using information provided from the sensor in order to keep the reservoir in an optimal state.
  • the method and apparatus for monitoring and controlling the temperature and humidity of the conventional storage as shown in Figure 1, the step of detecting the current temperature of the storage, the current humidity of the storage, the present temperature and the predetermined optimum temperature Comparing and adjusting the temperature of the cold storage until the current temperature reaches the optimum temperature, comparing the current humidity with a preset optimal humidity and the cold storage until the current humidity reaches the optimum humidity. It includes controlling the humidity of the.
  • the conventional method and apparatus for monitoring and controlling low temperature temperature and humidity detect the current temperature and humidity and compare the temperature and humidity of the cold storage regardless of the operational information that the food is put into or out of the storage compared to the preset optimal temperature. Since there is a problem that unnecessary temperature and humidity control may occur in the storage.
  • the method and apparatus for monitoring and controlling the low temperature and humidity of the related art are middleware or reasoning system that infers whether the environmental condition control device is inferred based on the sensing value or the accumulated sensing value at a moment. There is a problem that may not take appropriate action depending on the actual situation.
  • a method and a device for maintaining freshness of a conventional food include ethylene (C2H4) and water from the agricultural products to maintain the freshness of the agricultural products stored in a storage space in which agricultural products such as fruits and vegetables are stored.
  • C2H4 ethylene
  • water from the agricultural products to maintain the freshness of the agricultural products stored in a storage space in which agricultural products such as fruits and vegetables are stored.
  • TiO 2 titanium dioxide
  • the air is exposed to ultraviolet rays by an ultraviolet ray generating lamp 44, and the ethylene (C 2 H 4) is photooxidized and stored according to the formula C 2 H 4 + 4 H 2 O ⁇ 2 CO 2 + 6 H 2.
  • the problem to be solved by the present invention is to provide a method and system for providing a fresh grade of food, the fresh maintenance period and whether or not corruption by using information of ethylene, humidity, temperature, carbon dioxide of the storage space.
  • Another problem to be solved by the present invention is to provide a method and system for monitoring the freshness grade, freshness maintenance period and corruption of food by measuring ethylene concentration, humidity, temperature, carbon dioxide concentration, etc. in consideration of the actual situation.
  • Another problem to be solved by the present invention is to provide a method and system for determining the fresh grade, the fresh maintenance period and the degree of decay in consideration of the actual stored food state.
  • One aspect of the food condition monitoring method of the present invention includes a sensing information acquisition step of obtaining sensing information from sensors located inside the food storage; Food storage information obtaining step of obtaining food storage information of the food from the DB; A storage operation information obtaining step of obtaining storage operation information of the food storage; And calculating the food corruption status, freshness grade, and freshness period of each stored food by inferring the state of the food storage by applying the sensing information, the food storage information, and the storage operation information to a pre-written inference rule.
  • a status output step is calculating the food corruption status, freshness grade, and freshness period of each stored food by inferring the state of the food storage by applying the sensing information, the food storage information, and the storage operation information to a pre-written inference rule.
  • the food property information obtaining step of obtaining the attribution information of the stored food from the DB further comprises, wherein the food state output step further applies the attribution information to the inference rule of the food storage;
  • each of the stored foods is characterized by calculating whether the food is decaying, freshness grade, and freshness period.
  • the sensing information is at least one of ethylene concentration, carbon dioxide concentration, temperature, humidity
  • the food storage information is at least one of the ethylene concentration threshold, carbon dioxide concentration threshold, temperature threshold, humidity threshold of the food
  • Storage operation information is door opening and closing information of the storage, characterized in that the attribute information is at least one of the name of the stored food, the origin of the stored food, the history information before storage.
  • One aspect of the food condition monitoring system of the present invention is a sensor for detecting the internal situation of the food storage; DB for storing storage operation information and food storage information; A sensing information acquisition unit for receiving and storing sensing information from the sensor; Food storage information acquisition unit for receiving and storing food storage information from the DB; A storage operation information acquisition unit for receiving and storing storage operation information from the DB; And receiving the sensing information from the sensing information acquisition unit, receiving the food storage information from the food storage information acquisition unit, receiving the storage operation information from the storage operation information acquisition unit, and receiving the sensing information and the food. And a control unit that calculates whether or not the stored food is decayed, freshness, and fresh keeping period by applying the storage state information and the storage operation information to the prepared inference rule.
  • the DB is characterized in that to store the attribute information of the stored food, further comprises a food attribute information acquisition unit for obtaining the attribute information from the DB, the control unit transfers the attribute information from the food attribute information acquisition unit And receiving the sensing information, the food storage information, the storage operation information, and the attribute information to the inference rule to infer a situation, thereby calculating whether the stored food is corrupt, freshness, and freshness retention period.
  • the sensing information is at least one of ethylene concentration, carbon dioxide concentration, temperature, humidity
  • the food storage information is at least one of the ethylene concentration threshold, carbon dioxide concentration threshold, temperature threshold, humidity threshold of the food
  • the storage operation information is door opening and closing information of the storage
  • the attribute information is characterized in that the attribute information is at least one of the name of the stored food, the origin of the stored food, before the storage of the storage, and history information.
  • the food condition monitoring system and method according to the present invention it is possible to provide the freshness of the food, the freshness maintenance period and whether or not the food using the information of ethylene, humidity, temperature, carbon dioxide of the storage space.
  • the food condition monitoring system and method according to the present invention by measuring the ethylene concentration, humidity, temperature, carbon dioxide concentration, etc. in consideration of the actual situation, it is possible to provide a fresh grade, a fresh maintenance period and whether or not the corruption of the food.
  • the food condition monitoring system and method according to the present invention it is possible to provide the fresh grade, the freshness maintenance period and the degree of decay in consideration of the actual stored food condition.
  • FIG. 1 shows an apparatus for monitoring and controlling the temperature and humidity of a conventional storage
  • FIG. 2 is a view showing a method for maintaining a conventional food freshness
  • FIG. 4 is a block diagram illustrating a food condition monitoring system using ontology inference according to an embodiment of the present invention.
  • FIG. 5 is a flowchart illustrating a method for monitoring food status using ontology inference according to an embodiment of the present invention.
  • Situation or environmental information Various definitions exist depending on the application field, but in the computer field, it refers to external environmental information that an application system can detect as part of an application system operating environment. In order to construct an intelligent environment for performing situation awareness, situation inference technology is needed to collect various environmental information and infer the situation based on the information.
  • Environment information refers to information that can specify a situation of an entity.
  • Context-aware middleware for food storage uses environmental information to infer the circumstances necessary for food management and inform the user of the results.
  • the ontology is used to define the environment information, which is converted into a fact that can be utilized by a computer. Use rules to infer based on facts.
  • Ontologies are formal and explicit specitic representations of shared conceptualization. Ontology can be thought of as a kind of dictionary composed of words and relationships, including words related to specific domains hierarchically, and additionally inferring rules that can be extended to include web-based knowledge processing or application. Knowledge sharing and reuse among programs are possible.
  • OWL is a language designed to represent information on the Web and to process content directly in applications. OWL provides a rich vocabulary and formal meaning that can be processed by machines. SWRL has a structure that adds a rule description language to OWL, and is a language that can define rules that are complicated to express in OWL.
  • an ontology modeling environment information should be constructed.
  • context-aware middleware acquires facts by assigning context information to ontology through various methods, and the inference engine performs inference based on rules. Inference results are forwarded to the upper repository management system.
  • the first task to design an ontology for context-aware middleware is to define the environmental elements that make up the cold store.
  • the elements that make up a cold store include a store, a sensor, a standard for storage, a storage product, and storage information.
  • OWL 3 is a hierarchical structure of OWL by representing each element as a class according to an embodiment of the present invention.
  • the relationship between the components can be expressed by defining the attributes of the OWL.
  • properties in OWL you can define whether it is an object or data. Each can be expressed as an object property and a data property. Once you have defined a class, you define an individual.
  • SWRL that defines rules through relationships between ontology classes, visuals, and assets is required.
  • Information sources for obtaining the environmental information of the food storage are sensor information and storage management information.
  • Sensing information refers to information such as the type, location, sensing value of the sensor attached to the food storage.
  • ID is assigned to the sensor, and situation inference is performed in correspondence with the attribute of the ontology.
  • all the operational information is stored in a database.
  • Operational information is computerized, and the process of acquiring computer information is the same as the process of acquiring information from a database.
  • the obtained operational information is assigned an ID and displayed to be individually mapped.
  • Sources that provide sensing values and storage operation information have been defined, each with a unique ID. Since each ID has one specific value, mapping this ID to an individual value can populate the domain ontology's environment information. Each attribute has a range of individually appropriate forms, and the implemented individual has a sensing value or operational information corresponding to the source ID as a range value. No single sensor or operational information can have a double value.
  • the core functional modules of context aware middleware are modules for obtaining sensing and operational information, mapping modules, and context inference modules.
  • the sensing information and operation information acquisition module collects the operation information when the sensing information is acquired from the sensor and starts the reasoning.
  • the ontology mapping module is a module that assigns data to the OWL ontology model in use. This module performs the function of assigning a value to an individual according to ID classification.
  • FIG. 4 is a functional block diagram illustrating a food condition monitoring system using ontology inference according to the present invention.
  • the food condition monitoring system using the ontology inference according to an embodiment of the present invention will be described in detail with reference to FIG. 4.
  • the food condition monitoring system includes a food condition monitoring device, a database, and a plurality of sensors.
  • the food condition monitoring apparatus includes a food storage information acquisition unit, a sensing information acquisition unit, a food attribute information acquisition unit, a storage management information acquisition unit, and a control unit.
  • a control unit a control unit.
  • other configurations may be included in the food condition monitoring system or the food condition monitoring device.
  • the DB 100 stores storage operation information, attribute information of stored food, storage information of food, and the like.
  • the sensor 200 detects information such as ethylene concentration, carbon dioxide concentration, temperature, and humidity in the storage, which is sensing information, and detects information on ethylene concentration, carbon dioxide concentration, temperature, and humidity in the detected storage, and the food condition monitoring device 300.
  • To send). 4 illustrates only a temperature sensor, a humidity sensor, an ethylene sensor, and a carbon dioxide sensor, but is not limited thereto. That is, any sensor capable of sensing environmental information in the storage can be included in the present invention.
  • the food condition monitoring apparatus 300 may include a storage operation information acquisition unit 340, a sensing information acquisition unit 320, a food attribute information acquisition unit 330, a food storage information acquisition unit 310, and a controller 350. Can be.
  • the storage operation information acquisition unit 340, the food attribute information acquisition unit 330, and the food storage information acquisition unit 310 receive storage operation information, food attribute information, and food storage information from the DB 100.
  • the storage operation information may be a time at which food enters the storage, opening / closing time of the storage door, the number of times, and the like.
  • the food attribute information may be the name of the stored food, the origin of the stored food, or the like.
  • the food storage information may be a temperature threshold, humidity threshold, ethylene concentration threshold, carbon dioxide concentration threshold, and the like, in which the freshness of the stored food is maintained.
  • the sensing information acquisition unit 320 receives the sensing information from the sensor 200.
  • the control unit 350 applies sensing information, food storage information, storage management information, and food attribute information to pre-written inference rules, and infers the situation of the food storage, thereby determining whether each stored food is corrupt, fresh grade, and freshness period. Can be calculated
  • the controller 350 applies ontology inferences prepared in advance, and ontology-based inference of the situation of the food storage.
  • Ontology-based reasoning refers to defining relationships between sensing information, storage operation information, food attribute information, and food storage information in ontology language, and inferring by creating rules through the defined relationships.
  • relation and inference rules in ontology language, class, individual, and property must be defined as described above. Relationships and inference rules for ontology inference are defined using defined classes, individualities, and properties.
  • the storage is defined as a class of ontology, and sensing information, storage operation information, food attribute information, and food storage information are defined as individual, and the corresponding values are defined as variables.
  • “Storage” becomes a class, and one type of “Storage” is a subclass of the Storage class, and "301 Gimhae Rice Storage” is an independent type of rice storage.
  • the "sensor 200" is a class, "temperature sensor 200", “humidity sensor 200”, “ethylene sensor 200”, “carbon dioxide concentration sensor 200” of the sensor 200 Become independent. The sensing information becomes a property.
  • the storage environment is inferred by comparing the variable of the sensing information individual with the variable of the food storage information individual, and taking into account the variable of the storage operation information individual and the variable of the food attribute information individual.
  • an event occurs during the ontology inference process, and whether or not the event occurs may be in accordance with an inference rule written in the ontology language DSML + OIL, OWL, Ontolingun, or the like.
  • the relationship for ontology inference is defined in the ontology language, and the inference rule is created in the semantic web rule language (SWRL) based on the defined relationship. That is, when each class's individual information has a value corresponding to a defined inference rule, ontology inference is performed.
  • SWRL semantic web rule language
  • the control unit 350 allocates the sensing information from the sensor 200, the storage operation information from the DB 100, the food attribute information, and the food storage information to the inference rule, and infers and deduces the situation of the storage, thereby inducing food.
  • the decay status, freshness grade and freshness period can be calculated.
  • FIG. 5 is a flow chart illustrating a food condition monitoring method using ontology inference according to the present invention.
  • a method for monitoring food status using ontology inference according to an embodiment of the present invention will be described in detail with reference to FIG. 5.
  • the sensing information acquisition step (S310), storage operation information acquisition step (S330), attribute information acquisition step (S340), food Storage information acquisition step (S320), may include a food state output step.
  • the food condition monitoring apparatus 300 may acquire temperature, humidity, carbon dioxide concentration, and ethylene concentration information, which is sensing information, from the sensor 200 located in the storage.
  • the sensors 200 detect temperature, humidity, ethylene concentration, carbon dioxide concentration, and the like, and transmit them to the food condition monitoring apparatus 300.
  • the food condition monitoring apparatus 300 may obtain storage operation information from the DB 100.
  • the storage operation information may be information such as the time the food enters the storage, the time the door is opened, the number of times.
  • the food state monitoring apparatus 300 may obtain food attribute information from the DB 100.
  • the food attribute information may be the name of the food entered in the storage, the country of origin, the time of receipt of the food, fresh state, and the like.
  • the food condition monitoring apparatus 300 may obtain food storage information from the DB 100.
  • the food storage information may be an ethylene concentration threshold, a carbon dioxide concentration threshold, a temperature threshold, a humidity threshold, and the like of the food.
  • Food state output step (S350) by applying the sensing information, storage operation information, attribute information, food storage information obtained from the sensor 200 and DB 100 to the ontology inference rules, whether the food is corrupt, fresh grade and freshness Calculate the duration.
  • the senor 200, storage, and food are defined as classes for ontology-based inference, and sensing information, storage operation information, food attribute information, and food storage information are defined as individual.
  • inference rules are defined for relations between classes and event occurrences according to variable assignments.
  • the food state detecting apparatus allocates the transmitted sensing information, storage operation information, food storage information, and food attribute information to the inference rule, and ontology inference result, whether the event that is the inferred result occurs and the event occurrence. Types are used to calculate whether or not the food is decayed, freshness grade, and freshness retention period.

Landscapes

  • Chemical & Material Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Nutrition Science (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Food Science & Technology (AREA)
  • Polymers & Plastics (AREA)
  • Chemical Kinetics & Catalysis (AREA)
  • General Chemical & Material Sciences (AREA)
  • Cold Air Circulating Systems And Constructional Details In Refrigerators (AREA)

Abstract

The present invention relates to a method and system for recognizing a situation by using an ontology modeling technique for intelligently managing a food storeroom, and more particularly, to a system and method for monitoring the status of food that apply sensing information, storeroom operation related information, food storage related information, and food attribute related information to an inferring rule to recognize whether food kept in a storeroom has gone bad and to find out the freshness grade and the period over which freshness is maintained. An aspect of the method of monitoring the status of food according to the present invention includes: the step of obtaining sensing information in which sensing information is obtained from sensors located in a food storeroom; the step of obtaining food storage related information in which food storage related information is obtained from a DB; the step of obtaining storeroom operation related information in which storeroom operation related information is obtained; and the step of outputting the status of food in which the sensing information, the food storage related information, and the storeroom operation related information are applied to a pre-made inferring rule to infer the situation of a food storeroom in order to recognize whether each stored food has left and in order to find the freshness grade and the period over which freshness is maintained.

Description

온톨로지 기반 식품 상태 감시 시스템 및 방법Ontology-based Food Condition Monitoring System and Method
본 발명은 지능적 식품 저장고 관리를 위한 온톨로지 모델링과 상황인지 방법 및 시스템에 관한 것으로 더욱 상세하게는 더욱 상세하게는 센싱 정보, 저장고 운영 정보, 식품 보관 정보, 식품 속성 정보를 추론 규칙에 적용하여 저장고 보관 식품의 부패여부, 신선 등급, 신선 유지 기간을 산출하는 식품 상태 감시 시스템 및 방법에 관한 것이다.The present invention relates to ontology modeling and situational awareness method and system for intelligent food storage management, and more specifically, to the storage by applying sensing information, storage operation information, food storage information, food attribute information to inference rules The present invention relates to a food condition monitoring system and method for calculating food corruption, fresh grade, and freshness retention period.
국민의 생활수준이 높아짐에 따라 단순한 식품이 아니라 건강, 청정 식품에 대한 관심이 높아지고 있다. 그에 따라 식품 자체의 안정성, 유통과정의 투명성에 대해 관심과 요구가 커지고 있다. 현재 전국적으로 교통 인프라와 유통망의 발달로 빠른 식품을 빠르게 구매할 수 있게 되었다.As the standard of living of the people rises, interest in health and clean food is increasing, not just food. Accordingly, there is a growing interest and demand for the stability of the food itself and the transparency of the distribution process. Nowadays, with the development of transportation infrastructure and distribution network, fast food can be purchased quickly.
일반적으로 저장고란 곡물 등 농산물을 저장하기 위한 시설로 외기와의 차단성이 양호한 저장용 건물 또는 창고를 의미한다. 이러한 저장고는 곡물 등이 저장됨에 따라 온도 및 습도의 조절이 중요하다. 이를 위해 저장고에는 온도 센서와 습도 센서와 같은 감지센서와 저장고의 환경상태를 조절하기 위한 온풍기, 냉풍기 및 제습기와 환경상태 조절 장치들이 구비될 수 있다. Generally, a storage room is a facility for storing agricultural products such as grain, and means a storage building or a warehouse having good shielding from outside air. In such a storage, it is important to control temperature and humidity as grains and the like are stored. To this end, the reservoir may be equipped with a sensing sensor such as a temperature sensor and a humidity sensor, and a warm air fan, a cold fan, a dehumidifier, and an environmental condition adjusting device for adjusting the environmental condition of the reservoir.
그 뿐만 아니라, 저장고를 최적의 상태로 유지하기 위해 감지센서로부터 제공되는 정보를 이용하여 환경상태 조절 장지를 제어하기 위한 제어시스템이 마련된다.In addition, a control system is provided for controlling the environmental conditioning device using information provided from the sensor in order to keep the reservoir in an optimal state.
또한 종래에는 온도뿐 아니라 습도가 조절될 수 있고 원격 감시와 원격 제어가 가능하도록 하는 저온 저장고의 온도 및 습도의 감시와 제어를 위한 방법 및 장치(공개특허공보 10-2006-0017969호, 2006년02월 23일)가 출원된 바 있다.Also, conventionally, a method and apparatus for monitoring and controlling temperature and humidity of a cold storage, which can control not only temperature but also humidity, and enable remote monitoring and remote control (Publication Patent Publication No. 10-2006-0017969, 200602 March 23).
종래 저장고의 온도 및 습도의 감시와 제어를 위한 방법 및 장치는 도 1에 도시된 바와 같이 저장고의 현재 온도를 감지하는 단계, 저장고의 현재 습도를 감지하는 단계, 상기 현재 온도와 미리 설정된 최적 온도를 비교하고 상기 현재 온도가 상기 최적 온도에 도달할 때까지 상기 저온저장고의 온도를 조절하는 단계, 상기 현재 습도와 미리 설정된 최적 습도를 비교하고 상기 현재 습도가 상기최적 습도에 도달할 때까지 상기 저온저장고의 습도를 조절하는 단계를 포함하고 있다.The method and apparatus for monitoring and controlling the temperature and humidity of the conventional storage, as shown in Figure 1, the step of detecting the current temperature of the storage, the current humidity of the storage, the present temperature and the predetermined optimum temperature Comparing and adjusting the temperature of the cold storage until the current temperature reaches the optimum temperature, comparing the current humidity with a preset optimal humidity and the cold storage until the current humidity reaches the optimum humidity. It includes controlling the humidity of the.
그러나 종래 저온 온도 및 습도의 감시와 제어를 위한 방법 및 장치는 현재 온도와 습도를 감지하고 미리 설정된 최적 온도와 비교하여 저장고에 식품이 입고 또는 출고되는 운영정보와 관계없이 상기 저온저장고의 온도 및 습도를 조절하기 때문에 저장고에서 불필요한 온도 및 습도 조절이 발생할 수 있는 문제점이 있다.However, the conventional method and apparatus for monitoring and controlling low temperature temperature and humidity detect the current temperature and humidity and compare the temperature and humidity of the cold storage regardless of the operational information that the food is put into or out of the storage compared to the preset optimal temperature. Since there is a problem that unnecessary temperature and humidity control may occur in the storage.
즉, 종래 저온 온도 및 습도의 감시와 제어를 위한 방법 및 장치는 한 순간에 획득된 센싱 값이나 축적된 센싱 값을 기반으로 환경상태 조절 장치의 제어 여부를 추론하는 상황인지 미들웨어나 추론 시스템이기 때문에 실제 상황에 따른 적절한 조치가 이루어지지 않을 수 있는 문제점이 있다.That is, the method and apparatus for monitoring and controlling the low temperature and humidity of the related art are middleware or reasoning system that infers whether the environmental condition control device is inferred based on the sensing value or the accumulated sensing value at a moment. There is a problem that may not take appropriate action depending on the actual situation.
또한 종래에는 에틸렌 농도와 이산화탄소의 농도를 이용한 식품의 신선도 유지방법 및 장치(국내공개특허 제2005-0040259호, 2005년 5월 3일)가 출원된바 있다. In addition, the conventional method and device for maintaining the freshness of food using the concentration of ethylene and carbon dioxide (Korean Patent Publication No. 2005-0040259, May 3, 2005) has been filed.
종래 식품의 신선도 유지방법 및 그 장치는 도 2에 도시한 바와 같이, 과일, 채소 등의 농산물이 저장된 저장공간에서 저장된 농산물의 신선도를 유지시키도록, 상기 농산물에서 나오는 에틸렌(C2H4)과 수분을 포함하는 공기를 이산화티탄(TiO2) 광촉매 필터(42)를 통과시키면서 자외선 발생램프(44)에 의해 근자외선을 쬐어, 상기 에틸렌(C2H4)을 화학식 C2H4 + 4H2O →2CO2 + 6H2 에 따라 광산화 분해하여, 저장공간의 에틸렌 양을 줄이고 이산화탄소 량을 늘림에 의해 농산물의 신선도를 유지시키므로, 농산물을 신선하게 장기간 보관하여 제품의 가치를 높이는 효과가 있다.As shown in FIG. 2, a method and a device for maintaining freshness of a conventional food include ethylene (C2H4) and water from the agricultural products to maintain the freshness of the agricultural products stored in a storage space in which agricultural products such as fruits and vegetables are stored. While passing through the titanium dioxide (TiO 2) photocatalyst filter 42, the air is exposed to ultraviolet rays by an ultraviolet ray generating lamp 44, and the ethylene (C 2 H 4) is photooxidized and stored according to the formula C 2 H 4 + 4 H 2 O → 2 CO 2 + 6 H 2. By maintaining the freshness of agricultural products by reducing the amount of ethylene and increasing the amount of carbon dioxide in the space, there is an effect to increase the value of the product by storing fresh produce for a long time.
그런데, 종래의 방법 및 장치를 이용하면, 식품의 신선도를 유지할 수 있을 뿐, 식품의 부패 여부를 판단할 수 없는 문제점이 있었다. 또한, 실제상황을 고려한 에틸렌 농도, 온도, 습도, 이산화탄소 농도의 변화를 감시할 수 없는 문제점이 있었다. 더 나아가, 실제 보관 식품 상태를 고려한 식품의 신선도 및 부패정도를 판단할 수 없는 문제가 있었다.However, using the conventional method and apparatus, there is a problem that can not only determine whether the food is corrupt, but also maintain the freshness of the food. In addition, there was a problem that can not monitor the change in ethylene concentration, temperature, humidity, carbon dioxide concentration in consideration of the actual situation. Furthermore, there was a problem that can not determine the freshness and degree of corruption of the food in consideration of the actual stored food conditions.
본 발명이 해결하려는 과제는 저장공간의 에틸렌, 습도, 온도, 이산화탄소의 정보를 이용하여 식품의 신선등급, 신선 유지 기간 및 부패 여부를 제공하는 방법 및 시스템을 제공하는데 있다. The problem to be solved by the present invention is to provide a method and system for providing a fresh grade of food, the fresh maintenance period and whether or not corruption by using information of ethylene, humidity, temperature, carbon dioxide of the storage space.
본 발명이 해결하려는 다른 과제는 실제상황을 고려한 에틸렌 농도, 습도, 온도, 이산화탄소 농도 등을 측정하여 식품의 신선등급, 신선 유지 기간 및 부패 여부를 감시하는 방법 및 시스템을 제공하는데 있다. Another problem to be solved by the present invention is to provide a method and system for monitoring the freshness grade, freshness maintenance period and corruption of food by measuring ethylene concentration, humidity, temperature, carbon dioxide concentration, etc. in consideration of the actual situation.
본 발명이 해결하려는 또 다른 과제는 실제 보관 식품 상태를 고려하여 식품의 신선등급, 신선 유지 기간 및 부패 정도를 판단하는 방법 및 시스템을 제공하는데 있다.Another problem to be solved by the present invention is to provide a method and system for determining the fresh grade, the fresh maintenance period and the degree of decay in consideration of the actual stored food state.
본 발명의 식품 상태 감시 방법의 일 측면은 식품 저장고 내부에 위치한 센서들로부터 센싱 정보를 획득하는 센싱 정보 획득 단계; DB로부터 식품의 식품 보관 정보를 획득하는 식품 보관 정보 획득 단계; 식품 저장고의 저장고 운영 정보를 획득하는 저장고 운영 정보 획득 단계; 및 상기 센싱 정보, 상기 식품 보관 정보, 및 상기 저장고 운영 정보를 미리 작성된 추론 규칙에 적용하여, 식품 저장고의 상황을 추론함으로써, 보관 식품 각각의 식품 부패 여부, 신선등급 및 신선 유지 기간을 산출하는 식품 상태 출력 단계;를 포함한다. One aspect of the food condition monitoring method of the present invention includes a sensing information acquisition step of obtaining sensing information from sensors located inside the food storage; Food storage information obtaining step of obtaining food storage information of the food from the DB; A storage operation information obtaining step of obtaining storage operation information of the food storage; And calculating the food corruption status, freshness grade, and freshness period of each stored food by inferring the state of the food storage by applying the sensing information, the food storage information, and the storage operation information to a pre-written inference rule. A status output step.
여기서, 상기 식품 상태 출력 단계 전, 상기 DB로부터 보관 식품의 속성정보를 획득하는 식품 속성 정보 획득 단계를 더 포함하며, 상기 식품 상태 출력 단계는 상기 속성정보를 상기 추론 규칙에 추가 적용하여 식품 저장고의 상황을 추론함으로써, 보관 식품 각각의 식품 부패 여부, 신선등급 및 신선 유지 기간을 산출함을 특징으로 한다.Here, before the food state output step, the food property information obtaining step of obtaining the attribution information of the stored food from the DB further comprises, wherein the food state output step further applies the attribution information to the inference rule of the food storage; By inferring the situation, each of the stored foods is characterized by calculating whether the food is decaying, freshness grade, and freshness period.
여기서, 상기 센싱 정보는 에틸렌 농도, 이산화탄소 농도, 온도, 습도 중 적어도 하나이며, 상기 식품 보관 정보는 식품의 에틸렌 농도 임계값, 이산화탄소 농도 임계값, 온도 임계값, 습도 임계값 중 적어도 하나이며, 상기 저장고 운영 정보는 저장고의 문 개폐 정보이며, 상기 속성 정보는 보관 식품의 이름 및 보관 식품의 원산지, 저장고 입고전 이력 정보 중 적어도 하나임을 특징으로 한다. Here, the sensing information is at least one of ethylene concentration, carbon dioxide concentration, temperature, humidity, the food storage information is at least one of the ethylene concentration threshold, carbon dioxide concentration threshold, temperature threshold, humidity threshold of the food, Storage operation information is door opening and closing information of the storage, characterized in that the attribute information is at least one of the name of the stored food, the origin of the stored food, the history information before storage.
본 발명의 식품 상태 감시 시스템의 일 측면은 식품저장고의 내부 상황을 감지하는 센서; 저장고 운영 정보 및 식품 보관 정보를 저장하는 DB; 상기 센서로 부터 센싱 정보를 전송받아 저장하는 센싱 정보 획득부; 상기 DB로부터 식품 보관 정보를 전송받아 저장하는 식품 보관 정보 획득부; 상기 DB로부터 저장고 운영 정보를 전송받아 저장하는 저장고 운영 정보 획득부; 및 상기 센싱 정보 획득부로부터 상기 센싱 정보를 전달받고, 상기 식품 보관 정보 획득부로부터 상기 식품 보관 정보를 전달받고, 상기 저장고 운영 정보 획득부로부터 상기 저장고 운영 정보를 전달받고, 상기 센싱 정보, 상기 식품 보관 상태 정보와 상기 저장고 운영 정보를 작성된 추론 규칙에 적용하여 상황을 추론함으로서, 보관 식품의 부패 여부 및 신선도, 신선 유지 기간을 산출하는 제어부;를 포함한다.One aspect of the food condition monitoring system of the present invention is a sensor for detecting the internal situation of the food storage; DB for storing storage operation information and food storage information; A sensing information acquisition unit for receiving and storing sensing information from the sensor; Food storage information acquisition unit for receiving and storing food storage information from the DB; A storage operation information acquisition unit for receiving and storing storage operation information from the DB; And receiving the sensing information from the sensing information acquisition unit, receiving the food storage information from the food storage information acquisition unit, receiving the storage operation information from the storage operation information acquisition unit, and receiving the sensing information and the food. And a control unit that calculates whether or not the stored food is decayed, freshness, and fresh keeping period by applying the storage state information and the storage operation information to the prepared inference rule.
여기서, 상기 DB는 보관 식품의 속성 정보를 저장함을 특징으로 하며, 상기 속성 정보를 상기 DB로부터 획득하는 식품 속성 정보 획득부를 더 포함하며, 상기 제어부는 상기 식품 속성 정보 획득부로부터 상기 속성정보를 전달받고, 상기 센싱 정보, 상기 식품 보관 정보, 상기 저장고 운영 정보와 상기 속성 정보를 상기 추론 규칙에 적용하여 상황을 추론함으로서, 보관 식품의 부패 여부 및 신선도, 신선 유지 기간을 산출함을 특징으로 한다.Here, the DB is characterized in that to store the attribute information of the stored food, further comprises a food attribute information acquisition unit for obtaining the attribute information from the DB, the control unit transfers the attribute information from the food attribute information acquisition unit And receiving the sensing information, the food storage information, the storage operation information, and the attribute information to the inference rule to infer a situation, thereby calculating whether the stored food is corrupt, freshness, and freshness retention period.
여기서, 상기 센싱 정보는 에틸렌 농도, 이산화탄소 농도, 온도, 습도 중 적어도 하나이며, 상기 식품 보관 정보는 식품의 에틸렌 농도 임계값, 이산화탄소 농도 임계값, 온도 임계값, 습도 임계값 중 적어도 하나이며, 상기 저장고 운영 정보는 저장고의 문 개폐 정보이며, 상기 속성 정보는 속성 정보는 보관 식품의 이름 및 보관 식품의 원산지, 저장고 입고 전, 이력 정보 중 적어도 하나임을 특징으로 한다.Here, the sensing information is at least one of ethylene concentration, carbon dioxide concentration, temperature, humidity, the food storage information is at least one of the ethylene concentration threshold, carbon dioxide concentration threshold, temperature threshold, humidity threshold of the food, The storage operation information is door opening and closing information of the storage, and the attribute information is characterized in that the attribute information is at least one of the name of the stored food, the origin of the stored food, before the storage of the storage, and history information.
본 발명에 따른 식품 상태 감시 시스템 및 방법에 의하면, 저장공간의 에틸렌, 습도, 온도, 이산화탄소의 정보를 이용하여 식품의 신선등급, 신선 유지 기간 및 부패 여부를 제공할 수 있다. According to the food condition monitoring system and method according to the present invention, it is possible to provide the freshness of the food, the freshness maintenance period and whether or not the food using the information of ethylene, humidity, temperature, carbon dioxide of the storage space.
또한, 본 발명에 따른 식품 상태 감시 시스템 및 방법에 의하면, 실제상황을 고려한 에틸렌 농도, 습도, 온도, 이산화탄소 농도 등을 측정하여 식품의 신선등급, 신선 유지 기간 및 부패 여부를 제공할 수 있다.In addition, according to the food condition monitoring system and method according to the present invention, by measuring the ethylene concentration, humidity, temperature, carbon dioxide concentration, etc. in consideration of the actual situation, it is possible to provide a fresh grade, a fresh maintenance period and whether or not the corruption of the food.
더 나아가, 본 발명에 따른 식품 상태 감시 시스템 및 방법에 의하면, 실제 보관 식품 상태를 고려하여 식품의 신선등급, 신선 유지 기간 및 부패 정도를 제공할 수 있다.Furthermore, according to the food condition monitoring system and method according to the present invention, it is possible to provide the fresh grade, the freshness maintenance period and the degree of decay in consideration of the actual stored food condition.
도 1은 종래 저장고의 온도 및 습도의 감시와 제어를 위한 장치를 도시하고 있으며,1 shows an apparatus for monitoring and controlling the temperature and humidity of a conventional storage,
도 2는 종래 식품 신선도를 유지하는 방안을 도시한 도면이며,2 is a view showing a method for maintaining a conventional food freshness,
도 3은 요소들의 OWL 클래스 구성도이며,3 is an OWL class diagram of elements,
도 4는 본 발명의 일실시 예에 따른 온톨로지 추론을 이용한 식품 상태 감시 시스템을 도시한 블록도이며,4 is a block diagram illustrating a food condition monitoring system using ontology inference according to an embodiment of the present invention.
도 5는 본 발명의 일실시 예에 따른 온톨로지 추론을 이용한 식품 상태 감시 방법을 도시한 흐름도이다.5 is a flowchart illustrating a method for monitoring food status using ontology inference according to an embodiment of the present invention.
전술한, 그리고 추가적인 본 발명의 양상들은 첨부된 도면을 참조하여 설명되는 바람직한 실시 예들을 통하여 더욱 명백해질 것이다. 이하에서는 본 발명의 이러한 실시 예를 통해 당업자가 용이하게 이해하고 재현할 수 있도록 상세히 설명하기로 한다.The foregoing and further aspects of the present invention will become more apparent through the preferred embodiments described with reference to the accompanying drawings. Hereinafter will be described in detail to enable those skilled in the art to easily understand and reproduce through this embodiment of the present invention.
이하에서는 먼저 본 발명에서 사용하는 용어에 대해 알아보기로 한다.Hereinafter, first, the terms used in the present invention will be described.
상황 또는 환경 정보: 적용 분야에 따라 다양한 정의가 존재하나 컴퓨터 분야에서는 응용 시스템 운영 환경의 일부로서 응용 시스템이 감지할 수 있는 외부의 환경 정보를 의미한다. 상황 인지를 수행하기 위한 지능적 환경 구축을 위해서는 다양한 환경 정보를 수집하고, 정보를 바탕으로 상황을 추론할 수 있는 상황 추론 기술이 필요하다.Situation or environmental information: Various definitions exist depending on the application field, but in the computer field, it refers to external environmental information that an application system can detect as part of an application system operating environment. In order to construct an intelligent environment for performing situation awareness, situation inference technology is needed to collect various environmental information and infer the situation based on the information.
사용자와 응용 시스템간의 상호작용이 고려된 사람, 장소, 물체들을 실체(Entity)라고 하는데, 환경 정보(Context)는 어떤 실체의 상황을 특정할 수 있는 정보들을 의미한다.People, places, and objects that are considered to interact with a user and an application system are called entities. Environment information refers to information that can specify a situation of an entity.
상황 인지 기술: 식품 저장고를 위한 상황인지 미들웨어는 환경 정보를 이용하여 식품 관리에 필요한 상황을 추론하고 그 결과를 사용자에게 알려준다. 본 발명에서는 온톨로지를 이용하여 환경 정보를 정의하며, 이것을 컴퓨터가 활용할 수 있는 팩트(fact)로 변환한다. 팩트를 바탕으로 추론하기 위한 규칙을 활용한다.Context-aware technology: Context-aware middleware for food storage uses environmental information to infer the circumstances necessary for food management and inform the user of the results. In the present invention, the ontology is used to define the environment information, which is converted into a fact that can be utilized by a computer. Use rules to infer based on facts.
온톨로지는 공유된 개념화(shared conceptualization)에 대한 정형화되고 명시적인 명제(formal and explicit specitication)이다. 온톨로지는 단어와 관계들로 구성된 일종의 사전으로서 생각할 수 있으며, 그 속에는 특정 도메인에 관련된 단어들이 계층적으로 표현되어 있고, 추가적으로 이를 확장할 수 있는 추론 규칙이 포함되어 있어, 웹 기반의 지식 처리나 응용 프로그램 사이의 지식 공유, 재사용 등이 가능토록 되어 있다.Ontologies are formal and explicit specitic representations of shared conceptualization. Ontology can be thought of as a kind of dictionary composed of words and relationships, including words related to specific domains hierarchically, and additionally inferring rules that can be extended to include web-based knowledge processing or application. Knowledge sharing and reuse among programs are possible.
OWL은 웹에서 정보를 표현하고, 응용에서 직접 내용을 처리할 수 있도록 설계된 언어이다 OWL은 기계가 처리할 수 있는 풍부한 어휘와 형식적 의미를 제공한다. SWRL은 OWL에 규칙 기술 언어를 추가한 구조를 가지며, OWL에서 표현하기 복잡한 규칙을 정의할 수 있는 언어이다. OWL is a language designed to represent information on the Web and to process content directly in applications. OWL provides a rich vocabulary and formal meaning that can be processed by machines. SWRL has a structure that adds a rule description language to OWL, and is a language that can define rules that are complicated to express in OWL.
일반적인 환경에서 상황인지를 위해서는 환경 정보를 모델링한 온톨로지를 구성해야 한다. 그리고 상황인지 미들웨어는 다양한 방법을 통해 상황 정보를 획득, 온톨로지에 대입하여 사실을 획득하고 규칙 기반으로 추론 엔진이 추론을 수행한다. 추론 결과는 상위 저장고 관리 시스템으로 전달된다.In order to recognize the situation in a general environment, an ontology modeling environment information should be constructed. In addition, context-aware middleware acquires facts by assigning context information to ontology through various methods, and the inference engine performs inference based on rules. Inference results are forwarded to the upper repository management system.
상황인지 미들웨어를 위한 온톨로지를 설계하기 위해 가장 선행되어야 하는 작업은 저온 저장고를 구성하는 환경 요소들을 정의하는 것이다. 저온 저장고를 구성하는 요소는 저장고, 센서, 보관에 대한 기준, 보관 상품, 보관 정보 등이 있다.The first task to design an ontology for context-aware middleware is to define the environmental elements that make up the cold store. The elements that make up a cold store include a store, a sensor, a standard for storage, a storage product, and storage information.
도 3은 본 발명의 일실시 예에 따른 각 요소들을 클래스로 표현하여 OWL의 계층구조로 표현한 것이다. 구성요소들 간의 관계는 OWL의 속성을 정의하여 표현할 수 있다. OWL에서 속성을 표현할 때 객체인지, 데이터인지를 구분해서 정의할 수 있으며. 각각 객체 자산(Object Property)과 데이터 자산(Data Property)으로 표현할 수 있다. 클래스를 정의했다면 이후에는 인디비주얼을 정의한다.3 is a hierarchical structure of OWL by representing each element as a class according to an embodiment of the present invention. The relationship between the components can be expressed by defining the attributes of the OWL. When expressing properties in OWL, you can define whether it is an object or data. Each can be expressed as an object property and a data property. Once you have defined a class, you define an individual.
온톨로지를 이용하여 추론하기 위해서는 온톨로지의 클래스나 인디비주얼, 자산들 간의 관계를 통해 규칙을 정의한 SWRL이 필요하다.In order to infer using ontology, SWRL that defines rules through relationships between ontology classes, visuals, and assets is required.
식품 저장고의 상황인지를 위해서는 환경 정보의 실제 값을 획득해야 한다. 식품 저장고의 환경 정보를 획득할 정보원은 센서 정보와 저장고 관리 정보이다. To be aware of the situation in food storage, the actual value of environmental information must be obtained. Information sources for obtaining the environmental information of the food storage are sensor information and storage management information.
센싱 정보는 식품 저장고에 부착되어 있는 센서의 종류, 위치, 센싱 값 등의 정보를 의미한다. 구현된 온톨로지의 센서 인디비주얼에 값을 대입하기 위해 센서에 ID를 부여하고, 온톨로지의 속성에 대응시켜 상황 추론을 수행한다.Sensing information refers to information such as the type, location, sensing value of the sensor attached to the food storage. In order to assign a value to the sensor visual of the implemented ontology, ID is assigned to the sensor, and situation inference is performed in correspondence with the attribute of the ontology.
본 발명과 관련하여 운용 정보는 모두 데이터베이스에 저장되어 있다. 운영 정보는 전산으로 관리되며, 전산 정보를 획득하는 과정은 데이터베이스로부터 정보를 획득하는 과정과 동일하다. 획득한 운영 정보에는 ID가 부여되어 개별적으로 매핑 가능하게 표시된다.In connection with the present invention, all the operational information is stored in a database. Operational information is computerized, and the process of acquiring computer information is the same as the process of acquiring information from a database. The obtained operational information is assigned an ID and displayed to be individually mapped.
센싱 값과 저장고 운영 정보를 제공하는 정보원이 정의되었고, 각각 고유한 ID를 갖고 있다. ID별로 하나의 특정값을 갖고 있기 때문에 이 ID를 인디비주얼값으로 매핑시키면 도메인 온톨로지의 환경 정보를 채울 수 있다. 각 속성은 개별적으로 적합한 형태의 범위를 가지며, 구현된 인디비주얼은 정보원 ID에 해당하는 센싱 값 혹은 운영 정보를 범위의 값으로 갖는다. 단 하나의 센서나 운영 정보가 이중적인 값을 가질 수 없다.Sources that provide sensing values and storage operation information have been defined, each with a unique ID. Since each ID has one specific value, mapping this ID to an individual value can populate the domain ontology's environment information. Each attribute has a range of individually appropriate forms, and the implemented individual has a sensing value or operational information corresponding to the source ID as a range value. No single sensor or operational information can have a double value.
상황인지 미들웨어의 핵심 기능 모듈은 센싱 정보와 운영 정보를 획득하는 모듈과 매핑 모듈, 상황 추론 모듈이다. 센싱 정보 및 운영 정보 획득 모듈은 센서에서 센싱 정보가 획득되면 운영 정보를 수집하여 상황 추론을 시작한다. 온톨로지 매핑 모듈은 사용 중인 OWL 온톨로지 모델에 데이터를 대입시키는 모듈이다. 이 모듈은 ID 분류에 따라 인디비주얼에 값을 대입시키는 기능을 수행한다.The core functional modules of context aware middleware are modules for obtaining sensing and operational information, mapping modules, and context inference modules. The sensing information and operation information acquisition module collects the operation information when the sensing information is acquired from the sensor and starts the reasoning. The ontology mapping module is a module that assigns data to the OWL ontology model in use. This module performs the function of assigning a value to an individual according to ID classification.
도 4는 본 발명에 따른 온톨로지 추론을 이용한 식품 상태 감시 시스템을 나타낸 기능블록도이다. 이하 도 4를 이용하여 본 발명의 일실시 예에 따른 온톨로지 추론을 이용한 식품 상태 감시 시스템에 대해 상세하게 알아보기로 한다.4 is a functional block diagram illustrating a food condition monitoring system using ontology inference according to the present invention. Hereinafter, the food condition monitoring system using the ontology inference according to an embodiment of the present invention will be described in detail with reference to FIG. 4.
도 4에 의하면, 식품 상태 감시 시스템은 식품 상태 감시 장치와 데이터베이스, 복수의 센서를 포함한다. 식품 상태 감시 장치는 식품 보관 정보 획득부, 센싱 정보 획득부, 식품 속성 정보 획득부, 저장고 운영 정보 획득부, 제어부를 포함한다. 물론 상술한 구성 이외에 다른 구성이 식품 상태 감시 시스템 또는 식품 상태 감시 장치에 포함될 수 있다.According to FIG. 4, the food condition monitoring system includes a food condition monitoring device, a database, and a plurality of sensors. The food condition monitoring apparatus includes a food storage information acquisition unit, a sensing information acquisition unit, a food attribute information acquisition unit, a storage management information acquisition unit, and a control unit. Of course, in addition to the above-described configuration, other configurations may be included in the food condition monitoring system or the food condition monitoring device.
DB(100)에는 저장고 운영정보, 보관 식품의 속성 정보, 식품의 보관 정보 등이 저장된다.The DB 100 stores storage operation information, attribute information of stored food, storage information of food, and the like.
센서(200)들은 센싱 정보인 저장고 내부의 에틸렌 농도, 이산화탄소 농도, 온도, 습도와 같은 정보를 감지하고, 감지된 저장고 내부의 에틸렌 농도, 이산화탄소 농도, 온도, 습도의 정보를 식품 상태 감시 장치(300)로 전송한다. 도 4는 온도 센서, 습도 센서, 에틸렌 센서, 이산화탄소 센서만을 도시하고 있으나, 이에 한정되는 것은 아니다. 즉, 저장고 내부의 환경 정보를 센싱할 수 있는 센서라면 본 발명에 포함될 수 있다.The sensor 200 detects information such as ethylene concentration, carbon dioxide concentration, temperature, and humidity in the storage, which is sensing information, and detects information on ethylene concentration, carbon dioxide concentration, temperature, and humidity in the detected storage, and the food condition monitoring device 300. To send). 4 illustrates only a temperature sensor, a humidity sensor, an ethylene sensor, and a carbon dioxide sensor, but is not limited thereto. That is, any sensor capable of sensing environmental information in the storage can be included in the present invention.
식품 상태 감시 장치(300)는 저장고 운영 정보 획득부(340), 센싱 정보 획득부(320), 식품 속성 정보 획득부(330), 식품 보관 정보 획득부(310), 제어부(350)를 포함할 수 있다. The food condition monitoring apparatus 300 may include a storage operation information acquisition unit 340, a sensing information acquisition unit 320, a food attribute information acquisition unit 330, a food storage information acquisition unit 310, and a controller 350. Can be.
저장고 운영 정보 획득부(340), 식품 속성 정보 획득부(330), 식품 보관 정보 획득부(310)는 DB(100)로부터 저장고 운영 정보, 식품 속성 정보, 식품 보관 정보를 전송받는다. The storage operation information acquisition unit 340, the food attribute information acquisition unit 330, and the food storage information acquisition unit 310 receive storage operation information, food attribute information, and food storage information from the DB 100.
저장고 운영 정보는 저장고에 식품이 들어오는 시간, 저장고 문(door)의 개폐 시간, 횟수 등일 수 있다.The storage operation information may be a time at which food enters the storage, opening / closing time of the storage door, the number of times, and the like.
식품 속성 정보라함은 보관 식품의 이름, 보관 식품의 원산지 등일 수 있다.The food attribute information may be the name of the stored food, the origin of the stored food, or the like.
식품 보관 정보라함은 보관 식품의 신선함이 유지되는 온도 임계값, 습도 임계값, 에틸렌 농도 임계값, 이산화탄소 농도 임계값 등일 수 있다. The food storage information may be a temperature threshold, humidity threshold, ethylene concentration threshold, carbon dioxide concentration threshold, and the like, in which the freshness of the stored food is maintained.
센싱 정보 획득부(320)는 센서(200)로부터 센싱 정보를 전송받는다. The sensing information acquisition unit 320 receives the sensing information from the sensor 200.
제어부(350)는 센싱 정보, 식품 보관 정보, 저장고 운영 정보, 식품 속성 정보를 미리 작성된 추론 규칙에 적용하여, 식품 저장고의 상황을 추론함으로써, 보관 식품 각각의 부패 여부, 신선 등급 및 신선 유지 기간을 계산할 수 있다. 여기서, 제어부(350)는 미리 작성된 추론 규칙에 적용하여, 식품 저장고의 상황을 온톨로지 기반 추론한다. The control unit 350 applies sensing information, food storage information, storage management information, and food attribute information to pre-written inference rules, and infers the situation of the food storage, thereby determining whether each stored food is corrupt, fresh grade, and freshness period. Can be calculated Here, the controller 350 applies ontology inferences prepared in advance, and ontology-based inference of the situation of the food storage.
온톨로지 기반 추론은 센싱정보, 저장고 운영 정보, 식품 속성 정보, 식품 보관 정보 간의 관계를 온톨로지 언어로 정의하고, 정의된 관계를 통해 규칙을 생성하여 추론하는 것을 말한다. Ontology-based reasoning refers to defining relationships between sensing information, storage operation information, food attribute information, and food storage information in ontology language, and inferring by creating rules through the defined relationships.
온톨로지 언어에서 관계 및 추론규칙을 정의하기 위해서는 상술한 바와 같이 클래스, 인디비쥬얼, 프로포티를 정의해야 한다. 온톨로지 추론을 위한 관계 및 추론 규칙은 정의된 클래스, 인디비쥬얼, 프로포티를 이용하여 정의된다. 본 발명에 따른 식품 상태 감시 시스템에서는 저장고를 온톨로지의 클래스로 정의하고, 센싱 정보와 저장고 운영 정보, 식품 속성 정보, 식품 보관 정보를 각각 인디비쥬얼로 정의하여, 해당 값을 변수로 정의하여 하게 된다. In order to define relations and inference rules in ontology language, class, individual, and property must be defined as described above. Relationships and inference rules for ontology inference are defined using defined classes, individualities, and properties. In the food condition monitoring system according to the present invention, the storage is defined as a class of ontology, and sensing information, storage operation information, food attribute information, and food storage information are defined as individual, and the corresponding values are defined as variables.
좀더 자세히 설명하면, "저장고"는 클래스가 되고, 이 저장고의 한 종류인 "쌀 저장고"는 저장고 클래스의 보조 클래스이며, "김해 301번지 쌀 저장고"는 이 쌀 저장고의 인디비쥬얼이라 볼 수 있다. 또한 "센서(200)"는 클래스가 되고, "온도 센서(200)", "습도 센서(200)", "에틸렌 센서(200)", "이산화탄소 농도 센서(200)"는 센서(200)의 인디비쥬얼이 된다. 센싱 정보는 프로포티가 된다.In more detail, "Storage" becomes a class, and one type of "Storage" is a subclass of the Storage class, and "301 Gimhae Rice Storage" is an independent type of rice storage. In addition, the "sensor 200" is a class, "temperature sensor 200", "humidity sensor 200", "ethylene sensor 200", "carbon dioxide concentration sensor 200" of the sensor 200 Become independent. The sensing information becomes a property.
그리하여, 센싱 정보 인디비쥬얼의 변수와 식품 보관 정보 인디비쥬얼의 변수를 비교하고, 저장고 운영 정보 인디비쥬얼의 변수, 식품 속성 정보 인디비쥬얼의 변수를 참작하여, 저장고 환경을 추론하게 된다. Thus, the storage environment is inferred by comparing the variable of the sensing information individual with the variable of the food storage information individual, and taking into account the variable of the storage operation information individual and the variable of the food attribute information individual.
또한, 온톨로지 추론 과정에서는 이벤트가 발생하게 되는데, 이벤트 발생 여부는 온톨로지 언어인 DSML+OIL, OWL, Ontolingun 등으로 작성된 추론 규칙에 따를 수 있다. In addition, an event occurs during the ontology inference process, and whether or not the event occurs may be in accordance with an inference rule written in the ontology language DSML + OIL, OWL, Ontolingun, or the like.
상기에서 설명한 대로, 온톨로지 추론을 위한 관계를 온톨로지 언어로 정의하고, 정의된 관계를 바탕으로 SWRL(Semantic Web Rule Language)로 추론 규칙을 만들게 된다. 즉 각각의 클래스의 인디비쥬얼이 정의된 추론 규칙에 해당하는 값을 가지게 되면 온톨로지 추론을 수행하게 되는 것이다. As described above, the relationship for ontology inference is defined in the ontology language, and the inference rule is created in the semantic web rule language (SWRL) based on the defined relationship. That is, when each class's individual information has a value corresponding to a defined inference rule, ontology inference is performed.
제어부(350)는 추론 규칙에 센서(200)로부터의 센싱 정보, DB(100)로 부터의 저장고 운영 정보, 식품 속성 정보, 식품 보관 정보를 할당하여, 저장고의 상황을 추론하고, 추론함으로써, 식품의 부패여부, 신선 등급 및 신선 유지 기간을 계산 할 수 있다. The control unit 350 allocates the sensing information from the sensor 200, the storage operation information from the DB 100, the food attribute information, and the food storage information to the inference rule, and infers and deduces the situation of the storage, thereby inducing food. The decay status, freshness grade and freshness period can be calculated.
도 5는 본 발명에 따른 온톨로지 추론을 이용한 식품 상태 감시 방법을 나타낸 흐름도이다. 이하 도 5를 이용하여 본 발명의 일실시 예에 따른 온톨로지 추론을 이용한 식품 상태 감시 방법에 대해 상세하게 알아보기로 한다.5 is a flow chart illustrating a food condition monitoring method using ontology inference according to the present invention. Hereinafter, a method for monitoring food status using ontology inference according to an embodiment of the present invention will be described in detail with reference to FIG. 5.
도 5에 도시된 바와 같이 본 발명의 일 실시예에 따른 온톨로지 추론을 이용한 식품 상태 감시 방법은 센싱 정보 획득 단계(S310), 저장고 운영 정보 획득 단계(S330), 속성 정보 획득 단계(S340), 식품 보관 정보 획득 단계(S320), 식품 상태 출력 단계를 포함할 수 있다. As shown in Figure 5 food monitoring method using ontology inference according to an embodiment of the present invention, the sensing information acquisition step (S310), storage operation information acquisition step (S330), attribute information acquisition step (S340), food Storage information acquisition step (S320), may include a food state output step.
센싱 정보 획득 단계(S310)에서 식품 상태 감시 장치(300)는 저장고 내부에 위치한 센서(200)로부터 센싱정보인 온도, 습도, 이산화탄소 농도, 에틸렌 농도 정보등을 획득할 수 있다. 센서(200)들은 온도, 습도, 에틸렌 농도, 이산화탄소 농도등을 감지하여 식품 상태 감시 장치(300)에 전달한다. In the sensing information acquisition step (S310), the food condition monitoring apparatus 300 may acquire temperature, humidity, carbon dioxide concentration, and ethylene concentration information, which is sensing information, from the sensor 200 located in the storage. The sensors 200 detect temperature, humidity, ethylene concentration, carbon dioxide concentration, and the like, and transmit them to the food condition monitoring apparatus 300.
저장고 운영 정보 획득 단계(S330)에서 식품 상태 감시 장치(300)는 DB(100)로부터 저장고 운영 정보를 획득 할 수 있다. 여기서 저장고 운영 정보는 저장고에 식품이 들어오는 시간, 문이 개페되는 시간, 횟수 등의 정보 일 수 있다. In operation S330 of obtaining storage operation information, the food condition monitoring apparatus 300 may obtain storage operation information from the DB 100. Here, the storage operation information may be information such as the time the food enters the storage, the time the door is opened, the number of times.
속성 정보 획득 단계(S340)에서 식품 상태 감시 장치(300)는 DB(100)로부터 식품 속성 정보를 획득 할 수 있다. 여기서 식품 속성 정보는 저장고에 들어온 식품의 이름, 원산지, 식품의 입고 당시, 신선 상태 등 일 수 있다. In operation S340, the food state monitoring apparatus 300 may obtain food attribute information from the DB 100. Here, the food attribute information may be the name of the food entered in the storage, the country of origin, the time of receipt of the food, fresh state, and the like.
식품 보관 정보 획득 단계(S320)에서 식품 상태 감시 장치(300)는 DB(100)로부터 식품 보관 정보를 획득 할 수 있다. 여기서, 식품 보관 정보는 식품의 에틸렌 농도 임계값, 이산화탄소 농도 임계값, 온도 임계값, 습도 임계값 등일 수 있다. In the food storage information obtaining step (S320), the food condition monitoring apparatus 300 may obtain food storage information from the DB 100. Here, the food storage information may be an ethylene concentration threshold, a carbon dioxide concentration threshold, a temperature threshold, a humidity threshold, and the like of the food.
식품 상태 출력 단계(S350)는 센서(200)와 DB(100)로부터 획득된 센싱정보, 저장고 운영 정보, 속성 정보, 식품 보관 정보를 온톨로지 추론 규칙에 적용하여 식품의 부패여부, 신선등급과 신선 유지 기간을 계산한다. Food state output step (S350) by applying the sensing information, storage operation information, attribute information, food storage information obtained from the sensor 200 and DB 100 to the ontology inference rules, whether the food is corrupt, fresh grade and freshness Calculate the duration.
여기서, 온톨로지 기반 추론을 위해서 센서(200), 저장고, 식품을 클래스로 정의하고, 센싱 정보, 저장고 운영 정보, 식품 속성 정보, 식품 보관 정보를 인디비쥬얼로 정의한다. 또한, 각각의 클래스 간의 관계와 변수의 할당에 따른 이벤트 발생 등에 대해서 추론 규칙을 정의한다. Here, the sensor 200, storage, and food are defined as classes for ontology-based inference, and sensing information, storage operation information, food attribute information, and food storage information are defined as individual. In addition, inference rules are defined for relations between classes and event occurrences according to variable assignments.
식품 상태 출력 단계(S350)에서 식품 상태 감지 장치는 전송된 센싱 정보, 저장고 운영 정보, 식품 보관 정보, 식품 속성 정보를 추론 규칙에 할당하고, 온톨로지 추론 결과, 추론된 결과인 이벤트 발생 여부 및 이벤트 발생 종류를 이용하여 보관 식품의 부패 여부, 신선 등급, 신선 유지 기간을 계산하게 된다. In the food state output step (S350), the food state detecting apparatus allocates the transmitted sensing information, storage operation information, food storage information, and food attribute information to the inference rule, and ontology inference result, whether the event that is the inferred result occurs and the event occurrence. Types are used to calculate whether or not the food is decayed, freshness grade, and freshness retention period.
본 발명은 도면에 도시된 일실시 예를 참고로 설명되었으나, 이는 예시적인 것에 불과하며, 본 기술 분야의 통상의 지식을 가진 자라면 이로부터 다양한 변형 및 균등한 타 실시예가 가능하다는 점을 이해할 것이다.Although the present invention has been described with reference to one embodiment shown in the drawings, this is merely exemplary, and those skilled in the art will understand that various modifications and equivalent other embodiments are possible therefrom. .
[부호의 설명][Description of the code]
100: DB100: DB
200: 센서200: sensor
300: 식품상태 감시 장치300: food condition monitoring device

Claims (7)

  1. 식품 저장고 내부에 위치한 센서들로부터 센싱 정보를 획득하는 센싱 정보 획득 단계;Sensing information obtaining step of obtaining sensing information from sensors located inside the food storage;
    DB로부터 식품의 식품 보관 정보를 획득하는 식품 보관 정보 획득 단계;Food storage information obtaining step of obtaining food storage information of the food from the DB;
    상기 식품 저장고의 저장고 운영 정보를 획득하는 저장고 운영 정보 획득 단계; 및A storage operation information acquisition step of acquiring storage operation information of the food storage; And
    상기 센싱 정보, 상기 식품 보관 정보, 및 상기 저장고 운영 정보를 미리 작성된 추론 규칙에 적용하여, 상기 식품 저장고의 상황을 추론하여 보관 식품 각각의 식품 부패 여부, 신선등급 및 신선 유지 기간을 산출하는 식품 상태 출력 단계;를 포함하는 온톨로지 추론을 이용한 식품 상태 감시 방법.Food status that calculates whether the food decay, fresh grade and freshness of each stored food by inferring the situation of the food storage by applying the sensing information, the food storage information, and the storage operation information to a pre-written inference rule Food status monitoring method using an ontology inference comprising the output step.
  2. 제1항에 있어서, The method of claim 1,
    상기 저장고 운영 정보 획득 단계 이후에 상기 DB로부터 보관 식품의 속성정보를 획득하는 식품 속성 정보 획득 단계를 더 포함하며, After the step of acquiring the storage operation information further comprises the step of obtaining food attribute information to obtain the attribute information of the stored food from the DB,
    상기 식품 상태 출력 단계는 상기 속성정보를 상기 추론 규칙에 추가 적용하여 식품 저장고의 상황을 추론하여 보관 식품 각각의 식품 부패 여부, 신선등급 및 신선 유지 기간을 산출함을 특징으로 하는 온톨로지 추론을 이용한 식품 상태 감시 방법.In the food state output step, the attribute information is additionally applied to the inference rule to deduce the state of the food storage to calculate whether each food is decayed, fresh grade, and freshness retention period. Condition monitoring method.
  3. 제2항에 있어서, The method of claim 2,
    상기 센싱 정보는 에틸렌 농도, 이산화탄소 농도, 온도, 습도 중 적어도 하나이며, The sensing information is at least one of ethylene concentration, carbon dioxide concentration, temperature, humidity,
    상기 식품 보관 정보는 식품의 에틸렌 농도 임계값, 이산화탄소 농도 임계값, 온도 임계값, 습도 임계값 중 적어도 하나이며, The food storage information is at least one of ethylene concentration threshold, carbon dioxide concentration threshold, temperature threshold, humidity threshold of the food,
    상기 저장고 운영 정보는 저장고의 문 개폐 정보 및 저장고에 식품이 들어오는 시간 중 적어도 하나이며,The storage operation information is at least one of door opening and closing information of the storage and the time the food enters the storage,
    상기 속성 정보는 보관 식품의 이름 및 보관 식품의 원산지, 저장고 입고전 이력 정보 중 적어도 하나임을 특징으로 하는 온톨로지 추론을 이용한 식품 상태 감시 방법.The attribute information is a food state monitoring method using ontology inference, characterized in that at least one of the name of the stored food, the origin of the stored food, history information before storage.
  4. 식품저장고의 내부 상황을 감지하는 센서;A sensor for detecting an internal situation of the food storage;
    저장고 운영 정보 및 식품 보관 정보를 저장하는 DB;DB for storing storage operation information and food storage information;
    상기 센서로 부터 센싱 정보를 전송받아 저장하는 센싱 정보 획득부;A sensing information acquisition unit for receiving and storing sensing information from the sensor;
    상기 DB로부터 식품 보관 정보를 전송받아 저장하는 식품 보관 정보 획득부;Food storage information acquisition unit for receiving and storing food storage information from the DB;
    상기 DB로부터 저장고 운영 정보를 전송받아 저장하는 저장고 운영 정보 획득부; 및A storage operation information acquisition unit for receiving and storing storage operation information from the DB; And
    상기 센싱 정보 획득부로부터 상기 센싱 정보를 전달받고, 상기 식품 보관 정보 획득부로부터 상기 식품 보관 정보를 전달받고, 상기 저장고 운영 정보 획득부로부터 상기 저장고 운영 정보를 전달받고,Receiving the sensing information from the sensing information acquisition unit, receiving the food storage information from the food storage information acquisition unit, receiving the storage operation information from the storage operation information acquisition unit,
    상기 센싱 정보, 상기 식품 보관 상태 정보와 상기 저장고 운영 정보를 작성된 추론 규칙에 적용하여 상황을 추론함으로서, 보관 식품의 부패 여부 및 신선도, 신선 유지 기간을 산출하는 제어부;를 포함하는 온톨로지 추론을 이용한 식품 상태 감시 시스템.Food control using ontology inference, including; the control unit calculates whether or not the corruption of the stored food, freshness, freshness period by applying the sensing information, the food storage state information and the storage operation information to the prepared inference rule Condition monitoring system.
  5. 제4항에 있어서, The method of claim 4, wherein
    보관 식품의 속성 정보를 상기 DB로부터 획득하는 식품 속성 정보 획득부를 더 포함하며,Further comprising food attribute information acquisition unit for obtaining the attribute information of the stored food from the DB,
    상기 DB는 상기 속성 정보를 저장하고,The DB stores the attribute information,
    상기 제어부는 상기 식품 속성 정보 획득부로부터 상기 속성정보를 전달받고, 상기 센싱 정보, 상기 식품 보관 정보, 상기 저장고 운영 정보와 상기 속성 정보를 상기 추론 규칙에 적용하여 상황을 추론함으로서, 보관 식품의 부패 여부 및 신선도, 신선 유지 기간을 산출함을 특징으로 하는 온톨로지 추론을 이용한 식품 상태 감시 시스템.The control unit receives the attribute information from the food attribute information acquisition unit, and deduces a situation by applying the sensing information, the food storage information, the storage operation information, and the attribute information to the inference rule, thereby preventing corruption of the stored food. A food condition monitoring system using ontology inference, characterized by calculating whether or not, freshness, and freshness retention period.
  6. 제 5항에 있어서,The method of claim 5,
    상기 센싱 정보는 에틸렌 농도, 이산화탄소 농도, 온도, 습도 중 적어도 하나이며, The sensing information is at least one of ethylene concentration, carbon dioxide concentration, temperature, humidity,
    상기 식품 보관 정보는 식품의 에틸렌 농도 임계값, 이산화탄소 농도 임계값, 온도 임계값, 습도 임계값 중 적어도 하나이며, The food storage information is at least one of ethylene concentration threshold, carbon dioxide concentration threshold, temperature threshold, humidity threshold of the food,
    상기 저장고 운영 정보는 저장고의 문 개폐 정보 및 저장고에 식품이 들어오는 시간 중 적어도 하나이며,The storage operation information is at least one of door opening and closing information of the storage and the time the food enters the storage,
    상기 속성 정보는 보관 식품의 이름 및 보관 식품의 원산지, 저장고 입고 전, 이력 정보 중 적어도 하나임을 특징으로 하는 온톨로지 추론을 이용한 식품 상태 감시 시스템.The attribute information is a food condition monitoring system using ontology inference, characterized in that at least one of the name of the stored food and the origin of the stored food, before storage, storage history information.
  7. 센서별 환경정보 임계값이 저장되는 센싱정보 데이터베이스;A sensing information database storing sensor-specific environmental information thresholds;
    저장고 운영정보가 저장되는 운영정보 데이터베이스;An operation information database in which storage operation information is stored;
    저장고의 운영정보와 센서별 환경정보 임계값을 각 데이터베이스에 저장하는 설정정보 입력부;A setting information input unit for storing operation information of the storage and the environmental information threshold value of each sensor in each database;
    온도, 습도 중 적어도 하나의 환경 정보와 에틸렌 농도, 이산화탄소 농도 중 적어도 하나의 환경정보를 검출하고 그 검출된 정보를 환경정보 인지모듈로 전송하는 센서모듈;A sensor module for detecting at least one of environmental information of temperature and humidity, and at least one of environmental information of ethylene concentration and carbon dioxide concentration and transmitting the detected information to an environmental information recognition module;
    상기 센서모듈로부터 전송된 환경정보를 센싱정보 데이터베이스에 저장된 각 센서별 환경정보 임계값과 비교하여 임계값을 초과하는지를 판단하고, 초과할 경우 환경정보, 각 센서별 환경정보 임계값 및 운영정보를 매핑시키는 환경정보 인지모듈;It is determined whether the threshold value is exceeded by comparing the environmental information transmitted from the sensor module with the environmental information threshold value of each sensor stored in the sensing information database, and if exceeded, mapping the environmental information, the environmental information threshold value of each sensor, and the operation information. Environmental information recognition module;
    환경정보가 임계값을 초과한 것으로 판단되면 상기 센서모듈로부터 제공된 환경정보와 운영정보 데이터베이스에 저장된 저장고의 운영정보를 온톨로지 기반으로 추론하는 온톨로지 기반 추론모듈; 및An ontology-based reasoning module for inferring, based on ontology, operation information of a storage stored in an environment information and an operation information database provided from the sensor module when it is determined that the environment information exceeds a threshold value; And
    상기 온톨로지 기반 추론모듈에 의해 추론된 결과를 통해 환경상태 조절 장Control of environmental conditions through the results inferred by the ontology-based inference module
    치를 제어하는 제어부를 포함하는 온톨로지 기반의 저장고 환경상태 관리 시스템.Ontology-based storage environment management system including a control unit for controlling the value.
PCT/KR2012/011687 2011-12-28 2012-12-28 System and method for monitoring status of food based on ontology WO2013100683A1 (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
KR1020110144596A KR20130076140A (en) 2011-12-28 2011-12-28 Method and system which observe the state of food
KR10-2011-0144596 2011-12-28

Publications (1)

Publication Number Publication Date
WO2013100683A1 true WO2013100683A1 (en) 2013-07-04

Family

ID=48698019

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/KR2012/011687 WO2013100683A1 (en) 2011-12-28 2012-12-28 System and method for monitoring status of food based on ontology

Country Status (2)

Country Link
KR (1) KR20130076140A (en)
WO (1) WO2013100683A1 (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115777767A (en) * 2022-11-23 2023-03-14 宁夏农产品质量标准与检测技术研究所(宁夏农产品质量监测中心) Edible mushroom preservation method and system

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20020027009A (en) * 2000-10-04 2002-04-13 양용준 System for monitoring of a Storage Environment and Method therefor
KR20050017959A (en) * 2003-08-12 2005-02-23 학교법인조선대학교 Method and Apparatus for Monitoring and Controlling Temperature and Humidity in Low Temperature Storage House
KR20120076602A (en) * 2010-12-06 2012-07-09 한국식품연구원 Storeroom environment state management system and method of base ontology

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20020027009A (en) * 2000-10-04 2002-04-13 양용준 System for monitoring of a Storage Environment and Method therefor
KR20050017959A (en) * 2003-08-12 2005-02-23 학교법인조선대학교 Method and Apparatus for Monitoring and Controlling Temperature and Humidity in Low Temperature Storage House
KR20120076602A (en) * 2010-12-06 2012-07-09 한국식품연구원 Storeroom environment state management system and method of base ontology

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
KI HWAN, KIM ET AL.: "Ontology Modeling and Implementation of Situation Aware Middleware for Intelligent Food-warehouse Management System.", JOURNAL OF KIISE: COMPUTING PRACTICES AND LETTERS., vol. 17, no. 12, 15 December 2011 (2011-12-15), pages 657 - 661 *
SON, MIN YOUNG.: "Design and implementation of ontology based situation-awareness middleware for food-warehouse management.", PUSAN NATIONAL UNIVERSITY COMPUTER ENGINEERING, THESIS FOR MASTER'S DEGREE., 28 February 2011 (2011-02-28) *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115777767A (en) * 2022-11-23 2023-03-14 宁夏农产品质量标准与检测技术研究所(宁夏农产品质量监测中心) Edible mushroom preservation method and system
CN115777767B (en) * 2022-11-23 2024-01-26 宁夏农产品质量标准与检测技术研究所(宁夏农产品质量监测中心) Preservation method and system for edible fungi

Also Published As

Publication number Publication date
KR20130076140A (en) 2013-07-08

Similar Documents

Publication Publication Date Title
Emmanouilidis et al. Enabling the human in the loop: Linked data and knowledge in industrial cyber-physical systems
KR101349540B1 (en) System and method for providing context cognition to controll home network service
CN105590336B (en) Information displaying method and device
Aloulou et al. Uncertainty handling in semantic reasoning for accurate context understanding
CN107831719A (en) A kind of medical environment intelligent diagnostics and management system based on Internet of Things
Sebbak et al. Dempster–Shafer theory-based human activity recognition in smart home environments
Finkelstein Intelligent and knowledge based instrumentation—An examination of basic concepts
Ali et al. Microservices model in WoO based IoT platform for depressive disorder assistance
WO2013100683A1 (en) System and method for monitoring status of food based on ontology
AU2019231258B2 (en) System and method for preventing false alarms due to display images
CN209132626U (en) A kind of wisdom classroom management system based on Internet of Things
WO2020113305A1 (en) Method and system for smart environment management
Schumann et al. Adaptable fault identification for smart buildings
KR101198847B1 (en) Storeroom environment state management system and method of base ontology
CN108701401A (en) Alarm method, device, system and electronic equipment
Kučera et al. Semantic bms: Ontology for analysis of building automation systems data
Ji et al. Intelligent building using hybrid Inference with building automation system to improve energy efficiency.
CN111367163B (en) Intelligent farm environment controller and application thereof
CN103777608A (en) Internet of things system for harmless treatment of animal carcasses
Sfar et al. CAREDAS: context and activity recognition enabling detection of anomalous situation
Zhang et al. Artificial intelligence-based early warning method for abnormal operation and maintenance data of medical and health equipment
Baudisch et al. A framework for learning event sequences and explaining detected anomalies in a smart home environment
Bampi Ontology-driven monitoring system for ambient assisted living
CN212694281U (en) Wisdom beasts and birds are bred thing networking management and control system
CN116150285A (en) Building automation system data marking method based on big data

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 12863193

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 12863193

Country of ref document: EP

Kind code of ref document: A1