KR102485645B1 - A Distributed IoT System based on distributed ontology structure for Task-driven Smart Objects Collaboration - Google Patents

Abstract

The present invention relates to an IoT system for providing intelligent services, and one of the systems of the present invention is characterized in that it includes a server and at least one electronic device, wherein the server communicates with at least one electronic device. communication unit that can; a storage unit capable of storing information about a plurality of tasks provided for each user's behavior and a plurality of services that the at least one electronic device can perform; and receiving situation information from the at least one electronic device through the communication unit, determining a task corresponding to a user's action indicated by the received situation information from among the plurality of tasks, and determining the determined task among the at least one electronic device. and a processing unit for transmitting information about the service to a first electronic device capable of providing the service corresponding to a task, wherein the electronic device includes: a communication unit capable of communicating with a server; a storage unit capable of storing interaction history information with a user; A processing unit providing a corresponding service upon receiving information about a service from a server, wherein the corresponding service is provided based on the interaction history information stored in the storage unit.
According to the present invention, each smart object constituting the IoT is an autonomous distributed object that collects surrounding and user context information, understands its meaning, and provides personalized services to users based on this, and multiple smart objects By providing services in task units, which are a collective concept of provided services, it is possible to provide integrated services to users through the collaboration of several smart objects, and overcome the limitations of the centralized IoT system structure.

Description

Distributed IoT System based on distributed ontology structure for Task-driven Smart Objects Collaboration}

The present invention relates to an IoT system for providing intelligent services, and more specifically, to a distributed IoT system based on a distributed design ontology for task-based collaboration of smart objects.

Since Kevin Ashton of the MIT Auto-ID Center first introduced the word IoT (Internet of Things) in the early 2000s, we are living in contact with numerous IoT objects called 'smart objects' in our daily lives. The Echelon Corporate Overview announced in 2014 predicted that 40 billion smart objects worldwide would form an IoT environment by 2025, and according to the UK government report, as these smart objects are connected to the network, people and other smart objects in everyday life expected to exchange data with them. According to this prospect, as IoT has recently emerged as a major issue in industry and academia, research on how to design a system to provide user-customized services in the IoT environment is being actively conducted worldwide.

CERP-IoT (Cluster of European Research Projects on the Internet of Things) defined the characteristics and roles of things in the IoT environment as follows: Each thing constituting the IoT interacts with other things and the environment. Based on the collected information, it plays the role of an autonomous service provider that takes action according to the situation without direct intervention of the user on the events occurring in the surroundings. Although this definition is not a unified standard in the field of IoT, the majority of research is being conducted based on this concept.

In order for an IoT system to conform to the definition of CERP-IoT, it must at least satisfy the following requirements: ① contextual information collection, ② contextual information interpretation, ③ personalized service provision, and ④ task-oriented collaboration. The details of each requirement are as follows.

(1) Context Capturing

According to the definition of CERP-IoT, the most basic element to make each smart object an autonomous service provider is awareness of the surrounding context. The more contextual information is encountered, the richer the interaction between people and smart objects, and the more useful services can be provided. Therefore, in order to provide useful services tailored to the situation in the IoT environment, each smart object must be able to collect, store, and manage meaningful context information provided from other smart objects or environments.

(2) Context Reasoning

In order for the collected contextual information to be used as a basis for providing services appropriate to the context, it is essential to properly interpret the semantics of the current context. Understanding the meaning of the situation is considered one of the key skills for realizing the IoT vision. That is, in order to become an autonomous service provider, each smart object must be able to interpret what the current situation means to itself or the user based on the collected situation information.

(3) Provide personalized service (Personalization)

If it is possible to recognize and interpret the current situation and user information, each smart object should be able to provide a personalized service to the user accordingly. That is, each smart object must be able to actively provide a service according to the user's preference without user intervention. At this time, in order to properly establish a service adaptation strategy and increase the satisfaction of the user, the consumer of the service, each smart object must be able to learn the user's preference through continuous interaction with the user and update the adaptation strategy based on it. In fact, users go beyond simply recognizing and interpreting situations and recognize them as “smart” only when the personalized service provided by the smart object satisfies their needs.

(4) Task-oriented collaboration

If it is possible to recognize context, share, interpret, and adapt service behavior accordingly, another requirement that each smart object must have as an autonomous service provider is to collaborate with other smart objects to perform user tasks. It provides holistic and integrated support.

Looking back at our daily lives, we often need to interact with multiple smart objects to achieve a desired goal (for example, turning off the TV or lights, setting an alarm time, etc. to sleep). To support this, it is efficient to provide services in units of user 'task' that collectively includes the services of several smart objects. In order to provide user-customized services at the user task level, a technology capable of discovering several smart objects that need to provide services to perform a given task and requesting them to provide services must be developed.

However, systems developed through conventional research do not satisfy all of the above four requirements. For Sasidharan (2014) (Sasidharan, Sreekanth, et al. "Cognitive management framework for Internet of Things:―A prototype implementation." Internet of Things (WF-IoT), 2014 IEEE World Forum on. IEEE, 2014), Composite By designing and implementing a coordination mechanism between smart objects through an abstract concept called Virtual Object, the foundation for providing user task-oriented services was laid, but each smart object was abstracted into a Virtual Object and included as part of providing context-aware services. As an autonomous distributed object, it does not suggest what kind of internal structure it should have to make knowledge-based situation judgments and respond to environmental changes.

In the case of Lee (2014) (Lee, Ju Hyun, et al. "Context-aware inference in ubiquitous residential environments." Computers in Industry 65.1 (2014): 148-157), the structure of the proposed framework is Since it was designed with the server in charge of processing and processing in mind, there is also a limit to allowing each smart object to autonomously judge the situation and provide adaptive services. In addition, since this study mainly focuses on reasoning for context reasoning, it is assumed that input of context information and design of rules should be performed by system administrators or users. This assumption can be a fatal constraint for each smart object to autonomously provide services in an IoT environment.

In the case of Yu (2013) (Yu, Lian, et al. "Context-Aware Service Modeling and Rule Evolution." 2013 10th Web Information System and Application Conference. 2013), context information collected based on knowledge written in ontology It focuses on the design of a context engine that analyzes and writes the user's preference and the corresponding service provision method as a rule. In the case of this study, although the main purpose is not to make each smart object an autonomous service provider, if the structure of the proposed system is inherent in each smart object, it is expected that it will be able to have some degree of intelligence and autonomy required as a distributed object. see. However, there are still limitations in that there is no verification through application to actual smart objects and IoT environments, and there is no consideration for interaction between smart objects and collaboration between smart objects to support user tasks.

For Ni (2011) (Ni, Hongbo, et al. "CDTOM: A Context-driven Task-oriented Middleware for Pervasive Homecare Environment." arXiv preprint arXiv:1102,1152 (2011)), based on the context information collected The focus is on how to consistently support user tasks by combining various sensors and actuators that exist in the IoT environment. However, each sensor and actuator merely serves to report situational information to the server or provide services according to commands received from the server, and is included in the system as a completely unintelligent object. In this case, all the overhead is imposed on the server, and a single point of failure problem in which all systems are paralyzed when the server temporarily does not respond can occur as a serious issue.

The above information is summarized in a table as follows.

That is, most of the current IoT system research results are systemic in that each smart object, as an autonomous distributed object, understands the meaning of surrounding and user context information and functions to adaptively provide a service appropriate to the situation based on it. not enough to support In addition, each smart object of the IoT system proposed in previous studies is in charge of simply sensing environmental information or providing one-way services without high intelligence, and most tasks requiring intelligence are performed by a single server (e.g., home gateway). or cloud). If the aforementioned Echelon Corporate Overview or the UK government's prospects come true and a huge number of smart objects are connected to the network, traffic and data processing are concentrated on the server in such a centralized structure, resulting in serious deterioration in overall performance. In the event of a server failure, there is also a high risk of causing the entire system to stop operating (so-called single point of failure). Furthermore, the assumption that all services are provided based on one powerful server is also unrealistic.

Therefore, according to the present invention, each smart object constituting the IoT is an autonomous distributed object, and a system and several smart objects that can collect contextual information of the surroundings and users, understand the meaning, and provide personalized services to users based on this. A system that can provide integrated services to users through the collaboration of several smart objects by providing services in a task unit, which is a collective concept of the services provided, and a system that can overcome the limitations of a centralized IoT system structure. The purpose of this study is to suggest an ontology designed to be, and to provide a system based on this ontology.

To achieve the above object, one of the servers of the present invention includes a communication unit capable of communicating with at least one electronic device; a storage unit capable of storing information on a plurality of tasks provided for each user's behavior and information on a plurality of services that the at least one electronic device can perform; and receiving situation information from the at least one electronic device through the communication unit, determining a task corresponding to a user's action indicated by the received situation information from among the plurality of tasks, and determining the determined task among the at least one electronic device. and a processing unit configured to transmit information about the service to a first electronic device capable of providing the service corresponding to the task.

In the server, the information about the task may include task history information, and the processing unit may determine the task corresponding to the situation information based on the task history information. Based on this task history information, if the server itself infers the task the user wants to perform in certain situations, even if the user does not directly issue a task execution command, the service desired by the user is automatically provided by multiple smart objects in cooperation, so that the user's It has a great effect in terms of convenience.

Furthermore, the processing unit may generate information about the task corresponding to the situation information and at least one service corresponding to the task based on the task history information, and store the information in the storage unit. Through this, the server can automatically call smart object services suitable for performing the task after establishing user behavior or task information in a specific situation by itself and recognizing the specific situation in the future.

In the server, the processing unit may transmit the situation information received from a second electronic device other than the first electronic device to the first electronic device. In this way, if an electronic device additionally receives context information generated and collected by itself as well as context information generated and collected by another electronic device and uses it to provide personalized service, a more intelligent personalized service can be provided.

Furthermore, in the server, the plurality of tasks may be further classified according to places, and the processing unit may determine a task corresponding to a place indicated by the situation information.

One of the electronic devices of the present invention, the communication unit capable of communicating with the server; a storage unit capable of storing situation information; and a processor that provides the corresponding service upon receiving information about the service from the server, and in providing the corresponding service, determines and provides the content of the service based on the situation information stored in the storage unit. .

Furthermore, the context information may include a history of interaction with the user. Through this, each electronic device that has received a service provision request can provide personalized service to the user by its own judgment, and the existing centralized IoT system as the judgment ability is distributed compared to the system in which all judgments are made in the server. It is possible to provide intelligent services while mitigating the single point of failure problem, which is a disadvantage of

Further, in the electronic device, the processing unit may be characterized in that it receives the situation information received by the server from the second electronic device from the server. In this way, if an electronic device additionally receives context information generated and collected by itself as well as context information generated and collected by another electronic device and uses it to provide personalized service, a more intelligent personalized service can be provided.

One of the systems of the present invention for achieving the above object is an IoT system composed of a server and at least one electronic device, wherein the server includes information on a plurality of tasks provided for each user's behavior, and the at least one a storage unit capable of storing information about a plurality of services that electronic devices can perform; and receiving situation information from the at least one electronic device, determining a task corresponding to a user's action indicated by the received situation information from among the plurality of tasks, and corresponding to the determined task among the at least one electronic device. and a processing unit for transmitting information about the service to a first electronic device capable of providing the service, wherein the electronic device includes: a storage unit capable of storing situation information; and a processor that provides the corresponding service upon receiving information about the service from the server, and in providing the corresponding service, determines and provides the content of the service based on the situation information stored in the storage unit. .

In the server of the system, the information about the task may include task history information, and the processing unit may determine the task corresponding to the situation information based on the task history information.

Furthermore, in the server of the system, the processing unit generates information about the task corresponding to the situation information and at least one service corresponding to the task based on the task history information, and stores the information in the storage unit. that can be characterized.

In the server of the system, the processing unit may transmit the situation information received from a second electronic device other than the first electronic device to the first electronic device.

Furthermore, in the server of the system, the plurality of tasks may be further classified according to places, and the processing unit may determine a task corresponding to a place indicated by the situation information.

To achieve the above object, one of the server control methods according to the present invention provides information on a plurality of tasks prepared for each user's behavior and information on a plurality of services that at least one electronic device can perform. storing; Receiving context information from the at least one electronic device; determining a task corresponding to a user's behavior indicated by the received situation information from among the plurality of tasks; and transmitting information about the service to a first electronic device capable of providing the service corresponding to the determined task among the at least one electronic device.

To achieve the above object, one method of controlling an electronic device according to the present invention includes the steps of storing context information; Receiving information about a service from a server; and determining and providing contents of the received service based on the stored context information.

As described above, according to the present invention, each smart object constituting the IoT is an autonomous distributed object that collects surrounding and user context information, understands its meaning, and provides personalized services to users based on this. , By providing services in task units, which are the collective concept of services provided by multiple smart objects, it is possible to provide integrated services to users through the collaboration of multiple smart objects, and to overcome the limitations of the centralized IoT system structure. there is.

1 is an exemplary view of the system of the present invention;
2 is a block diagram showing the configuration of a server 101 in the present invention.
3 is a block diagram showing the configuration of electronic devices 102, 103, 104 in the present invention.
4 is a diagram showing the overall design structure of an ontology according to an embodiment of the present invention.
5 is a diagram showing a detailed design of an IoT component ontology 401 according to an embodiment of the present invention.
6 is a diagram illustrating a detailed design of a service function ontology 404 according to an embodiment of the present invention.
7 is a diagram showing a detailed design of a context information ontology 403 according to an embodiment of the present invention.
8 is a diagram illustrating a detailed design of a task ontology 402, according to an embodiment of the present invention.
9 is a diagram illustrating a method of generating an instance of an IoT component ontology 401 according to an embodiment of the present invention.
10 is a diagram illustrating a method of creating an instance of a context information ontology 403 and a method of defining a relationship with a smart object service according to an embodiment of the present invention.
11 is a diagram illustrating a method of creating an instance of a smart object service function ontology 404 according to an embodiment of the present invention.
12 is a diagram illustrating a method of generating and transmitting a service specification of a smart object to the lightweight server 101 according to an embodiment of the present invention.
13 is a diagram illustrating a method of instantiating a task ontology 402 according to an embodiment of the present invention.
14 is a diagram illustrating a method of creating context information instances related to a user's variable task performance intention according to an embodiment of the present invention.
15 is a diagram showing a control method of the server 101 according to an embodiment of the present invention.
16 is a diagram illustrating a control method of electronic devices 102, 103, and 104 according to an embodiment of the present invention.

Hereinafter, embodiments of the present invention that can specifically realize the above object will be described with reference to the drawings. However, the technical idea of the present invention and its core configuration and operation are not limited to the configurations or operations described in the following embodiments. In describing the present invention, if it is determined that a detailed description of a known technology or configuration related to the present invention may unnecessarily obscure the subject matter of the present invention, the detailed description will be omitted.

The terms or words used in this specification and claims should not be construed as being limited to their usual or dictionary meanings, and the inventors can properly define the concept of terms in order to best explain their invention. Based on the principle, it should be interpreted as a meaning and concept consistent with the technical idea of the present invention.

In the embodiments of the present invention, terms including ordinal numbers, such as first and second, are used only for the purpose of distinguishing one component from another, and expressions in the singular number are plural unless the context clearly indicates otherwise. contains an expression of

In addition, in the embodiments of the present invention, terms such as 'comprise', 'include', and 'have' refer to one or more other features, numbers, steps, operations, elements, parts, or combinations thereof. Or it should be understood as not precluding the possibility of addition.

In addition, in an embodiment of the present invention, a 'module' or 'unit' performs at least one function or operation, may be implemented as hardware or software, or may be implemented as a combination of hardware and software, and is integrated into at least one module. and can be implemented with at least one processor.

The present invention relates to an IoT system. Internet of Things (IoT) refers to an environment in which objects in daily life are connected through wired and wireless networks to share information. Here, things include various embedded systems such as home appliances, mobile devices, and wearable computers. In a broad sense, IoT includes not only wired and wireless network equipment, but also software and services for integration and operation between electronic devices corresponding to things. The Internet of Things basically consists of a gateway connecting networks, communication networks such as telephone lines, power lines, and wireless, middleware that controls and interoperates information devices, and information devices with added networking functions.

1 is an exemplary diagram of the system of the present invention. As shown in FIG. 1, the system of the present invention includes one server 101 and at least one smart device 102, 103, 104 (meaning the same as the 'smart object' used above, but 'smart device' in relation to the server). ' or 'electronic device'), and when one server and at least one smart device as described above are referred to as a 'group' 100, the system of the present invention can also be configured in several groups . Although the server is treated separately from the smart device in concept here, the server may also be a smart device.

Any device that can be a component of the Internet of Things may correspond to the server or smart device of the present invention. That is, the server or smart device of the present invention can be any device that can correspond to T (Thing) of IoT (Internet of Things). For example, there are various sensors such as environmental sensors and door sensors, webcams, power measurement modules, projectors, air conditioners, lights, robot vacuum cleaners, dehumidifiers, set-top boxes, game consoles, smart TVs, and integrated control modules.

'Server' and other 'smart devices' can be classified according to functions. Hernandez (2014) (Perez Hernandez, Marco E., and Stephan Reiff-Marganiec. "Classifying Smart Objects using Capabilities." Smart Computing (SMARTCOMP), 2014 International Conference on. IEEE, 2014) classifies smart devices into the following five steps: It is classified into: Essential (Level 1) stage with basic ID information and minimum communication ability, Networked (Level 2) stage where data can be processed through built-in programs, context information history is collected and service is provided based on rules. The Enhanced (Level 3) step that can provide information, the Aware (Level 4) step that can perform a more in-depth analysis of the user's intentions and purposes, and the situation, and finally the Aware (Level 4) step that allows you to learn everything on your own like a normal user and learn from others. IoT-Complete (Level 5) stage to establish social relationships with users and objects in IoT.

The present invention targets smart devices of the Networked (Level 2), Enhanced (Level 3), and Aware (Level 4) stages among the above classifications. A 'server' refers to a smart device at the Aware (Level 4) level, and other 'smart devices' correspond to the Networked (Level 2) or Enhanced (Level 3) level. As such, since the smart device of the present invention is basically Networked (Level 2) or higher, it can independently generate and transmit contextual information and provide certain services to users. In the case of a smart device at the Enhanced (Level 3) stage, it is possible to further analyze the history of interaction with the user and provide a personalized service specialized to the user.

On the other hand, the server, as a device at the Aware (Level 4) stage, infers what task the user wants to perform based on contextual information, identifies smart devices that need to provide services to perform the inferred task, and It plays a role in organizing collaboration between smart devices.

2 is a block diagram showing the configuration of a server 101 in the present invention. The server 101 is composed of a communication unit 201, a storage unit 202, and a processing unit 203.

The communication unit 201 performs communication with the smart devices 102, 103, and 104. Specifically, the communication unit 201 communicates with at least one smart device, receives information and situation information about the smart device, and provides a service to at least one of the at least one smart device according to the processing result of the processing unit 203. send request

Here, 'situational information' collectively refers to information defining characteristics of a situation, such as a person, place, thing, object, time, etc., that affect interactions between a user and other users, systems, or device applications. For example, network connection status, communication bandwidth, and computing context such as printers, displays, and workstations, user context including user profile, location, and people around them, lighting, noise level, and traffic. There are physical contexts such as state and temperature, and time contexts such as time, week, month, and season.

The communication unit 201 may perform communication with the smart devices 102, 103, and 104 through a wired or wireless network, and thus may include a communication protocol for a wireless local area network (WLAN) in a broad sense. . In addition, communication modules corresponding to other communication methods such as Bluetooth, Wi-Fi, Zigbee, IR communication, and RF communication may be included.

When the IoT system of the present invention is used as a home network, the communication module can perform communication according to various home network communication standards. For example, communication may be performed according to a home network communication standard such as DLNA (Digital Living Network Alliance). The DLNA refers to a wired/wireless network capable of sharing digital contents such as music, photos, and videos stored in electronic devices such as home computers, home appliances, and portable terminals.

The storage unit 202 stores information about a plurality of tasks provided for each user's behavior and a plurality of services that the at least one smart device can perform. In the case where the server 101 has jurisdiction over a specific place, for example, the storage unit 202 of the server 101 includes situational information related to the place, information on smart devices present at the place, and user information at the place. Information on tasks that can be performed and information about smart devices to be provided with services when each task is performed are stored. Furthermore, the storage unit 202 may store user task history information.

The specific form of the storage unit 202 can be anything that can perform a function of storing information, such as a hard disk drive (HDD), a solid state drive (SSD), and a flash memory, and random access RAM (RAM). It does not exclude volatile memory such as memory).

The processing unit 203 receives situation information from the at least one smart device 102, 103, 104 through the communication unit 201, and responds to a user's behavior indicated by the received situation information among the plurality of tasks. A task is determined, and information about the service is transmitted to a first electronic device capable of providing the service corresponding to the determined task among the at least one smart device 102 , 103 , and 104 . Any type of CPU (Central Processing Unit), AP (Application Processor), etc., can perform this information processing function.

The processing unit 203 may transmit the situation information received from a second electronic device other than the first electronic device to the first electronic device. In this way, if one smart device receives not only the situation information generated and collected by itself but also the situation information generated and collected by other smart devices and uses it to provide personalized service, more intelligent personalized service can be provided.

Figure 3 is a block diagram showing the configuration of the electronic device 300 (102, 103, 104) (hereinafter referred to as 'smart device') of the present invention. The electronic devices 102, 103, and 104 also have the same basic configuration as the server 101 in that they are composed of a communication unit 301, a storage unit 302, and a processing unit 303.

The communication unit 301 communicates with at least one server 101, transmits information and situation information about the electronic devices 102, 103, and 104, and receives a service provision request from the at least one server 101. As in the case of the server 101, anything that can perform these communication functions can be a communication unit, and as a communication method, a wireless communication method will be mainly used due to the nature of IoT, but the possibility of using wired communication is not excluded. .

The storage unit 302 stores situation information and information about at least one service provided by the electronic devices 102 , 103 , and 104 . Furthermore, the storage unit 302 may also store interaction history information with the user. As mentioned in the server 101, the specific form of the storage unit 202 can be anything that can perform a function of storing information such as HDD, SSD, Flash Disk, etc., and volatile memory such as RAM is not excluded. .

When receiving information about a service from the server 101, the processing unit 303 provides the corresponding service. Here, in providing the determined service, a personalized service is provided to the user based on the situation information stored in the storage unit 302 . Furthermore, the processing unit 303 may provide a personalized service to the user by further referring to the interaction history information with the user. As mentioned in the case of the server 101, any type of CPU (Central Processing Unit), AP (Application Processor), etc. can be used as long as it can perform an information processing function.

Just as it is possible for the processing unit 203 of the server 101 to transmit the situation information received from the second electronic device other than the first electronic device to the first electronic device, the processing unit 303 of the electronic devices 102, 103, and 104 ) It is also possible to receive the situation information received by the server 101 from a second electronic device other than the first electronic device. As in the case of the server 101, the effect is to receive not only the situation information directly collected by the first electronic device, which is one smart device, but also the situation information generated by the second electronic device, which is another smart device, to provide personalized service. As it can be used for provision, more intelligent personalized service can be provided.

As can be seen through the configuration and operation of the server 101 and the smart devices 102, 103, and 104 as described above, each smart device 102, 103, and 104 in the IoT system of the present invention provides personalized service to the user. In that it has autonomous learning and judgment capabilities to provide, most of the work requiring intelligence is left to the server, and each smart device simply performs only sensing of environmental information or providing one-way services. is different. In addition, the server 101 has information about a task, which is a collective concept of services provided by several smart devices 102, 103, and 104, and information about services provided by each smart device 102, 103, and 104, , it is possible to determine the smart device (102, 103, 104) that provides a service necessary to perform a specific task. In addition, since the server 101 also stores context information, it is possible to infer a task to be performed by a user in a specific situation through determining a relationship between the context information and the performed task. Furthermore, the server 101 and the group 100 of the smart devices 102, 103, and 104 as described above do not necessarily need to be one, and a plurality of groups may form one system. In this case, since a plurality of servers 101 exist, there is an effect of solving the problem of performance degradation and single point of failure caused by concentration of all intelligent processing in a single server.

<Work of the present invention in the examples According to the ontology design structure>

Hereinafter, as an embodiment of the present invention, an example of ontology design, which is the basis for the operation of the IoT system of the present invention, is presented, and the process of operating the present invention on the ontology structure will be described in detail. The following embodiment assumes a situation in which one server 101 has jurisdiction over smart devices 102, 103, and 104 located in one 'place' for convenience of explanation, but one server 101 has jurisdiction The scope of the smart devices 102, 103, and 104 need not be limited to a physical 'place'.

The design of the ontology is closely related to the structure of the entire system. As described above, the system of the present invention targets a distributed system structure in order to mitigate issues such as single point failure and server performance degradation that the single server-based service provision structure has. In this system structure, the server 101 is reduced in weight by distributing part of the function of storing knowledge and reasoning based on contextual information to each smart device 102, 103, and 104. The distribution of judgment capabilities requires that each smart device (102, 103, 104) as well as the server 101 be equipped with knowledge that is the basis for judgment.

The ontology that is the basis of the IoT system according to an embodiment of the present invention targeting such a distributed system structure is an IoT component ontology 401, a task ontology 402, a context information ontology 403, and a service function. Ontology 404 is included. These ontologies include smart objects in the IoT environment (hereinafter referred to as 'smart objects' collectively for the 'server' and 'smart device' in the ontology) and services, users, and key concepts related to user's surrounding context information and By defining the relationship between them, the basic skeleton of the IoT system of this embodiment is provided. The role of each ontology is as follows.

1. IoT Element Ontology (401): Expresses the form in which smart objects, which are components of the Internet of Things, are included in the system.

2. Task Ontology (402): Defines factors affecting the formation of user's intention and information on related smart object services for each task.

3. Context Ontology (403): Expresses the system and characteristics of context information generated and shared from each smart object.

4. Service Functionality Ontology 404: Expresses information about what function each service provides and how.

The overall design structure of the ontology including the relationship between the above four ontologies and the components within each ontology is shown in FIG. 4 . The detailed structure of each ontology is shown in FIGS. 5 to 8.

The detailed structure of the ontology will be described below along with the process of creating specific instances of each ontology.

One. Internet of Things Component Ontology (401)

The role of the smart object is 'server 101' {hereinafter, the server of the present invention is also referred to as a 'lightweight server' in that the processing burden is lighter than that of a general server, and it can be a smart object in charge of a specific place. Whether it is also called 'VPO' (Virtual Place Object)} or general 'smart objects' (102, 103, 104), all smart objects have an identity within the system as a component of the IoT system. The developer of each smart object service must specify the identity of the service he/she develops according to the IoT component ontology 401. 9 is a diagram showing the method.

(1) The smart object is a smart object (502) that independently creates and collects contextual information or provides services to users, and a lightweight server that collects contextual information generated for each location and organizes collaboration between the smart objects (502). (101) is composed of VPO (503). Therefore, prior to the creation of the ontology, the developer of the smart object service must determine the role of the smart object to be developed [Fig. 9 ①].

(2) When the corresponding smart object is the lightweight server 101, the type of IoT_Element 501, which is a component corresponding to the smart object, is set to VPO 503 [Fig. 9 ②].

(3) If the corresponding smart object is a general smart object (102, 103, 104), the developer sets the type of IoT_Element (501) to SmartObject (502) [Fig. 9 ③].

(4) Each IoT_Element 501 is published to the system as an Agent 504, a virtual object unit that provides services. To define its name, an agent instance 504 is created (eg, SmartFridgeAgent, VPOAgent) [ Fig. 9 ④].

(5) The IoT_Element 501 and the previously created agent instance 504 are connected through the exposedAs relationship 505 (eg, SmartFridge-exposedAs-SmartFridgeAgent) [Fig. 9 ⑤].

(6) Each Agent 504 may provide one or more Services 506. For example, a smart refrigerator may provide smart cooling and cooking menu recommendation services. In this way, the service provided by the corresponding smart object is created as a service ontology instance 506 [Fig. 9 ⑥].

(7) An agent instance 504 and service instances 506 provided by the agent are connected through a providedService relationship 507 (eg, SmartFridgeAgent-providesService-SmartCooling) [Fig. 9 ⑦].

Through the above process, information about whether the role of a specific smart object is the lightweight server 101 or general smart objects (102, 103, 104), and what functions the smart object provides is defined on the ontology. In other words, other smart objects can understand the role and services of the smart object and utilize them.

2. Context information ontology (403)

The context information ontology 403 is an ontology that establishes a system for context information generated or collected by each service. The highest concept is Context (701), which includes SocialContext (702) recognized by the user, EnvironmentalContext (703) such as temperature, humidity, and illumination, TemporalContext (704) that expresses the date, and current service status. Sub-Contexts, such as Status 705, can be arbitrarily defined.

The smart objects 102, 103, and 104, depending on the characteristics of the work to be performed, simply create contextual information, collect and interpret generated contextual information, or provide smart services based on the contextual information. cases can be distinguished. Temperature, humidity, and illuminance sensors are examples of the former, and smart lights that adjust the brightness of light based on the user's occupancy status in the current space are examples of the latter. FIG. 10 is a diagram illustrating a procedure of creating an ontology for context information generated or collected by the smart objects 102, 103, and 104.

(1) When this smart object (102, 103, 104) plays a role of 'creating' context information, the type (or class) (702, 703, 704) of context information to be created is defined on the ontology Check if it exists [Fig. 10 ①, ②].

(2) If the types of context information (702, 703, 704) to be created are not defined in the ontology, the corresponding type is created in the context information ontology (403) as a subclass of Context (701) [Fig. 10 ③] .

(3) The smart objects 102, 103, and 104 that generate context information create the context information they create as ontology instances 701 together with the types of context information 702, 703, and 704 (eg: Temperature-type-EnvironmentalContext) [Fig. 10 ④].

(4) By connecting the service 506 provided by this smart object and the situation information 701 generated by the smart object through the updates relationship 706, other service developers can create new service rules using this information. it allows For example, when the relationship of TemperatureReportingService-updates-Temperature is shared, since the information that temperature information can be used has been disclosed, other service developers have developed service rules that automatically adjust the heating temperature of the air conditioner based on the temperature value of the current space. It can be written [Fig. 10 ⑤].

(5) Next, when this smart object service 506 'collects' other contextual information, the type (or class) of the contextual information to be collected and utilized (702, 703, 704) is the contextual information ontology 403 ) is defined on [Fig. 10 ⑥, ⑦].

(6) If the type of context information to be collected (702, 703, 704) is not defined in the context information ontology 403, the corresponding type is created in the ontology as a subclass of the Context class [Fig. 10 ⑧].

(7) The smart objects 102, 103, and 104 that collect contextual information should create contextual information ontology instances 701 together with the types of contextual information 702, 703, and 704 that they want to collect. (Example: Temperature-type-EnvironmentalContext) [Fig. 10 ⑨].

(8) By connecting the service 506 of the smart object and the context information 701 collected by the service through the hasInterest relationship 707, it is specified that the corresponding information shared in the current space can be received. For example, in the case of the automatic heating temperature control service illustrated in [Fig. 10 ⑤], the value can be received and used whenever the temperature value is updated in the current space by setting the relationship of AutoAirconTempControlService-hasInterest-Temperature [Fig. 10 ⑩].

Regarding a specific data structure representing context information, context information can be expressed based on a data structure called triple. Each triple consists of Subject, Predicate, and Object. Here, the subject represents the subject of the corresponding situation, the generator of situation information, or a variable having an object as a value. The predicate expresses the meaning of situational information by defining the relationship between the subject and the object, and the object expresses the object manipulated by the subject or the change in the state of the subject. For example, when user A is manipulating smart object B, a triple of context information corresponding thereto can be expressed as <Subject: User_A, Predicate: operates, Object: SmartObject_B>. As another example, when indicating the temperature of the current space, a triple of <Subject: Place_C, Predicate: hasTemperature, Object: 24> may be used.

3. Service function ontology (404)

After creating the ontology instance 701 of related context information, an instance of the service function ontology 404 should be created as a specification for the corresponding function of the smart object service. Other service developers can refer to this information to find out what service functions are being provided in the current space and refer to them in their own service development process.

A method of creating a service function ontology 404 is shown in FIG. 11 . The subject of creation of the service function ontology 404 is also the developer of the corresponding smart object service, as in FIGS.

(1) If this smart object service 506 provides one or more Functions 601 at a user-recognized level (eg, turning on lights, opening windows, turning on air conditioners, etc.), the details of these functions are provided. It is created in the form of an ontology instance 601 [Fig. 11 ①].

(2) For specification of service functions, after generating the functions provided by the service 506 as an ontology instance 601, the relationship of Service(506)-providesFunctionality(602)-Functionality(601) is set (e.g. RoomCoolingService -providesFunction-TurnOnAircon) [Fig. 11 ②].

(3) The function 601 provided by the service 506 is implemented in the form of a method 603 in a program, and the function instance 601 and the method instance 603 are connected through a hasMethod relationship 604. The definition of hasMethod relationship 604 can be used for method reflection in the future. For example, if a method called turnOn (603) is implemented in the air conditioner service and a relationship called RoomCooling (601)-hasMethod (604)-turnOn (603) is defined, the RoomCooling function (601) in which the user lowers the room temperature When requesting the execution of , this is connected to the turnOn method 603 of the air conditioner, and the turnOn method 603 can be automatically executed [Fig. 11 ③].

(4) The method of performing the service function may vary according to the option (FunctionalityOption) 605 (eg, lighting may be brightly lit or dimly lit). Therefore, it is also written whether each service function 601 can have such an option 605 [Fig. 11 ④].

(5) If a specific function (601) can be executed in various ways according to different options (605), the option is created as an ontology instance (605), and Functionality (601)-hasOption (606)-FunctionalityOption (605) Set the relationship (eg RoomCooling-hasOption-StrongCooling, RoomCooling-hasOption-WeakCooling) [Fig. 11 ⑤].

(6) If various options 605 exist for the service function 601, the specification of how each option 605 should be given must also be written as an ontology (607). For example, in the case of StrongCooling above, it is necessary to define whether the input value is a numeric type such as 1, 2, or 3 or a string type such as “strong/medium/low” (607). Specifications written in this way can be referred to by the smart object that performs the function when the user requests the execution of the corresponding function [FIG. 11 ⑥].

(7) Next, it is specified whether the performance of these functions changes specific context information [Fig. 11 ⑦].

(8) In case of change, which situation information is updated is displayed by connecting it in the relationship of Functionality (601) - updates (608) - Context (701) [Fig. 11 ⑧].

4. Task Ontology 402: smart for task performance of objects Collaborative information creation methods

Next, a method of inferring the user's intention to perform the task and creating a task instance 801 containing information of smart objects necessary to perform the determined task, that is, information related to collaboration for task performance, will be described.

The developer of the lightweight server 101 needs to build information about which task the user wants to perform in a certain situation and which smart object function can be supported as a knowledge base of the lightweight server 101. This can be built based on the structure of the task ontology 402 shown in FIG. 8 and other related ontology concepts, and FIG. 13 is a diagram showing the construction method. Hereinafter, the method will be described using FIG. 13 as follows.

(1) Recognizes a user task to create related knowledge and creates it as a Task type ontology instance 801 (eg Meeting-type-Task) [Fig. 13 ①].

(2) For each task, a user activity (Activity) 802, which is a unit constituting the task, is created as an ontology instance 802 (eg, Cleaning-type-Activity, DisplayingSlide-type-Activity, etc.) [Fig. 13 ② ].

(3) The created task 801 and the user activity ontology instance 802 are connected through the composedOf relationship 803 to define which activity the user performs or should perform for each task (e.g., Task-composedOf -Cleaning, Task-composedOf-DisplayingSlide) [FIG. 13 ③].

(4) For each user activity 802, which smart object service 506 function 601 can support it is identified [FIG. 13 ④]. Here, comparing the concepts of 'function 601' and 'user activity 802', 'function 601' refers to individual operations that occur in each smart object, such as power on and off, and 'user activity 802 ' is a concept of the above 'function' of a smart object, such as turning on a light, opening a window, or turning on an air conditioner, from the user's point of view.

(5) Task(801)-composedOf(803)-Activity(802), Activity(802)-supportedBy(804)- Functionality(601), Service(506)-providesFunctionality(602)-Functionality(601) chain connection is completed [Fig. 13 ⑤].

As such, the task ontology instance 801 determines which activity 802 or function 506 a task is composed of, and which smart object 501 (or service 506) supporting such function 506 is. It stores information about relational characteristics such as existence of a link in the form of a link. By following these links, the server 101 can perform logical reasoning about which smart object service each task is composed of, and can lead the result of the reasoning to collaboration between smart objects to perform actual tasks. there is. That is, when a command to perform a specific task is issued by the user or by the server 101's own judgment based on the situation information, the server 101 examines the above link to determine which activity 802 should be performed, After determining the function 601 to be executed to perform the activity 802 and the service 506 providing the function, each smart object 501 providing the corresponding service 506 is provided with the corresponding service. By requesting the execution of step 506, collaboration in units of tasks consisting of the operation of several smart objects can be drawn.

Hereinafter, an implementation and operation example of an IoT system based on the ontology having the above structure according to an embodiment of the present invention will be described in more detail.

In this embodiment, the smart objects 102, 103, and 104 are located in a seminar room or a rest room. The composition, type and classification of smart objects present in each place, user tasks that can be performed at each place, and examples of functions for each smart object to be provided to perform the task are summarized in a table as follows.

In this embodiment, for convenience of description, it is assumed that the lightweight server 101 has jurisdiction over smart devices located in the same 'place', but the range of smart devices managed by one server is a physical 'place'. need not be limited.

The IoT system developer or each smart object service developer determines the Internet of Things (401) ontology (401 ) instance, context information on context information collected by the smart object Ontology 403 instance, service function ontology 404 instance related to service functions provided by the smart object, and Internet of Things Ontology 401 instance and context information A mutual relationship between the ontology 403 instance and the service function ontology 404 instance is created. Furthermore, when the smart object serves as the lightweight server 101, a user task, an activity constituting each task, and a task ontology 402 instance for each smart object function to be provided to perform the task are also created.

There are various ontology languages and ontology development tools that can be used to implement and create the ontology structure of this embodiment and each ontology instance accordingly. CycL, KIF, Ontoligua, LOOM, OCML, F-Logic, SHOE, XOL, RDF, RDF Schema, OIL, DAML+OIL, OWL, and XTM are available as ontology languages, and Protege and WebODE are available as ontology development tools. , Ontoedit, KAON, Ontolingua server, WebOnto, OilEd, SemanticWorks, etc.

There are various libraries that can be used to create and store context information generated in this embodiment according to the ontology, but Apache Jena and H2DB are used in this embodiment.

Apache Jena is a library that creates and stores ontology triples written in OWL in JAVA and performs rule-based reasoning on them. It can perform a function of searching only necessary triples among stored contextual information through SPARQL-type queries. In this embodiment, when initializing a smart object, a module (model class) provided by the Apache Jena library is created and used as a space to store context information expressed in the form of an ontology triple during runtime.

H2DB is a pure JAVA-based database engine that provides basic database functions such as data storage and retrieval, and is based on a lightweight design with a library file size of only 1.5MB. In this embodiment, the above database is used as an external medium for storing the user's interaction history.

The ontology instances created through the above method are transmitted to the lightweight server 101 as service descriptions for the smart object. 12 is a diagram showing the process. After the lightweight server 101 or smart object service developer creates the Internet of Things ontology instance 501 for the identity of each smart object 102, 103, 104 [Fig. 12 ①], the range of instances to be additionally created is It depends on the role of each smart object. If the role is the lightweight server (VPO) 101, an instance of the task ontology 402 should be created [Fig. 12 ②]. However, in the case of general smart objects (102, 103, 104) other than the lightweight server 101, when context information is created and collected, an instance of the context information ontology 403 is created [Fig. 12 ③, ④], and the service function If is provided, an instance of the service function ontology 404 is created [Fig. 12 ⑤]. Instances created in this way are transmitted to the lightweight server 101 as service specifications for the smart object [Fig. 12 ⑥]. The delivery of these service specifications may be directly transmitted to the lightweight server 101 by the developer or a method in which the lightweight server 101 itself collects from smart objects is also possible.

Ontology instances delivered through the above process are service specifications of smart objects, and have information on what functions exist in the current space and what kind of contextual information smart object services exist. Accordingly, the lightweight server 101 that stores these service specifications can configure user tasks covering multiple service domains based on function information of each service. For example, if a smart air conditioner providing a function to maintain a room at an appropriate temperature, a smart projector providing a presentation function, and a smart light fixture providing a lighting control function deliver service specifications, the lightweight server 101 bundles them together. You can configure a user task called “Have a team meeting”. These user tasks may be directly configured by a system or lightweight server developer, but the lightweight server 101 may configure itself through reasoning when an interaction history with a user is sufficiently accumulated. That is, the lightweight server 101 stores the context information of interest from surrounding smart objects, and based on this, records the user interaction history of how a specific user behaved in a certain situation, and then based on this, the user in a specific situation After constructing action or task information by itself, when a specific situation is recognized in the future, smart object services suitable for performing the task can be automatically called.

Through the above process, all ontology instances corresponding to the smart object configuration and task scenarios in [Table 2] above are created, and the above instances are the lightweight server 101 in charge of the seminar room, respectively, or the integrated control module in charge of the break room. A process of providing a service corresponding to a task to be performed by a user after being transmitted as a service specification to the smart TV, which is the server 101, will be described as follows.

As a method for determining the task to be performed by the user, the user may directly set a specific task to the server 101 and issue an execution command, or the server 101 may infer and determine the user's intention to perform the task based on context information. there is.

First, a case where a user directly gives a command to perform a specific task to the server 101 will be described. When a user enters the lounge and commands the smart TV of the server 101 in charge of the IoT system in the lounge to perform a 'watching movie' task, the server 101 generates a task ontology instance 801 corresponding to the viewing movie task. ) and that the activity instance 802 connected to the task through the composedOf relationship 803 has the functions of turning on the smart TV, changing the screen input mode to a video playback image source, playing a video file, turning on the air conditioner, and adjusting the brightness of the lights. figure out Afterwards, the Functionality instance 601 connected to each of the above activity instances 802 through the supportedBy (804) relationship is identified, and the service instance 506 connected to each Functionality instance 601 through the providedFunctionality relationship 602 is identified, Furthermore, IoT_Element instance 501 connected to service instance 506 through providedService relationship 507 and exposedAs relationship 505 is traced. Through this process, the server 101 can identify the smart object 501 capable of providing the service 506 corresponding to each activity instance 802 constituting the 'watching a movie' task, A service provision request can be sent to the smart object 501 .

Each smart object 501 receiving the above service provision request from the server 101 may directly provide the service to the user, but the situation obtained from other smart objects 102, 103, and 104 via the server 101 Based on the information and the history of each smart object 501's interaction with the user so far, specific contents of the service may be determined and provided, that is, a personalized service may be provided to the user. For example, when a request to provide a brightness control service for a light, which is one of the smart objects, is transmitted from the server 101 according to a command to perform a 'watch a movie' task, the light is set to a brightness that has been set mainly by the user while watching a movie. The brightness of the lamp may be adjusted to the brightness corresponding to the user interaction history stored in the internal storage unit 302 of the lamp. In this way, when each smart object 501 that has received a service provision request provides a personalized service to the user by its own judgment, compared to a system in which all judgments are made in the server 101, the judgment ability is distributed, so that the existing central It is possible to provide intelligent services while mitigating the single point of failure problem, which is a disadvantage of centralized IoT systems.

Next, as another method for determining the task to be performed by the user, a method for the server 101 to infer and determine the user's intention to perform the task based on context information without a direct command from the user will be described. This is explained along with how to set up the structure on which the reasoning is based. A method of setting a structure that is the basis of reasoning is shown in FIG. 14 .

Since the user's intention to perform the task is variable according to the surrounding situation, this variability must be reflected in the ontology design. To achieve this purpose, in the present invention, the user (805), place (806), and task (801) are placed at the center of the task ontology (402), and the link is defined as follows.

(1) The lightweight server 101 always collects the user's task performance history in order to utilize it to determine the user's intention. In order to understand how the user's intention to perform the task varies depending on the situation, the accumulated user interaction data is analyzed [Fig. 14 ①].

(2) As a result of data analysis, context information that is determined to affect the user's task performance intention for each place is created as an ontology instance 701 of Context type [Fig. 14 ②].

(3) In order to associate the created situation information instance 701 with the place where the task was performed, a hasContext relationship 807 is defined (e.g., SeminarRoom-hasContext-Temperature, SeminarRoom-hasContext-PresentUserCount) [Fig. 14 ③] .

(4) User tasks performed by each place, which can be characterized by various contextual information, are created as a Task type ontology instance 801, and the user 805, place 806, contextual information 701, task 801 ) is connected in the relationship of User (805)-locatedIn (808)-Place (806), User (805)-conducts (809)-Task (801) [Fig. 14 ④].

(5) The user recognizes the use of the place currently located in various ways depending on past experiences. In this way, how the user perceives the current place is defined as placeness 810 in one embodiment of the present invention (e.g., meeting rooms are various places such as meetings, meals, phone calls, and group studies depending on the case). surname) [Fig. 14 ⑤].

A user's variable intention related to task performance may be determined based on the above-described placeness 810 . Therefore, the ontologies created through the relationship of hasContext (807), locatedIn (808), and conducts (809) are collectively defined as the concept of placeness (810) that the user has. For example, if a specific user listens to music in a conference room on a rainy day, the user may perceive the situation of the conference room on a rainy day as a placeness of a music listening room.

(6) After creating an ontology instance 810 for placeness, it is connected in the relationship of User(805)-hasPlaceness(811)-Placeness(810) [Fig. 14 ⑥].

(7) The result of analyzing the user's task performance history configured in the frame of Context (701) - Place (806) - Placeness (810) - User (805) - Task (801) can be applied to grasp the user's intention to perform the task. [Fig. 14 ⑦].

For example, as a result of a Smart TV, a server 101 in charge of a break room, collecting user A's task performance history and the corresponding situation information history for a certain period of time and analyzing the task performance history, 'Every rainy day, user A When it is identified that 'I listened to music in the conference room', the "Task-User-Place-Context" relationship for this user, "Listening to music-User A-Conference room-Rainy day", is the Placeness of "Listening to music" for User A. 811, and in the future, when user A enters the meeting room on a rainy day, the server 101, Smart TV, uses the above information to determine that the placeness is a "music listening room" and the task associated with the placeness. A command to perform the “listen to music” task may be given through reasoning. In this way, when the server 101 infers the task itself, even if the user does not directly issue a task execution command, the service desired by the user is automatically provided by the various smart objects 102, 103, and 104 in cooperation, so in terms of user convenience It works great.

The user's task performance history is analyzed above to recognize contextual information that is determined to affect the user's task performance intention, and based on the analysis result, it is used to infer the user's task performance intention from contextual information collected in real time in the future. As a method, there are a rule-based reasoning method and a pattern-based reasoning method, but the reasoning method is not limited thereto. An example of a rule-based reasoning method is association rule mining, and examples of a pattern-based reasoning method include Hidden Markov Model (HMM) and Hidden Markov Logic (HML).

Next, a method of providing a user personalized service of the smart object 501 requested to provide a service to perform a task will be described.

Each of the smart objects 501 received a service provision request from the server 101 that manages the collaboration of smart objects for task performance does not simply provide the requested service mechanically, but also provides information on the interaction history with the user in the meantime. It is possible to provide a personalized service to the user from In this way, in order to personalize the service provision method of each smart object for the user, each smart object must collect the interaction history with the user, find a meaningful pattern from the collected and accumulated user interaction history information, and use it as the user's preference. have to learn

Various techniques can be applied for pattern discovery and learning, examples of which are Neural Networks, SVM, Clustering, Decision Tree, Association Rule Mining, and Rough Set Theory techniques, but the pattern discovery and learning techniques are not limited thereto.

The level of personalized service provided may vary according to the classification of the corresponding smart object. In the case of smart objects in the Networked (Level 2) stage, which have relatively low computing power, they can only interpret or infer the information they generate, so in the case of temperature sensors, for example, temperature sensors are generally Numbers are created as data, but meanings such as cold, warm, or hot can be given to the data through the user's interaction history.

In the case of smart objects of the Enhanced (Level 3) stage with more computing power, they can store the context and related knowledge collected from other smart objects together, so they can use it together with the information they have or create, and the smart objects of the Networked stage It is possible to infer and provide services at a more complex level than . For example, if information that the temperature and humidity are high and that many people are staying in the current space is collected from surrounding smart objects, and there is a specific temperature that has been frequently set through the past history, in the case of air conditioning service, for the comfort of users You will be able to turn on the cooling by setting that specific temperature.

15 is a diagram illustrating a control method of the server 101 according to an embodiment of the present invention. The control method includes the steps of storing information about a plurality of tasks provided for each user's behavior and information about a plurality of services that at least one electronic device can perform (S1501), and from the at least one electronic device. Receiving situation information (S1502), determining a task corresponding to the user's behavior indicated by the received situation information from among the plurality of tasks (S1503), and determining a task corresponding to the determined task among the at least one electronic device. and transmitting information about the service to a first electronic device capable of providing the service (S1504).

16 is a diagram illustrating a control method of electronic devices 102, 103, and 104 according to an embodiment of the present invention. The control method includes a step of storing situation information (S1601), a step of receiving information about a service from a server (S1602), and a step of determining and providing the contents of the received service based on the stored situation information (S1603). ).

Although the present invention has been described above with limited embodiments and drawings, those skilled in the art can make various modifications and variations from the above description. For example, the described techniques may be performed in an order different from the method described, or the components of the described system, structure, device, circuit, etc. may be combined or combined in a different form than the method described, or other components or equivalents may be used. Appropriate results can be achieved even if substituted or substituted by Therefore, other implementations, other embodiments and equivalents of the claims are intended to be within the scope of the claims, and the methods disclosed herein are to be considered in an illustrative rather than a limiting sense.

101: server
102, 103, 104: electronic device
401: IoT component ontology
402: task ontology
403: context information ontology
404: service function ontology

Claims (16)

in the server,
A communication unit capable of communicating with at least one electronic device;
a storage unit capable of storing information about a plurality of tasks and information about a plurality of services that the at least one electronic device can provide; and
receive user input;
determining a task corresponding to the user input from among the plurality of tasks;
A processing unit configured to transmit information about the service to a first electronic device capable of providing the service corresponding to the determined task among the at least one electronic device,
The processing unit allows the first electronic device to provide the first situation information collected by the first electronic device and at least one service among the plurality of services, and a second electronic device different from the first electronic device. The server further transmits the second context information to the first electronic device so that content of the service can be determined and provided based on the second context information received from the server. delete According to claim 1,
The server according to claim 1 , wherein the processing unit generates information about the task and at least one service corresponding to the task based on task history information, and stores the information in the storage unit. delete According to claim 1,
The server, characterized in that the plurality of tasks are classified by location. In electronic devices,
A communication unit capable of communicating with the server;
a storage unit capable of storing situation information; and
When receiving information about a service that the electronic device can provide among a plurality of services from the server, a processing unit determining and providing the content of the corresponding service based on the stored situation information;
The context information is collected by first context information collected by the electronic device and a second electronic device capable of providing at least one of the plurality of services and different from the electronic device, and received through the server. An electronic device characterized in that it includes the second situation information. According to claim 6,
The electronic device characterized in that the first and second situation information includes a history of interaction with the user. delete In the IoT system consisting of a server and at least one electronic device,
The server,
a storage unit capable of storing information about a plurality of tasks and information about a plurality of services that the at least one electronic device can provide; and
A first electronic device capable of receiving a user input, determining a task corresponding to the received user input from among the plurality of tasks, and providing the service corresponding to the determined task among the at least one electronic device. Including a processing unit to transmit information about the service,
In transmitting the information about the service, the first electronic device may provide the first situation information collected by the first electronic device and at least one service among the plurality of services, and the first electronic device Characterized in that the second situation information is further transmitted to the first electronic device so that the content of the service can be determined and provided based on the second situation information received from the second electronic device different from the device,
the electronic device,
The third context information collected by the electronic device and a third electronic device including the second electronic device capable of providing at least one service among the plurality of services and different from the electronic device, a storage unit capable of storing situation information including fourth situation information received through the server; and
and a processing unit that determines and provides the content of the corresponding service based on the stored situation information when receiving information about a service that the electronic device can provide among a plurality of services from the server. . delete In the server of claim 9,
The processing unit generates information about the task and at least one service corresponding to the task based on task history information, and stores the information in the storage unit. delete In the server of claim 9,
The IoT system, characterized in that the plurality of tasks are classified by location. In the electronic device of claim 9,
The first to fourth context information includes a history of interaction with the user. In the server control method,
storing information about a plurality of tasks and information about a plurality of services that at least one electronic device can provide;
receiving user input;
determining a task corresponding to the user input from among the plurality of tasks; and
Transmitting information about the service to a first electronic device capable of providing the service corresponding to the determined task among the at least one electronic device,
In the transmitting step, the first electronic device may provide the first situation information collected by the first electronic device and at least one service among the plurality of services, and the second electronic device may be different from the first electronic device. and further transmitting the second context information to the first electronic device so that content of the service can be determined and provided based on the second context information received from the electronic device. delete

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