• Journal of IKEEE
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• v.11 no.4
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• pp.279-282
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• 2007

In this paper, we introduce the general way for producing context information to support context-aware applications. It can fetch raw data from the service environments, translate it to reasonable context information, and provide to multiple applications. It is designed originally for the ubiquitous computing middleware and based on the ontology processing model. Automated service applications can use this system as the form of libraries or of web services for deciding its semantic cause of action.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.5
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• pp.209-218
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• 2005

In this paper, we propose CIVE, context-based interactive system for heterogeneous distributed virtual environments that delivers contexts irom real world to virtual environment and vice versa. The proposed system ronsists of obi-UCAM for generating user's contexts, NAVER for managing virtual environment, and Interface for linking obi-UCAM with NAVER. The connection between real and virtual worid through context is brneficial in following ways. Firstly. CIVE Provides a personalized user interface for virtual environment according to a user profile such as identity, age and vernacular. Secondly, translating all input signals into context, it guarantees adaptive access that enables a user to exploit unencumbered input devices controlling a shared object in virtual environment even if he moves with his own device from a virtual system to another. Finally, it provides a mechanism for synchronizing distributed virtual systems that share context representing changes at remote nodes. The context reduces the inconsistency of representing the same data among heterogeneous systems. Therefore, CIVE plays an important role in implementing VR applications such as teleconference, game and entertainment.

• Journal of Korea Entertainment Industry Association
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• v.13 no.4
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• pp.63-70
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• 2019

We extract the symptom of panic disorder from the context awareness environment. It extracts body context information through natural movement that exists in everyday life and uses a component of panic disorder. The ontology theory can be used to provide information on the degree of symptoms of panic disorder through inference process. For the components of panic disorder to the information processing based on ontology are defined as Classes. Panic disorder index is expressed through ontology modeling so that the condition of panic disorder can be known. The derivation of panic disorder component and panic disorder index will enable context awareness based information service for panic disorder. The context information is periodically synchronized with the context awareness on based device. Panic disorder can be used to improve the lifestyle of panic disorder.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1159-1166
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• 2010

Today, detecting the location of moving object has been traced as various methods in our world. In this paper, we preset the system to improve the estimation accuracy utilizing detail localization using radar sensor based on WSN and situational awareness for a calibration (context aware) database, Rail concept. A variety of existing location tracking method has a problem with receiving of data and accuracy as tracking methodology, and since these located data are the only data to be collected for location tracing, the context aware or monitering as the surrounding environment is limited. So, in this paper, we enhanced the distance aware accuracy using radar sensor utilizing the Doppler effect among the distance measuring method, estimated the location using the Triangulation algorithm. Also, since we composed the environment data(temperature, illuminancem, humidity, noise) to entry of the database, it can be utilized in location-based service according to the later action information inference and positive context decision. In order to verify the validity of the suggested method, we give a few random situation and built test bed of designed node, and over the various test we proved the utilizing the context information through route tracking of moving and data processing.

• The KIPS Transactions:PartA
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• v.15A no.1
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• pp.35-44
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• 2008

It is important to manage access control for secure ubiquitous applications. In this paper, we present an access-control system for executing policy file which includes access control rules. We implemented Context-aware Access Control Manager(CACM) based on Java Context-Awareness Framework(JCAF) which provides infrastructure and API for creating context-aware applications. CACM controls accesses to method call based on the access control rules in the policy file. We also implemented a support tool to help programmers modify incorrect access control rules using static analysis information, and a simulator for simulating ubiquitous applications. We describe simulation results for several ubiquitous applications.

• Knowledge Management Research
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• v.9 no.4
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• pp.51-63
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• 2008

Effective energy consumption now becomes one of the area of knowledge management which potentially gives global impact. It is considerable for the energy management to optimize the usage of energy, rather than decreasing energy consumption at any cases. To resolve these challenges, an intelligent and personalized system which helps the individuals control their own behaviors in an optimal and timely manner is needed. So far, however, since the legacy energy management systems are nation-wide or organizational, individual-level energy management is nearly impossible. Moreover, most estimating methods of energy consumption are based on forecasting techniques which tend to risky or analysis models which may not be provided in a timely manner. Hence, the purpose of this paper is to propose a novel individual-level energy management system which aims to realize timely and personalized energy management based on context-aware computing approach. To do so, an index model for energy consumption is proposed with a corresponding service framework.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.4
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• pp.44-50
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• 2017

To understand whether Falling, which is one of the causes of injuries, occurs, various behavior recognition research is proceeding. However, in most research recognize only the fact that Falling has occurred and provide the service. As well as the occurrence of the Falling, the risk varies greatly based on the type of Falling and the situation before and after the Falling. Therefore, when Falling occurs, it is necessary to infer the user's current situation and provide appropriate services. In this paper, we propose to base on Fog Computing and Cloud Computing to design Context-aware System using analysis of behavior data and process sensor data in real-time. This system solved the problem of increase latency and server overload due to large capacity sensor data.

• ETRI Journal
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• v.29 no.2
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• pp.169-178
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• 2007

With the advent of ubiquitous computing environments, it has become increasingly important for applications to take full advantage of contextual information, such as the user's location, to offer greater services to the user without any explicit requests. In this paper, we propose context-aware active services based on context-aware middleware for URC systems (CAMUS). The CAMUS is a middleware that provides context-aware applications with a development and execution methodology. Accordingly, the applications based on CAMUS respond in a timely fashion to contextual information. This paper presents the system architecture of CAMUS and illustrates the content recommendation and control service agents with the properties, operations, and tasks for context-aware active services. To evaluate CAMUS, we apply the proposed active services to a TV application domain. We implement and experiment with a TV content recommendation service agent, a control service agent, and TV tasks based on CAMUS. The implemented content recommendation service agent divides the user's preferences into common and specific models to apply other recommendations and applications easily, including the TV content recommendations.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.253-255
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• 2003

We address an integrated multimedia framework based on a software agent platform for context-aware multimedia computing. We adopt the FIPA (Foundation for Intelligent Physical Agents) platform which provides agent communications and management mechanisms. In order to express context information, we use MPEG-21 metadata for describing user characteristics and usage environment. We encapsulate such context information as a FIPA message to be delivered between agents. Based on context information, appropriate multimedia content delivery becomes possible. We present our system implementation with a use case scenario and show that our proposed framework is effective for context-aware multimedia computing so that personalization of multimedia consumption can be possible.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.1
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• pp.25-32
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• 2020

In the context-aware system, rule-based AI technology has been used in the abstraction process for getting context information. However, the rules are complicated by the diversification of user requirements for the service and also data usage is increased. Therefore, there are some technical limitations to maintain rule-based models and to process unstructured data. To overcome these limitations, many studies have applied machine learning techniques to Context-aware systems. In order to utilize this machine learning-based model in the context-aware system, a management process of periodically injecting training data is required. In the previous study on the machine learning based context awareness system, a series of management processes such as the generation and provision of learning data for operating several machine learning models were considered, but the method was limited to the applied system. In this paper, we propose a training data generating method of a machine learning model to extend the machine learning based context-aware system. The proposed method define the training data generating model that can reflect the requirements of the machine learning models and generate the training data for each machine learning model. In the experiment, the training data generating model is defined based on the training data generating schema of the cardiac status analysis model for older in health status notification service, and the training data is generated by applying the model defined in the real environment of the software. In addition, it shows the process of comparing the accuracy by learning the training data generated in the machine learning model, and applied to verify the validity of the generated learning data.