• Journal of KIISE:Computing Practices and Letters
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• v.12 no.1
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• pp.56-65
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• 2006

Recently the study on service robots has been proliferated in many fields, and there are active developments for indoor services such as supporting for elderly people. It is important for robot to recognize objects and situations appropriately for effective and accurate service. Conventional object recognition methods have been based on the pre-defined geometric models, but they have limitations in indoor environments with uncertain situation such as the target objects are occluded by other ones. In this paper we propose a Bayesian network model to reason the probability of target objects for effective detection. We model the relationships between objects by activities, which are applied to non-static environments more flexibly. Overall structure is constructed by combining common-cause structures which are the units making relationship between objects, and it makes design process more efficient. We test the performance of two Bayesian networks for verifying the proposed Bayesian network model through experiments, resulting in accuracy of $86.5\%$ and $89.6\%$ respectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.1
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• pp.198-205
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• 2007

In ubiquitous environment a user can be provided with context-aware services based on his or her current location, time, and atmosphere. LBS(Location-Based Services) play an important role for ubiquitous context-aware computing. Because deployment and maintenance of this specialized equipment is costly, many studies have been conducted on positioning using only wireless equipment under a wireless LAN infrastructure. Because a CPS(Cooperative Positioning System) that uses the RSSI (Received Signal Strength Indicator) between mobile equipments is more accurate than beacon based positioning system, it requires great concentration in its applications. This study investigates the relationship between nodes by analyzing a WiPS (Wireless LAN indoor Positioning System), a similar type of CPS, and proposes a improved WiCOPS-d(Wireless Cooperative Positioning System using node density) to increase performance by determining the convergence adjustment factor based on node density.

• Information Systems Review
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• v.21 no.4
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• pp.47-68
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• 2019

As cloud services and deployment models become diverse, there are a growing number of cloud computing selection options. Therefore, financial companies need a methodology to select the appropriated cloud for each financial computing system. This study adopted the Balanced Scorecard (BSC) framework to classify factors for the introduction of cloud computing in financial companies. Using Analytic Hierarchy Process (AHP), the evaluation items are layered into the performance perspective and the cloud consideration factor and a comprehensive decision model is proposed. To verify the proposed research model, a system of financial company is divided into three: account, information, and channel system, and the result of decision making by both financial business experts and technology experts from two financial companies were collected. The result shows that some common factors are important in all systems, but most of the factors considered are very different from system to system. We expect that our methodology contributes to the spread of cloud computing adoption.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.79-88
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• 2024

We used actual field data to analyze from a traffic engineering perspective how AI and edge computing technologies affect the reduction of traffic accidents. By providing object information from 20m behind with AI object recognition, the driver secures a response time of about 3.6 seconds, and with edge technology, information is displayed in 0.5 to 0.8 seconds, giving the driver time to respond to intersection situations. In addition, it was analyzed that stopping before entering the intersection is possible when speed is controlled at 11-12km at the 10m point of the intersection approach and 20km/h at the 20m point. As a result, it was shown that traffic accidents can be reduced when the high object recognition rate of AI technology, provision of real-time information by edge technology, and the appropriate speed management at intersection approaches are executed simultaneously.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.5
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• pp.151-155
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• 2017

With the rapid growth of the up-to-date wireless network and Internet technologies, huge and various types of things around us are connected to the Internet and build the hyper-connected society, and lots of smart applications using these technologies are actively developed recently. IoT connects human, things, space, and data with various types of networks to construct the hyper-connected network that can create, collect, share and appling realtime information. Furthermore, most of the smart applications are concentrated on the service that can collect and store realtime contexts using various sensors and cloud technology, and provide intelligence by making inferences and decisions from them nowadays. In this paper, we design a smart application that can accurately control and process the current state of the specific context in realtime by using the state-of-the-art ICT techniques such as various sensors and cloud technologies on the IoT based mobile computing environment.

• The KIPS Transactions:PartD
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• v.12D no.4 s.100
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• pp.647-656
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• 2005

This paper proposes an adaptive resource self-management system that collects system resources, user information, and usage patterns as context information for utilization in self-configuration. This system ill ease the system maintenance burden on users by automation of large part of configuration tasks such as install, reconfiguration and update, and will also decrease cost and errors. Working from the gathered context information, this system allows users to select appropriate components and install them for user's system context. This also offers a more personalized configuration setting by using user's existing application setting and usage pattern. To avoid the overload on central server to transfer and manage related files, we employ Peer-to-Peer method. h prototype was developed to evaluate the system and a comparison study with the conventional methods of manual configuration and MS-IBM systems was conducted to validate the proposed system in terms of functional capacity, install time and etc.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.7
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• pp.551-562
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• 2013

Current CCTV systems, which require continuous monitoring of the screens, have the limitation to detect and respond to the crime scenes in timely manner. Therefore, in recent years, the request for more intlligent surveillance system, with a ubiquitous sensor network, is increasing in order to behave more humanly fashions. Such systems require cllective data processing of the environments based on various sensors. In this article, we suggests a new paradigm based surveillance system which integrates PSD and dual PIR sensors. The proposed system evlves from a existing indoor intrusion detection system which can only identify the intrusion event to a better inteligent system with context awareness. We have conducted the various simulations in order to prove the effectiveness of the proposed system.

• Journal of KIISE:Software and Applications
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• v.32 no.3
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• pp.192-201
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• 2005

For the past ten years, the goal of ubiquitous computing research has been the establishment of a new technology system with the aim 'Anytime, Anywhere, and Any form'. The needs for agent technology innovations such as ontology-based structure, ontology-based agent communication language, and multi-agents frameworks have been identified. This paper proposes a noble multi-agents architecture for ubiquitous systems. We suggest four major steps in the interaction between human and agents which enable ubiquitous agents to process by themselves to provide adaptive service to meet human's needs. First, we propose a semantic web technology to represent the association between information resources more explicitly Second, we construct a semantic ontology so that agents can recognize web contents.'Third, we propose a method to communicate between agents using OWL ontologies. Finally, we suggest a multi-agents structure based on the JADE of FIPA to analyze messages and get information. The semantic multi-agents framework proposed in this paper infers semantic situations using semantic web technology based on ontologies. A service provided is inferred differently according to user state because the multi-agents communicate by using OWL ontology language. Therefore, our system better infers context information than other without ontologies.

• Journal of Digital Contents Society
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• v.18 no.3
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• pp.535-542
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• 2017

The ubiquitous computing made it happen to easily take cognizance of context, which includes user's location, status, behavior patterns and surrounding places. And it allows providing the catered service, designed to improve the quality and the interaction between the provider and its customers. The personalized recommendation service needs to obtain logical reasoning to interpret the context information based on user's interests. We researched a model that connects to the practical value to users for their daily life; information about restaurants, based on several mobile contexts that conveys the weather, time, day and location information. We also have made various approaches including the accurate rating data review, the equation of Naïve Bayes to infer user's behavior-patterns, and the recommendable places pre-selected by preference predictive algorithm. This paper joins a vibrant conversation to demonstrate the excellence of this approach that may prevail other previous rating method systems.

• Smart Media Journal
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• v.13 no.3
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• pp.9-17
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• 2024

Due to the recent pandemic and the development of ICT technology, the use of non-face-to-face and unmanned systems is expanding, and it is very important to understand emotions in communication in non-face-to-face situations. As emotion recognition methods for various facial expressions are required to understand emotions, artificial intelligence-based research is being conducted to improve facial expression emotion recognition in image data. However, existing research on facial expression emotion recognition requires high computing power and a lot of learning time because it utilizes a large amount of data to improve accuracy. To improve these limitations, this paper proposes a method of recognizing facial expressions using age and gender, which are image meta information, as a method of recognizing facial expressions with even a small amount of data. For facial expression emotion recognition, a face was detected using the Yolo Face model from the original image data, and age and gender were classified through the VGG model based on image meta information, and then seven emotions were recognized using the EfficientNet model. The accuracy of the proposed data classification learning model was higher as a result of comparing the meta-information-based data classification model with the model trained with all data.