• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.6
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• pp.2050-2077
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• 2015

One of the major issues in emerging cloud management system needs the efficient service level agreement negotiation framework, with an optimal negotiation strategy. Most researchers focus mainly on the atomic service negotiation model, with the assistance of the Agent Controller in the broker part to reduce the total negotiation time, and communication overhead to some extent. This research focuses mainly on composite service negotiation, to further minimize both the total negotiation time and communication overhead through the pre-request optimization of broker strategy. The main objective of this research work is to introduce an Automated Dynamic Service Level Agreement Negotiation Framework (ADSLANF), which consists of an Intelligent Third-party Broker for composite service negotiation between the consumer and the service provider. A broker consists of an Intelligent Third-party Broker Agent, Agent Controller and Additional Agent Controller for managing and controlling its negotiation strategy. The Intelligent third-party broker agent manages the composite service by assigning its atomic services to multiple Agent Controllers. Using the Additional Agent Controllers, the Agent Controllers manage the concurrent negotiation with multiple service providers. In this process, the total negotiation time value is reduced partially. Further, the negotiation strategy is optimized in two stages, viz., Classified Similarity Matching (CSM) approach, and the Truncated Negotiation Group Gale Shapely Stable Matching (TNGGSSM) approach, to minimize the communication overhead.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.11
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• pp.2016-2034
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• 2011

Ubiquitous Healthcare (u-Healthcare) is the intelligent delivery of healthcare services to users anytime and anywhere. To provide robust healthcare services, recognition of patient daily life activities is required. Context information in combination with user real-time daily life activities can help in the provision of more personalized services, service suggestions, and changes in system behavior based on user profile for better healthcare services. In this paper, we focus on the intelligent manipulation of activities using the Context-aware Activity Manipulation Engine (CAME) core of the Human Activity Recognition Engine (HARE). The activities are recognized using video-based, wearable sensor-based, and location-based activity recognition engines. An ontology-based activity fusion with subject profile information for personalized system response is achieved. CAME receives real-time low level activities and infers higher level activities, situation analysis, personalized service suggestions, and makes appropriate decisions. A two-phase filtering technique is applied for intelligent processing of information (represented in ontology) and making appropriate decisions based on rules (incorporating expert knowledge). The experimental results for intelligent processing of activity information showed relatively better accuracy. Moreover, CAME is extended with activity filters and T-Box inference that resulted in better accuracy and response time in comparison to initial results of CAME.

• Journal of the Korea Society of Computer and Information
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• v.15 no.10
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• pp.147-156
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• 2010

There are some of the studies on sensor middleware. However the standard middleware has not yet been defined. Especially, this paper focuses on the processing an intelligent service of the main functions of middleware. Several applications in the sensor network environment support not only monitoring services, but also sensor-based context-awareness and intelligent services based on sensors. However, the previous studies about USN middleware only mentioned the need for intelligent service and did not discuss the architecture and method for supporting the intelligent service in detail. Therefore this paper designs a USN middleware for providing intelligent services and proposes the method for processing the services. For this purpose, this paper proposes the Sensor-Service ontology to define the concept of services and sensors for USN applications and the relationship between them. The Sensor-Service ontology is used to infer high-level information from low-level information. To apply a variety of environmental context to intelligent services, the paper uses the rule-based reasoning. This paper implements the proposed intelligent service middleware as a prototype and then shows that the middleware can be used for a variety of USN applications through the performance evaluation.

• Journal of Korea Spatial Information System Society
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• v.11 no.1
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• pp.157-168
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• 2009

Geospatial information, which deeply has an effect on our life, have been evolved as intelligent geospatial information in Ubiquitous era. Also, Various services are introduced using the intelligent geospatial information. However, there is no classification system, for understanding the intelligent geospatial information services, considering any developers and users. It needs to be classification system to classify these services. In this paper, we introduced a concept of intelligent geospatial information and developed a service classification matrix regarding to the features of the services. This service classification matrix has three scales; service domain, service intelligent level, and geo-location accuracy. The propose of this matrix can be utilized in two aspects. First, the matrix can improve the reality that doesn't reflect actual demands for the services. Second, the matrix can present the goal of the new services or the development direction. The matrix can be utilized to the geospatial industry as creating the new blue ocean services. However, the service classification matrix needs to modify and complement to have no anything wrong when the various services are applied to the matrix. In the long run, the matrix has to be utilized as a material to make out a service roadmap or TRM(Technical Reference Model).

• Journal of Korean Society of Rural Planning
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• v.21 no.4
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• pp.177-186
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• 2015

The main objective of this study was to assess the applicability of IoT (Internet of Things)-based flood management under climate change by developing intelligent water level monitoring platform based on IoT. In this study, Arduino Uno was selected as the development board, which is an open-source electronic platform. Arduino Uno was designed to connect the ultrasonic sensor, temperature sensor, and data logger shield for implementing IoT. Arduino IDE (Integrated Development Environment) was selected as the Arduino software and used to develop the intelligent algorithm to measure and calibrate the real-time water level automatically. The intelligent water level monitoring platform consists of water level measurement, temperature calibration, data calibration, stage-discharge relationship, and data logger algorithms. Water level measurement and temperature calibration algorithm corrected the bias inherent in the ultrasonic sensor. Data calibration algorithm analyzed and corrected the outliers during the measurement process. The verification of the intelligent water level measurement algorithm was performed by comparing water levels using the tape and ultrasonic sensor, which was generated by measuring water levels at regular intervals up to the maximum level. The statistics of the slope of the regression line and $R^2$ were 1.00 and 0.99, respectively which were considered acceptable. The error was 0.0575 cm. The verification of data calibration algorithm was performed by analyzing water levels containing all error codes in a time series graph. The intelligent platform developed in this study may contribute to the public IoT service, which is applicable to intelligent flood management under climate change.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.146.2-146
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• 2001

Recently, a need of non-industrial robot, such as service, medical, entertainment and house-keeping robot, has been increased. Therefore, the capability of robot which can do intelligent behavior like interaction with men and its environment become more prominent than the capability of executing simple repetitive task. To implement an intelligent robot which provides intelligent behavior, an effective system architecture including perception, learning, reasoning and action part is necessary. Control architectures for intelligent robot can be divided into two different classes. One is deliberative type controller which is applicate to high level intelligence like environment ...

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.163-171
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• 2023

The intelligent transportation system has made a huge leap in the level of human services, which has had a positive impact on the quality of life of users. On the other hand, these services are becoming a new source of risk due to the use of data collected from vehicles, on which intelligent systems rely to create automatic contextual adaptation. Most of the popular privacy protection methods, such as Dummy and obfuscation, cannot be used with many services because of their impact on the accuracy of the service provided itself, they depend on changing the number of vehicles or their physical locations. This research presents a new approach based on the shuffling Nicknames of vehicles. It fully maintains the quality of the service and prevents tracking users permanently, penetrating their privacy, revealing their whereabouts, or discovering additional details about the nature of their behavior and movements. Our approach is based on creating a central Nicknames Pool in the cloud as well as distributed subpools in fog nodes to avoid intelligent delays and overloading of the central architecture. Finally, we will prove by simulation and discussion by examples the superiority of the proposed approach and its ability to adapt to new services and provide an effective level of protection. In the comparison, we will rely on the wellknown privacy criteria: Entropy, Ubiquity, and Performance.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.2
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• pp.108-117
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• 2009

The South Korean government is looking for a solution to the ever-growing problems of traffic congestion, and surging international oil prices: the use of the humble bicycle to get to places. However, Many people feel inconvenient using bicycle because of the insufficient bicycle infrastructure and lack of the safety and connectivity between existing pathways. In this study, bicycle level of service model using ordered probit model is developed considering safety, convenience, connectivity, and factors that affect bicycle LOS. The ordered probit model would be recommended for the research which relates in choice, preference and strength etc. Bicycle level of service criteria is calculated by applying this model reflecting bicyclist's point of view. The model which develops from this research which accomplishes a bicycle level of service evaluation and represent alternative solution to encourage bicyclist. It is believed that the proposed model would be greatly utilized in bicycle network planning, bicycle road and facility alternatives testing, projects funding priority.

• Journal of KIISE
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• v.43 no.12
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• pp.1365-1375
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• 2016

One of the most important capabilities for autonomous service robots working in living environments is to recognize and understand the correct context in dynamically changing environment. To generate high-level context knowledge for decision-making from multiple sensory data streams, many technical problems such as multi-modal sensory data fusion, uncertainty handling, symbolic knowledge grounding, time dependency, dynamics, and time-constrained spatio-temporal reasoning should be solved. Considering these problems, this paper proposes an effective dynamic context management and spatio-temporal reasoning method for intelligent service robots. In order to guarantee efficient context management and reasoning, our algorithm was designed to generate low-level context knowledge reactively for every input sensory or perception data, while postponing high-level context knowledge generation until it was demanded by the decision-making module. When high-level context knowledge is demanded, it is derived through backward spatio-temporal reasoning. In experiments with Turtlebot using Kinect visual sensor, the dynamic context management and spatio-temporal reasoning system based on the proposed method showed high performance.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.2
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• pp.41-54
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• 2013

In this paper, We collected location based services of the user's past moving paths through the GPS. Using the collected by location-based services through the analysis of the similarity between the user's of service level agreement recommended of mobile contact area(SLA) proposed that can be. S-RCA method based on Service Level Agreement of the users in order to provide the service user's path distance, time, and to predict the direction of the movement paths and collect. The data collected by the interests and requirements of users through classification with the same interests and the needs of users to move between the analysis of the similarity between the path is used to analyze the results of analysis of the path-specific tolerance range (distance, time, and space) is determined according to the difference in the contact area. From a small area of the error range for users first to recommended and through their smartphones recommended contact area (S-RCA) to meet with the other party to make a choice of recommended methods. We verify through experiments that proposed method(S-RCA) a valid and reliable mobile contact area were recommended.