• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.4
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• pp.825-840
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• 2015

Adaptive bitrate (ABR) streaming technology has become an important and prevalent feature in many multimedia delivery systems, with content providers such as Netflix and Amazon using ABR streaming to increase bandwidth efficiency and provide the maximum user experience when channel conditions are not ideal. Where such systems could see improvement is in the delivery of live video with a closed loop cognitive control of video encoding. In this paper, we present streaming camera system which provides spatially and temporally adaptive video streams, learning the user's preferences in order to make intelligent scaling decisions. The system employs a hardware based H.264/AVC encoder for video compression. The encoding parameters can be configured by the user or by the cognitive system on behalf of the user when the bandwidth changes. A cognitive video client developed in this study learns the user's preferences(i.e. video size over frame rate) over time and intelligently adapts encoding parameters when the channel conditions change. It has been demonstrated that the cognitive decision system developed has the ability to control video bandwidth by altering the spatial and temporal resolution, as well as the ability to make scaling decisions.

• Journal of IKEEE
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• v.21 no.4
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• pp.412-415
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• 2017

In this paper, we propose a multi license plate recognition system using high resolution $360^{\circ}$ omnidirectional IP camera. The proposed system consists of a planar division part of $360^{\circ}$ circular image and a multi license plate recognition part. The planar division part of the $360^{\circ}$ circular image are divided into a planar image with enhanced image quality through processes such as circular image acquisition, circular image segmentation, conversion to plane image, pixel correction using color interpolation, color correction and edge correction in a high resolution $360^{\circ}$ omnidirectional IP Camera. Multi license plate recognition part is through the multi-plate extraction candidate region, a multi-plate candidate area normalized and restore, multiple license plate number, character recognition using a neural network in the process of recognizing a multi-planar imaging plates. In order to evaluate the multi license plate recognition system using the proposed high resolution $360^{\circ}$ omnidirectional IP camera, we experimented with a specialist in the operation of intelligent parking control system, and 97.8% of high plate recognition rate was confirmed.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.1
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• pp.31-37
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• 2024

In this study, we propose a machine vision-based pedestrian signal detection algorithm that operates efficiently even in computing resource-constrained environments. This algorithm demonstrates high efficiency within limited resources and is designed to minimize the impact of ambient lighting by sequentially applying HSV color space-based image processing, binarization, morphological operations, labeling, and other steps to address issues such as light glare. Particularly, this algorithm is structured in a relatively simple form to ensure smooth operation within embedded system environments, considering the limitations of computing resources. Consequently, it possesses a structure that operates reliably even in environments with low computing resources. Moreover, the proposed pedestrian signal system not only includes pedestrian signal detection capabilities but also incorporates IoT functionality, allowing wireless integration with a web server. This integration enables users to conveniently monitor and control the status of the signal system through the web server. Additionally, successful implementation has been achieved for effectively controlling 50W LED pedestrian signals. This proposed system aims to provide a rapid and efficient pedestrian signal detection and control system within resource-constrained environments, contemplating its potential applicability in real-world road scenarios. Anticipated contributions include fostering the establishment of safer and more intelligent traffic systems.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.3
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• pp.208-217
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• 2016

This paper describes a simulation method to generate sensor measurements for location estimation of an underwater robot. Field trial of a navigation method of an underwater robot takes much time and expenses and it is difficult to change the environment of the field trial as desired to test the method in various situations. Therefore, test and verification of a navigation method through simulation is inevitable for underwater environment. This paper proposes a method to generate sensor measurements of range, depth, velocity, and attitude taking the uncertainties of measurements into account through simulation. The uncertainties are Gaussian noise, outlier, and correlation between the measurement noise. Also, the method implements uncertainty in sampling time of measurements. The method is tested and verified by comparing the uncertainty parameters calculated statistically from the generated measurements with the designed uncertainty parameters. The practical feasibility of the measurement data is shown by applying the measurement data for location estimation of an underwater robot.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2002.11a
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• pp.363-369
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• 2002

가정 내에서의 초고속망 이용이 활성화되면서 가정 내에서의 활동은 매우 다양하고 복잡하며 그에 따른 서비스도 여러 가지 형태가 존재한다. 외부 인터넷망과 연동되는 홈 네트워크의 개념이 생기기 전부터 흠 오토메이션, 홈시큐리티 등의 서비스를 제공하기 위한 고립적인 형태의 망과 서비스 제공 시스템이 있었다. 월드 와이드 웹 서비스를 기본으로 한 인터넷의 폭발적인 활성화와 고속 인터넷망의 확산에 따라 가정 내에서 제공되는 서비스를 인터넷과 연계시키려는 시도가 보편화되었고 가정 내에서 사용되는 독립적인 기기들을 인터넷에 연결하여, 외부의 정보를 이용해서 활용하거나, 가전내의 기기들을 외부에서 액세스할 수 있게 되었다. 이렇게 하여 보다 풍부한 서비스를 제공하고, 사용상의 시간적인 제약을 완화할 수 있다. 예들 들어 인터넷상에서 조리법을 전송받아 전자레인지를 작동할 수 있으며, 외부에서 잘못 켜둔 가스밸브를 잠글 수도 있다. 가정 내에서 wrhd되던 이러한 서비스들은 서로 다른 하드웨어와 통신방법을 사용하고 있어, 이러한 서비스를 통합하여 운영, 관리할 수 있도록 하는 흠 서버의 개념이 대두되었다. 외부 인터넷 망과 연계된 흠 오토메이션, 홈 시큐리티등을 제공할 수 있는 기반이 마련되었고, 가정 내에서 독립적으로 제공되던 서비스들을 단일 홈 서버를 통해서 관리하려는 시도가 진행되었다. 그러나 홈 서버는 개발하는 업체의 보유기술에 따라 중심기능은 약간씩 차이를 보이고 있다. 홈 서버 응용 영역은 전문 지식을 소유한 인력과의 연계가 필요하고, 다양한 서비스 영역 행위가 아주 복잡하기 때문에 이들을 연결해 주는 자치 시스템을 필요로 한다. 또한 홈 서버 서비스 영역에서 정보는 각 영역 전문가가 가진 지식의 전달을 필요로 하기 때문에, 지식을 주고받는 멀티 에이전트의 시스템의 활용 영역으로 적당하다. 멀티 에이전트 시스템은 분산된 환경에서 에이전트간에 에이전트 통신 언어를 사용해서 대화를 하기도 하고, 상호 협력하는 에이전트들로 구성된 시스템을 뜻하며 흠 서버처럼 동적이고 고도의 자치성을 요구하는 영역에 적당하다. 멀티 에이전트 플랫폼으로는 FIPA(Foundation for Intelligent Physical Agents)가 제시한 에이전트 표준 플랫폼이 1997년부터 2000년에 이르기까지, 계속적으로 변화, 발전하고 있다. 본 연구는 FIPA에서 제시하는 플랫폼을 기반으로 홈 서버에 정보가전을 제어하는 에이전트를 두고 외부에서 다른 에이전트가 홈 서버에 위치하는 에이전트와의 통신을 통하기 정보가전을 지능적으로 제어하도록 하였다. 정보가전 에이전트는 가정 내 가전제품을 외부에서 제어하기 위한 에이전트이다. 단순한 관리가 아닌 에이전트로 하여금 지능적으로 가전제품 관리를 하게 한다. 정보가전 에이전트는 홈 서버에서 작동하는 에이전트와 PDA에서 작동하는 에이전트로 구성된다. 정보가전 에이전트는 전력량, 수도 사용량 제어와 가전제품 제어 기능과 보안 관련 서비스를 제공한다. 두 에이전트는 FIPA에서 정의된 규격에 맞게 만들어지기 때문에 FIPA명세서를 따르는 다른 에이전트와 자유로운 통신이 가능하다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.32-35
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• 2019

One of the major problems with the livestock industry is that in the summer, livestock will die from heat waves or infectious diseases. Under these circumstances, what livestock need is a proper indoor temperature and a regular sterilization system. Therefore, in this study, we developed a system that automatically controls the power of the fan according to the temperature inside the shaft, and a function that provides feed and sterilization on a regular basis, so that we could manage the toast efficiently. It also proposed the ability to automatically control the power of the fan, to display the temperature inside the shaft to mobile applications, and to provide food and sterilization. First, the function of controlling the power of the fan automatically turns the fan on when the temperature inside the shaft rises above a certain level. Conversely, if the temperature inside the shaft falls below a certain level, turn off the fan. Second, the function of the mobile application is to check the temperature inside the shaft. The third feeding function is periodically fed using a servo motor, and the feeding provided is delivered to livestock through a conveyor belt. Finally, the sterilization function is a function to sterilize livestock periodically using DC motor pump. The intelligent congratulatory functions proposed in this study may contribute to the health of livestock.

• Journal of Internet Computing and Services
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• v.17 no.5
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• pp.17-23
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• 2016

Wireless sensor-actuator networks (WSANs) enhance the existing wireless sensor networks (WSNs) by equipping sensor nodes with an actuator. The actuators work with the sensor nodes and perform application-specific operations. The WSAN systems have several applications such as disaster relief, intelligent building, military surveillance, health monitoring, and infrastructure security. These applications require capability of reliable data transfer to act responsively and accurately. Biologically inspired modeling techniques have received considerable attention for achieving robustness, scalability, and adaptability, while retaining individual simplicity. In this paper, an epidemic-inspired algorithm for data dissemination with delay constraints while minimizing energy consumption in WSAN is proposed. The steady states and system stability are analyzed using control theory. Also, simulation results indicate that the proposed scheme provides desirable dissemination delay and energy saving.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1705-1711
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• 1991

On-line fault detection and diagnosis has an increasing interest in a chemical process industry, especially for a process control and automation. The chemical process needs an intelligent operation-aided workstation which can do such tasks as process monitoring, fault detection, fault diagnosis and action guidance in semiautomatic mode. These tasks can increase the performance of a process operation and give merits in economics, safety and reliability. Aiming these tasks, series of researches have been done in our lab. Main results from these researches are building appropriate knowledge representation models and a diagnosis mechanism for fault detection and diagnosis in a chemical process. The knowledge representation schemes developed in our previous research, the symptom tree model and the fault-consequence digraph, showed the effectiveness and the usefulness in a real-time application, of the process diagnosis, especially in large and complex plants. However in our previous approach, the diagnosis speed is its demerit in spite of its merits of high resolution, mainly due to using two knowledge models complementarily. In our current study, new knowledge representation scheme is developed which integrates the previous two knowledge models, the symptom tree and the fault-consequence digraph, into one. This new model is constructed using a material balance, energy balance, momentum balance and equipment constraints. Controller related constraints are included in this new model, which possesses merits of the two previous models. This new integrated model will be tested and verified by the real-time application in a BTX process or a crude unit process. The reliability and flexibility will be greatly enhanced compared to the previous model in spite of the low diagnosis speed. Nexpert Object for the expert system shell and SUN4 workstation for the hardware platform are used. TCP/IP for a communication protocol and interfacing to a dynamic simulator, SPEEDUP, for a dynamic data generation are being studied.

• Journal of Korea Multimedia Society
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• v.11 no.10
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• pp.1376-1384
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• 2008

Numerous researches on network self-configuration have been conducted on Wireless Sensor Network (WSN) and Ad Hoc network but the results have not been applied yet for factory automation. This paper presents development of intelligent process management systems conducting process monitoring and control irrelevant to physical position of a plant operator. The systems are indispensable for diagnosis of rotating machines which cannot exploit wired network. The system was implemented in a Personal Digital Assistant (PDA) using Bluetooth communication protocol. When a mobile terminal reaches to communication range of the process management server, the server detects the mobile terminal to reconfigure plant network automatically. The server authenticates a user of the terminal to download and installs monitoring and control program considering authorized level of the user. If the terminal leaves communication range of the server, it deletes the node from the network and removes the program automatically to save resources and prevent security problems such as missing terminal. Operation of developed functions was verified in a testbed emulating steel-making plant.