• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.78-80
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• 2011

In the area of data fusion, dealing with heterogeneous data sources, numerous models have been proposed in last three decades to facilitate different application domains i.e. Department of Defense (DoD), monitoring of complex machinery, medical diagnosis and smart buildings. All of these models shared the theme of multiple levels processing to get more reliable and accurate information. In this paper, we consider five most widely acceptable fusion models (Intelligence Cycle, Joint Directors of Laboratories, Boyd control, Waterfall, Omnibus) applied to different areas for data fusion. When they are exposed to a real scenario, where large dataset from heterogeneous sources is utilize for object monitoring, then it may leads us to non-efficient and unreliable information for decision making. The proposed variation works better in terms of time and accuracy due to prior data diminution.

• Journal of Korea Multimedia Society
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• v.10 no.12
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• pp.1612-1621
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• 2007

In this paper, we introduced our designed TDMA (Time Division Multiple Access) based MAC (Medium Access Control) protocol for Home Networks called HomeTDMA. We have implemented and tested it in a test bed using crossbow motes and TinyOS. We also have compared HomeTDMA and CSMA (Carrier Sense Multiple Access) in terms of space and time complexity, channel access time, delivery success ratio, and throughput. Based on our results, HomeTDMA has an advantage over CSMA on channel access time, throughput and delivery success ratioIn the case of complexity, HomeTDMA is more complex compared to CSMA. Thus, CSMA is more appropriate in wireless sensor networks (WSNs) where memory, energy, and throughput are important parameters to be considered. However, HomeTDMA has a natural advantage of collision free medium access and is very promising for home networks where a reliable transmission or data transfer and congestion control is highly preferred.

• Journal of the Korea Society of Computer and Information
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• v.21 no.11
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• pp.49-57
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• 2016

In this paper, we propose the novel tracking method which uses the weighted discriminative correlation filter (DCF). We also propose the PSPR instead of conventional PSR as tracker performance evaluation method. The proposed tracking method uses multiple DCF to estimates the target position. In addition, our proposed method reflects more weights on the correlation response of the tracker which is expected to have more performance using PSPR. While existing multi-DCF-based tracker calculates the final correlation response by directly summing correlation responses from each tracker, the proposed method acquires the final correlation response by weighted combining of correlation responses from the selected trackers robust to given environment. Accordingly, the proposed method can provide high performance tracking in various and complex background compared to multi-DCF based tracker. Through a series of tracking experiments for various video data, the presented method showed better performance than a single feature-based tracker and also than a multi-DCF based tracker.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1453-1461
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• 2022

The accuracy of peripheral object recognition algorithms using 3D data sensors such as LiDAR in autonomous vehicles has been increasing through many studies, but this requires high performance hardware and complex structures. This object recognition algorithm acts as a large load on the main processor of an autonomous vehicle that requires performing and managing many processors while driving. To reduce this load and simultaneously exploit the advantages of 3D sensor data, we propose 2D data-based recognition using the ROI generated by extracting physical properties from 3D sensor data. In the environment where the brightness value was reduced by 50% in the basic image, it showed 5.3% higher accuracy and 28.57% lower performance time than the existing 2D-based model. Instead of having a 2.46 percent lower accuracy than the 3D-based model in the base image, it has a 6.25 percent reduction in performance time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3066-3079
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• 2016

Recent years have witnessed a dramatic increase in topology research of wireless sensor networks (WSNs) where both energy consumption and survivability need careful consideration. To balance energy consumption and ensure survivability against both random failures and deliberate attacks, we resort to complex network theory and propose an energy-aware preferential attachment (EPA) model to generate a robust topology for WSNs. In the proposed model, by taking the transmission range and energy consumption of the sensor nodes into account, we combine the characters of Erdős -Rényi (ER) model and Barabasi-Albert (BA) model in this new model and introduce tunable coefficients for balancing connectivity, energy consumption, and survivability. The correctness of our theoretic analysis is verified by simulation results. We find that the topology of WSNs built by EPA model is asymptotically power-law and can have different characters in connectivity, energy consumption, and survivability by using different coefficients. This model can significantly improve energy efficiency as well as enhance network survivability by changing coefficients according to the requirement of the real environment where WSNs deployed and therefore lead to a crucial improvement of network performance.

• Journal of the Korea Society of Computer and Information
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• v.24 no.9
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• pp.21-27
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• 2019

In this paper, we propose a deep auto-encoder-based pipe leak detection (PLD) technique from time-series acoustic data collected by microphone sensor nodes. The key idea of the proposed technique is to learn representative features of the leak-free state using leak-free time-series acoustic data and the deep auto-encoder. The proposed technique can be used to create a PLD model that detects leaks in the pipeline in an unsupervised learning manner. This means that we only use leak-free data without labeling while training the deep auto-encoder. In addition, when compared to the previous supervised learning-based PLD method that uses image features, this technique does not require complex preprocessing of time-series acoustic data owing to the unsupervised feature extraction scheme. The experimental results show that the proposed PLD method using the deep auto-encoder can provide reliable PLD accuracy even considering unsupervised learning-based feature extraction.

• 한국태양에너지학회:학술대회논문집
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• 2011.04a
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• pp.213-216
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• 2011

The feasibility study must be conducted for construction of complex for generation of electric power such as items to get permission and grid connection etc. including wind resource to construct a complex for wind power generation. Since wind power can be used by converting only around 20~40% of energy coming in that kinetic energy of wind passes through blades and driving device into electric energy, when constructing a complex, the survey of wind resource takes up the most important part. Data logger used to measure this wind energy are expressed by calculating generally electromotive that is created from a sensor, variable-type, pulse-type signal to be proper for the actual value, and most data loggers have a type without considering geographical features. Besides, in the case of Met mast that is installed to survey the wind resource, since it is installed lower than the hub height of a wind power generator due to permission matters and the economic factors, the height of wind speed by utilizing Deacon equation is compensated to revise this. In this study, a device measuring wind speed was made by using algorithm that is possible to compensate the height of wind speed according to regional features and by applying Deacon equation, and the function of data storage through SD card or RS232 communication was added as well. Besides it's possible to check data more easily with a type of graph by using LCD touch screen for the convenience of users.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.6
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• pp.149-156
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• 2008

SLAM(Simultaneous Localization and Mapping) system is to find a global position and build a map with sensing data when an unmanned-robot navigates an unknown environment. Two kinds of system were developed. One is used distance measurement sensors such as an ultra sonic and a laser sensor. The other is used stereo vision system. The distance measurement SLAM with sensors has low computing time and low cost, but precision of system can be somewhat worse by measurement error or non-linearity of the sensor In contrast, stereo vision system can accurately measure the 3D space area, but it needs high-end system for complex calculation and it is an expensive tool. In this paper, we implement the SLAM system using a single camera image and a PSD sensors. It detects obstacles from the front PSD sensor and then perceive size and feature of the obstacles by image processing. The probability SLAM was implemented using the data of sensor and image and we verify the performance of the system by real experiment.

• Journal of Korea Multimedia Society
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• v.13 no.1
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• pp.122-132
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• 2010

The analysis of ocean environment offers us essential information for ocean exploration. But ocean environment has a lot of environmental variables such as the movements of nodes by an ocean current, corrosion by salt water, attenuation of radio wave, occurrences of multi-path and difficulty of sensor nodes' deployment. It is accordingly difficult and complex to gather and process the environmental information through ocean data communication due to these constraints of ocean environment unlike the terrestrial wireless networks. To overcome these problems, we organized ocean communication network for monitoring underwater environment by real experiment in Gyeongpoho similar to ocean environment. Therefore, this paper aims at overcoming major obstacles in ocean environment, effectively deploying sensor nodes for ocean environment monitoring and defining an efficient structure suitable for communication environment by the implementation of ocean environment monitoring system in Gyeongpoho.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.6
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• pp.666-671
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• 2019

The flight controller(FC) used in small-sized drone was developed as simple structure does not perform complex operations because it uses different MCU with large-sized drone. Also, the balance control of small-sized drone should be simpler than Kalman filter using complex filter and the method using Complementary filter has relatively more operations. So, the method to realize the balance control on small-sized drone effectively using two-track control operating as proper method for above is suggested in this research. This method is a system maintaining effective balance with simple structure and less operations by operating adaptively for the unbalance of the drone with the acceleration sensor with the advantage which performing accurate correction by data processing for long term change and gyroscope sensor maintaining the balance of the drone by data processing for short term change. It is confirmed that stable operation was performed mostly based on the test result for repeatable test more than 100 times using two-track control and it maintained normal state operation more than 98% excluding the difficulty of maintaining normal operation when meets sudden and rapid wind yet.