• Journal of Sensor Science and Technology
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• v.21 no.1
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• pp.46-52
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• 2012

The rapid water pollution in stream, river, lake and sea in recent years raises an urgent need for continuous monitoring and policymaking to conserve the global clean environment. In particular, the increasing water pollution in coastal marine areas adds to the importance of the environmental monitoring systems. In this paper, the mobile server is designed to gathers information of the water quality at coastal areas. The obtained data by the server is transmitted from field servers to the base station via multi-hop communication in wireless sensor network. The information collected includes dissolved oxygen(DO), hydrogen ion exponent(pH), temperature, etc. By the information provided the real-time monitoring of water quality at the coastal marine area. In addition, wireless sensor network-based flooding routing protocol was designed and used to transfer the measured water quality information efficiently. Telosb sensor node is programmed using nesC language in TinyOS platform for small scale wireless sensor network monitoring from a remote server.

• Journal of Convergence Society for SMB
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• v.1 no.1
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• pp.39-44
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• 2011

Recently, due to people's incontinent use all over the world, fossil fuels such as coal, oil, and natural gas were nearly to be exhausted and also causes serious environment pollutions. Therefore, there is a strong need to develop solar, wind, hydro, biomass, geothermal to replace fossil fuels to prevent suffering from above problems. Wish advances in sensor technology, such data is collected as a kind of stream data which arrives in an online manner so that it is characterized as high- speed, real-time and unbounded and it requires fast data processing to get the up-to-date results. Therefore, the traditional data processing techniques are not fit to deal with stream data. In this paper, we propose a kalman filter-based algorithm to process renewable stream data.

• Journal of KIISE:Databases
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• v.35 no.1
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• pp.1-16
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• 2008

Join queries having heavy cost are necessary to Data Stream Management System in Sensor Network where plural short information is generated. It is reasonable that each join operator has a sliding-window constraint for preventing DISK I/O because the data stream represents the infinite size of data. In addition, the join operator should be able to take multiple inputs for overall results. It is possible for the MJoin operator with sliding-windows to do so. In this paper, we consider the data stream environment where multiple MJoin operators are registered and propose MMJoin which deals with issues of building and processing a globally shared query considering characteristics of the MJoin operator with sliding-windows. First, we propose a solution of building the global shared query execution plan. Second, we solved the problems of updating a window size and routing for a join result. Our study can be utilized as a fundamental research for an optimization technique for multiple continuous joins in the data stream environment.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.27 no.4
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• pp.1-14
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• 2024

Otters, designated as Class I endangered wildlife due to population declines resulting from urban development and stream burial, have seen increased appearances in freshwater environments since the nationwide ban on stream filling in 2020 and the implementation of urban stream restoration projects. There is a pressing need for scientific and strategic conservation measures for otters, an umbrella and vulnerable species in aquatic ecosystems. Therefore, this study predicts potential otter habitats using the species distribution model MaxEnt, focusing on Hwangguji Stream in Suwon, and proposes conservation strategies. Otter signs were surveyed over three years from 2019 to 2021 with citizen scientists, serving as presence data for the model. The model's outcomes were enhanced by analyzing 'river nature map' as a boundary. MaxEnt compared the performance of 60 combinations of feature classes and regularization multipliers to prevent model complexity and overfitting. Additionally, unmanned sensor cameras observed otter density for model validation, confirming correlations with the species distribution model results. The 'LQ-5.0' parameter combination showed the highest explanatory power with an AUC of 0.853. The model indicated that the 'adjacent land use' variable accounted for 31.5% of the explanation, with a preference for areas around cultivated lands. Otters were found to prefer shelter rates of 10-30% in riparian forests within 2 km of bridges. Higher otter densities observed by unmanned sensors correlated with increasing model values. Based on these results, the study suggests three conservation strategies: establishing stable buffer zones to enhance ecological connectivity, improving water quality against non-point source pollution, and raising public awareness. The study provides a scientific basis for potential otter habitat management, effective conservation through governance linking local governments, sustainable biodiversity goals, and civil organizations.

• Journal of Internet Computing and Services
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• v.19 no.4
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• pp.1-6
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• 2018

In smart cities, data from various kinds of sensors are collected and processed to provide smart services to the citizens. Noise information services with noise maps using the collected sensor data from various kinds of ubiquitous sensor networks is one of them. This paper presents a research result which generates three dimensional (3D) noise maps in real-time for smart cities. To make a noise map, we have to converge many informal data which include big image data of geographical Information and massive sensor data. Making such a 3D noise map in real-time requires the processing of the stream data from the ubiquitous sensor networks in real-time and the convergence operation in real-time. They are very challenging works. We developed our own methodology for real-time distributed and parallel processing for it and present it in this paper. Further, we developed our own real-time 3D noise map generation system, with the methodology. The system uses open source softwares for it. Here in this paper, we do introduce one of our systems which uses Apache Storm. We did performance evaluation using the developed system. Cloud computing was used for the performance evaluation experiments. It was confirmed that our system was working properly with good performance and the system can produce the 3D noise maps in real-time. The performance evaluation results are given in this paper, as well.

• Proceedings of the Korean Information Science Society Conference
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• 2007.06b
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• pp.470-475
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• 2007

최근 센서 네트워크에 대한 연구가 활발한 가운데 센서 네트워크에서의 보안에 관한 중요성 또한 대두되고 있어, 센서 노드 및 센서 네트워크 상의 정보를 안전하게 관리하기 위한 암호 알고리즘의 구현이 필수적이다. 센서 노드 상에서 이용될 수 있는 암호로는 TinyECC 등의 공개키 암호와 AES와 같은 표준 블록 암호가 있으나, 속도 면에서 좀더 효율적일 것으로 기대되는 스트림 암호는 아직 표준화된 바가 없으며, 현재 eSTREAM 프로젝트에서 표준화가 진행 중에 있다. 이에 본 논문에서는 센서 노드에 가장 적합한 스트림 암호를 찾기 위해서 eSTREAM의 2단계에 제출 되어있는 스트림 암호들 중 소프트웨어용 암호 7개를 구현하고 성능을 비교한다. 또한 참조 구현으로서 하드웨어용 스트림 암호 및 AES-CTR에 대한 실험 결과도 제시한다. 본 논문의 실험 결과에 따르면 위 스트림 암호 중 Dragon이 속도 측면에서 가장 효율적인 것으로 나타났으며, 초당 약 12.5KB의 암호화 성능을 보여 센서 노드에서 사용하기에 적합한 것으로 판단된다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1146-1165
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• 2022

A huge amount of data in the form of videos and images is being produced owning to advancements in sensor technology. Use of low performance commodity hardware coupled with resource heavy image processing and analyzing approaches to infer and extract actionable insights from this data poses a bottleneck for timely decision making. Current approach of GPU assisted and cloud-based architecture video analysis techniques give significant performance gain, but its usage is constrained by financial considerations and extremely complex architecture level details. In this paper we propose a data pipeline system that uses open-source tools such as Apache Spark, Kafka and OpenCV running over commodity hardware for video stream processing and image processing in a distributed environment. Experimental results show that our proposed approach eliminates the need of GPU based hardware and cloud computing infrastructure to achieve efficient video steam processing for face detection with increased throughput, scalability and better performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.3
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• pp.247-254
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• 2014

For wireless multimedia sensor network (WMSN), it is crucial to select appropriate channels to deliver multimedia data stream generated by image and voice sensors periodically or continuously. Although most of previous researches assume that fixed channels are used for wireless sensor networks, they causes limit to support various application areas. In this paper, we apply link-setup algorithms developed for wireless cognitive radio networks for searching common channels between two nodes without common control channels. We also show the algorithm causes serious performance degradation as the total number of used channels increases, and then propose a new link-setup algorithm to resolve the problem. Therefore, the proposed algorithm shows 30 % higher performance compared to existing algorithms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.4
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• pp.833-839
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• 2007

In case of wireless sensor networks being applied to a target environment having continuous data transfer, high-speed data transmission and processing is necessary to meet increased bandwidth needs. This paper proposes a novel multipath routing algorithm to increase the bandwidth of continuous data stream for the wireless sensor network using dual channel routers. We evaluate performance of the proposed algorithm in the wireless sensor network using the dual channel touter based on ZigBee protocol. According to the experimental evaluation, the proposed algorithm showed outstanding performance enhancement with the bandwidth of 150kbps, which is about twice of existing single channel router.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.7
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• pp.630-642
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• 2013

To transmit vital signal stream of mobile patients remotely, it requires mobility of patient and watcher, sensing function of patient's abnormal symptom and self-organizing service binding of related computing resources. In the existing relative researches, the vital signal stream is transmitted as a centralized approach which exposure the single point of failure itself and incur data traffic to central server although it is localized service. Self-organizing middleware platform based on heterogenous overlay network is a middleware platform which can transmit real-time data from sensor device(including vital signal measure devices) to Smartphone, TV, PC and external system through overlay network applied self-organizing mechanism. It can transmit and save vital signal stream from sensor device autonomically without arbitration of management server and several receiving devices can simultaneously receive and display through interaction of nodes in real-time.