A Sensor Data Management System for USN based Fire Detection Application (USN 기반의 화재감시 응용을 위한 센서 데이터 처리 시스템)

Wonik Park (박원익); Kim, Young-Kuk (김영국)

A Sensor Data Management System for USN based Fire Detection Application

Journal of The Korea Society of Computer and Information
Abbr : JKSCI
2011, 16(5), pp.135-146
Publisher : The Korean Society Of Computer And Information
Research Area : Engineering > Computer Science

Wonik Park ¹, Kim, Young-Kuk ¹

¹충남대학교

Accredited

ABSTRACT

These days, the research of a sensor data management system for USN based real-time monitoring application is active thanks to the development and diffusion of sensor technology. The sensor data is rapidly changeable, continuous and massive row level data. However, end user is only interested in high level data. So, it is essential to effectively process the row level data which is changeable, continuous and massive. In this paper, we propose a sensor data management system with multi-analytical query function using OLAP and anomaly detection function using learning based classifier. In the experimental section, we show that our system is valid through the some experimental scenarios. For the this, we use a sensor data generator implemented by ourselves.

KEYWORDS

USN, Stream data, Fire Detection, OLAP, Multi-dimensional analysis, Anomaly detection

Citation status

* References for papers published after 2023 are currently being built.

[journal] Jiawei, H / 2005 / Stream Cube: An Architecture for Multi-Dimensional Analysis of Data Streams / Distrib. Parallel Databases 18(2) : 173~197

[confproc] P. Domingos / 1996 / Beyond Independence: Conditions for the Optimality of The Simple Bayesian Classifier / In Proc. Int. Conf. Machine Learning : 105~112

[journal] A. Arasu / 2003 / Stream: The Stanford Data Stream Management System / in IEEE Data Engineering Bulletin 4(1)

[confproc] C. Don, U / 2002 / Monitoring Streams: A New Class of Data Management Applications / In Proc. Int. Conf. Very Large DataBase : 215~226

[confproc] C. Sirish / 2003 / TelegraphCQ: Continuous Dataflow Processing / In Proc. Int. Conf. Innovative Data Systems Research : 11~18

[web] / Cougar Project / http://www.cs.cornell.edu/boom/2003sp/ProjectArch/CougarSM/index.php

[journal] C. Jianjun / 2000 / NiagaraCQ: A Scalable Continuous Query System for Internet Databases / SIGMOD Rec : 379~390

[confproc] Calton Pu / 1998 / Update Monitoring: The CQ Project / Proc. Int. Conf. Worldwide Computing and Its Applications, Tuskuba, Japan, Lecture Notes in Computer Science : 396~411

[confproc] R. Philipp, sch / 2009 / Sample synopses for approximate answering of group-by queries / In Proc. Int. Conf. Extending Database Technology, ACM : 403~414

[confproc] K. Henning, hler / 2010 / Sampling dirty data for matching attributes / In Proc. Int. Conf. Management of data, Indianapolis : 63~74

[journal] Alfredo Cuzzocrea / 2010 / Event-based Lossy Compression for Effective and Efficient OLAP over Data Streams / Data & Knowledge Engineering 69(7) : 678~708

[journal] Yufei Tao / 200603 / Maintaining sliding window skylines on data streams / IEEE Transactions on Knowledge and Data Engineering / Institute of Electrical and Electronics Engineers 18(3) : 377~391

[other] Abhirup Chakraborty / 2010 / A Disk-based, Adaptive Approach to Memory-limited Computation of Windowed Stream Joins

[journal] Hua-Fu Li / 2009 / Mining Frequent Itemsets over Data Streams using Efficient Window Sliding Techniques / Expert Systems with Applications: An Int. Journal 36(2) : 1466~1477

[journal] W. Hai / 2008 / Histograms based on the Minimum Description Length Principle / The VLDB Journal : 419~442

[journal] L. Xin / 2009 / A New Approach to Building Histogram for Selectivity Estimation in Query Processing Optimization / Comput. Math. Appl : 1037~1047

[confproc] H. Ming-Jyh / 2005 / Integrating DCT and DWT for Approximating Cube Streams / In Proc. Int. Conf. Information and knowledge management : 179~189

[journal] Xiao-Bo Fan / 2007 / MRST: An Efficient Monitoring Technology of Summarization on Stream Data / Journal of Computer Science and Technology 22(2) : 190~196

[confproc] Hanady Abdulsalam / 2008 / Classifying Evolving Data Streams Using Dynamic Streaming Random Forests / In Proc. Int. Conf. Database and Expert Systems Applications

[confproc] Wei Qu / 2009 / Mining Multi-label Concept-Drifting Data Streams Using Dynamic Classifier Ensemble / In Proc. Int. Conf. Machine Learning: Advances in Machine Learning

[confproc] Qu Wei / 2009 / Mining Multi-label Concept-drifting Data Streams Using Ensemble Classifiers / In Proc. Int. Conf. Fuzzy systems and knowledge discovery : 14~16

[confproc] Mohammad M. Masud / 2010 / Classification and Novel Class Detection of Data Streams in a Dynamic Feature Space / In Proc. Int. Conf. Machine learning and knowledge discovery in databases: Part II : 20~24

[journal] Panagiotis Antonellis / 2009 / Algorithms for Clustering Clickstream Data / Information Processing Letters 109(8) : 381~385

[journal] Li Wan / 2009 / Density-based Clustering of Data Streams at Multiple Resolutions / ACM Trans. on Knowledge Discovery from Data) 3(3) : 1~28

[journal] Li Tu / 2009 / Stream Data Clustering based on Grid Density and Attraction / ACM Trans. on Knowledge Discovery from Data 3(3) : 1~27

[confproc] Maria Kontaki / 2008 / Continuous Trend-Based Clustering in Data Streams / In Proc. Int. Conf. Data Warehousing and Knowledge Discovery

[confproc] Bai-En Shie / 2010 / Online Mining of Temporal Maximal Utility Itemsets from Data Streams / In Proc. Int. Conf. Applied Computing : 22~26

[confproc] 정병수 / 2008 / Efficient Frequent Pattern Mining over Data Streams / ACM : 1447~1448

[confproc] Yoshiaki Yasumura / 2007 / Quick Adaptation to Changing Concepts by Sensitive Detection / In Proc. Int. Conf. Industrial, engineering, and other applications of applied intelligent systems

[journal] Alfredo Cuzzocrea / 2010 / Event-based Lossy Compression for Effective and Efficient OLAP over Data Streams / Data & Knowledge Engineering 69(7) : 678~708

[confproc] Alfredo Cuzzocrea / 2009 / CAMS: OLAPing Multidimensional Data Streams Efficiently / In Proc. Int. Conf. Data Warehousing and Knowledge Discovery

[journal] Sébastien Nedjar / 2009 / Emerging Cubes: Borders, Size Estimations and Lossless Reductions / Information Systems 34(6) : 536~550

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Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65