Data Management Issues and Data Mining of Real Time System Application for Environment Monitoring




Dinesh Kumar Saini;Sanad Al Maskari

Key Words

Data Management ; Real Time Systems ; Data Mining ; Environment Monitoring Systems


MIS REVIEW:An International Journal

Volume or Term/Year and Month of Publication

20卷1期(2014 / 09 / 01)

Page #

31 - 43

Content Language


English Abstract

Environment pollution monitoring and control is very big problem for the whole world. Taking decision in the environment is becoming more challenging. The aim of this paper is to present the challenges surrounding environmental data sets and to address these in order to develop solutions. Environmental data sets present a number of data management challenges including data collection, integration, quality and data mining. Environment data sets are also very dynamic and this presents additional challenges ranging from data gathering to data integration, particularly as these data sets are normally very large and expanding continuously. Statistical methods are very effective and economical way to analyze small, static data sets but they are not applicable for dynamic, real-time and large data sets. The use of data mining methods to discover hidden knowledge in large datasets therefore presents great potential to improve environmental management decisions. A representative environmental data set from quantitative air quality monitoring instruments has been assessed and will be used to demonstrate some of the issues in applying data mining approaches to poor data quality.

Topic Category 基礎與應用科學 > 資訊科學
社會科學 > 管理學
  1. Friedman, J.H. (n.d.), 'Data mining and statistics: what's the connection?', available at http://statweb.stanford.edu/~jhf/ftp/dm-stat.pdf (accessed 21 November 2014).
  2. Abdelzaher, T.,Blum, B.,Cao, Q.,Evans, D.,George, J.,George, S.(2010).EnviroTrack: towards an environmental computing paradigm for distributed sensor networks.Proceedings of the 24th International Conference on Distributed Computing Systems,Tokyo, Japan:
  3. Aberer, K.,Sathe, S.,Chakraborty, D.,Martinoli, A.,Barrenetxea, G.,Faltings, B.(2010).OpenSense: open community driven sensing of environment.Proceedings of the ACM SIGSPATIAL International Workshop on GeoStreaming,San Jose, CA:
  4. Al-Maskari, S.S.,Saini, D.K.,Omar, W.M.(2010).Cyber infrastructure and data quality for environmental pollution control in Oman.Proceeding of International Conference on Data Analysis, Data Quality & Metadata Management,Singapore:
  5. Arasu, A.,Babcock, B.,Babu, S.,Datar, M.,Ito, K.,Nishizawa, I.(2003).STREAM: the Stanford stream data manager.IEEE Data Engineering Bulletin,26(1),19-26.
  6. Bootsma, R.J.,Marteniuk, R.G.,Mackenzie, C.L.,Zaal, F.T.J.M.(1994).The speedaccuracy trade-off in manual prehension: effects of movement amplitude, object size and object width on kinematic characteristics.Experimental Brain Research,98(3),535-541.
  7. Crumiere, M.(1999).Boca Raton, FL.,Folrida Atlantic University.
  8. European Commission(2001).IST 2001: Technologies Serving People.Belgium:European Commission.
  9. Fayyad, U.,Piatetsky-Shapiro, G.,Smyth, P.(2006).From data mining to knowledge discovery: an overview.Advances in Knowledge Discovery and Data Mining,Menlo Park, CA:
  10. Foster, I.(2002).The grid: a new infrastructure for 21st century science.Physics Today,55(2),42-47.
  11. Gehrke, J.,Madden, S.(2004).Query processing in sensor networks.IEEE Pervasive Computing,3(11),46-55.
  12. Green, G.C.,Chan, A.D.C.,Goubran, R.A.(2009).Identification of food spoilage in the smart home based on neural and fuzzy processing of odour sensor responses.Proceedings of Annual International Conference of the IEEE Engineering in Medicine and Biology Society,Minneapolis, MN:
  13. Helmbold, D.P.,Long, P.M.(1994).Tracking drifting concepts by minimizing disagreements.Machine Learning,14,27-45.
  14. Hill, J.,Szewczyk, R.,Woo, A.,Hollar, S.,Culler, D.,Pister, K.(2000).System architecture directions for network sensors.ASPLOS,35(11),93-104.
  15. Kahn, J.M.,Katz, R.H.,Pister, K.S.J.(1999).Next century challenges: mobile networking for "smart dust".Proceedings of ACM/IEEE International Conference on Mobile Computing and Networking,Seattle, WA:
  16. Li, Y.,Callahan, T.,Darnell, E.,Harr, R.,Kurkure, U.,Stockwood, J.(2000).Hardwaresoftware co-design of embedded reconfigurable architectures.Proceedings of the Design Automation Conference,Los Angeles, CA:
  17. Pan, L.,Yang, S.Y.(2007).A new intelligent electronic nose system for measuring and analyzing livestock and poultry farm odours.Environment Monitoring and Assessment,135,399-408.
  18. Roppel, T.A.,Padgetta, M.L.,Waldemark, J.,Wilson, D.(1998).Feature-level signal processing for near-real-time odor identification.The SPIE Conference on Detection and Remediation Technologies for Mines and Minelike Targets III,Orlando, FL:
  19. Saini, D.K.,Yousif, J.H.(2013).Environmental scrutinizing system based on soft computing technique.International Journal of Computer Applications,62(13),45-50.
  20. Sohn, J.H.,Smith, R.,Yoong, E.,Leis, J.W.,Galvin, G.(2003).Quantification of odours from piggery effluent ponds using an electronic nose and an artificial neural network.Biosystems Engineering,86(4),399-410.
  21. Wood, A.,Stankovic, J.A.(2000).Denial of service in sensor networks.IEEE Computer,35(10),54-62.