Data Visualization and Enhanced Learning in Engineering Education Through Oil Pollution Studies and Environmental Impact Assessment

  • James UhomoibhiEmail author
  • Conor White
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 716)


Big Data and Data Analytics have in recent times become important areas of focus in academia, in business and in society. This paper utilises experiments involving data visualisation of oil pollution studies and their effects on environment for enhanced learning in engineering education. Tracking and analysis of images and the use of accessible applications for the analysis of acquired data revealed the level of impact of the different types of oil pollution on grass vegetation. In accounting for these changes the primary RGB colours and corresponding values are used. The use of spectral analysis applications available in spectroscopy and comparison of results would in future prove useful in assessing some aspects of these changes in relation to wavelength and colours changes. The results of these studies would contribute in no small measure to the determination of best cleaning strategies for oil spills.


Data visualisation Enhanced learning Engineering education Oil pollution Environment 


  1. 1.
    Fisman, L.: The effects of local learning on environmental awareness in children: an empirical investigation. J. Environ. Educ. 36(3), 39–50 (2005)CrossRefGoogle Scholar
  2. 2.
    Grasha, A., Yangarber-Hicks, N.: Integrating teaching styles and learning styles with instructional technology. Coll. Teach. 48(1), 2–10 (2000)CrossRefGoogle Scholar
  3. 3.
    Howe, R.W., Disinger, J.F.: Teaching Environmental Education Using Out-of-School Settings and Mass Media. ERIC/SMEAC Environmental Education Digest No. 1. ERIC Clearinghouse for Science Mathematics and Environmental Education, Columbus OH (1988)Google Scholar
  4. 4.
    Kunkle, D.R.: Lehigh Gap History and Restoration. Wildlife Information Center, Slatington (2004)Google Scholar
  5. 5.
    Environmental Literacy Council: Resources for Environmental Literacy. NSTA Press, Arlington (2007)Google Scholar
  6. 6.
    Collins Dictionary of Science. HarperCollins Publishers, Glasgow (2003)Google Scholar
  7. 7.
    Onime, C., Uhomoibhi, J.: Cost effective visualization of research data for cognitive development using mobile augmented reality. In: AVI 2016, International Conference Workshop: Road Mapping Infrastructures for Advanced Visual Interfaces Supporting Big Data Applications in Virtual Research Environments 7–10 June 2016, Bari, Italy (2016)Google Scholar
  8. 8.
    Harrison, J., Uhomoibhi, J.: Engineering study of tidal stream renewable energy generation and visualization: issues of process modelling and implementation. In: AVI 2016, International Conference Workshop: Road Mapping Infrastructures for Advanced Visual Interfaces Supporting Big Data Applications in Virtual Research Environments, 7–10 June 2016, Bari, Italy (2016)Google Scholar
  9. 9.
    Onime, C., Uhomoibhi, J.: Smart technologies and applications for visualization in higher science and Engineering education: issues of knowledge integration and virtual experimentation. In: IEEE EDUCON 2017, IEEE Global Engineering Education International Conference, 26–28 April 2017, Athens, Greece (2017)Google Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Faculty of Computing and Engineering, Computer Science Research InstituteUlster UniversityNewtownabbeyNorthern Ireland, UK
  2. 2.Faculty of Computing and Engineering, School of EngineeringUlster UniversityNewtownabbeyNorthern Ireland, UK

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