Abstract
As the human population growth and industry pressure in most developing countries continue to increase, effective water quality assessment has become critical for river waters. A major challenge, however, faced in water quality assessment is the process of data capturing and chemical laboratory approaches, which could be expensive and time consuming. This work develops ubiquitous particle swarm optimization (PSO) made-easy framework for mobile networks. The framework experimentally assesses water health status of Southern Africa river waters. Simulation results show that the proposed framework is able to obtain good results with economical solution when compared with assessment results obtained by the state of the art.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Wechmongkhonkon, S., Poomtong, N., Areerachakul, S.: Application of artificial neural network to classification surface water quality. World Acad. Sci. Eng. Technol. 6(9), 205–209 (2012)
Prüss-Üstün, A., Bos, R., Gore, F., Bartram, J.: Safer water, better health, p. 53 (2008)
Juahir, H., Zain, S.M., Aris, A.Z., Yusoff, M.K., Bin Mokhtar, M.: Spatial assessment of Langat River water quality using chemometrics. J. Environ. Monit. 12(1), 287–295 (2010)
Thareja, S., Trivedi, P.: Assessment of water quality of Bennithora River in Karnataka through multivariate analysis. Nat. Sci. 8(6), 51–56 (2010)
Gleick, P.H.: Dirty Water: Estimated deaths from water-related diseases 2000–2020. Pacific Inst. Res. Rep., pp. 1–12, 2002
Aazami, J., Esmaili-Sari, A., Abdoli, A., Sohrabi, H., Van den Brink, P.J.: Monitoring and assessment of water health quality in the Tajan River, Iran using physicochemical, fish and macroinvertebrates indices. J. Environ. Heal. Sci. Eng. 13(1), 29 (2015)
Kennedy, J., Eberhart, R.C.: A discrete binary version of the particle swarm algorithm. In: 1997 IEEE International Conference on Systems, Man, Cybernetics Computer Cybernetics Simulation, vol. 5, pp. 4–8, (1997)
Eberhart, R., Kennedy, J.: A new optimizer using particle swarm theory. In: MHS 1995 Proceedings of the Sixth International Symposium Micro Machine Human Science, pp. 39–43 (1995)
Shi, Y., Eberhart, R.: A modified particle swarm optimizer. In: 1998 IEEE International Conference Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No. 98TH8360), pp. 69–73 (1998)
Bai, Q.: Analysis of particle swarm optimization algorithm. Comput. Inf. Sci. 3(1), 180–184 (2010)
Zhang, Y., Wang, S., Ji, G.: A comprehensive survey on particle swarm optimization algorithm and its applications (2015)
Dian, P.R., Siti, M.S., Siti, S.Y.: Particle swarm optimization: technique, system and challenges. Int. J. Comput. Appl. 14(1), 19–27 (2011)
Peer, E.S., Van Den Bergh, F., Engelbrecht, A.P.: Using neighbourhoods with the guaranteed convergence PSO. In: Proceedings of the 2003 IEEE Swarm Intelligence Symposium. SIS 2003 (Cat. No. 03EX706), no. 2 (2003)
Gordon, B., Callan, P., Vickers, C.: WHO guidelines for drinking-water quality. WHO Chron. 38(3), 564 (2008)
Clerc, M.: A method to improve Standard PSO. Technical report, pp. 1–18 (2009)
Kennedy, J., Eberhart, R.C., Shi, Y.: Swarm Intell. Scholarpedia 2(9), 1462 (2001)
Clerk, M.: Stagnation analysis in particle swarm optimization or what happens when nothing happens. no. CSM-460 (2006)
Zadeh, L.: Fuzzy sets. Inf. Control 8, 338–353 (1965)
Pullanikkatil, D.: Water quality assessment of mohokare river
Tanor, E.B., George, M.J.: Physico-Chemical Assessment of Pollution in the Caledon River Around Maseru City, Lesotho, pp. 776–782 (2014)
Acknowledgement
The authors gratefully acknowledge the resources made available by the University of South Africa and Lesotho Department of Waters Affairs for providing surface waters.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Makojoa, K.B.G., Osunmakinde, I.O. (2016). Are the Days of Field-to-Laboratory Analysis Gone? Effects of Ubiquitous Environmental River Water Quality Assessment. In: Glitho, R., Zennaro, M., Belqasmi, F., Agueh, M. (eds) e-Infrastructure and e-Services. AFRICOMM 2015. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 171. Springer, Cham. https://doi.org/10.1007/978-3-319-43696-8_16
Download citation
DOI: https://doi.org/10.1007/978-3-319-43696-8_16
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-43695-1
Online ISBN: 978-3-319-43696-8
eBook Packages: Computer ScienceComputer Science (R0)