Abstract
Aquaculture plays an important role in providing food security to the world and increasing steadily as one of the most sustainable methods of food production. The monitoring of water quality has great significance in aquaculture. Monitoring the water quality parameters such as Temperature, Dissolved Oxygen, Salinity, pH etc. enables us understanding the farm in-depth & helps to optimize the use of resources, improve sustainability, profitability and most importantly to reduce the impact of aquaculture on the environment. Water quality determines the fish behavior and health of the farm as well. The objective of this paper is to review current research works and studies on water quality monitoring systems and various estimation techniques, in order to understand different challenges faced in water quality monitoring for aquaculture. The study starts with the evolution of water quality monitoring, importance of wireless sensor networks and gives overall perspective on presentwater quality monitoring systems [1].
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Clark, M., Tilman, D.: Comparative analysis of environmental impacts of agricultural production systems, agricultural input efficiency, and food choice. Environ. Res. Lett. 12(6), 064016 (2017)
Wee, R.Y.: Top 15 countries for aquaculture production. https://wwwworldatlas.com/articles/top-15-countries-for-aquaculture-production.html (2017)
Huan, J., Cao, W., Qin, Y.: Prediction of dissolved oxygen in aquaculture based on EEMD and LSSVM optimized by the bayesian evidence framework. Comput. Electron. Agric. 150, 257–265 (2018)
Adu-Manu, K.S., Tapparello, C., Heinzelman, W., Katsriku, F.A., Abdulai, J.-D.: Water quality monitoring using wireless sensor networks: current trends and future research directions. ACM Trans. Sen. Netw. 13(1), 4:1–4:41 (2017)
Bhardwaj, J., Gupta, K.K., Gupta, R.: A review of emerging trends on water quality measurement sensors. In: 2015 International Conference on Technologies for Sustainable Development (ICTSD), pp. 1–6, February 2015
Sawaya, K., Olmanson, L., Heinert, N., Brezonik, P., Bauer, M.: Extending satellite remote sensing to local scales: land and water resource monitoring using high-resolution imagery. Remote Sens. Environ. 88(1–2), 144–156 (2003)
Baronti, P., Pillai, P., Chook, V.W., Chessa, S., Gotta, A., Hu, Y.F.: Wireless sensor networks: a survey on the state of the art and the 802.15.4 and ZigBee standards. Comput. Commun. 30(7), 1655–1695 (2007). wired/Wireless Internet Communications
IEEE standard for information technology– local and metropolitan area networks– specific requirements– part 15.1a: wireless medium access control (MAC) and physical layer (PHY) specifications for wireless personal area networks (WPAN). IEEE Std 802.15.1-2005 (Revision of IEEE Std 802.15.1-2002), pp. 1–700, June 2005
Partalas, I., Tsoumakas, G., Hatzikos, E.V., Vlahavas, I.: Greedy regression ensemble selection: theory and an application to water quality prediction. Inf. Sci. 178(20), 3867–3879 (2008)
Liu, S., Tai, H., Ding, Q., Li, D., Xu, L., Wei, Y.: A hybrid approach of support vector regression with genetic algorithm optimization for aquaculture water quality prediction. Math. Comput. Model. 58(3), 458–465 (2013). computer and Computing Technologies in Agriculture 2011 and Computer and Computing Technologies in Agriculture 2012
Yu, H., Chen, Y., Hassan, S., Li, D.: Dissolved oxygen content prediction in crab culture using a hybrid intelligent method. Sci. Rep. 6, 27292 (2016)
Zhu, C., Liu, X., Ding, W.: Prediction model of dissolved oxygen based on FOA-LSSVR. In: 2017 36th Chinese Control Conference (CCC), pp. 9819–9823, July 2017
Ren, Q., Zhang, L., Wei, Y., Li, D.: A method for predicting dissolved oxygen in aquaculture water in an aquaponics system. Comput. Electron. Agricu. 151, 384–391 (2018)
Kamilaris, A., Kartakoullis, A., Prenafeta-Boldú, F.X.: A review on the practice of big data analysis in agriculture. Comput. Electron. Agric. 143, 23–37 (2017)
Atzori, L., Iera, A., Morabito, G.: The Internet of Things: a survey. Comput. Netw. 54(15), 2787–2805 (2010)
Gubbi, J., Buyya, R., Marusic, S., Palaniswami, M.: Internet of Things (IoT): a vision, architectural elements, and future directions. Future Gener. Comput. Syst. 29(7), 1645–1660 (2013)
Al-Fuqaha, A., Guizani, M., Mohammadi, M., Aledhari, M., Ayyash, M.: Internet of Things: a survey on enabling technologies, protocols, and applications. IEEE Commun. Surv. Tutorials, 17(4), 2347–2376 (2015)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Kozhiparamban, R.A.H., Vettath Pathayapurayil, H. (2020). Review on Water Quality Monitoring Systems for Aquaculture. In: Hemanth, D.J., Kumar, V.D.A., Malathi, S., Castillo, O., Patrut, B. (eds) Emerging Trends in Computing and Expert Technology. COMET 2019. Lecture Notes on Data Engineering and Communications Technologies, vol 35. Springer, Cham. https://doi.org/10.1007/978-3-030-32150-5_71
Download citation
DOI: https://doi.org/10.1007/978-3-030-32150-5_71
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-32149-9
Online ISBN: 978-3-030-32150-5
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)