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Smart Sensors for Real-Time Water Quality Monitoring pp 217–238Cite as

Remote Monitoring of Water Quality for Intensive Fish Culture

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Part of the book series: Smart Sensors, Measurement and Instrumentation ((SSMI,volume 4))

Abstract

Water quality monitoring and forecasting plays an important role in modern intensive fish farming management. This paper describes an online water quality monitoring system for intensive fish culture in China, which is combined with web-server-embedded and mobile telecommunication technology. Based on historical data, this system is designed to forecast water quality with artificial neural networks (ANNs) and control the water quality in time to reduce catastrophic losses. The forecasting model for dissolved oxygen half an hour ahead has been validated with experimental data. The results demonstrate that multi-parametric, long-distance and online monitoring for water quality information can be accurately acquired and predicted by using this established monitoring system.

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Author information

Authors and Affiliations

  1. College of Information and Electrical Engineering, China Agricultural University, Beijing, 100083, P.R. China

    D. Li & S. Liu

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  1. D. Li
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  2. S. Liu
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Correspondence to D. Li .

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Editors and Affiliations

  1. Massey University (Turitea), Palmerston North, New Zealand

    Subhas C Mukhopadhyay

  2. The School of Built Environment, Liverpool John Moores University, Liverpool, United Kingdom

    Alex Mason

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Li, D., Liu, S. (2013). Remote Monitoring of Water Quality for Intensive Fish Culture. In: Mukhopadhyay, S., Mason, A. (eds) Smart Sensors for Real-Time Water Quality Monitoring. Smart Sensors, Measurement and Instrumentation, vol 4. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37006-9_10

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  • DOI: https://doi.org/10.1007/978-3-642-37006-9_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37005-2

  • Online ISBN: 978-3-642-37006-9

  • eBook Packages: EngineeringEngineering (R0)

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