Connected sensors, innovative sensor deployment and intelligent data analysis for online water quality monitoring

Manjakkal, L. , Mitra, S., Petillot, Y., Shutler, J., Scott, M. , Willander, M. and Dahiya, R. (2021) Connected sensors, innovative sensor deployment and intelligent data analysis for online water quality monitoring. IEEE Internet of Things Journal, 8(18), pp. 13805-13824. (doi: 10.1109/JIOT.2021.3081772)

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Abstract

The sensor technology for water quality monitoring (WQM) has improved during recent years. The cost-effective sensorised tools that can autonomously measure the essential physical -chemical and biological (PCB) variables are now readily available and are being deployed on buoys, boats and ships. Yet, there is a disconnect between the data quality, data gathering and data analysis due to the lack of standardized approaches for data collection and processing, spatio-temporal variation of key parameters in water bodies and new contaminants. Such gaps can be bridged with a network of multiparametric sensor systems deployed in water bodies using autonomous vehicles such as marine robots and aerial vehicles to broaden the data coverage in space and time. Further, intelligent algorithms (e. g. artificial intelligence (AI)) could be employed for standardised data analysis and forecasting. This paper presents a comprehensive review of the sensors, deployment and analysis technologies for WQM. A network of networked water bodies could enhance the global data intercomparability and enable WQM at global scale to address global challenges related to food (e.g., aqua/agriculture), drinking water, and health (e.g., water borne diseases).

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Scott, Professor Marian and Manjakkal, Dr Libu and Dahiya, Professor Ravinder and Mitra, Dr Srinjoy
Authors: Manjakkal, L., Mitra, S., Petillot, Y., Shutler, J., Scott, M., Willander, M., and Dahiya, R.
College/School:College of Science and Engineering > School of Engineering
College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering
College of Science and Engineering > School of Mathematics and Statistics > Statistics
Journal Name:IEEE Internet of Things Journal
Publisher:IEEE
ISSN:2327-4662
ISSN (Online):2327-4662
Published Online:19 May 2021
Copyright Holders:Copyright © 2021 The Authors
First Published:First published in IEEE Internet of Things Journal 8(18): 13805-13824
Publisher Policy:Reproduced under a Creative Commons License

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
301728Engineering Fellowships for Growth: Printed Tactile SKINRavinder DahiyaEngineering and Physical Sciences Research Council (EPSRC)EP/R029644/1ENG - Electronics & Nanoscale Engineering
303114Innovative Network for Training in Water and Food Quality using Disposable Sensors,Ravinder DahiyaEuropean Commission (EC)813680ENG - Electronics & Nanoscale Engineering