Connected Sensors, Innovative Sensor Deployment, and Intelligent Data Analysis for Online Water Quality Monitoring

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-biological (PCB) variables are now readily available and are being deployed on buoys, boats, and ships. Yet, th...

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Published in:IEEE Internet of Things Journal
Main Authors: Manjakkal, Libu, Mitra, Srinjoy, Petillot, Yvan R., Shutler, Jamie, Scott, E. Marian, Willander, Magnus, Dahiya, Ravinder
Format: Article in Journal/Newspaper
Language:English
Published: Linköpings universitet, Fysik, elektroteknik och matematik 2021
Subjects:
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-180887
https://doi.org/10.1109/JIOT.2021.3081772
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spelling ftlinkoepinguniv:oai:DiVA.org:liu-180887 2023-05-15T17:53:55+02:00 Connected Sensors, Innovative Sensor Deployment, and Intelligent Data Analysis for Online Water Quality Monitoring Manjakkal, Libu Mitra, Srinjoy Petillot, Yvan R. Shutler, Jamie Scott, E. Marian Willander, Magnus Dahiya, Ravinder 2021 application/pdf http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-180887 https://doi.org/10.1109/JIOT.2021.3081772 eng eng Linköpings universitet, Fysik, elektroteknik och matematik Linköpings universitet, Tekniska fakulteten Univ Glasgow, Scotland Univ Edinburgh, Scotland Univ Heriot Watt, Scotland Univ Exeter, England IEEE Internet of Things Journal, 2327-4662, 2021, 8:18, s. 13805-13824 orcid:0000-0001-6235-7038 http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-180887 doi:10.1109/JIOT.2021.3081772 ISI:000703315500002 info:eu-repo/semantics/openAccess Sensors Monitoring Robot sensing systems Water pollution Intelligent sensors Water quality Pollution measurement Connected sensors intelligent data analysis Internet of Things (IoT) robotics sensor deployment water quality monitoring (WQM) Communication Systems Kommunikationssystem Article in journal info:eu-repo/semantics/article text 2021 ftlinkoepinguniv https://doi.org/10.1109/JIOT.2021.3081772 2022-05-01T08:24:35Z 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-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, spatiotemporal 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. Furthermore, intelligent algorithms [e.g., artificial intelligence (AI)] could be employed for standardized data analysis and forecasting. This article 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 a global scale to address global challenges related to food (e.g., aqua/agriculture), drinking water, and health (e.g., water-borne diseases). Funding Agencies|Engineering and Physical Sciences (EPSRC)UK Research & Innovation (UKRI)Engineering & Physical Sciences Research Council (EPSRC) [EP/R029644/1]; ORCA hub [EP/R026173/1]; European Commission through AQUASENSE [H2020-MSCA-ITN-2018-813680] Article in Journal/Newspaper Orca LIU - Linköping University: Publications (DiVA) IEEE Internet of Things Journal 8 18 13805 13824
institution Open Polar
collection LIU - Linköping University: Publications (DiVA)
op_collection_id ftlinkoepinguniv
language English
topic Sensors
Monitoring
Robot sensing systems
Water pollution
Intelligent sensors
Water quality
Pollution measurement
Connected sensors
intelligent data analysis
Internet of Things (IoT)
robotics
sensor deployment
water quality monitoring (WQM)
Communication Systems
Kommunikationssystem
spellingShingle Sensors
Monitoring
Robot sensing systems
Water pollution
Intelligent sensors
Water quality
Pollution measurement
Connected sensors
intelligent data analysis
Internet of Things (IoT)
robotics
sensor deployment
water quality monitoring (WQM)
Communication Systems
Kommunikationssystem
Manjakkal, Libu
Mitra, Srinjoy
Petillot, Yvan R.
Shutler, Jamie
Scott, E. Marian
Willander, Magnus
Dahiya, Ravinder
Connected Sensors, Innovative Sensor Deployment, and Intelligent Data Analysis for Online Water Quality Monitoring
topic_facet Sensors
Monitoring
Robot sensing systems
Water pollution
Intelligent sensors
Water quality
Pollution measurement
Connected sensors
intelligent data analysis
Internet of Things (IoT)
robotics
sensor deployment
water quality monitoring (WQM)
Communication Systems
Kommunikationssystem
description 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-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, spatiotemporal 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. Furthermore, intelligent algorithms [e.g., artificial intelligence (AI)] could be employed for standardized data analysis and forecasting. This article 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 a global scale to address global challenges related to food (e.g., aqua/agriculture), drinking water, and health (e.g., water-borne diseases). Funding Agencies|Engineering and Physical Sciences (EPSRC)UK Research & Innovation (UKRI)Engineering & Physical Sciences Research Council (EPSRC) [EP/R029644/1]; ORCA hub [EP/R026173/1]; European Commission through AQUASENSE [H2020-MSCA-ITN-2018-813680]
format Article in Journal/Newspaper
author Manjakkal, Libu
Mitra, Srinjoy
Petillot, Yvan R.
Shutler, Jamie
Scott, E. Marian
Willander, Magnus
Dahiya, Ravinder
author_facet Manjakkal, Libu
Mitra, Srinjoy
Petillot, Yvan R.
Shutler, Jamie
Scott, E. Marian
Willander, Magnus
Dahiya, Ravinder
author_sort Manjakkal, Libu
title Connected Sensors, Innovative Sensor Deployment, and Intelligent Data Analysis for Online Water Quality Monitoring
title_short Connected Sensors, Innovative Sensor Deployment, and Intelligent Data Analysis for Online Water Quality Monitoring
title_full Connected Sensors, Innovative Sensor Deployment, and Intelligent Data Analysis for Online Water Quality Monitoring
title_fullStr Connected Sensors, Innovative Sensor Deployment, and Intelligent Data Analysis for Online Water Quality Monitoring
title_full_unstemmed Connected Sensors, Innovative Sensor Deployment, and Intelligent Data Analysis for Online Water Quality Monitoring
title_sort connected sensors, innovative sensor deployment, and intelligent data analysis for online water quality monitoring
publisher Linköpings universitet, Fysik, elektroteknik och matematik
publishDate 2021
url http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-180887
https://doi.org/10.1109/JIOT.2021.3081772
genre Orca
genre_facet Orca
op_relation IEEE Internet of Things Journal, 2327-4662, 2021, 8:18, s. 13805-13824
orcid:0000-0001-6235-7038
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-180887
doi:10.1109/JIOT.2021.3081772
ISI:000703315500002
op_rights info:eu-repo/semantics/openAccess
op_doi https://doi.org/10.1109/JIOT.2021.3081772
container_title IEEE Internet of Things Journal
container_volume 8
container_issue 18
container_start_page 13805
op_container_end_page 13824
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