Design of a smart system for rapid bacterial test

2.50
Hdl Handle:
http://hdl.handle.net/10547/623902
Title:
Design of a smart system for rapid bacterial test
Authors:
Patil, Rajshree; Levin, Saurabh; Rajkumar, Samuel; Ajmal, Tahmina ( 0000-0003-2170-5248 )
Abstract:
In this article, we present our initial findings to support the design of an advanced field test to detect bacterial contamination in water samples. The system combines the use of image processing and neural networks to detect an early presence of bacterial activity. We present here a proof of concept with some tests results. Our initial findings are very promising and indicate detection of viable bacterial cells within a period of 2 h. To the authors' knowledge this is the first attempt to quantify viable bacterial cells in a water sample using cell splitting. We also present a detailed design of the complete system that uses the time lapse images from a microscope to complete the design of a neural network based smart system.
Affiliation:
Institute of Chemical Technology (ICT), Mumbai; Foundation for Environmental Monitoring, Bangalore; University of Bedfordshire
Citation:
Patil R, Levin S, Rajkumar S, Ajmal T (2020) 'Design of a smart system for rapid bacterial test', Water, 12 (1), pp.15-.
Publisher:
MDPI
Journal:
Water
Issue Date:
19-Dec-2019
URI:
http://hdl.handle.net/10547/623902
DOI:
10.3390/w12010015
Additional Links:
https://www.mdpi.com/2073-4441/12/1/15/htm
Type:
Article
Language:
en
ISSN:
2073-4441
EISSN:
2073-4441
Appears in Collections:
Computing

Full metadata record

DC FieldValue Language
dc.contributor.authorPatil, Rajshreeen
dc.contributor.authorLevin, Saurabhen
dc.contributor.authorRajkumar, Samuelen
dc.contributor.authorAjmal, Tahminaen
dc.date.accessioned2020-03-24T10:48:02Z-
dc.date.available2020-03-24T10:48:02Z-
dc.date.issued2019-12-19-
dc.identifier.citationPatil R, Levin S, Rajkumar S, Ajmal T (2020) 'Design of a smart system for rapid bacterial test', Water, 12 (1), pp.15-.en
dc.identifier.issn2073-4441-
dc.identifier.doi10.3390/w12010015-
dc.identifier.urihttp://hdl.handle.net/10547/623902-
dc.description.abstractIn this article, we present our initial findings to support the design of an advanced field test to detect bacterial contamination in water samples. The system combines the use of image processing and neural networks to detect an early presence of bacterial activity. We present here a proof of concept with some tests results. Our initial findings are very promising and indicate detection of viable bacterial cells within a period of 2 h. To the authors' knowledge this is the first attempt to quantify viable bacterial cells in a water sample using cell splitting. We also present a detailed design of the complete system that uses the time lapse images from a microscope to complete the design of a neural network based smart system.en
dc.language.isoenen
dc.publisherMDPIen
dc.relation.urlhttps://www.mdpi.com/2073-4441/12/1/15/htmen
dc.rightsGreen - can archive pre-print and post-print or publisher's version/PDF-
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectwater contaminationen
dc.subjectartificial intelligenceen
dc.subjectbacterial contaminationen
dc.subjectmicroscopeen
dc.subjectH122 Water Quality Controlen
dc.titleDesign of a smart system for rapid bacterial testen
dc.typeArticleen
dc.identifier.eissn2073-4441-
dc.contributor.departmentInstitute of Chemical Technology (ICT), Mumbaien
dc.contributor.departmentFoundation for Environmental Monitoring, Bangaloreen
dc.contributor.departmentUniversity of Bedfordshireen
dc.identifier.journalWateren
dc.date.updated2020-03-24T10:39:12Z-
dc.description.noteopen access article-
This item is licensed under a Creative Commons License
Creative Commons
All Items in UOBREP are protected by copyright, with all rights reserved, unless otherwise indicated.