Affiliation
Institute of Chemical Technology (ICT), MumbaiFoundation for Environmental Monitoring, Bangalore
University of Bedfordshire
Issue Date
2019-12-19Subjects
water contaminationartificial intelligence
bacterial contamination
microscope
H122 Water Quality Control
Metadata
Show full item recordAbstract
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.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
MDPIJournal
WaterAdditional Links
https://www.mdpi.com/2073-4441/12/1/15/htmType
ArticleLanguage
enISSN
2073-4441EISSN
2073-4441ae974a485f413a2113503eed53cd6c53
10.3390/w12010015
Scopus Count
Collections
The following license files are associated with this item:
- Creative Commons
Except where otherwise noted, this item's license is described as Green - can archive pre-print and post-print or publisher's version/PDF