A continuous, in-situ, near-time fluorescence sensor coupled with a machine learning model for detection of fecal contamination risk in drinking water: Design, characterization and field validation
Journal Article
Overview
publication date
- July 15, 2022
has subject area
- Alkalies - Drinking Water
- Amino Acids, Aromatic - Tryptophan
- Amino Acids, Essential - Tryptophan
- Anions - Drinking Water
- Computing Methodologies - Machine Learning
- Diet, Food, and Nutrition - Drinking Water
- Electromagnetic Phenomena - Fluorescence
- Environment and Public Health - Water Microbiology
- Environmental Exposure - Environmental Monitoring
- Feces
- Food and Beverages - Drinking Water
- Gammaproteobacteria - Escherichia coli
- Gram-Negative Facultatively Anaerobic Rods - Escherichia coli
- Humans
- Mathematical Concepts - Machine Learning
- Microbiology - Water Microbiology
- Optical Phenomena - Fluorescence
- Oxygen Compounds - Drinking Water
- Public Health Practice - Environmental Monitoring
has restriction
- hybrid
Date in CU Experts
- January 17, 2023 12:55 PM
Full Author List
- Bedell E; Harmon O; Fankhauser K; Shivers Z; Thomas E
author count
- 5
citation count
- 19
published in
- Water Research Journal
Other Profiles
International Standard Serial Number (ISSN)
- 0043-1354
Electronic International Standard Serial Number (EISSN)
- 1879-2448
Digital Object Identifier (DOI)
Additional Document Info
volume
- 220
number
- ARTN 118644