Unreliable Results of a Commercial Real-Time Water Quality Sensor in Identifying Fecal Contamination of Drinking Water

Low-cost technologies are increasingly being explored and marketed as capable of filling gaps in global water quality monitoring (WQM), especially in resource-limited settings. This study evaluates a commercially available, low-cost triboelectric-based sensor that is marketed for real-time detection of E. coli in drinking and environmental waters. A result of 0 indicates contaminated water, whereas a result of 99 indicates “safe” water. A total of 199 water samples were prepared by serial dilution of raw wastewater influent into deionized water to produce a range of E. coli concentrations from <1 to >100 CFU/100 mL in evaluating the triboelectric sensor. Sensor readings were collected using three settings on each of five devices, generating nearly 9,000 individual readings to compare against Membrane Filtration taken in triplicate as the true E. coli concentration. Spearman’s rank correlation revealed no statistical significance between the sensor score and E. coli concentrations (ρ = -0.1493, p = 0.0603). When sensor readings were taken in aggregate, a moderate predictive capacity was observed as a presence/absence classification (AUC = 0.77), though this requires 15 measurements per sample, which is beyond the guidelines of the technology. The sensor frequently misclassified both known-negative and known-positive samples, with a high rate (64%) of score clustering at the extremes (0 or 99). These findings indicate that the sensor in its current form is not suitable for public health evaluation of microbial contamination in drinking water. The lack of predictive ability, which contradicts the marketed capacities and user expectations, is likely not unique to the evaluated sensor. This study highlights the importance of rigorous validation of novel WQM technologies before deployment to identify the appropriate application of sensors, which may remain beneficial, even if not for immediate public health use.

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Publication Details

Published
2025-09-19
DOI
https://doi.org/10.31223/x53748
Primary Topic
Water Quality Monitoring Technologies
Type
article
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article

Unreliable Results of a Commercial Real-Time Water Quality Sensor in Identifying Fecal Contamination of Drinking Water

J. Wang, Timothy Purvis, Kevin J. Zhu, Cecilia M. McHugh et al.
Water Quality Monitoring Technologies
article

Unreliable Results of a Commercial Real-Time Water Quality Sensor in Identifying Fecal Contamination of Drinking Water

J. Wang, Timothy Purvis, Kevin J. Zhu, Cecilia M. McHugh, Joe M. Brown, T.N. Nguyen, Siya Yeolekar, Eddy Ding
article en

Abstract

Low-cost technologies are increasingly being explored and marketed as capable of filling gaps in global water quality monitoring (WQM), especially in resource-limited settings. This study evaluates a commercially available, low-cost triboelectric-based sensor that is marketed for real-time detection of E. coli in drinking and environmental waters. A result of 0 indicates contaminated water, whereas a result of 99 indicates “safe” water. A total of 199 water samples were prepared by serial dilution of raw wastewater influent into deionized water to produce a range of E. coli concentrations from <1 to >100 CFU/100 mL in evaluating the triboelectric sensor. Sensor readings were collected using three settings on each of five devices, generating nearly 9,000 individual readings to compare against Membrane Filtration taken in triplicate as the true E. coli concentration. Spearman’s rank correlation revealed no statistical significance between the sensor score and E. coli concentrations (ρ = -0.1493, p = 0.0603). When sensor readings were taken in aggregate, a moderate predictive capacity was observed as a presence/absence classification (AUC = 0.77), though this requires 15 measurements per sample, which is beyond the guidelines of the technology. The sensor frequently misclassified both known-negative and known-positive samples, with a high rate (64%) of score clustering at the extremes (0 or 99). These findings indicate that the sensor in its current form is not suitable for public health evaluation of microbial contamination in drinking water. The lack of predictive ability, which contradicts the marketed capacities and user expectations, is likely not unique to the evaluated sensor. This study highlights the importance of rigorous validation of novel WQM technologies before deployment to identify the appropriate application of sensors, which may remain beneficial, even if not for immediate public health use.

Openalex Percentile: Top 76%
Water Quality Monitoring Technologies
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