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Dataset for a wireless sensor network based drinking-water quality monitoring and notification system.


ABSTRACT: This paper presents the collected experimental data for water quality monitoring which was conducted in ten experiments by using five different common sources of water contaminants namely soil, salt, washing powder, chlorine and vinegar and their combination. The data were collected indoors at room temperature during the day for several days using sensors that measure pH, turbidity, flow rate, and conductivity in water. The water consumption risk (CR) was calculated as deviation based on the water quality parameters standards proposed by the World Health Organisation (WHO) and the South African Department of Water Affairs (DWA), with respect to the sensor measurement readings obtained. While the error measurements were calculated based on the expected parameter measurement per conducted experiment and repeated for 26 measurements. Pure tap water was the benchmark of water safe for human consumption. The first five experiments were performed by introducing each contaminant into the water and thereafter, two contaminants in the sixth experiment and their additions until all different contaminants were experimented at once in the last experiment.

SUBMITTER: Sithole MPP 

PROVIDER: S-EPMC6879973 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Dataset for a wireless sensor network based drinking-water quality monitoring and notification system.

Sithole Mhambi Phila Philadephian MPP   Nwulu Nnamdi I NI   Dogo Eustace M EM  

Data in brief 20191116


This paper presents the collected experimental data for water quality monitoring which was conducted in ten experiments by using five different common sources of water contaminants namely soil, salt, washing powder, chlorine and vinegar and their combination. The data were collected indoors at room temperature during the day for several days using sensors that measure pH, turbidity, flow rate, and conductivity in water. The water consumption risk (CR) was calculated as deviation based on the wat  ...[more]

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