Smart Water Quality Monitoring System

Among the largest global health, environmental, and industrial issues is water pollution.The newest technologies, such as machine learning and the Internet of Things, are being studied to meet the growing demand for water monitoring solutions. In order to determine the factors of water quality, including temperature, turbidity, dissolved oxygen (DO), and pH level, and electrical conductivity in real-time and predict them, this study proposes a Smart Water System for Monitoring Quality, which combines of IoT sensors, cloud storage, and machine learning algorithms. To predict the degree of contamination and issue automatic alerts to the concerned parties through which necessary action can be taken, The gathered sensor data isArtificial Neural Network analysis(ANN) to enable prompt action in the urban and industrial water bodies as well as agricultural waters.

Authors

Publication Details

Journal
International Journal for Research in Applied Science and Engineering Technology
Published
2025-09-10
DOI
https://doi.org/10.22214/ijraset.2025.74111
Primary Topic
Water Quality Monitoring Technologies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Smart Water Quality Monitoring System

Imran Ali S
International Journal for Research in Applied Science and Engineering Technology
Water Quality Monitoring Technologies
article

Smart Water Quality Monitoring System

Imran Ali S
article en

Abstract

Among the largest global health, environmental, and industrial issues is water pollution.The newest technologies, such as machine learning and the Internet of Things, are being studied to meet the growing demand for water monitoring solutions. In order to determine the factors of water quality, including temperature, turbidity, dissolved oxygen (DO), and pH level, and electrical conductivity in real-time and predict them, this study proposes a Smart Water System for Monitoring Quality, which combines of IoT sensors, cloud storage, and machine learning algorithms. To predict the degree of contamination and issue automatic alerts to the concerned parties through which necessary action can be taken, The gathered sensor data isArtificial Neural Network analysis(ANN) to enable prompt action in the urban and industrial water bodies as well as agricultural waters.

International Journal for Research in Applied Science and Engineering TechnologyVol. 13(9)
Openalex Percentile: Top 77%
Water Quality Monitoring Technologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.