Real-Time Industrial Water Pollution Evaluation Using Edge–Cloud IoT Architecture and Multi-Parameter Sensing

The escalating concerns regarding environmental pollution, particularly industrial water pollution, have necessitated the development of advanced monitoring systems to ensure water resource safety and sustainability. This paper presents an innovative IoT-based Industrial Water Pollution Evaluation System that integrates sensor networks, communication technologies, and data analytics to provide real-time, comprehensive water quality assessment in industrial environments. Our system employs an ESP32 microcontroller connected to four critical sensors (pH, temperature, turbidity, and TDS) to monitor water quality parameters continuously. The collected data is transmitted to a cloud platform and visualized through a dedicated Android application, enabling proactive pollution control measures. Experimental results demonstrate the system’s effectiveness in detecting various pollution scenarios with high accuracy. This solution addresses the limitations of traditional monitoring methods by offering cost-effective, real-time monitoring capabilities that support sustainable water management practices in industrial settings.

Authors

Institutions

Publication Details

Journal
NDT
Published
2025-09-09
DOI
https://doi.org/10.3390/ndt3030021
Citations
1
Primary Topic
Water Quality Monitoring Technologies
Type
article
Field-Weighted Citation Impact
0.82
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Real-Time Industrial Water Pollution Evaluation Using Edge–Cloud IoT Architecture and Multi-Parameter Sensing

Anwar Ali Sathio, Saeed Anwar, Raja Vavekanand, Vijay Kumar Singh
1 citations
NDT
Water Quality Monitoring Technologies
0.82
article

Real-Time Industrial Water Pollution Evaluation Using Edge–Cloud IoT Architecture and Multi-Parameter Sensing

Anwar Ali Sathio, Saeed Anwar, Raja Vavekanand, Vijay Kumar Singh
article en
1 citations

Abstract

The escalating concerns regarding environmental pollution, particularly industrial water pollution, have necessitated the development of advanced monitoring systems to ensure water resource safety and sustainability. This paper presents an innovative IoT-based Industrial Water Pollution Evaluation System that integrates sensor networks, communication technologies, and data analytics to provide real-time, comprehensive water quality assessment in industrial environments. Our system employs an ESP32 microcontroller connected to four critical sensors (pH, temperature, turbidity, and TDS) to monitor water quality parameters continuously. The collected data is transmitted to a cloud platform and visualized through a dedicated Android application, enabling proactive pollution control measures. Experimental results demonstrate the system’s effectiveness in detecting various pollution scenarios with high accuracy. This solution addresses the limitations of traditional monitoring methods by offering cost-effective, real-time monitoring capabilities that support sustainable water management practices in industrial settings.

NDTVol. 3(3)
Shaheed Benazir Bhutto University (PK)
Openalex Percentile: Top 23%
Water Quality Monitoring Technologies
0.82
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.