Research Article
Development and Experimental Validation of an
IoT-enabled Water Quality Measurement Framework
Issue:
Volume 14, Issue 2, April 2026
Pages:
52-71
Received:
9 February 2026
Accepted:
21 February 2026
Published:
4 March 2026
Abstract: Sensors act as transducers that convert physical signals into electrical outputs for analysis. When integrated with IoT, they enhance water quality monitoring by improving accuracy, autonomy, and real-time detection of parameters such as pathogens, temperature, and Total Dissolved Solids/Electrical Conductivity (TDS/EC). In line with SDG 6, this study developed an IoT-based system for on-site monitoring and real-time data transmission to relevant authorities. The system uses TDS/EC sensors to measure dissolved ion concentration and a DS18B20 digital temperature sensor to provide temperature compensation for conductivity values. Data are processed via an Arduino Mega and transmitted to the Thing Speak cloud. Our results show temperature stability (28–30°C) and demonstrate that compensation significantly reduces variability, stabilizing TDS/EC readings and improving correlation. The compensation results demonstrated that raw TDS/EC values had a weak correlation with temperature, whereas compensated readings remained stable across the same conditions. The temperature histogram highlights the narrow range of environmental variation, reinforcing dataset stability. Histograms of raw versus compensated data confirm that DS18B20-based compensation enhances measurement accuracy and reliability, ensuring that detected anomalies reflect true water quality variations rather than environmental noise. Collectively, these plots validate that DS18B20-based compensation significantly improves accuracy and reliability in real-time IoT water quality monitoring. In summary, the correlation and regression analysis clearly demonstrate the effectiveness of the temperature compensation mechanism. A strong positive correlation (r = 0.82) and high R² value (0.67) indicate that raw TDS/EC measurements are heavily influenced by temperature fluctuations. After applying DS18B20-based temperature compensation, these effects were significantly reduced, with the correlation dropping to 0.18 and R² decreasing to 0.03. This confirms that temperature compensation enhances the stability, reliability, and interpretability of conductivity-based water quality measurements.
Abstract: Sensors act as transducers that convert physical signals into electrical outputs for analysis. When integrated with IoT, they enhance water quality monitoring by improving accuracy, autonomy, and real-time detection of parameters such as pathogens, temperature, and Total Dissolved Solids/Electrical Conductivity (TDS/EC). In line with SDG 6, this st...
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Research Article
Composite Assessment of Sand Mining Impacts in a Hill River: The Langkaih River, Northeast India
Renthlei Zonunsanga,
Benjamin Lalengliana Sailo*
,
Laldinpuia,
Michael Lalnunpuia,
Ralte Lalhmangaihzuala,
Lalrinawma,
Jonathan Lalrinawma,
Rosiamliana
Issue:
Volume 14, Issue 2, April 2026
Pages:
72-88
Received:
6 February 2026
Accepted:
24 February 2026
Published:
10 March 2026
DOI:
10.11648/j.ijema.20261402.12
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Views:
Abstract: Sand mining in small, steep hill rivers remains poorly quantified despite rising global concern over aggregate-driven ecological degradation. This study develops an integrated, indicator-based framework to evaluate the environmental and socio-economic impacts of manual and mechanical sand mining along the Langkaih River, Mizoram, Northeast India—a transboundary hill river recently subjected to a ban on mechanized extraction. Water quality was assessed at upstream, active, and downstream sites using the Water Quality Index (WQI) and a novel Water Quality Impact Gradient (WQIG), combined with turbidity analysis and livelihood surveys. These datasets informed two composite indicators—the Sand Mining Vulnerability Index (SMVI) and an Integrated Sustainability Index (ISI)—linking environmental pressure, socio-economic dependence, and adaptive capacity. Results show that mechanical suction mining generated extreme turbidity plumes and WQI deterioration from “Poor” to “Unsuitable for drinking,” with a 470% WQIG increase and high vulnerability (SMVI ≈ 64). Manual extraction caused moderate, reversible impacts (WQIG = −29%), higher employment intensity, and greater overall sustainability (ISI = 0.91 vs. 0.27). The framework transparently differentiates mining methods by environmental and livelihood performance, supporting evidence-based regulation in data-limited hill systems. The findings provide a transferable model for sustainable sand governance to protect drinking-water security and riverine ecosystem health across Himalayan and tropical basins.
Abstract: Sand mining in small, steep hill rivers remains poorly quantified despite rising global concern over aggregate-driven ecological degradation. This study develops an integrated, indicator-based framework to evaluate the environmental and socio-economic impacts of manual and mechanical sand mining along the Langkaih River, Mizoram, Northeast India—a ...
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