IoT Based Real-time River Water Quality Monitoring System

Chowdury, Mohammad Salah Uddin; Emran, Talha Bin; Ghosh, Subhasish; Pathak, Abhijit; Alam, Mohd. Manjur; Absar, Nurul; Andersson, Karl; Hossain, Mohammad Shahadat

doi:10.1016/j.procs.2019.08.025

Cited by 151 publications

(59 citation statements)

References 15 publications

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“…The parameter E. coli remains constantly high for the whole year, while TP decreases in spring. NH 4 -N furtherly increases in summer and BOD 5 shows lower values in autumn. The second factor (PC2) explains 56% of the total variance and has a strong positive loading on DO and positive moderate loading on NO 3 -N. While the oxygen remains high all year round, the NO 3 -N levels are quite low if one considers the seasonal trend.…”

Section: Comparison With Pcamentioning

confidence: 91%

MIMR Criterion Application: Entropy Approach to Select the Optimal Quality Parameter Set Responsible for River Pollution

Mirauda

Ostoich

2020

Sustainability

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Surface water quality has a vital role when defining the sustainability of the ecological environment, public health, and the social and economic development of whole countries. Unfortunately, the rapid growth of the worldwide population together with the current climate change have mostly determined fluvial pollution. Therefore, the employment of effective methodologies, able to rapidly and easily obtain reliable information on the quality of rivers, is becoming fundamental for an efficient use of the resource and for the implementation of mitigation measures and actions. The Water Quality Index (WQI) is among the most widely used methods to provide a clear and complete picture of the contamination status of a river stressed by point and diffuse sources of natural and anthropic origin, leading the policy makers and end-users towards a more and more correct and sustainable management of the water resource. The parameter choice is one of the most important and complex phases and recent statistical techniques do not seem to show great objectivity and accuracy in the identification of the real water quality status. The present paper offers a new approach, based on entropy theory and known as the Maximum Information Minimum Redundancy (MIMR) criterion, to define the optimal subset of chemical, physical, and biological parameters, describing the variation of the river quality level in space and time and thus identifying its pollution sources. An algorithm was implemented for the MIMR criterion and applied to a sample basin of Northeast Italy in order to verify its reliability and accuracy. A comparison with the Principal Component Analysis (PCA) showed how the MIMR is more suitable and objective to obtain the optimal quality parameters set, especially when the amount of investigated variables is small, and can thus be a useful tool for fast and low-cost water quality assessment in rivers.

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Section: Comparison With Pcamentioning

confidence: 91%

MIMR Criterion Application: Entropy Approach to Select the Optimal Quality Parameter Set Responsible for River Pollution

Mirauda

Ostoich

2020

Sustainability

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“…It can obtain the status of water pollution and also provide an important reference for subsequent treatment decisions [1]. Due to the lack of rapid and effective detection and treatment methods, large-scale water pollution incidents are still occurring repeatedly [2,3]. In the past three decades, more and more researches focus on water quality detection and lots of guidelines and quality standards have been developed by specialized regulators and organizations [1,3].…”

Section: Introductionmentioning

confidence: 99%

“…Due to the lack of rapid and effective detection and treatment methods, large-scale water pollution incidents are still occurring repeatedly [2,3]. In the past three decades, more and more researches focus on water quality detection and lots of guidelines and quality standards have been developed by specialized regulators and organizations [1,3]. Traditional water quality detection requires taking water samples back to the laboratory, which takes too much time.…”

Section: Introductionmentioning

confidence: 99%

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A MEMS-Based Multi-Parameter Integrated Chip and Its Portable System for Water Quality Detection

Wang

Bian

et al. 2020

Micromachines

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As an important means to protect water resources, water quality detection is of great social and economic significance. Water quality detection sensors processed by micro-electro-mechanical system (MEMS) technology have the advantages of low-cost, small size, and high sensitivity. In this paper, a multi-parameter water quality detection integrated sensor chip is further studied, and a portable detection system using this chip is developed. Temperature, pH, oxidation-reduction potential (ORP), conductivity and concentration of copper ions (Cu2+) are selected as typical water quality parameters. Experiments of sensor calibrations using this portable detection system were performed in standard solutions. The sensor has a sensitivity of −57.34 mV/pH in pH detection and 5.95 Ω/°C in temperature response. ORP is directly detected by Pt microelectrode on the chip and the relative error is less than 3%. The electrode constant of the sensor is 1.416 cm−1 and the linearity is 0.9995 in conductivity detection. With the gold nanoparticles deposited on the electrode, the detection peak of Cu2+ appears at 280 mV and the sensor shows good linearity to the concentration of Cu2+ in the range of 0–0.6 mg/L. The detection limit of Cu2+ concentration is 2.33 μg/L. Through measurement and calculation, the accuracy of the portable system is within 4%. This portable multi-parameter water quality detection system with the MEMS-based integrated chip shows great potential in the field and fast detection.

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“…An instant response and action to on-going illegal discharge could be taken to avoid the subsequent continuous pollution in agricultural water resources. Existing manual sampling exhibited difficulties in real-time water quality monitoring, in terms of frequency and intensity of sampling [9]. The development and deployment of continuous automatic sampling and real-time water quality monitoring system were important to overcome the aforementioned issue.…”

Section: Introductionmentioning

confidence: 99%

Establishment of an Automatic Real-Time Monitoring System for Irrigation Water Quality Management

Syu

Chang

Pan

2020

IJERPH

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In order to provide the real-time monitoring for identifying the sources of pollution and improving the irrigation water quality management, the integration of continuous automatic sampling techniques and cloud technologies is essential. In this study, we have established an automatic real-time monitoring system for improving the irrigation water quality management, especially for heavy metals such as Cd, Pb, Cu, Ni, Zn, and Cr. As a part of this work, we have first provided several examples on the basic water quality parameters (e.g., pH and electrical conductance) to demonstrate the capacity of data correction by the smart monitoring system, and then evaluated the trend and variance of water quality parameters for different types of monitoring stations. By doing so, the threshold (to initiate early warming) of different water quality parameters could be dynamically determined by the system, and the authorities could be immediately notified for follow-up actions. We have also provided and discussed the representative results from the real-time automatic monitoring system of heavy metals from different monitoring stations. Finally, we have illustrated the implications of the developed smart monitoring system for ensuring the safety of irrigation water in the near future, including integration with automatic sampling for establishing information exchange platform, estimating fluxes of heavy metals to paddy fields, and combining with green technologies for nonpoint source pollution control.

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IoT Based Real-time River Water Quality Monitoring System

Cited by 151 publications

References 15 publications

MIMR Criterion Application: Entropy Approach to Select the Optimal Quality Parameter Set Responsible for River Pollution

MIMR Criterion Application: Entropy Approach to Select the Optimal Quality Parameter Set Responsible for River Pollution

A MEMS-Based Multi-Parameter Integrated Chip and Its Portable System for Water Quality Detection

Establishment of an Automatic Real-Time Monitoring System for Irrigation Water Quality Management

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