Recent Advances in Information and Communications Technology (ICT) and Sensor Technology for Monitoring Water Quality

Park, Jungsu; Kim, Keugtae; Lee, Woo Hyoung

doi:10.3390/w12020510

Cited by 79 publications

(50 citation statements)

References 138 publications

(257 reference statements)

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“…Here, we present them depending on the type of device and the relevant water parameters that can be monitored. sensors can also be used to monitor profile-based ambient fluctuations [39]. The most common and widely available solute for chemical sensors is pH and nitrate.…”

Section: A In Situ Sensorsmentioning

confidence: 99%

Sustainable Marine Ecosystems: Deep Learning for Water Quality Assessment and Forecasting

et al. 2021

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An appropriate management of the available resources within oceans and coastal regions is vital to guarantee their sustainable development and preservation, where water quality is a key element. Leveraging on a combination of cross-disciplinary technologies including Remote Sensing (RS), Internet of Things (IoT), Big Data, cloud computing, and Artificial Intelligence (AI) is essential to attain this aim. In this paper, we review methodologies and technologies for water quality assessment that contribute to a sustainable management of marine environments. Specifically, we focus on Deep Leaning (DL) strategies for water quality estimation and forecasting. The analyzed literature is classified depending on the type of task, scenario and architecture. Moreover, several applications including coastal management and aquaculture are surveyed. Finally, we discuss open issues still to be addressed and potential research lines where transfer learning, knowledge fusion, reinforcement learning, edge computing and decision-making policies are expected to be the main involved agents.

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Section: A In Situ Sensorsmentioning

confidence: 99%

Sustainable Marine Ecosystems: Deep Learning for Water Quality Assessment and Forecasting

et al. 2021

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“…Some of these parameters, including pH and temperature, were identified as Key Performance Indicators (KPI) towards developing a Smart Water Quality Monitoring System (SWQMS) [ 23 ]. Smart and cost-effective water quality monitoring systems have been demonstrated, that utilize Internet of Things (IoT) [ 24 ] and Information and Communications Technology (ICT) [ 25 ] to enable connections between different sensors and devices. Currently available integrated sensing systems typically include free chlorine.…”

Section: Introductionmentioning

confidence: 99%

A Low-Cost Multi-Parameter Water Quality Monitoring System

Alam

Clyne

Deen

2021

Sensors

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Multi-parameter water quality monitoring is crucial in resource-limited areas to provide persistent water safety. Conventional water monitoring techniques are time-consuming, require skilled personnel, are not user-friendly and are incompatible with operating on-site. Here, we develop a multi-parameter water quality monitoring system (MWQMS) that includes an array of low-cost, easy-to-use, high-sensitivity electrochemical sensors, as well as custom-designed sensor readout circuitry and smartphone application with wireless connectivity. The system overcomes the need of costly laboratory-based testing methods and the requirement of skilled workers. The proposed MWQMS system can simultaneously monitor pH, free chlorine, and temperature with sensitivities of 57.5 mV/pH, 186 nA/ppm and 16.9 mV/°C, respectively, as well as sensing of BPA with <10 nM limit of detection. The system also provides seamless interconnection between transduction of the sensors’ signal, signal processing, wireless data transfer and smartphone app-based operation. This interconnection was accomplished by fabricating nanomaterial and carbon nanotube-based sensors on a common substrate, integrating these sensors to a readout circuit and transmitting the sensor data to an Android application. The MWQMS system provides a general platform technology where an array of other water monitoring sensors can also be easily integrated and programmed. Such a system can offer tremendous opportunity for a broad range of environmental monitoring applications.

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“…This yields the user and the designer to propose new measurement techniques to monitor a safe grade in consuming water. The recent developments have given an insight on quality measurement equipment but lack the accuracy and precision of the measurement setup (Park et al 2020). When water quality is disturbed it alters the surroundings of the natural habitat including humans.…”

Section: Graphical Abstract Introductionmentioning

confidence: 99%

Integration of sensors for dam water quality analysis – a prototype

Rose

Mary

Karthik

2021

Water Science and Technology

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Water consumed is stored in several water bodies in and around us, out of which dams accommodate a major portion of water. The quantity and quality monitoring of water in Dams is troublesome due to its large surface area and high depths. Though groundwater resources are the primary water source in India, Dams plays a vital role in water distribution and storage network. Central Water Commission in India has identified more than 5,000 dams of which a major portion is persistently consumed by the rural and urban population for drinking and irrigation. The water quality of these reservoirs is of serious concern as it would not only affect the socio-economic status of the nation but the aquatic systems as well. Water quality control and management are vital for delivering clean water supply to the common society. Because of their size, collecting, assessing, and managing a vast volume of water quality data is critical. Water quality data is primarily obtained through manual field sampling; however, real-time sensor monitoring is increasingly being used for more efficient data collection. The literature depicts that the methodsinvolving remote sensing and image processing of water quality analysis consume time, require sample collection at various depths, analysis of collected samples, and manual interpretations. The objective of this study is to propose a novel cost-effective method to monitor water quality devoid of considerable human intervention. The sensor-based online monitoring aids in assessing the sample with limited technology, at various depths of water in the dam to analyze turbidity which gives the major indication of pure water. The quality analysis of the dam water is worthy if the water is assessed at the distribution end before consumption. Hence, to enhance the water management system, other quality parameters like pH, conductivity, temperature are sensed and monitored in the distribution pipeline. The unstable pH can alter the chemical and microbiological aspects of water resulting in a variation of other water quality parameters Temperature variations affect the amount of dissolved oxygen in the water bodies which results in unstable quality parameters. The change in dissolved solvents and the ionic concentration alters the electrical conductivity of the water and the increased concentration of salts also results in turbidity. The data from all the sensors are processed by the microcontroller, transmitted, and displayed in a mobile application comprehensible to the layman.

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Recent Advances in Information and Communications Technology (ICT) and Sensor Technology for Monitoring Water Quality

Cited by 79 publications

References 138 publications

Sustainable Marine Ecosystems: Deep Learning for Water Quality Assessment and Forecasting

Sustainable Marine Ecosystems: Deep Learning for Water Quality Assessment and Forecasting

A Low-Cost Multi-Parameter Water Quality Monitoring System

Integration of sensors for dam water quality analysis – a prototype

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