A review of emerging trends on water quality measurement sensors

Bhardwaj, Jyotirmoy; Gupta, Karunesh Kumar; Gupta, Rajiv

doi:10.1109/ictsd.2015.7095919

Cited by 42 publications

(25 citation statements)

References 56 publications

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“…Python has been experimented in a wide variety of applications ranging from environmental, home and industrial. Python framework has also been used in the development of ubiquitous wireless sensor network frameworks (Bocchino et al, 2015). Python facilitates the task of application development and minimizes the dependency on expertise of the embedded system.…”

Section: Cps Soft Computing Framework Developmentmentioning

confidence: 99%

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Bhardwaj¹

2017

Preprint

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The overall system cost and comparison analysis ? The cost analysis has been addressed in revised manuscript in section 2.4. overall cost of sensors and hardware unit was 589 US $. However, this cost does not include the cost of consumables, data collection, power source, scientific supervision, labor, resources used for sample collection and shipping to analytical laboratories b. Does the proposed system is feasible for rural deployments ? Yes, as system is low cost and capable to sustain for longer period of times due to low power requirements. C1

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Section: Cps Soft Computing Framework Developmentmentioning

confidence: 99%

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Bhardwaj¹

2017

Preprint

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“…Starting from the late 2000s, new technologies were introduced to address some of these limitations. In particular, new sensors were developed that utilize fiber optics, laser technology, biosensors, optical sensors, and microelectronic mechanical systems (MEMS) to detect different water quality parameters in situ [Bhardwaj et al 2015;Sawaya et al 2003], whereas computing and telemetry technologies were introduced to support the data acquisition and monitoring processes. Moreover, new methodologies like satellite image acquisition to remotely estimate some water quality parameters [Sawaya et al 2003] and architectures for visualizing the water quality parameters through the Internet were introduced to monitor lakes, rivers, and other water bodies [Hall et al 2007].…”

Section: Introductionmentioning

confidence: 99%

Water Quality Monitoring Using Wireless Sensor Networks

Adu-Manu

Tapparello

Heinzelman

et al. 2017

ACM Trans. Sen. Netw.

241

128

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Water is essential for human survival. Although approximately 71% of the world is covered in water, only 2.5% of this is fresh water; hence, fresh water is a valuable resource that must be carefully monitored and maintained. In developing countries, 80% of people are without access to potable water. Cholera is still reported in more than 50 countries. In Africa, 75% of the drinking water comes from underground sources, which makes water monitoring an issue of key concern, as water monitoring can be used to track water quality changes over time, identify existing or emerging problems, and design effective intervention programs to remedy water pollution. It is important to have detailed knowledge of potable water quality to enable proper treatment and also prevent contamination. In this article, we review methods for water quality monitoring (WQM) from traditional manual methods to more technologically advanced methods employing wireless sensor networks (WSNs) for in situ WQM. In particular, we highlight recent developments in the sensor devices, data acquisition procedures, communication and network architectures, and power management schemes to maintain a long-lived operational WQM system. Finally, we discuss open issues that need to be addressed to further advance automatic WQM using WSNs.

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“…Traditionally turbidity measurements have involved onsite water sample collection and subsequent laboratory analysis, which is both labour-intensive and costly [3]. Several studies have shown that the need for continuous online water quality monitoring has become essential to the water industry and for ecosystem research [4] [5]. These studies have also proven the need for high spatial and temporal resolution of the on-line monitoring systems in order to recover adequate data on which to base downstream control measures or ecosystem models or both.…”

Section: Introductionmentioning

confidence: 99%

Low-Cost Turbidity Sensor for Low-Power Wireless Monitoring of Fresh-Water Courses

et al. 2018

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This paper reports on a low-cost turbidity sensor design for continuous on-line water quality monitoring applications. The measurement of turbidity by agricultural and environmental scientists is restricted by the current cost and functionality of available commercial instruments. Although there are a number of low-cost turbidity sensors exploited within domestic 'white-goods', such as dishwashers, the lack of sensitivity and power-usage of these devices make them unsuitable for freshwater quality monitoring purposes. The recent introduction of wireless protocols and hardware, associated with the 'Internet-of-Things' concept for machine-tomachine autonomous sensing and control, has enabled the largescale networked intelligent water turbidity monitoring system that implements relatively low-cost sensors to be developed. The proposed sensor uses both transmitted light and orthogonal (90 degrees) scattered light detection principles, and is 2-3 orders of magnitude lower in cost as compared to the existing commercial turbidity sensors. With an 850nm infrared LED, and dual orthogonal photodetectors, the proposed design is capable of measuring turbidity within the range of 0-1000 Nephelometric Turbidity Unit (NTU) with improved accuracy and robustness as compared to the existing low cost turbidity sensors. The combination of orthogonal and transmitted light detection unit provide both 0-200 NTU high resolution and accuracy sensing and 0-1000 NTU lower resolution and accuracy sensing capability. Results from calibration experiment are presented, which proved that the proposed sensor design produced a comparable turbidity reading as a commercial turbidity sensor.

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A review of emerging trends on water quality measurement sensors

Cited by 42 publications

References 56 publications

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Water Quality Monitoring Using Wireless Sensor Networks

Low-Cost Turbidity Sensor for Low-Power Wireless Monitoring of Fresh-Water Courses

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