scholarly journals An Open Source Water Quality Measurement System for Remote Areas

2021 ◽  
Vol 12 (1) ◽  
pp. 50
Author(s):  
Muhammad Owais Tariq ◽  
Asif Siddiq ◽  
Hafsa Irshad ◽  
Muhammad Aman ◽  
Muhammad Shahbaz Khan
Keyword(s):  
Water Quality ◽  
Drinking Water ◽  
Monitoring System ◽  
Ph Value ◽  
Water Quality Monitoring ◽  
Ion Concentration ◽  
Quality Monitoring ◽  
World Health ◽  
Average Error ◽  
Remote Areas

The unavailability of safe drinking water leads to poor conditions related to mental and physical health. To quantify the quality of water, laboratories testing the water are present in major cities which assess the basic quality parameters of drinking water, e.g., total dissolved salts (TDS), ion concentration (conductivity), turbidity, and pH value as recommended by the World Health Organization (WHO). The unavailability of such testing laboratories at remote locations makes the testing of the drinking water difficult. Establishing such laboratories is a tedious job as it requires a lot of costly equipment and specially trained personnel to operate them, making them difficult to handle. To address these issues, a water quality monitoring system for remote areas was designed which is capable of measuring basic measurable qualities of salt concentration, ion concentration, turbidity, and pH value. With the utilization of such a system, the user can qualify the water present in the vicinity as safe or unsafe for drinking purposes. The results from the proposed system are evaluated based on standard testing results and it is found that our water quality monitoring system is in agreement with the standard lab results with an average error of 2.9%, 1.4%, 1.2%, and 1.2% for pH, turbidity, conductivity, and TDS, respectively.

scholarly journals Development of Miniaturized Water Quality Monitoring System Using Wireless Communication

Sensors ◽  
2019 ◽  
Vol 19 (17) ◽  
pp. 3758
Author(s):  
Hsing-Cheng Yu ◽  
Ming-Yang Tsai ◽  
Yuan-Chih Tsai ◽  
Jhih-Jyun You ◽  
Chun-Lin Cheng ◽  
...  
Keyword(s):  
Water Quality ◽  
Electrical Conductivity ◽  
Wireless Communication ◽  
Monitoring System ◽  
Industrial Waste ◽  
Continuous Monitoring ◽  
Copper Ion ◽  
Water Quality Monitoring ◽  
Ion Concentration ◽  
Quality Monitoring

Recently, environmental pollution resulting from industrial waste has been emerging in an endless stream. The industrial waste contains chemical materials, heavy metal ions, and other toxic materials. Once the industrial waste is discharged without standards, it might lead to water or environmental pollution. Hence, it has become more important to provide evidence-based water quality monitoring. The use of a multifunctional miniaturized water quality monitoring system (WQMS), that contains continuous monitoring, water quality monitoring, and wireless communication applications, simultaneously, is infrequent. Thus, electrodes integrated with polydimethylsiloxane flow channels were presented in this study to be a compound sensor, and the sensor can be adopted concurrently to measure temperature, pH, electrical conductivity, and copper ion concentration, whose sensitivities are determined as 0.0193 °C/mV, −0.0642 pH/mV, 1.1008 mS/V·cm (from 0 mS/cm to 2 mS/cm) and 1.1975 mS/V·cm (from 2 mS/cm to 5.07 mS/cm), and 0.0111 ppm/mV, respectively. A LoRa shield connected into the system could provide support as a node of long range wide area network (LoRaWAN) for wireless communication application. As mentioned above, the sensors, LoRa, and circuit have been integrated in this study to a continuous monitoring system, WQMS. The advantages of the multifunctional miniaturized WQMS are low cost, small size, easy maintenance, continuous sampling and long-term monitoring for many days. Every tested period is 180 min, and the measured rate is 5 times per 20 min. The feedback signals of the miniaturized WQMS and measured values of the instrument were obtained to compare the difference. In the measured results at three different place-to-place locations the errors of electrical conductivity are 0.051 mS/cm, 0.106 mS/cm, and 0.092 mS/cm, respectively. The errors of pH are 0.68, 0.87, and 0.56, respectively. The errors of temperature are 0.311 °C, 0.252 °C, and 0.304 °C, respectively. The errors of copper ion concentration are 0.051 ppm, 0.058 ppm, 0.050 ppm, respectively.

scholarly journals Iot Based Water Quality Monitoring System using Machine Learning

2019 ◽  
Vol 8 (4) ◽  
pp. 11801-11805
Keyword(s):  
Machine Learning ◽  
Water Quality ◽  
Drinking Water ◽  
Distributed Computing ◽  
Monitoring System ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Web Of Things ◽  
Water Condition ◽  
Minimal Effort

In the present occasions, because of urbanization and contamination, it has gotten important to screen and assess the nature of water arriving at our homes. Guaranteeing safe inventory of drinking water has become a major test for the cutting edge progress. In this desk work, we present a structure and improvement of a minimal effort framework for continuous checking of the water quality (WQ) in IoT (web of things). The framework comprise of a few sensors are accustomed to guesstimatingsomatic and element limitations of the water. The parameters like temperature, PH, turbidity, conductivity, broke up oxygen of the water can be estimated. The deliberate qualities from the sensors can be prepared by the center controller. The RBPI B+ (RBPI) model can be consumed as a center controller. At last, the instrument facts can be understood on web utilizing distributed computing. Here the information's are handled utilizing AI calculation it sense the water condition if the WQis great it open the entryway divider else it shuts the door divider. This whole procedure happens naturally without human mediation therefore spare an opportunity to contract with the circumstance physically. The uniqueness of our proposed research is to get the water observing framework with high recurrence, high portability, and low controlled.

scholarly journals An Efficient Method in Real Time for Water Quality Monitoring Using Internet of Things

2018 ◽  
Vol 7 (2.32) ◽  
pp. 170 ◽  
Author(s):  
K Bhagavan ◽  
R Vamsi Krishna ◽  
A Chandu Lakshmi Gangadhar ◽  
M Arun
Keyword(s):  
Water Quality ◽  
Drinking Water ◽  
Internet Of Things ◽  
Water Quality Monitoring ◽  
Water Utilities ◽  
Quality Monitoring ◽  
Single Individual ◽  
Remote Areas ◽  
The World ◽  
Valuable Product

In this day and age, Internet of Things (IoT) and Remote Sensing (RS) procedures are being utilized as a part of various regions of research for observing, gathering and breaking down information from remote areas. Drinking water is a valuable product for every single individual as drinking water utilities confront a considerable measure of new difficulties progressively activity. These difficulties start in light of restricted water assets, developing populace, maturing foundation and so on in this way there is a requirement for better techniques to screen the water quality. Keeping in mind the end goal to guarantee the protected and providing of drinking water the quality ought to be checked progressively. In this paper we intend to present the arrangement and development of a minimal attempt framework for genuine observing of water quality in an IoT situation. The structure comprises of a few sensors which are utilized for estimating physical and substance parameters of water [1]. The frameworks, for example, temperature, pH, turbidity, conductivity, broke down oxygen of the water can be estimated. Utilizing this framework a man can recognize toxins from a water body from anyplace in the world. 

scholarly journals Construction and research of water quality monitoring system based on ZigBee technology

2020 ◽  
Vol 165 ◽  
pp. 03060
Author(s):  
Fan Heng
Keyword(s):  
Water Quality ◽  
Monitoring System ◽  
Ph Value ◽  
Water Quality Monitoring ◽  
Quality Parameters ◽  
Sensor Nodes ◽  
Quality Monitoring ◽  
Test Model ◽  
Hardware System ◽  
Zigbee Technology

The water quality monitoring system proposed in this paper is to establish a monitoring system by using the ZigBee technology .The sensor nodes are placed in the monitoring area to form a tree-type network topology, and the data of the water quality parameters (including PH value, turbidity, water temperature, electric conductivity, etc.) are collected and analyzed. This paper mainly expounds the construction of the hardware system of the monitoring system, establishes the test model of the hardware system, simulates the placement of the sensor node to obtain the experimental data, and provides the hardware test result for the overall system design.

Methodological Approaches to Organization of Drinking Water Quality Monitoring Programs

2020 ◽  
pp. 4-8
Author(s):  
Yu.A. Novikova ◽  
I.O. Myasnikov ◽  
A.A. Kovshov ◽  
N.A. Tikhonova ◽  
N.S. Bashketova
Keyword(s):  
Water Quality ◽  
Drinking Water ◽  
Water Supply ◽  
Cold Water ◽  
Water Quality Monitoring ◽  
Drinking Water Quality ◽  
Quality Monitoring ◽  
Water Supply Systems ◽  
Monitoring Programs ◽  
Supply Systems

Summary. Introduction: Drinking water is one of the most important environmental factors sustaining life and determining human health. The goal of the Russian Federal Clean Water Project is to improve drinking water quality through upgrading of water treatment and supply systems using advanced technologies, including those developed by the military-industrial complex. The most informative and reliable sources of information for assessing drinking water quality are the results of systematic laboratory testing obtained within the framework of socio-hygienic monitoring (SGM) and production control carried out by water supply organizations. The objective of our study was to formulate approaches to organizing quality monitoring programs for centralized cold water supply systems. Materials and methods: We reviewed programs and results of drinking water quality laboratory tests performed by Rospotrebnadzor bodies and institutions within the framework of SGM in 2017–2018. Results: We established that drinking water quality monitoring in the constituent entities of the Russian Federation differs significantly in the number of monitoring points (566 in the Krasnoyarsk Krai vs 10 in Sevastopol) and measured indicators, especially sanitary and chemical ones (53 inorganic and organic substances in the Kemerovo Region vs one indicator in the Amur Region). Discussion: For a more complete and objective assessment of drinking water quality in centralized cold water supply systems, monitoring points should be organized at all stages of water supply with account for the coverage of the maximum number of people supplied with water from a particular network. Thus, the number of points in the distribution network should depend, inter alia, on the size of population served. In urban settlements with up to 10,000 inhabitants, for example, at least 4 points should be organized while in the cities with more than 3,000,000 inhabitants at least 80 points are necessary. We developed minimum mandatory lists of indicators and approaches to selecting priority indices to be monitored at all stages of drinking water supply.

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