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.

scholarly journals GSM Based Water Quality Monitoring System Using Arduino

2019 ◽  
Vol 6 (4) ◽  
pp. 22-26
Author(s):  
S Gokulanathan ◽  
P Manivasagam ◽  
N Prabu ◽  
T Venkatesh
Keyword(s):  
Water Quality ◽  
Monitoring System ◽  
Rapid Development ◽  
Water Quality Monitoring ◽  
Quality Parameters ◽  
Vital Role ◽  
Quality Monitoring ◽  
Human Society ◽  
Power Efficient

This paper investigates about water quality monitoring system through a wireless sensor network. Due to the rapid development and urbanization, the quality of water is getting degrade over year by year, and it leads to water-borne diseases, and it creates a bad impact. Water plays a vital role in our human society and India 65% of the drinking water comes from underground sources, so it is mandatory to check the quality of the water. In this model used to test the water samples and through the data it analyses the quality of the water. This paper delivers a power efficient, effective solution in the domain of water quality monitoring it also provides an alarm to a remote user, if there is any deviation of water quality parameters.

scholarly journals Design of On-line Water Quality Monitoring System

2021 ◽  
Vol 271 ◽  
pp. 02009
Author(s):  
Tan Fenfang
Keyword(s):  
Water Quality ◽  
Monitoring System ◽  
Human Life ◽  
Water Quality Monitoring ◽  
Quality Parameters ◽  
Quality Monitoring ◽  
Agricultural Wastewater ◽  
On Line ◽  
Normal Production ◽  
Software And Hardware

Water is the source of human life. However, a large amount of domestic sewage, industrial wastewater and agricultural wastewater produced in human production and life pollute the surface water, threatening normal production and life of people.In order to grasp the water quality fully, the temperature, PH. turbidity and conductivity sensors are adopted to collect various water quality parameters, and necessary software and hardware design of the on-line water quality' monitoring system is completed to provide a basis for subsequent water quality monitoring in various industries.

scholarly journals Design of Water Quality Monitoring System for Crab Larvae using IOT

2020 ◽  
Vol 3 (1) ◽  
pp. 46-49
Author(s):  
Wahyudi Sofyan ◽  
Muhammad Niswar ◽  
Andani Achmad
Keyword(s):  
Water Quality ◽  
Real Time ◽  
Monitoring System ◽  
Sensor Node ◽  
Water Quality Monitoring ◽  
Sensor Nodes ◽  
Quality Monitoring ◽  
Transport Protocol ◽  
Message Queue ◽  
Crab Larvae

Abstract Water quality is one of the determining factors in maintaining survival and growth of crab larvae, therefore we need a tool that can monitor water quality which includes temperature parameters, pH and salinity in real time and online in crab larva culture. This system consists of several sensor nodes with the main component being Arduino Uno which is connected by several sensor nodes as a publisher and Raspberry Pi 3 (RPi3) board as a broker. Data from each sensor node will be sent to brokers with different topics - and stored to a database using a wireless network. The application system used with the MQTT (Message Queue Telemetry Transport) protocol uses a red node. Red node will display data of each sensor node in the form of gauge and graph. In this study a water quality monitoring system was designed and developed. This tool uses the MQTT (Message Queue Telemetry Transport) protocol to display sensor node data in real time.

Study on Automation Control with Water Quality Monitoring System Based on GPRS Technology

2013 ◽  
Vol 738 ◽  
pp. 239-242 ◽  
Author(s):  
Shi Wei Lin ◽  
Yu Wen Zhai
Keyword(s):  
Water Quality ◽  
Monitoring System ◽  
Production Efficiency ◽  
Water Quality Monitoring ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
System Structure ◽  
Quality Monitoring ◽  
Automation Control ◽  
Economy Benefit

The method of water quality monitoring applied by reservoirs is sampling in the scene and analyzing at the laboratory at present. Based on analyzing key problem of water quality monitoring, automatic water quality monitoring system based on GPRS is provided in this paper. The system structure and principle are introduced. The system collects, transmits and processes water quality parameters automatically, so the production efficiency and the economy benefit are improved greatly.

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 Wireless water quality monitoring system for high density aquaculture application

2019 ◽  
Vol 13 (2) ◽  
pp. 507 ◽  
Author(s):  
F. A. Saparudin ◽  
T. C. Chee ◽  
A. S. Ab Ghafar ◽  
H. A. Majid ◽  
N. Katiran
Keyword(s):  
Water Quality ◽  
Monitoring System ◽  
Water Quality Monitoring ◽  
High Density ◽  
Public Access ◽  
Sensor Nodes ◽  
Quality Monitoring ◽  
Water Quality Parameter ◽  
Smart Devices ◽  
Multiple Sensor

<span>Water quality is one of the major factors that greatly affects growth and mortality rate of aquatic livestock especially in high density aquaculture system.  Conventional method requires fish farmer to perform manual water quality test and record on multiple fish tanks in regular basis. This process is meticulous, and may affect aquatic livestock that needs close and immediate attention. In this paper, water quality monitoring system for the high density aquaculture environment is proposed. The monitoring system is composed of multiple sensor nodes and sensor/server node hybrid, which used to collect and manage the water quality parameter data of multiple tanks. The sensor nodes collect and store the water quality parameters in local database and transmit them to the server node through a wireless communication. The server node is used for data analysis, processing and allow public access via web browser through various Wi-Fi enabled smart devices. This paper presents a proof-of concept of clustered wireless monitoring system focused on the use of multiple sensor nodes to determine the water parameter in real time. This system is cost effective, quickly deployable, and user-friendly with wireless capabilities.</span>

scholarly journals Integration of Remote Sensing and Mexican Water Quality Monitoring System Using an Extreme Learning Machine

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4118
Author(s):  
Leonardo F. Arias-Rodriguez ◽  
Zheng Duan ◽  
José de Jesús Díaz-Torres ◽  
Mónica Basilio Hazas ◽  
Jingshui Huang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Extreme Learning Machine ◽  
Monitoring System ◽  
Field Measurements ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Chl A ◽  
Learning Machine ◽  
Level 2

Remote Sensing, as a driver for water management decisions, needs further integration with monitoring water quality programs, especially in developing countries. Moreover, usage of remote sensing approaches has not been broadly applied in monitoring routines. Therefore, it is necessary to assess the efficacy of available sensors to complement the often limited field measurements from such programs and build models that support monitoring tasks. Here, we integrate field measurements (2013–2019) from the Mexican national water quality monitoring system (RNMCA) with data from Landsat-8 OLI, Sentinel-3 OLCI, and Sentinel-2 MSI to train an extreme learning machine (ELM), a support vector regression (SVR) and a linear regression (LR) for estimating Chlorophyll-a (Chl-a), Turbidity, Total Suspended Matter (TSM) and Secchi Disk Depth (SDD). Additionally, OLCI Level-2 Products for Chl-a and TSM are compared against the RNMCA data. We observed that OLCI Level-2 Products are poorly correlated with the RNMCA data and it is not feasible to rely only on them to support monitoring operations. However, OLCI atmospherically corrected data is useful to develop accurate models using an ELM, particularly for Turbidity (R2=0.7). We conclude that remote sensing is useful to support monitoring systems tasks, and its progressive integration will improve the quality of water quality monitoring programs.

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