scholarly journals Pengendalian Kualitas Air untuk Tanaman Hidroponik Menggunakan Raspberry Pi dan Arduino Uno

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Ryan Ganesha Calibra ◽  
Irfan Ardiansah ◽  
Nurpilihan Bafdal
Keyword(s):  
Water Quality ◽  
Growth And Development ◽  
Low Cost ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Raspberry Pi ◽  
Time Data ◽  
Soil Nutrition ◽  
Remote System ◽  
Total Dissolved Solid

Water quality is very important for plant’s growth and development. Some of the important part of the water qualities are TDS(Total Dissolved Solid), EC(Electrical Conductivity), pH(Acidity). Cultivation inside a greenhouse provides some benefits but also have some deficiency, such as lack of soil nutrition because most plants inside greenhouse uses non soil growing media. To overcome the deficiency, An automated and remote system is needed to ease the controlling of water quality and nutrition feeding to the plant. This study aims to create low-cost greenhouse water quality monitoring that automatically display the real time data on a website. This research is done by using an engineering design methods. This system can be integrated with auto-pot watering system . The result shows that the system can adjust the TDS and pH as programmed, which are TDS= 1000-1200, and pH =5.5-6.5(these are recommended needs for Tomato plant). The TDS sensor in this reseach have the limitation of reading 0~1500ppm.

Smart and Low Cost Real Time Water Quality Monitoring System Using IoT

2019 ◽  
Author(s):  
Jeba Anandh S ◽  
Anandharaj M ◽  
Aswinrajan J ◽  
Karankumar G ◽  
Karthik P
Keyword(s):  
Water Quality ◽  
Real Time ◽  
Monitoring System ◽  
Low Cost ◽  
Water Quality Monitoring ◽  
Quality Monitoring

scholarly journals A Low-Cost Water Quality Monitoring System for the Ayeyarwady River in Myanmar Using a Participatory Approach

Water ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 1984 ◽  
Author(s):  
Thanda Thatoe Nwe Win ◽  
Thom Bogaard ◽  
Nick van de Giesen
Keyword(s):  
Water Quality ◽  
Mobile Phone ◽  
Low Cost ◽  
School Teacher ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Quality Data ◽  
Water Quality Data ◽  
Lower Accuracy

Newly developed mobile phone applications in combination with citizen science are used in different fields of research, such as public health monitoring, environmental monitoring, precipitation monitoring, noise pollution measurement and mapping, earth observation. In this paper, we present a low-cost water quality mobile phone measurement technique combined with sensor and test strips, and reported the weekly-collected data of three years of the Ayeyarwady River system by volunteers at seven locations and compared these results with the measurements collected by the lab technicians. We assessed the quality of the collected data and their reliability based on several indicators, such as data accuracy, consistency, and completeness. In this study, six local governmental staffs and one middle school teacher collected baseline water quality data with high temporal and spatial resolution. The quality of the data collected by volunteers was comparable to the data of the experienced lab technicians for sensor-based measurement of electrical conductivity and transparency. However, the lower accuracy (higher uncertainty range) of the indicator strips made them less useful in the Ayeyarwady with its relatively small water quality variations. We showed that participatory water quality monitoring in Myanmar can be a serious alternative for a more classical water sampling and lab analysis-based monitoring network, particularly as it results in much higher spatial and temporal resolution of water quality information against the very modest investment and running costs. This approach can help solving the invisible water crisis of unknown water quality (changes) in river and lake systems all over the world.

Temporal scale effect of loading data on instream nitrate-nitrogen load computation

2012 ◽  
Vol 66 (1) ◽  
pp. 36-44 ◽  
Author(s):  
Abhijit Patil ◽  
Zhiqiang Deng
Keyword(s):  
Water Quality ◽  
Scale Effect ◽  
Nitrate Nitrogen ◽  
Watershed Modeling ◽  
Water Quality Monitoring ◽  
Temporal Scale ◽  
Quality Monitoring ◽  
Hydrologic Simulation ◽  
Time Data ◽  
Daily Data

The temporal scale effect of loading data on nitrate-nitrogen load computation was examined using outputs of watershed modeling tool Hydrologic Simulation Program-FORTRAN (HSPF) for the Amite River in Louisiana, USA. The daily nitrate-nitrogen concentrations simulated using the HSPF were employed first to obtain daily, weekly, bi-weekly, and monthly average data and then to develop load duration curves for the data with four different temporal scales. The duration curves exhibited high variability in the load estimated using daily data as compared with those based on bi-weekly and monthly data. According to daily data, the nitrate-nitrogen load in the winter was found to be 2,780 kg. The nitrate-nitrogen load decreased with increasing temporal (daily, weekly, bi-weekly, and monthly) scale (commonly used in water quality monitoring) of the data. The coefficient of variation, used to quantify the effect of temporal scale on the load, was found to be linearly and inversely correlated with the logarithm of the time scale. Based on the finding, empirical equations were proposed to extrapolate near real-time data for flow and nitrate-nitrogen, greatly simplifying nutrient monitoring and reducing the cost involved in water quality monitoring.

scholarly journals On the Use of an IoT Integrated System for Water Quality Monitoring and Management in Wastewater Treatment Plants

Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 1096 ◽  
Author(s):  
Ramón Martínez ◽  
Nuria Vela ◽  
Abderrazak el Aatik ◽  
Eoin Murray ◽  
Patrick Roche ◽  
...  
Keyword(s):  
Water Quality ◽  
Wireless Sensor Networks ◽  
Wastewater Treatment ◽  
Sensor Networks ◽  
Low Cost ◽  
Treatment Plant ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Wireless Sensor ◽  
Smart Water

The deteriorating water environment demands new approaches and technologies to achieve sustainable and smart management of urban water systems. Wireless sensor networks represent a promising technology for water quality monitoring and management. The use of wireless sensor networks facilitates the improvement of current centralized systems and traditional manual methods, leading to decentralized smart water quality monitoring systems adaptable to the dynamic and heterogeneous water distribution infrastructure of cities. However, there is a need for a low-cost wireless sensor node solution on the market that enables a cost-effective deployment of this new generation of systems. This paper presents the integration to a wireless sensor network and a preliminary validation in a wastewater treatment plant scenario of a low-cost water quality monitoring device in the close-to-market stage. This device consists of a nitrate and nitrite analyzer based on a novel ion chromatography detection method. The analytical device is integrated using an Internet of Things software platform and tested under real conditions. By doing so, a decentralized smart water quality monitoring system that is conceived and developed for water quality monitoring and management is accomplished. In the presented scenario, such a system allows online near-real-time communication with several devices deployed in multiple water treatment plants and provides preventive and data analytics mechanisms to support decision making. The results obtained comparing laboratory and device measured data demonstrate the reliability of the system and the analytical method implemented in the device.

scholarly journals System-Aware Smart Network Management for Nano-Enriched Water Quality Monitoring

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
B. Mokhtar ◽  
M. Azab ◽  
N. Shehata ◽  
M. Rizk
Keyword(s):  
Water Quality ◽  
Network Management ◽  
Real Time ◽  
Learning Algorithm ◽  
Rule Learning ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
System Control ◽  
Test Bed ◽  
Time Data

This paper presents a comprehensive water quality monitoring system that employs a smart network management, nano-enriched sensing framework, and intelligent and efficient data analysis and forwarding protocols for smart and system-aware decision making. The presented system comprises two main subsystems, a data sensing and forwarding subsystem (DSFS), and Operation Management Subsystem (OMS). The OMS operates based on real-time learned patterns and rules of system operations projected from the DSFS to manage the entire network of sensors. The main tasks of OMS are to enable real-time data visualization, managed system control, and secure system operation. The DSFS employs a Hybrid Intelligence (HI) scheme which is proposed through integrating an association rule learning algorithm withfuzzylogic and weighted decision trees. The DSFS operation is based on profiling and registering raw data readings, generated from a set of optical nanosensors, as profiles of attribute-value pairs. As a case study, we evaluate our implemented test bed via simulation scenarios in a water quality monitoring framework. The monitoring processes are simulated based on measuring the percentage of dissolved oxygen and potential hydrogen (PH) in fresh water. Simulation results show the efficiency of the proposed HI-based methodology at learning different water quality classes.

scholarly journals IDC Sensor for Low-Cost Water Quality Monitoring Applications

2021 ◽  
Vol 26 ◽  
Author(s):  
Diego Mendez-Chaves ◽  
Manuel Perez ◽  
Alejandro Farfan ◽  
Eduardo Gerlein
Keyword(s):  
Water Quality ◽  
Large Scale ◽  
Low Cost ◽  
Complete Solution ◽  
Implementation Process ◽  
Measuring Method ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
New Paradigm ◽  
Monitoring Applications

In order to properly monitor the health status of the hydrological resources of a region, in terms of water contamination, a scalable and low-cost system is necessary to map the water quality at different locations and allow the prioritization of more sophisticated and expensive monitoring campaigns on those areas where a suspicious behavior seems to be occurring. This paper presents the design and implementation process of such an IoT-based solution for low-cost and scalable water quality monitoring applications. To achieve that end, we propose the utilization of a low-cost inter-digital capacitance (IDC) sensor to characterize the conductivity of the water, a very telling parameter about the level of pollution in the water. Additionally, an embedded method to measure such sensor was designed and implemented, which considers the requirements of a portable platform: low computational capabilities, small memory and low power consumption. Our results show that an IDC sensor is capable of detecting the changes of the capacitance of the sample, and therefore mapping the changes in the conductivity of the water. Additionally, integrating an embedded measuring method is a valid option for in-situ characterization of water samples and the complete solution enables a new paradigm for water quality monitoring in large scale scenarios.

Digital Colorimetry: Raspberry Pi-Based Sensors for Ar and Water Quality Monitoring

2021 ◽  
Vol MA2021-02 (55) ◽  
pp. 1593-1593
Author(s):  
Aleksandar Radu ◽  
Matthew O'Brien ◽  
Ernesto Val
Keyword(s):  
Water Quality ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Raspberry Pi ◽  
Digital Colorimetry

A Low-Cost IoT Based Automatic Water Quality Monitoring System for Textile Industry

2021 ◽  
Author(s):  
Avishek Das Gupta ◽  
Zafar Sadek ◽  
Md. Harunur Rashid Bhuiyan ◽  
Md. Golam Kibria ◽  
Tarik Reza Toha ◽  
...  
Keyword(s):  
Water Quality ◽  
Monitoring System ◽  
Textile Industry ◽  
Low Cost ◽  
Water Quality Monitoring ◽  
Quality Monitoring

scholarly journals A Reliable Wireless System for Water Quality Monitoring and Level Control

2016 ◽  
Vol 8 (3) ◽  
pp. 1 ◽  
Author(s):  
Hyder Khaleeq ◽  
Ali Abou-ElNour ◽  
Mohammed Tarique
Keyword(s):  
Water Quality ◽  
Distribution System ◽  
Drinking Water Treatment ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Quality Data ◽  
Level Control ◽  
Time Data ◽  
Wireless System ◽  
Water Quality Data

With the ever increasing growth in population water quality monitoring has become a critical issue in the recent years. Water quality monitoring is very important for aquaculture, waste water management, drinking water treatment, water distribution system, and other environmental applications. Recently numerous researchers have been initiated to build wireless system for water quality monitoring (WSWQM). The two fold objectives of WSWQM are (a) monitoring of water quality from a remote location with minimum supervision, and (b) initiating immediate corrective actions to maintain the required water quality standard. In this paper we present a system model for WSWQM. In this system we integrate a number of sensors, transmitters, receiver, myRIO microcontroller, and IEEE 802.11 Wi-Fi technology. The sensors generate water quality data including pH, conductivity, and temperature. The real-time data are then sent wirelessly to a local control unit for analyzing, recording, and displaying. The system is also able to send alarm messages automatically to a remote management center when water quality fails to meet the required standard. In order to ensure high accuracy and reliability we use industry standard sensors and instruments to implement this system.

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