Water Quality Management System Research Articles

Research on intelligent river water quality management system using blockchain-internet of things

Research on intelligent river water quality management system using blockchain-internet of things

An Effective Smart Water Quality Monitoring and Management System Using IoT and Machine Learning

An Effective Smart Water Quality Monitoring and Management System Using IoT and Machine Learning

Water Quality Assessment Using the Water Quality Index, and Geographic Information Systems in Nador Canal, Morocco

In recent decades, water pollution has emerged as a significant concern, posing a threat to both humans and natural ecosystems. This study aimed to assess the spatial variations in water quality in the Nador Canal, Morocco using the water quality index combined with multivariate statistical techniques and geographic information systems (GIS). The parameters examined were then compared to the maximum permissible limit values recommended by Moroccan surface water standards and the World Health Organization. The results indicated that the WQI of Nador Canal is generally suitable for irrigation and unsuitable for drinking. It indicated that the quality of surface water in the Nador Canal is affected by organic pollutants, and this is evidenced by low levels of dissolved oxygen, the levels of elements were high, especially chlorine and sodium, in addition to a high concentration of ammonia, nitrate, and phosphate in some of the stations studied. Principal component analysis (PCA) results revealed that PC1–PC3 collectively accounted for 73% of the variation in surface water quality within the study area. The cluster analysis also proves that the water quality is relatively polluted. Potential contributing factors to surface water pollution include changes in the hydrological regime, household waste discharges, and agricultural activities. These findings furnish essential insights into water quality, particularly its suitability for irrigation, and contribute to enhancing the water quality management system of the Nador Canal in the Gharb region of Morocco.

IoT Based Water Quality Management System using ESP32

Water pollution is one of the biggest fears for the green globalization. In order to ensure the safe supply of the drinking water the quality needs to be monitor in real time. In this paper we present a design and development of a low cost system for real time monitoring of the water quality in IOT(internet of things).The system consist of several sensors is used to measuring physical and chemical parameters of the water. The parameters such as temperature, PH, turbidity of the water can be measured. The measured values from the sensors can be processed by the core controller. The Arduino model can be used as a core controller. Finally, the sensor data can be viewed on internet using WI-FI system. The objective of this water quality monitoring system using internet of things is to find the quality of the water i.e. how the pH content varies and sending message to the corresponding authorities. We are going to implement this project at municipal water tanks and drinking water reservoir. For that we are using an Arduino board for finding pH value and GSM module for message technique. We use a led display to have continuous observation on water parameters. Finally the user gets message of pH value of water Further we extend this project by sending the sensor data to cloud for global monitoring of water quality

Automated Water Monitoring & Managing System for Aquaculture Using IOT

In recent years, the Internet of Things (IoT) has emerged as a transformative technology with profound implications for various sectors, including environmental monitoring and management. This paper presents an innovative IoT-based automated water quality monitoring and management system (AWQMS) designed to revolutionize the way we monitor and safeguard water resources.The AWQMS leverages a network of IoT-enabled sensors deployed at strategic locations throughout water bodies, continuously measuring crucial parameters such as pH, dissolved oxygen, turbidity, temperature, and conductivity. These sensors are equipped with wireless communication capabilities, enabling real-time data transmission to a centralized data acquisition and processing platform. At the heart of the AWQMS lies advanced data analytics and machine learning algorithms, which analyze incoming data streams to detect anomalies and deviations from predefined water quality thresholds. Key Word: Automated Water Monitoring and Managing system, IoT based solution, sensor-based monitoring, Real time monitoring system, cost-effectiveness.

Design and development of an IoT-based intelligent water quality management system for aquaculture

Water quality is generally known to directly affect the health and growth rate of aquatic organisms and determines the success of any aquaculture fish production. However, water quality problems are difficult to detect early in aquaculture production facilities, largely because it requires a high level of technical understanding of the physio-chemical properties of water. In this research, an IoT-based intelligent water quality management system for aquaculture was designed and developed to monitor temperature, pH, and turbidity. ESP32 Microcontroller programmed with the C programming language was used to implement the smart control module which received data from the sensors and transmitted to a cloud database. A web application was also developed which enabled real-time monitoring and control of the system by a user from anywhere in the world, via any internet-connected device. Alarms and notifications could be received via WhatsApp Messenger. The system demonstrated capacity to improve the efficiency and productivity of aquaculture production.

Smart Aquaponics: An Automated Water Quality Management System for Sustainable Urban Agriculture

As the demand for high-quality food rises, especially amidst the COVID-19 pandemic and the continuous development of society meaning that people demand to eat well, ensuring food security has become increasingly urgent. Agricultural technology is evolving, with aquaponic systems emerging as a promising solution to urban food needs. However, these systems present challenges, such as maintaining optimal water quality and minimizing environmental control errors. In this study, we propose a comprehensive approach combining a literature review and controlled experiments. Through the literature review, the recent findings on water management and sustainability in food production were analyzed, providing crucial insights for enhancing aquaponic system performance. Building on this, a series of experiments were conducted to develop and test a water quality management system using PID control. The integration of PID control showed good performance and reduced errors in SIMULINK, and we applied three controls to manage the stability and responsiveness of the aquaponic system. The optimal values obtained from the controller of the vegetable tank system were 4,706,691,503 and −174.418; for the fish tank, they were 36,167, 0.00126, and −174.418; and for the heater system, they were 4.761, 0.0488, and −31.88. This solution is expected to be responsive and provide stable control over various variables.

Mplementation of Extreme Learning Machine for Water Quality Control in Vannamei Shrimp Ponds

The application of science and technology knowledge is crucial in supporting the Indonesian Government's program to increase the production of Litopenaesus Vannamei shrimp. This research collaborates with shrimp pond farmers to develop technology that supports the cultivation of vaname shrimp. The water quality affect the harvest results, and the water parameters such as pH, dissolved oxygen (DO), alkalinity, salinity, and temperature should be monitored and adjusted if the parameters exceed the predetermined limits. We have developed an Extreme Learning Machine-based water quality management system tailored to the geographic conditions of Indonesia. This tool uses sensors to read data from the pond water, which is then processed by a microcontroller and displayed in a web-based information system. This tool helps farmers determine the water conditions and condition it accordingly. Based on experimental result error dari data training adalah 0.0001 dan error pada data testing yaitu sebesar 0.1851, it can be seen the Extreme Learning Machine has good performance for this research.

Analyzing the Effectiveness of IOT-Enabled Water Quality Management Systems with Fish Disease Index Parameters – A Critical Review

This research review article examines the effectiveness of Internet of Things (IoT)-enabled water quality management systems in controlling fish diseases. The research conducted a critical review of the literature to analyze the effectiveness of such systems. Through a systematic review of the literature, the authors identified various fish diseases and their associated parameters that are monitored by IoT-enabled water quality management systems. The article then discussed the impacts of various parameters on fish health, and the importance of monitoring these parameters. The authors also highlighted the benefits of using such systems, such as cost-effectiveness, accuracy, and improved data collection and analysis. Finally, the authors proposed various strategies to improve the effectiveness of IoT-enabled water quality management systems, such as the use of multi-parameter sensors, real-time monitoring, and the integration of different sensors to capture a broader range of parameters. In conclusion, the authors argued that IoT-enabled water quality management systems are a cost-effective and accurate way to monitor and manage fish diseases. However, more research is needed to improve the efficiency and accuracy of such systems.

Artificial Intelligence in Internet of Things System for Predicting Water Quality in Aquaculture Fishponds

Aquaculture has long been a critical economic sector in Taiwan. Since a key factor in aquaculture production efficiency is water quality, an effective means of monitoring the dissolved oxygen content (DOC) of aquaculture water is essential. This study developed an internet of things system for monitoring DOC by collecting essential data related to water quality. Artificial intelligence technology was used to construct a water quality prediction model for use in a complete system for managing water quality. Since aquaculture water quality depends on a continuous interaction among multiple factors, and the current state is correlated with the previous state, a model with time series is required. Therefore, this study used recurrent neural networks (RNNs) with sequential characteristics. Commonly used RNNs such as long short-term memory model and gated recurrent unit (GRU) model have a memory function that appropriately retains previous results for use in processing current results. To construct a suitable RNN model, this study used Taguchi method to optimize hyperparameters (including hidden layer neuron count, iteration count, batch size, learning rate, and dropout ratio). Additionally, optimization performance was also compared between 5-layer and 7-layer network architectures. The experimental results revealed that the 7-layer GRU was more suitable for the application considered in this study. The values obtained in tests of prediction performance were mean absolute percentage error of 3.7134%, root mean square error of 0.0638, and R-value of 0.9984. Therefore, the water quality management system developed in this study can quickly provide practitioners with highly accurate data, which is essential for a timely response to water quality issues. This study was performed in collaboration with the Taiwan Industrial Technology Research Institute and a local fishery company. Practical application of the system by the fishery company confirmed that the monitoring system is effective in improving the survival rate of farmed fish by providing data needed to maintain DOC higher than the standard value.

Metal-organic framework-based materials for the abatement of air pollution and decontamination of wastewater.

Developing new and efficient technologies for environmental remediation is becoming significant due to the increase in global concerns such as climate change, severe epidemics, and energy crises. Air pollution, primarily due to increased levels of H2S, SOx, NH3, NOx, CO, volatile organic compounds (VOC), and particulate matter (PM) in the atmosphere, has a significant impact on public health, and exhaust gases harm the natural sulfur, nitrogen, and carbon cycles. Similarly, wastewater discharged to the environment with metal ions, herbicides, pharmaceuticals, personal care products, dyes, and aromatics/organic compounds is a risk for health since it may lead to an outbreak of waterborne pathogens and increase the exposure to endocrine-disrupting agents. Therefore, developing new and efficient air and water quality management systems is critical. Metal-organic frameworks (MOFs) are novel materials for which the main application areas include gas storage and separation, water harvesting from the atmosphere, chemical sensing, power storage, drug delivery, and food preservation. Due to their versatile structural motifs that can be modified during synthesis, MOFs also have a great promise for green applications including air and water pollution remediation. The motivation to use MOFs for environmental applications prompted the modification of their structures via the addition of metal and functional groups, as well as the creation of heterostructures by mixing MOFs with other nanomaterials, to effectively remove hazardous contaminants from wastewater and the atmosphere. In this review, we focus on the state-of-the-art environmental applications of MOFs, particularly for water treatment and air pollution, by highlighting the groundbreaking studies in which MOFs have been used as adsorbents, membranes, and photocatalysts for the abatement of air and water pollution. We finally address the opportunities and challenges for the environmental applications of MOFs.

A STUDY ON INTERNATIONAL COMMUNICATION STANDARDS AND PERFORMANCE STANDARDS FOR SMART WATER QUALITY SENSORS

The world is now building an artificial intelligence (AI) water quality management system to detect water quality accidents at an early stage and predict water quality vulnerable areas in advance beyond measuring the water quality. In other words, by applying big data analysis and artificial intelligence technology to the conventional water quality measurement system that monitors water quality in real time, an artificial intelligence-based water quality measurement and water quality prediction system is built at the same time, and drones and unmanned ships are also introduced. It means implementing water quality management. Water quality accident prediction based on artificial intelligence measures water quality throughout the site of use through intelligent spatial analysis based on the integrated water quality database. On the other hand, the location of the site detected through artificial intelligence is displayed on the comprehensive monitoring screen, and special management such as on-site monitoring, replacement of consumables, and maintenance is carried out to prevent water quality accidents. In particular, the prediction accuracy of artificial intelligence is to create an algorithm for predicting future values by learning the characteristics and patterns of accumulated data. It depends on the function of the smart sensor itself. However, until now, there has been no international standard for smart sensors, so it was difficult to establish system interlocking or modularization for each manufacturer and site. Therefore, we present the most important standard communication standards for smart water quality sensors in the field and international standard performance specifications for smart sensors, and this research data is provided to all organizations engaged in water quality around the world for water quality measurement and prediction system data system for AI application.

Applications of Online UV-Vis Spectrophotometer for Drinking Water Quality Monitoring and Process Control: A Review.

Water quality monitoring is an essential component of water quality management for water utilities for managing the drinking water supply. Online UV-Vis spectrophotometers are becoming popular choices for online water quality monitoring and process control, as they are reagent free, do not require sample pre-treatments and can provide continuous measurements. The advantages of the online UV-Vis sensors are that they can capture events and allow quicker responses to water quality changes compared to conventional water quality monitoring. This review summarizes the applications of online UV-Vis spectrophotometers for drinking water quality management in the last two decades. Water quality measurements can be performed directly using the built-in generic algorithms of the online UV-Vis instruments, including absorbance at 254 nm (UV254), colour, dissolved organic carbon (DOC), total organic carbon (TOC), turbidity and nitrate. To enhance the usability of this technique by providing a higher level of operations intelligence, the UV-Vis spectra combined with chemometrics approach offers simplicity, flexibility and applicability. The use of anomaly detection and an early warning was also discussed for drinking water quality monitoring at the source or in the distribution system. As most of the online UV-Vis instruments studies in the drinking water field were conducted at the laboratory- and pilot-scale, future work is needed for industrial-scale evaluation with ab appropriate validation methodology. Issues and potential solutions associated with online instruments for water quality monitoring have been provided. Current technique development outcomes indicate that future research and development work is needed for the integration of early warnings and real-time water treatment process control systems using the online UV-Vis spectrophotometers as part of the water quality management system.

Assessment of an automated IoT-biofloc water quality management system in the Litopenaeus vannamei’s mortality and growth rate

Climate change greatly influenced aquaculture in the Philippines and the deteriorating water quality; in effect, fish production reduced drastically. Thus, fish farmers and aquaculture researchers have been searching for innovative technologies to address these issues. One technology is the biofloc systems. This technology uses a zero-water exchange and accumulates microorganisms that serves as a food source. In the biofloc, water quality management is highly recommended. This study aimed to assess the technical and operational effect on the shrimp growth and survival of the developed automated water quality management internet of things (IoT) system in a biofloc system. The hardware prototype comes with a mobile application which has features namely: account management, fish/shrimp profile, water quality management, auto feeding and manual controls. This study conducts experimental research which assessed the impact of an indoor pond biofloc with the developed prototype on the Litopenaeus vannamei’s growth and survival rates. Results were favorable to the biofloc system with the developed prototype, having a 10% higher survival rate and 3.2% higher growth rate, compared to the traditional recirculating aquaculture systems. Adapting the biofloc and the IoT prototype, a fish farmer may earn P78,300 pesos for each white leg shrimp (Litopenaeus vannamei) harvesting period.

Solar Based Water Quality Management System in Agriculture

The huge expansion in worldwide mechanical yield, country to metropolitan float and the over-use of land and ocean assets, the nature of water accessible to individuals has crumbled incredibly. The high utilization of fertilizers in agricultures and furthermore different synthetic substances in areas, for example, mining and development have contributed massively to the general decrease of water quality universally. A sun light based Smart water system framework has been proposed. The horticultural land is checked with the assistance of five sensors and water system is computerized with the assistance of Microcontroller. The status of the water system of the specific land is suggested to the clients Mobile utilizing GSM Technique. By utilizing this water system framework, assets like water and Electricity can be minimalistic ally utilized with increment in water system productivity, and decrease in labour cost. The entire unit is given force flexibly with the assistance of solar panels which is been connected to the battery. The battery will be getting charged by this solar panel. We also use ultrasonic sensor to check any illegal entry of animals or birds into our land.

Database Development for Water Quality Index using Geographical Information System

The present study aimed to identify drainage pollution at Parit Raja, Johor in accordance to the Water Quality Index (WQI) and based on Geographic Information System (GIS) data analysis. A total of 18 sampling stations at six drainage ditches were selected to be sampling points. The parameters investigated included Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Suspended Solid (SS), Ammonia Nitrogen (AN) and pH. ArcGIS software was selected and the water quality data were gathered and digitized in the GIS as data storage system in order to develop database. The results revealed that 13 stations were categorized as polluted, 5 stations classified as slightly polluted. These findings indicated that GIS have an ability to provide interactive visual and attribute information effectively in order to improve water quality management system. Therefore, GIS can be applied on a big study area and this is useful for wastewater management by authorities.

Bacterial Communities Associated With Penaeus vannamei Boone, 1931 Surface and Its Rearing Water in Biofloc Culture System

The biofloc system is an ecologically sustainable shrimp culture system. The conglomerates of beneficial bacteria, algae and protozoa in pond water serve as a water quality management system and as a feed additive to the shrimps. This study aimed to characterise the microbial communities associated with the biofloc pond water and the surface of Penaeus vannamei Boone, 1931, reared in it using the Illumina Miseq sequencing technology. The multiple alpha diversity measures indicated the shrimp surface samples to be richer in diversity than the pond water samples. Analysis of the bacterial community revealed that Proteobacteria, Bacteroidetes, Planctomycetes and Cyanobacteria formed the principal phyla. There was a shift in the relative abundance of bacterial communities at each time point. The operational taxonomic units (OTU) analyses revealed that 18.38 % OTUs were shared by the pond water samples, the shrimp surface samples shared 29.35 % at the three different time points. PICRUST analysis revealed that the bacterial communities in the biofloc rearing water, and shrimp surface, were likely involved in intensive microbial metabolism and core housekeeping functions. The information generated will help understand the bacterial community composition associated with optimal water quality and shrimp health in a biofloc culture system.

수변 생태 경관을 고려한 녹조저감장치 및 통합관리시스템 디자인 연구

한국은 OECD 회원국 34개국 중 ‘물 스트레스’가 가장 높은 국가로 보고되었다. 이를 해결하기 위해 도심내 인공 하천과 인공수로 등의 친환경을 기초로 한 도시 개발이 적극적으로 추진 중이다. 기후변화 등에 의한 외부 환경요인으로 인한 녹조현상은 수변 자연환경의 훼손은 물론 안전한 수질 확보를 위한 친수공간의 급속한 감소를 일으켜 심각한 사회/경제적 문제로 대두되고 있으며, 또한 4대강을 비롯한 하천의 녹조현상은 외부 환경요인뿐만 아니라 자연순환이 배제된 설계와 관리시스템 부재에 따른 내부 오염으로 환경파괴의 주범으로 작용하고 있어 이를 해결하기 위한 친환경적인 수질 개선 시스템과 실시간 모니터링 시스템의 도입이 절실하다. 본 연구에서는 수변 환경에 대한 종합적인 분석을 통해 경관 및 자연 친화적 녹조저감장치 개발로 수변 환경을 이용하는 대중들에게 더욱 쾌적한 수변 공간을 제공하고자 한다. 연구 결과는 다음과 같다. 현재 국내 녹조저감장치의 수준은 호소 내에서의 오염물질처리 또는 수질 개선을 위한 기술적 접근은 현 단계로서는 호소 생태계 전체의 생물, 물리, 지질, 화학적 측면을 망라하는 전반적인 호소의 동태학을 제대로 이해하지 못하고 있는 수준이며 따라서 호소 내에 적용하는 기술도 단편적인 기술들에 관한 연구와 적용에 머물고 있다. 이는 호소라는 복잡하고 살아있는 생태시스템을 전반적으로 이해하지 못한 채 단순 개발된 기술을 적용한 결과가 주원인이라고 판단되며, 기술의 효율성을 높이기 위해서는 부영양화와 녹조 발생의 원인과 이들에 영향을 미치는 요인들의 복잡성을 고려하는 것이 필수적이다. 따라서 기본 폭기을 기본으로 블록의 개념과 융합하여 크기와 깊이, 자연생태에 따라 결합과 해체가 언제나 가능하며 형태에 따라 변형이 가능한 디자인 개발이 필요하다. 세부적으로는 3단계의 디자인으로 나누어 1. 부유부 디자인이 필요하며, 2. 임팰러 디자인, 3. 공기 유도관과 유입기 디자인 개발 수립이 필요하다.

Value of a made-in-Ontario management system standard for municipal wastewater and stormwater utilities

Abstract This paper builds on previous research to address the question of whether there is practical value for a made-in-Ontario municipal management system standard (MSS) for wastewater and stormwater related activities, in addition to the Drinking Water Quality Management System Standard (DWQMS) that is already statutorily required. This research specifically addressed the questions: is there value in a mandatory or voluntary MSS; are there neutral, positive, or negative effects of having an MSS; and what standard is more adequate? Through a focus group method, this research finds evidence in support of and wide recognition of the practical value an MSS in assisting municipalities in meeting their environmental objectives, addressing property damage risks, providing an additional mechanism of public accountability, and improving alignment with the legal structure. It was also apparent that there is no political appetite in the provincial government to embark on a mandated MSS, so the preferred option at this time appears to be a provincially endorsed, voluntary, sector-specific standard for wastewater and for stormwater, which could constitute a catalyst to boost voluntary uptake of MSS by small to medium municipalities (as is already occurring with large municipalities). This standard could be based on a customized variation of the ISO 14001 and DWQMS.

A Comparative Analysis of Drinking Water Quality Management Systems in Poland

Purpose: The article aims to present and discuss the results of comparative analysis of applied methods in water treatment processes, and to assess whether they belong to the group of advanced and strategic methods used in the treatment and improvement of drinking water quality. Design/Approach/Methodology: The theoretical part of the article discusses the state of drinking water regions of Poland in terms of its chemical, physical, and biological properties, considering the level of pollution. Next, the drinking water quality management scheme in Poland is presented from the organizational point of view, then, Poland's drinking water quality regulations, both national and EU, have been characterized, as well as a few legal norms and programs supporting the ecological campaign in Poland I drink tap water. In the succeeding part of the article, attention was paid to a detailed analysis of the methods used in Poland in the processes of drinking water treatment and improvement. Findings: Based on the comparative analysis, final conclusions have been drawn up indicating the most effective and ecologically sound methods used in water treatment processes to improve drinking water status in the regions of Poland in such a way that it not only meets legal and environmental standards but is also an essential factor in improving the quality of health, life and economic situation of a given social group. Practical Implications: The article brings a number of valuable information that can be the base material and reference to further research, programs and studies for local governments, practitioners and scientific specialists dealing with issues of improving the quality of drinking water, effective management of water resources, ecology or aspects of environmental protection. Originality/Value: The results of the comparative analysis and theoretical considerations in this article complement the current research in the field of drinking water quality management, and may become a valuable resource of knowledge and a set of specimens that can be useful in developing dissertations in the field of management, environment and ecology.