Water Quality Monitoring with Arduino Based Sensors

Arduino-Based Readout Electronics for Nuclear and Particle Physics

Open Hardware-based microcontrollers, especially the Arduino platform, have become a comparably easy-to-use tool for rapid prototyping and implementing creative solutions. Such devices in combination with dedicated front-end electronics can offer low-cost alternatives for student projects, slow control and independently operating small-scale instrumentation. The capabilities can be extended to data taking and signal analysis at mid-level rates. Two detector realizations are presented, which cover the readouts of proportional counter tubes and of scintillators or wavelength-shifting fibers with silicon photomultipliers (SiPMs). The SiPMTrigger realizes a small-scale design for coincidence readout of SiPMs as a trigger or veto detector. It consists of a custom mixed signal front-end board featuring signal amplification, discrimination and a coincidence unit for rates of up to 200 kHz. The nCatcher transforms an Arduino Nano to a proportional counter readout with pulse shape analysis: time over threshold measurement and a 10-bit analog-to-digital converter for pulse heights. The device is suitable for low-to-medium-rate environments up to 5 kHz, where a good signal-to-noise ratio is crucial. We showcase the monitoring of thermal neutrons. For data taking and slow control, a logger board is presented that features an SD card and GSM/LoRa interface.

Internet of Things and citizen science as alternative water quality monitoring approaches and the importance of effective water quality communication

The increasing demand for water and worsening climate change place significant pressure on this vital resource, making its preservation a global priority. Water quality monitoring programs are essential for effectively managing this resource. Current programs rely on traditional monitoring approaches, leading to limitations such as low spatiotemporal resolution and high operational costs. Despite the adoption of novel monitoring approaches that enable better data resolution, the public's comprehension of water quality matters remains low, primarily due to communication process deficiencies. This study explores the advantages and challenges of using Internet of Things (IoT) and citizen science as alternative monitoring approaches, emphasizing the need for enhancing public communication of water quality data. Through a systematic review of studies implemented on-field, we identify and propose strategies to address five key challenges that IoT and citizen science monitoring approaches must overcome to mature into robust sources of water quality information. Additionally, we highlight three fundamental problems affecting the water quality communication process and outline strategies to convey this topic effectively to the public.

The Secret Lives of Miniature Batteries

This article describes the design, implementation, and use of a new system to investigate the behavior of small batteries that power sensor and wireless systems that consume relatively high power during infrequent short activity periods. The system enables simple, low-cost, long-term (days to weeks) monitoring of batteries under such loads. Data collected by this system revealed a major cause of failures in wildlife tracking tags, an effect called concentration polarization, which causes a transient increase in the internal resistance of the battery. The article describes the goals and the design of the system, failures that it revealed, mechanisms to mitigate the limitations of miniature batteries, as well as a methodology to optimize and validate the design of tags powered by miniature batteries.

Low-Cost Water Quality Sensors for IoT: A Systematic Review

In many countries, water quality monitoring is limited due to the high cost of logistics and professional equipment such as multiparametric probes. However, low-cost sensors integrated with the Internet of Things can enable real-time environmental monitoring networks, providing valuable water quality information to the public. To facilitate the widespread adoption of these sensors, it is crucial to identify which sensors can accurately measure key water quality parameters, their manufacturers, and their reliability in different environments. Although there is an increasing body of work utilizing low-cost water quality sensors, many questions remain unanswered. To address this issue, a systematic literature review was conducted to determine which low-cost sensors are being used for remote water quality monitoring. The results show that there are three primary vendors for the sensors used in the selected papers. Most sensors range in price from US$6.9 to US$169.00 but can cost up to US$500.00. While many papers suggest that low-cost sensors are suitable for water quality monitoring, few compare low-cost sensors to reference devices. Therefore, further research is necessary to determine the reliability and accuracy of low-cost sensors compared to professional devices.

Low-Cost Internet-of-Things Water-Quality Monitoring System for Rural Areas

Water is a vital source for life and natural environments. This is the reason why water sources should be constantly monitored in order to detect any pollutants that might jeopardize the quality of water. This paper presents a low-cost internet-of-things system that is capable of measuring and reporting the quality of different water sources. It comprises the following components: Arduino UNO board, Bluetooth module BT04, temperature sensor DS18B20, pH sensor-SEN0161, TDS sensor-SEN0244, turbidity sensor-SKU SEN0189. The system will be controlled and managed from a mobile application, which will monitor the actual status of water sources. We propose to monitor and evaluate the quality of water from five different water sources in a rural settlement. The results show that most of the water sources we have monitored are proper for consumption, with a single exception where the TDS values are not within proper limits, as they outperform the maximum accepted value of 500 ppm.

PortAqua: a low-cost, compact water quality meter for science communication

Water quality monitoring allows communities to achieve sustainable management of water resources, which is crucial for life-supporting processes. Water quality is determined by measuring chemical, physical, and biological parameters, requiring sophisticated meters and trained specialists to perform the measurement. However, in low-income communities, water quality is determined by using human senses-smell, color, and taste-since meter acquisition is limited by costs and most people do not know how to monitor water quality. Therefore, accessible technology is necessary to empower communities to have a sustainable lifestyle. In this paper, we present the design and implementation of PortAqua, a 2-parameter water quality meter (WQM), to promote training on water quality measurement. Using basic electronic components, PortAqua is capable of measuring pH with an error of 0.4, and conductivity with an error of 33% at 85 µS cm^-1, and 8.7% at 1413 µS cm^-1. To demonstrate its preliminary effectiveness as a WQM and its science communication capabilities, the meter has been used in a hands-on workshop with undergraduate and graduate students. During the workshop, attendees participated in a short lecture about water quality measurement techniques and local regulations. Then, they collected water samples from a local source, measured the samples using PortAqua, and discussed the results based on the concepts and regulations. The workshop's effectiveness was evaluated through pre- and post-assessments which revealed increased knowledge of water quality regulations, measurement, and parameters at the end of the activity.

Advancements in Monitoring Water Quality Based on Various Sensing Methods: A Systematic Review

Nowadays, water pollution has become a global issue affecting most countries in the world. Water quality should be monitored to alert authorities on water pollution, so that action can be taken quickly. The objective of the review is to study various conventional and modern methods of monitoring water quality to identify the strengths and weaknesses of the methods. The methods include the Internet of Things (IoT), virtual sensing, cyber-physical system (CPS), and optical techniques. In this review, water quality monitoring systems and process control in several countries, such as New Zealand, China, Serbia, Bangladesh, Malaysia, and India, are discussed. Conventional and modern methods are compared in terms of parameters, complexity, and reliability. Recent methods of water quality monitoring techniques are also reviewed to study any loopholes in modern methods. We found that CPS is suitable for monitoring water quality due to a good combination of physical and computational algorithms. Its embedded sensors, processors, and actuators can be designed to detect and interact with environments. We believe that conventional methods are costly and complex, whereas modern methods are also expensive but simpler with real-time detection. Traditional approaches are more time-consuming and expensive due to the high maintenance of laboratory facilities, involve chemical materials, and are inefficient for on-site monitoring applications. Apart from that, previous monitoring methods have issues in achieving a reliable measurement of water quality parameters in real time. There are still limitations in instruments for detecting pollutants and producing valuable information on water quality. Thus, the review is important in order to compare previous methods and to improve current water quality assessments in terms of reliability and cost-effectiveness.

Recent Advances of Smart Systems and Internet of Things (IoT) for Aquaponics Automation: A Comprehensive Overview

Aquaponics is an innovative, smart, and sustainable agricultural technology that integrates aquaculture (farming of fish) with hydroponics in growing vegetable crops symbiotically. The correct implementation of aquaponics helps in providing healthy organic foods with low consumption of water and chemical fertilizers. Numerous research attempts have been directed toward real implementations of this technology feasibly and reliably at large commercial scales and adopting it as a new precision technology. For better management of such technology, there is an urgent need to use the Internet of things (IoT) and smart sensing systems for monitoring and controlling all operations involved in the aquaponic systems. Thence, the objective of this article is to comprehensively highlight research endeavors devoted to the utilization of automated, fully operated aquaponic systems, by discussing all related aquaponic parameters aligned with smart automation scenarios and IoT supported by some examples and research results. Furthermore, an attempt to find potential gaps in the literature and future contributions related to automated aquaponics was highlighted. In the scope of the reviewed research works in this article, it is expected that the aquaponics system supported with smart control units will become more profitable, intelligent, accurate, and effective.

Iron and manganese mobilisation due to dam height increase for a tropical reservoir in South East Asia

The aim of this research was the analysis of the effect of a dam height raise on the water quality of a tropical reservoir used for drinking water purposes in South East Asia. Analyses of iron, manganese, pH and ammonia were performed over a 5-year period from daily water sampling at the reservoir. In addition, high-frequency monitoring data of nitrate, ammonium, pH and blue-green algae were obtained using a monitoring probe. The results showed that due to the raising of the reservoir water level, previously oxic sediments became submerged, triggering an increase in iron and manganese in particular due to the establishment of reducing conditions. Manganese concentrations with values up to 4 mg L^-1 are now exceeding guideline values. The analysis strongly indicated that both iron and manganese have a seasonal component with higher iron and manganese concentrations during the wet season. Over a three-year period afterwards, concentrations did not go back to pre-raise levels. The change in water quality was accompanied by a change in pH from previous values of around 5 to pH values of around 6.5. Geochemical simulations confirmed the theory that the increasing concentrations of iron and manganese are due to the dissolution of MnO₂ and ferric oxyhydroxides oxidising organic matter in the process. This study showed that changes in reservoir water levels with the establishment of reducing conditions can have long-term effects on the water quality of a reservoir.

Smart microalgae farming with internet-of-things for sustainable agriculture

Agriculture farms such as crop, aquaculture and livestock have begun the implementation of Internet of Things (IoT) and artificial intelligence (AI) technology in improving their productivity and product quality. However, microalgae farming which requires precise monitoring, controlling and predicting the growth of microalgae biomass has yet to incorporate with IoT and AI technology, as it is still in its infancy phase. Particularly, the cultivation stage of microalgae involves many essential parameters (i.e. biomass concentration, pH, light intensity, temperature and tank level) which require precise monitoring as these parameters are important to ensure an effective biomass productivity in the microalgae farming. Besides, the conventional practices in the current process equipment are still powered by electricity, thus further development by integrating IoT into these processes can ease the production process. Further to that, many researchers has studied the machine learning approach for the identification and classification of microalgae. However, there are still limited studies reported on applying machine learning for the application of microalgae industry such as optimising microalgae cultivation for higher biomass productivity. Therefore, the implementation of IoT and AI in microalgae farming can contribute to the development of the global microalgae industry. The purpose of this current review paper focuses on the overview microalgae biomass production process along with the implementation of IoT toward the future of smart farming. To bridge the gap between the conventional and microalgae smart farming, this paper also highlights the insights on the implementation phases of microalgae smart farming starting from the infant stage that involves the installation and programming of IoT hardware. Then, it is followed by the application of machine learning to predict and auto-optimise the microalgae smart farming process. Furthermore, the process setup and detailed overview of microalgae farming with the integration of IoT have been discussed critically. This review paper would provide a new vision of microalgae farming for microalgae researchers and bio-processing industries into the digitalisation industrial era.

Management and Sustainable Exploitation of Marine Environments through Smart Monitoring and Automation

Monitoring of aquatic ecosystems has been historically accomplished by intensive campaigns of direct measurements (by probes and other boat instruments) and indirect extensive methods such as aero-photogrammetry and satellite detection. These measurements characterized the research in the last century, with significant but limited improvements within those technological boundaries. The newest advances in the field of smart devices and increased networking capabilities provided by emerging tools, such as the Internet of Things (IoT), offer increasing opportunities to provide accurate and precise measurements over larger areas. These perspectives also correspond to an increasing need to promptly respond to frequent catastrophic impacts produced by drilling stations and intense transportation activities of dangerous materials over ocean routes. The shape of coastal ecosystems continuously varies due to increasing anthropic activities and climatic changes, aside from touristic activities, industrial impacts, and conservation practices. Smart buoy networks (SBNs), autonomous underwater vehicles (AUVs), and multi-sensor microsystems (MSMs) such as smart cable water (SCW) are able to learn specific patterns of ecological conditions, along with electronic “noses”, permitting them to set innovative low-cost monitoring stations reacting in real time to the signals of marine environments by autonomously adapting their monitoring programs and eventually sending alarm messages to prompt human intervention. These opportunities, according to multimodal scenarios, are dramatically changing both the coastal monitoring operations and the investigations over large oceanic areas by yielding huge amounts of information and partially computing them in order to provide intelligent responses. However, the major effects of these tools on the management of marine environments are still to be realized, and they are likely to become evident in the next decade. In this review, we examined from an ecological perspective the most striking innovations applied by various research groups around the world and analyzed their advantages and limits to depict scenarios of monitoring activities made possible for the next decade.

Soil and Groundwater Investigation for Sustainable Agricultural Development: A Case Study from Brunei Darussalam

Brunei has made significant progress in agricultural development over the past four decades. However, crop production, such as rice, is still insufficient to meet the demands of the growing population, mainly due to the scarcity of water resources, acidic soils, and advancing environmental deterioration. This study conducted soil and groundwater investigations at three selected rice cultivation sites in Brunei Darussalam. The geoelectrical resistivity method using the vertical electrical sounding (VES) technique delineated subsurface stratigraphy with resistivities ranging from 1 to 180 Ωm in the investigated area. A potential aquifer zone was inferred in one of the surveyed areas with resistivities ranging from 10 to 150 Ωm at depths of about 40 to 60 m below ground level. Groundwater levels were also shallower in irrigated sites compared to non-irrigated sites. Groundwater physicochemical properties revealed high alkalinity and mineralisation, as evident from high magnesium, bicarbonate, ammoniacal nitrogen, and iron, as well as pH values in the water samples, believed to be the effects of leaching of salt ions into the shallow aquifer through infiltration recharge. In addition, soil physicochemical properties showed that the soils near a pumping well were more acidic, had lower moisture, and total nutrients, likely due to the effects of groundwater pumping. Our results demonstrate that future irrigation activities need to consider local aquifer characteristics, groundwater flow paths, and nutrient transport to ensure sustainable development in agricultural areas.

Water Quality Monitoring and Management of Building Water Tank Using Industrial Internet of Things

Water being one of the foremost needs for human survival, conservation, and management of the resource must be given ultimate significance. Water demand has increased tremendously all over the world from the past decade due to urbanization, climatic change, and ineffective management of water. The advancement in sensor and wireless communication technology encourages implementing the IoT in a wide range. In this study, an IoT-based architecture is proposed and implemented for monitoring the level and quality of water in a domestic water tank with customized hardware based on 2.4 GHz radiofrequency (RF) communication. Moreover, the ESP 8266 Wi-Fi module-based upper tank monitoring of the proposed architecture encourages provide real-time information about the tank through internet protocol (IP). The customized hardware is designed and evaluated in the Proteus simulation environment. The calibration of the pH sensor and ultrasonic value is carried out for setting the actual value in the prototype for obtaining the error-free value. The customized hardware that is developed for monitoring the level and quality of water is implemented. The real-time visualization and monitoring of the water tank are realized with the cloud-enabled Virtuino app.

Microwave Sensors for In Situ Monitoring of Trace Metals in Polluted Water

Thousands of pollutants are threatening our water supply, putting at risk human and environmental health. Between them, trace metals are of significant concern, due to their high toxicity at low concentrations. Abandoned mining areas are globally one of the major sources of toxic metals. Nowadays, no method can guarantee an immediate response for quantifying these pollutants. In this work, a novel technique based on microwave spectroscopy and planar sensors for in situ real-time monitoring of water quality is described. The sensors were developed to directly probe water samples, and in situ trial measurements were performed in freshwater in four polluted mining areas in the UK. Planar microwave sensors were able to detect the water pollution level with an immediate response specifically depicted at three resonant peaks in the GHz range. To the authors’ best knowledge, this is the first time that planar microwave sensors were tested in situ, demonstrating the ability to use this method for classifying more and less polluted water using a multiple-peak approach.