Turbidity Sensor Research Articles

MONITORING FILTER PADA TANGKI AIR MENGGUNAKAN SENSOR TURBIDITY BERBASIS ARDUINO MEGA 2560 VIA SMS GATEWAY

Clean water has a very important role in human life. If an area is difficult to get clean water for daily needs, then they have to buy water to get it. Based on these problems, research was carried out in the form of a filter tool that can be used to filter turbid water into clean water so that it can be used for daily needs and can be monitored in real-time. To be able to make these tools requires software to program so that all hardware can run, the components used are electronic components consisting of an Arduino Mega 2560, HC-SR04 Sensor, Turbidity Sensor, SIM 800L, Waterpump, and a simple water filter as a compliment. This tool works automatically, when the water tank is full of clean water, the user will receive a notification in the form of an SMS. It is hoped that the existence of this tool can help to get clean and healthy water for daily needs.

Sediment Transport in Sewage Pressure Pipes, Part I: Continuous Determination of Settling and Erosion Characteristics by In-Situ TSS Monitoring Inside a Pressure Pipe in Northern Germany

Continuous measurement systems are widely spread in sewers, especially in non-pressure systems. Due to its relatively low costs, turbidity sensors are often used as a surrogate for other indicators (solids, heavy metals, organic compounds). However, little effort is spent to turbidity sensors in pressurized systems so far. This work presents the results of one year in-situ turbidity/total suspended solids (TSS) monitoring inside a pressure pipe (600 mm diameter) in an urban region in northern Germany. The high-resolution sensor data (5 s interval) are used for the determination of solids sedimentation (within pump pauses) and erosion behavior (within pump sequences). In-situ results from sensor measurements are similar to laboratory results presented in previous studies. TSS is decreasing exponentially in pump pauses under dry weather inflow with an average of 0.23 mg/(L s). During pump sequences, solids eroded completely at a bed shear stress of 0.5 N/m². Sedimentation and erosion behavior changes with the inflow rate. Solids settle faster with increasing inflow: at storm water inflow with an average of 0.9 mg/(L s) and at diurnal inflow variation up to 0.6 mg/(L s) at 12:00 a.m. The results are used as calibration data for a sediment transport simulation in Part II.

FPGA Implementation of Smart Water Quality Monitoring System

Water quality is important to our health and well- being .Water quality monitoring plays a vital role in keeping the planet healthy and sustainable. Due to increasing industrialization and environmental imbalance, water quality and fresh water quantity are decreasing day by day. In this paper, a reconfigurable hardware system is developed to monitor the water quality and physical parameters are monitored using temperature sensor and turbidity sensor; chemical parameters are monitored using pH sensor; in addition CO2 and water level sensors are used. These sensors are interfaced with the reconfigurable hardware i.e., FPGA. This FPGA is used to monitor the water related parameters such as water quality, waste water parameters and also used in agricultural fields. The hardware is implemented using Verilog HDL. Wireless Sensor Network enables interface between human and computer by means of wireless link. The output is displayed in the personal computer.

Design and development of a quasi-digital sensor and instrument for water turbidity measurement

In this paper, the design, realization, fabrication and assembly of a prototype water turbidity monitoring instrument based on an opto-resistive quasi-digital sensor has been proposed. The turbidity sensor has been constructed with LED (590 nm) as the light source, a light-dependent resistor, fixed capacitor and logic gate inverter. The primary output signal from the sensor is in the form of a transistor–transistor-logic pulse stream with 50% duty cycle. This form of the output signal can be directly interfaced with the microcontroller. To process pulse stream from the sensor, to convert into turbidity value in NTU and to display on an LCD, a microcontroller (PIC18f4550)-based embedded system has been developed. The turbidity monitoring instrument has been constructed, calibrated and experimentally tested by measuring the turbidity of the water in the range of 0–1000 NTU. The turbidity of 0–1000 NTU corresponded to the output frequency of 40.6–18.8 kHz with sensitivity of 22 Hz/NTU. This is a high-precision, low-power, portable instrument with low manufacturing costs compared to commercial turbidity monitoring instruments.

Salinity Detection in Households using Raspberry Pi 3b+

Water is an excellent solvent and usually contains wide variety of dissolved minerals and other chemicals. Water molecules form hydrogen bonds with each other and strongly polar that is able to dissolve or suspend many different compounds. This paper focuses on the water storage monitoring system for households with pH sensor and turbidity sensor. The acceptable standard pH range forwaterstoragetank isbetween6.5to8.0.ThedatareadingofthepHismonitored andifthepHrangesbetweenacceptablerangethewaterwillcontinueto checkwater.densityusingturbiditysensorandbothmeasuredvaluesa refurthercompared.Ifthe obtained pH and turbidity values are between the acceptable range then the system displays the output as drinking water. If the pH and water density values are out of range and it is displayed as salinewater.

Biased measurements by stationary turbidity‐fluorescence instruments due to phototactic zooplankton behavior

AbstractSubmersible fluorescence and turbidity sensors are widely used in studies of oceans and lakes. To reduce the instrument size, an overlapping interrogation volume is commonly used for the two sensors. Fluorescence sensors emit blue light for excitation and measure the red light emitted by excited chlorophyll pigments. However, during the night, many phototactic zooplankters are attracted to the blue light. If the instrument is fixed in place (e.g., on a mooring), the aggregation of the attracted animals may bias both the fluorescence and turbidity readings. To examine this potential bias, we carried out experiments with natural assemblages of zooplankton and Artemia nauplii in tanks equipped with a commercially available fluorescence‐turbidity sensor. Our findings indicate that zooplankters were attracted by the blue light emitted from a fluorometer during the dark, biasing the reading of both sensors. The bias in fluorescence was likely due to phytoplankton in the guts of the aggregated zooplankton. The induction of turbulence in the tank greatly reduced the bias, likely due to the inability of the zooplankton to counteract the resulting flow and swim toward the light. Field observations carried out with a similar instrument in a coastal station off Japan were consistent with the laboratory experiments. Our findings indicate a need to redesign coupled fluorescence‐turbidity sensors and to reevaluate the results of past studies where they had been used with stationary observing systems.

Pembuatan Sistem Filter dan Monitor Air Pada Reservoir Berbasis Mikrokontroler ATMEGA328

The development of a filter and monitor water system needs to be improved, because there are still many in the use of clean water that have not covered the standard for clean water use, namely 5NTU (Nephelometric Turbidity Unit). Filter systems and water monitors can help the problems of the community in using dirty water into clean water. In the filtering system and water monitoring in the reservoir it is controlled by the Atmega328 microcontroller. and water monitoring can operate in accordance with block diagrams that match the design. This system uses Arduino as the system's main controller. The input component uses a Turbidity sensor, and an Ultrasonic Sensor, while the output component uses a relay driver, servo motor, ACV water pump, and GSM SIM800L. Based on the testing and analysis conducted, it was concluded that the filter system and water monitor in an ATMEGA328 based microcontroller reservoir could work well.

Real-time water quality monitoring of an artificial lake using a portable, affordable, simple, Arduino-based open source sensor

Water quality assessment is vital to identify existing problems and any changes that emerge in water sources over a period of time. Conventional water quality monitoring systems remain to be limited to on-site sample collection and further analysis in environmental laboratories. The progress in Arduino-based low-cost and open-source hardware has paved the way for the development of low-cost, portable, and on-site measuring platforms. In this work, we have assembled an Arduino-based open-source water testing platform out of commercially available sensors and controllers. The water testing system was powered by a 9 V battery and had the capability of measuring water turbidity, acidity, and temperature on-site in real-time. The calibration and validation studies were carried out to assess the measurement capabilities of turbidity and pH sensors in the lab using calibration samples and UV-Vis-NIR absorption spectroscopy. The water quality platform was tested in an artificial lake that is located at Sabanci University Campus (Istanbul, Turkey), which serves as a reservoir for treated wastewaters and rainwater. Untreated wastewater samples were collected from the wastewater treatment station of the university for comparison. The measurements performed on several locations along the coast of the artificial lake were also validated in the laboratory. The water testing platform showed significant potential for miniaturization and portability of such analytical platforms for on-site environmental monitoring.

The NE Lau Basin: Widespread and Abundant Hydrothermal Venting in the Back-Arc Region Behind a Superfast Subduction Zone

The distribution of hydrothermal venting reveals important clues about the presence of magma in submarine settings. The NE Lau Basin in the southwest Pacific Ocean is a complex back-arc region of widespread hydrothermal activity. It includes spreading ridges, arc volcanoes, and intra-plate volcanoes that provide a perhaps unique laboratory for studying interactions between hydrothermal activity and magma sources. Since 2004, multiple cruises have explored the water column of the NE Lau Basin. Here we use these data to identify and characterize 43 active hydrothermal sites by means of optical, temperature, and chemical tracers in plumes discharged by each site. Seventeen of 20 prominent volcanic edifices dispersed among the Tofua arc, spreading ridges, and plate interiors host active hydrothermal sites. Fourteen apparently discharge high-temperature fluids, including a multi-year submarine eruption at the intra-plate volcano W Mata. The 430 km of spreading ridges host 31 active sites, one an eruption event in 2008. Our data show that the relationship between site spatial density (sites/100 km of ridge crest) and ridge spreading rate (8-42 mm/yr) in the NE Lau Basin follows the same linear trend as previously established for the faster-spreading (40-90 mm/yr) ridges in the central Lau Basin. The lower site density in the NE Lau Basin compared to the central Lau is consistent with recent plate reconstructions that more than halved earlier estimates of ~50-100 mm/yr spreading rates in the NE Lau Basin. Combined data from the spreading ridges throughout the entire Lau back-arc basin demonstrates that hydrothermal sites, normalized to spreading rate, are ~10× more common than expected based on existing mid-ocean ridge data. This increase documents the ability of meticulous exploration, using both turbidity and chemical sensors, to more fully describe the true hydrothermal population of a spreading ridge, compared to conventional techniques. It further reveals that the Lau back-arc basin, benefiting from both ridge and arc magma sources, supports an exceptionally high population of ridge and intra-plate hydrothermal sites.

Online sensor validation in sensor networks for bioprocess monitoring using swarm intelligence.

Sensor faults can impede the functionality of monitoring and control systems for bioprocesses. Hence, suitable systems need to be developed to validate the sensor readings prior to their use in monitoring and control systems. This study presents a novel approach for online validation of sensor readings. The basic idea is to compare the original sensor reading with predictions for this sensor reading based on the remaining sensor network's information. Deviations between original and predicted sensor readings are used to indicate sensor faults. Since especially batch processes show varying lengths and different phases (e.g., lag and exponential phase), prediction models that are dependent on process time are necessary. The binary particle swarm optimization algorithm is used to select the best prediction models for each time step. A regularization approach is utilized to avoid overfitting. Models with high complexity and prediction errors are penalized, resulting in optimal predictions for the sensor reading at each time step (5% mean relative prediction error). The sensor reliability is calculated by the Kullback-Leibler divergence between the distribution of model-based predictions and the distribution of a moving window of original sensor readings (moving window size = 10 readings). The developed system allows for the online detection of sensor faults. This is especially important when sensor data are used as input to soft sensors for critical quality attributes or the process control system. The proof-of-concept is exemplarily shown for a turbidity sensor that is used to monitor a Pichia pastoris-batch process.

Application of continuous turbidity sensors to supplement estimates of total phosphorus concentrations in the Grand River, Ontario, Canada

Accurate estimates of total phosphorus (TP) loadings to eastern Lake Erie are critical for developing load reduction targets and for determining if commitments are being met under the Great Lakes Water Quality Agreement, 2012 (GLWQA). Currently, loading calculations from Canadian priority tributaries are supported by year-round event-focused water quality sampling using automated samplers and laboratory water quality measurements. Here we evaluate the suitability of continuously-measured parameters, namely turbidity and flow, to supplement or enhance knowledge about TP concentrations in the Grand River, ON, by providing continuous data alongside event-focused sample measurements. A series of simple and multiple linear regression models were evaluated and compared with respect to their ability to predict TP water concentrations as a function of different combinations of explanatory variables. Explanatory variables included turbidity, flow, season and flow condition (i.e. hysteresis). The models that performed best explained 63–65% of the variation of TP which is comparable to surrogate model applications in the U. S and elsewhere. Additional model calibration work is needed due to gaps in turbidity data particularly during high flow events. We emphasize the need for continued automated, event-focused water quality sampling. However, provided that operational challenges are overcome, our results indicate that sensor-derived water quality parameters to predict TP concentrations is a promising technique that may supplement and improve nutrient loading estimates in the Grand River into the future and provides guidance for the utilization of this method in other tributaries.

Real-time monitoring and warning system in urban rivers

Urban rivers water quality is not suitable for use. The volume of river water in the city is fast full when it rains. Both of these problems need to be monitored. The purpose of monitored to give a warning to a community around the rivers. The rivers water quality determined base on the pH sensor, and turbidity sensor detection. The river water level is determined based on the results of ultrasonic sensor readings. The reading of three sensors is sent via GSM (General Service Mobile) communication network in SMS (Short Message Service) form. The reading also sent via internet data communication network to the server and displayed on web page form. This study indicates that all three sensors are able to detect pH, turbidity, and surface level of the river. The Sensors reading delivered via the GSM communication network, it provides real-time river water information. Whereas sensor readings sent via data communication networks provide river water information that is not real-time. Thus, sensor readings of water urban rivers better delivered via GSM on SMS form than via data communication on Web page form.

Kajian Tingkat Akurasi Sensor pada Rancang Bangun Alat Ukur Total Dissolved Solids (TDS) dan Tingkat Kekeruhan Air

Total Dissolved Solids (TDS) and turbidity of water are parameters to determine the quality of water. In this research, instruments development and study of accuracy level for TDS meter and turbidimeter have been made. Instruments were made using TDS sensor and turbidity sensor that were inexpensive and available on the market. The samples used for instruments examination were water with dye (Rhodamine B) and powder of coffee as impurities. The results showed that the sensors worked properly and provided a better accuracy in measuring water samples with coffee impurities than dye impurities. The inaccuracy on the determination of water samples with dye impurities due to dye particles which have soluble properties on water and microscopic size than particles of coffee.

Design of Filtering Systems for Monitoring the Quality of Household Drinking Water

Processing water products sources into ready-to-drink water have been widely circulated in community, one of it's a household drinking water filter with 4 filter stages. Drinking water itself is indispensable for human body. It's because most of the human body is made up of water. To meet the water needs in human body, drinking water is required. Drinking water that consumed by community must meet drinking water standards that have been determined by Minister of Health Decree No. 492/2010, which must meet physical, chemical, biological and radioactive requirements.This research aimed at monitoring several drinking water quality parameters in form of Ph (6.5 - 8.5), Turbidity (<5 NTU) and temperature (22 ? - 27 ?) by using pH sensor, turbidity sensor and temperature sensor, and ON/OFF scheduling of ultraviolet light as an inhibitor of bacterial growth which then monitoring results will be sent via nodeMCU ESP8266 and displayed on WEB. The results of the Ph sensor readings show a reading accuracy of up to 97.28%, on the temperature sensor the reading accuracy reaches 98.7%, while the turbidity sensor has an accuracy level of up to 98.875%, the ON/OFF of UV light goes according to schedule. The application software used able to read and store data in real time from water quality sensor so users can monitor quality of drinking water. Water from filtration of water filter can be categorized as suitable for drinking in accordance with drinking water standard in the Decree of Minister of Health No. 492 in 2010.

Sistem Alat Ukur Kekeruhan Berbasis Mikrokontroler ATMega16A-PU

The fabrication of the ATMega16A-PU microcontroller-based the system turbidity sensor consists of sensor module Turbidity SKU:SEN0189 including with the signal conditioning, power supply unit, the ATMega16A-PU microcontroller module, LCD 16 x 2 character, and personal computer (PC). The measuring system is used to measure the quality of water on theriverMartapura South Kalimantan, Indonesia. The physical parameters that measured is the of water. The measuring of turbidity detected by the sensor through the light that traverse the suspended particles in water. The output signal from the sensor in from of the voltage signal is connectedwith ATMega16A-PU microcontroller viaport A0. The voltage signal output is inversely proportional to the turbidity. Theequation of sensor characteristic is obtained by comparing the measuring device with HACH DR 890 Colorimeter turbid meter gauge. The characteristic equation obtained is counted into five equations to get a small error value, where v1 = -0.0036k1 + 4.0834, v2 = -0.0024k2 + 3.9351, v3 = -0.003k3 + 4.1777, v4 = -0.0033k4 + 4.3355, v5 = -0.0034k5 + 4.4315, the five equations have different measurement ranges. The result of data measurement are displayed on the LCD 16 x 2 character and the personal computer (PC) with the Delphi.7 interface program. The advantages of personal computer (PC) interface are the data measurement result could monitor and stroge in excel and database format. The results of the measuring instrument show a difference of 1 NTU to 15 NTU with the largest deviation is ± 28.7 and a standard deviation of ± 4.57 in the range of 31 NTU to 510 NTU

Modeling Pesticide and Sediment Transport in the Malewa River Basin (Kenya) Using SWAT

Understanding the dynamics of pesticide transport in the Malewa River and Lake Naivasha, a major fresh water resource, is critical to safeguard water quality in the basin. In this study, the soil and water assessment tool (SWAT) model was used to simulate the discharge of sediment and pesticides (notably the organochlorine residues of lindane, methoxychlor and endosulfan) into the Malewa River Basin. Model sensitivity analysis, calibration and validation were performed for both daily and monthly time steps using the sequential uncertainty fitting version 2 (SUFI-2) algorithm of the SWAT-CUP tool. Water level gauge data as well as a digital turbidity sensor (DTS-12) for suspended sediment transport were used for the SWAT calibration. Pesticide residues were measured at Upper and Down Malewa locations using a passive sampling technique and their quantity was determined using laboratory gas chromatography. The sensitivity analysis results showed that curve number (CN2), universal soil loss equation erodibility factor (USLE-K) and pesticide application efficiency (AP_EF) formed the most sensitive parameters for discharge, sediment and pesticide simulations, respectively. In addition, SWAT model calibration and validation showed better results for monthly discharge simulations than for daily discharge simulations. Similarly, the results obtained for the monthly sediment calibration demonstrated more match between measured and simulated data as compared to the simulation at daily steps. Comparison between the simulated and measured pesticide concentrations at upper Malewa and down Malewa locations demonstrated that although the model mostly overestimated pesticide loadings, there was a positive association between the pesticide measurements and the simulations. Higher concentrations of pesticides were found between May and mid-July. The similarity between measured and simulated pesticides shows the potential of the SWAT model as initial evaluation modelling tool for upstream to downstream suspended sediment and pesticide transport in catchments.

Simulated nutrient and plankton dynamics in the Great Barrier Reef (2011–2016)

Abstract The dynamics of nutrients, phytoplankton, zooplankton and water clarity of the iconic Great Barrier Reef World Heritage Area (GBRWHA) are influenced by seasonal variation in coastal and oceanic conditions, and anthropogenic inputs. We use the 3-dimensional coupled catchment-hydrodynamic-sediment-wave-optical-biogeochemical eReefs model to hindcast nutrient and planktonic responses to changes in seasonal and annual variability over a six-year period (2011–2016). In this paper we present a comparison of the eReefs model conducted against a range of in situ observations that included 24 water quality moorings, 2 nutrient sampling programs (with a total of 18 stations) and time-series of taxon-specific plankton abundance. At 14 near-coastal stations the simulated chlorophyll a (Chl a), when compared with chlorophyll extractions from water samples, had an average root mean square (RMS) error of 0.30 mg m−3 and a Willmott index of 0.59. For the same sites, simulated turbidity, when compared with turbidity sensors, had a Willmott index of 0.58 and simulated nitrate + nitrite had a Willmott index of 0.41 when compared with tri-annual water samples. Comparison with a spatially-resolved statistical model of zooplankton based on >900 observations in the region showed similarities in the relationship and spatial distribution of simulated and observed biomass, where both show zooplankton biomass is greatest inshore, biomass is highest around shallow reef areas and in the southern and central GBRWHA, and greater in summer than winter. Additionally, we investigate planktonic and nutrient responses to climatic variation. The first two years of the simulation coincided with La Nina events that drive greater than average winds, rainfall and river discharge. Throughout all years, simulated Chl a increases from north to south and from outer to inner coastal regions. Dissolved inorganic nitrogen, primary production and phytoplankton biomass were higher during La Nina in inshore and mid-shelf waters, while offshore regions were similar in all years from 2011 to 2016. Simulated Secchi depth was deeper offshore and decreased from offshore to inner coastal regions and from north to south. The eReefs simulation contributes to the understanding at a high spatial and temporal resolution of where and how nutrients and plankton originate and interact within the Great Barrier Reef.

Pilot study of in-line continuous flocculation water treatment plant

Human consumption of groundwater without treatment is not safe and can cause water-borne diseases and other kinds of illnesses. Usually, groundwater extracted through boreholes may be acidic and contains impurities such as organic and inorganic contaminants, microbes, and heavy metals. Hence, it becomes imperative to treat groundwater to make it potable for human consumption. This pilot study was conceptualized based on a simple and the most economical technological approach in groundwater treatment. It employed the basic concepts and working principles of essential unit operations such as coagulation, sedimentation, filtration, and adsorption to ensure potable water for human consumption based on WHO standard specifications. The plant specifically treats groundwater of pH 6.30-6.50. The average flow rate of the plant is 12,570 cm3/min (0.7542 m3/hr) and a centrifugal pump of 0.5 HP and a pipe size of 20 mm diameter were selected for this design. Equipment used were determined, sized and selected as required and the treated water quality is ensured through laboratory routine tests carried out in the course of the continuous operation of the pilot plant. Sand filter and carbon purifier are inevitable and a turbidity sensor is proposed for the filters to optimize the backwash operation. Capital cost evaluation was carried out using the percentage of delivered equipment cost method and the total capital cost for this pilot plant was estimated as One Thousand, Seven Hundred and Eighty-Two-Ringgit (RM 1,782.00 ≈ USD445.50). Thus, with this successful pilot study for a continuous treatment operation, a plant scale-up is feasible for groundwater purification to ensure potable water security in both rural and urban communities.

MICROCONTROLLER-BASED pH AND TURBIDITY MEASURING SYSTEM

Sustaining and monitoring appropriate pH levels is important in agricultural, industrial and environmental processes. For measurement of the pH level, it is essential to choose the correct pH probe. Turbidity can be measured by turbidity meters for the assessment of water quality or the proficiency of purification process. Research Objectives: To investigate the water quality of streams and lakes, to measure various pH levels of liquids and to measure different turbidity values of liquids. Methodology: The microcontroller based pH level and turbidity measuring system is designed and constructed using a pH probe -KADY pH tester / meter, amplifier circuit, turbidity sensor, PIC 16F887 microcontroller circuit, 16 x 2 line LCD module and power supply circuit. Findings and Research outcomes: In pure water, pH is 5.5-6.9 and voltage is 700-720mV. In coca, pH is 2-3 and voltage is 620 – 640 mV. In salt water, pH is 9-10 and voltage is 780-800 mV. In orange, turbidity is 300-900 NTU and voltage is 1.0V-0.7V. In coca, turbidity is 65-80 NTU and voltage is 1.4V – 1.58V. In milk, turbidity is >4000 NTU and voltage is 0-0.1 V. Conclusion: The pH sensor circuit and turbidity sensor circuit can be assembled together with constructed microcontroller circuit. Article DOI: https://dx.doi.org/10.20319/mijst.2018.42.266274 This work is licensed under the Creative Commons Attribution-Non-commercial 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc/4.0/ or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA.

Plastic fiber evanescent sensor in measurement of turbidity

The construction and working principles of a plastic fiber sensor for examining the level of turbidity is studied in this paper. This work focuses on designing an inexpensive turbidity sensor that incorporates a pair of multimode fibers (MMF) that are attached side by side and their beveled tips are mounted vertically. The efficiency of different beveled angles is evaluated by simulation with Tracepro software. The reflected signal is collected by immersing the sensor head into a water mixture and analyzed for various concentration. It was found that there is a linear increment of output intensity when concentration of mixture is increased. The turbidity sensor is tested with real samples that are collected from lake, river and coastal areas to demonstrate its consistency with commercial apparatus in natural compounds. The results showed that the proposed sensor structure is able to produce reliable results in a dynamic range of detection from 0 to 1000 Nephelometric Turbidity Unit (NTU) to facilitate practical field measurements.