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To continue sleep research activities during the lockdown resulting from the COVID-19 pandemic, experiments that were previously conducted in laboratories were shifted to the homes of volunteers. Furthermore, for extensive data collection, it is necessary to use a large number of portable devices. Hence, to achieve these objectives, we developed a low-cost and open-source portable monitor (PM) device capable of acquiring electroencephalographic (EEG) signals using the popular ESP32 microcontroller. The device operates based on instrumentation amplifiers. It also has a connectivity microcontroller with Wi-Fi and Bluetooth that can be used to stream EEG signals. This portable single-channel 3-electrode EEG device allowed us to record short naps and score different sleep stages, such as wakefulness, non rapid eye movement sleep (NREM), stage 1 (S1), stage 2 (S2), stage 3 (S3) and stage 4 (S4). We validated the device by comparing the obtained signals to those generated by a research-grade counterpart. The results showed a high level of accurate similarity between both devices, demonstrating the feasibility of using this approach for extensive and low-cost data collection of EEG sleep recordings.
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In this study, we propose a method based on phase space reconstruction to estimate the short-term future behavior of pressure signals in pipelines. The pressure time series data were obtained from an IoT experimental model conducted in the laboratory. The proposed hydraulic system demonstrated the presence of traces of weak chaos in the time series of the pressure signal. Fractal dimension analysis revealed a complex fractal structure in the data, indicating the existence of nonlinear dynamics. Similarly, Lyapunov coefficients, divergent trajectories, and autocorrelation analysis confirmed the presence of weak chaos in the time series. The results demonstrated the existence of apparently chaotic patterns that follow the theory proposed by Kolmogorov for deterministic dynamic systems that exhibit apparently random behaviors. Phase space reconstruction allowed us to show the dynamic characteristics of the signal so that short-term predictions were stable. Finally, the study of strange attractors in pipeline pressure time series can have significant contributions to anomaly detection.â¢A methodology is proposed for the reconstruction of the phase space to estimate the short-term future behavior of pressure signals in pipelines in real time.â¢The analysis of the proposed hydraulic system revealed some indications of weak chaos in the time series of the pressure signal obtained experimentally.â¢The methodology implemented and the results of this study showed that the short-term predictions were very accurate and consistent; Chaotic patterns were also identified that support the theory proposed by Kolmogorov.
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This work presents a low-cost transcription loop-mediated isothermal amplification (RT-LAMP) instrument for nucleic acid detection, employing an Arduino Nano microcontroller. The cooling system includes customized printed circuit boards (PCBs) that serve as electrical resistors and incorporate fans. An aluminum block is designed to accommodate eight vials. The system also includes two PCB heaters-one for sample heating and the other for vial lid heating to prevent condensation. The color detection system comprises a TCS3200 color 8-sensor array coupled to one side of the aluminum heater body and a white 8-LED array coupled to the other side, controlled by two Multiplexer/Demultiplexer devices. LED light passes through the sample, reaching the color sensor and conveying color information crucial for detection. The top board is maintained at 110 ± 2 °C, while the bottom board is held at 65 ± 0.5 °C throughout the RT-LAMP assay. Validation tests successfully demonstrated the efficacy of the colorimetric RT-LAMP reactions using SARS-CoV-2 RNA amplification as a sample viability test, achieving 100% sensitivity and 97.3% specificity with 66 clinical samples. Our instrument offers a cost-effective (USD 100) solution with automated result interpretation and superior sensitivity compared to visual inspection. While the prototype was tested with SARS-CoV-2 RNA samples, its versatility extends to detecting other pathogens using alternative primers, showcasing its potential for broader applications in biosensing.
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RNA Viral , DNA Polimerase Dirigida por RNA , DNA Polimerase Dirigida por RNA/genética , RNA Viral/genética , Alumínio , Técnicas de Diagnóstico Molecular , Técnicas de Amplificação de Ácido Nucleico , RNA Polimerases Dirigidas por DNA , Sensibilidade e EspecificidadeRESUMO
Different types of environmental pollution cause negative consequences to ecosystems throughout the globe, which humanity is now trying to mitigate. It is necessary to know the level of pollution problems in the immediate environment, to evaluate the impact of human activities, and mitigation strategies necessary to ensure habitability. For this reason, in this work, a low-cost pollution measurement station for outdoor or indoor use is proposed and developed that measures air pollution (particulate matter and CO2), noise (level and direction), light pollution (power and multispectral), and also relative humidity and ambient temperature. The system stores the data in an SD memory or transmits data in real-time to the internet via WiFi. The purposes of the system are to be used in environmental studies, to deploy monitoring networks, or to ensure the habitability of a living or working space. The prototype integrates the measurement of the different sources of contamination in a single compact device at USD$ 628.12 without sacrificing measurement accuracy. The system is validated for each variable with reference equipment, obtaining an average error of approximately 2.67% in the measurement of all the variables measured. The system is easy to assemble and has an option for power supply using solar photovoltaic devices and an alternative for connection to 2G/3G mobile networks.
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This contribution shows the possibilities of applying a low-cost, multi-purpose data logger built around an Arduino Mega 2560 single-board computer. Most projects use this kind of hardware to develop single-purpose data loggers. In this work, a data logger with a more general hardware and software architecture was built to perform measurement campaigns in very different domains. The wide applicability of this data logger was demonstrated with short-term monitoring campaigns in relation to outdoor air quality, human activity in an office, motion of a journey on a bike, and exhaust gas monitoring of a diesel generator. In addition, an assessment process and corresponding evaluation framework are proposed to assess the credibility of low-cost scientific devices built in-house. The experiences acquired during the development of the system and the short measurement campaigns were used as inputs in the assessment process. The assessment showed that the system scores positively on most product-related targets. However, unexpected events affect the assessment over the longer term. This makes the development of low-cost scientific devices harder than expected. To assure stability and long-term performance of this type of design, continuous evaluation and regular engineering corrections are needed throughout longer testing periods.
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Overweight and obesity promote diabetes and heart disease onset. Triglycerides are key biomarkers for cardiovascular disease, strokes, and other health issues. Scientists have devised methods and instruments for the detection of these molecules in liquid samples. In this study, an enzymatic biosensor was developed using an Arduino-based microfluidic platform, wherein a lipolytic enzyme was immobilized on an ethylene-vinyl acetate polymer through physical adsorption. This low-cost optical biosensor employed a spectrophotometric transducer and was assessed in liquid samples to indirectly detect triglycerides and fatty acids using p-nitrophenol as an indicator. The average triglyceride level detected in the conducted experiments was 47.727 mg/dL. The biosensor exhibited a percentage of recovery of 81.12% and a variation coefficient of 0.791%. Furthermore, the biosensor demonstrated the ability to detect triglyceride levels without the need for sample dilution, ranging from 7.6741 mg/dL to 58.835 mg/dL. This study successfully developed an efficient and affordable enzymatic biosensor prototype for triglyceride and fatty acid detection. The lipolytic enzyme immobilization on the polymer substrate provided a stable and reproducible detection system, rendering this biosensor an exciting option for the detection of these molecules.
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Microfluídica , Infarto do Miocárdio , Humanos , Adsorção , Ácidos Graxos , PolímerosRESUMO
Nowadays, monitoring aspects related to sustainability and safety in mining activities worldwide are a priority, to mitigate socio-environmental impacts, promote efficient use of water, reduce carbon footprint, use renewable energies, reduce mine waste, and minimize the risks of accidents and fatalities. In this context, the implementation of sensor technologies is an attractive alternative for the mining industry in the current digitalization context. To have a digital mine, sensors are essential and form the basis of Industry 4.0, and to allow a more accelerated, reliable, and massive digital transformation, low-cost sensor technology solutions may help to achieve these goals. This article focuses on studying the state of the art of implementing low-cost sensor technologies to monitor sustainability and safety aspects in mining activities, through the review of scientific literature. The methodology applied in this article was carried out by means of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and generating science mapping. For this, a methodological procedure of three steps was implemented: (i) Bibliometric analysis as a quantitative method, (ii) Systematic review of literature as a qualitative method, and (iii) Mixed review as a method to integrate the findings found in (i) and (ii). Finally, according to the results obtained, the main advances, gaps, and future directions in the implementation of low-cost sensor technologies for use in smart mining are exposed. Digital transformation aspects for data measurement with low-cost sensors by real-time monitoring, use of wireless network systems, artificial intelligence, machine learning, digital twins, and the Internet of Things, among other technologies of the Industry 4.0 era are discussed.
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ABSTRACT With an estimated approximately 2 million deaths per year, diabetes is one of the top 5 deadliest noncommunicable diseases globally. Although this disease is not fatal, the degradation of the patient's health due to a bad plan to control their glucose levels can have a fatal outcome. In order to lay the foundations for the development of a device that allows estimating glucose levels in some body fluid, we present the results obtained not only for the estimation of glucose in deionized water, but also describe the development and configuration of the created device. After analyzing 50 signals obtained from 5 different glucose concentrations, the feasibility of using the developed device for the analysis is evident, since, considering the K-Nearest Neighbors (KNN) algorithm, all the signals were associated correctly to the glucose group to which they belong.
RESUMEN Con un estimado de aproximadamente 2 millones de muertes por año, la diabetes es una de las 5 enfermedades no transmisibles más mortales a nivel mundial. Aunque esta enfermedad no es mortal, el deterioro de la salud del paciente por un mal plan para controlar sus niveles de glucosa puede tener un desenlace fatal. Con el fin de sentar las bases para el desarrollo de un dispositivo que permita estimar los niveles de glucosa en algún fluido corporal, presentamos los resultados obtenidos no solo para la estimación de glucosa en agua desionizada, sino que también describimos el desarrollo y configuración del dispositivo creado. Luego de analizar 50 señales obtenidos a partir de 5 concentraciones de glucosa diferentes, se evidencia la factibilidad de utilizar el dispositivo desarrollado para el análisis, ya que, considerando el algoritmo K-Nearest Neighbors (KNN), todas las señales se asociaron correctamente al grupo de glucosa al que pertenecen.
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ABSTRACTAnaerobic digestion (AD) relies on the cooperation of specific microbial communities, making it susceptible to process disruptions that could impact biogas production. In this regard, this study presents a technological solution based on the Arduino platform, in the form of a simple online monitoring system that can track the produced biogas profile, named as biogas analyzer module (BAM). The applicability of the BAM focused on monitoring the biogas produced from sugarcane vinasse inoculated with sewage sludge biodigestion processed in mesophilic conditions (38 oC), in a pH range of 6.5-7.5, and following a three-stage operational model: (i) an adaptation (168â h), (ii) complete mixing (168â h), and (iii) bio-stimulation with glycerol (192â h). Then, the lab-made BAM was used to trace the produced biogas profile, which registered a total biogas volume of 8,719.86 cm3 and biomethane concentration of 95.79% (vol.), removing 90.8% (vol) of carbon dioxide (CO2) and 65.2% (vol) of hydrogen sulfide (H2S). In conclusion, the results ensured good accuracy and efficiency to the device created by comparisons with established standards (chromatographic and colorimetric methods), as well as the cost reduction. The developed device would likely be six times cheaper than what is available in the market.
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A Helmholtz-type electromagnetic emission device, which uses an oscillating magnetic field (OMF), with potential applications in biotechnological research, was built and validated. The coils were connected to an alternating current (AC) generator to generate a 0.5 to 110 mT field at their center. OMF measurements were performed with a Hall effect sensor with a digital signal connection (Arduino nano) and data output to a PC using LabVIEW v2017SP1 software. The fermentation process of the cocoa bean variety CCN 51, exposed to four levels of OMF density for 60 min (0, 5, 40, and 80 mT/60 min), was analyzed. Different variables of the grain fermentation process were evaluated over six days. The ANOVA test probed the device's linearity, accuracy, precision, repeatability, reliability, and robustness. Moreover, CCN 51 cocoa beans' EMF-exposure effect was evaluated under different OMF densities for 60 min. The results show the validity of the equipment under working conditions and the impact of EMF (electromagnetic fields) on the yield, deformation, and pH of cocoa beans. Thus, we concluded that the operation of the prototype is valid for use in biotechnological studies.
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Stereotaxic surgery is a less invasive form of surgery that uses a three-dimensional coordinate system to place instruments at a specific location in the brain. Through this type of surgery, one can place needles among other tools within the structures of the brain. Therefore, injections can be given in order to deliver substances that cannot cross the blood-brain barrier. The two most important parameters of the microinjection to control are volume and speed. The volume should not be so large that it displaces the brain tissue and tears it. The injection speed must also be slow so that the liquid that comes out of the syringe can diffuse into the tissue without displacing it and damaging it. Thus, the objectives of the present work are: 1) To develop not a 3D printed prototype but an end-user device. 2) The device must be for animal research only. 3) It must have the same precision in volume and speed as commercial devices. 4) It must be adjustable for microsyringes from 0.5 µl to 1 ml. 5) It must be possible to place it directly on the stereotaxic surgery apparatus and to use it separately. 6) The price must be substantially lower than that of the commercial devices.
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Fast, sensitive, simple, and cheap sensors are highly desirable to be applied in the health system because they improve point-of-care diagnostics, which can reduce the number of cases of infection or even deaths. In this context, here we report the development of a label-free genosensor using a screen-printed electrode modified with 2D-carbonylated graphitic carbon nitride (c-g-C3N4), poly(diallyldimethylammonium) chloride (PDDA), and glutathione-protected gold nanoparticles (GSH-AuNPs) for photoelectrochemical (PEC) detection of SARS-CoV-2. We also made use of Arduino and 3D printing to miniaturize the sensor device. The electrode surface was characterized by AFM and SEM techniques, and the gold nanoparticles by UV-Vis spectrophotometry. For SARS-CoV-2 detection, capture probe DNA was immobilized on the electrode surface. The hybridization of the final genosensor was tested with a synthetic single-strand DNA target and with natural saliva samples using the photoelectrochemistry method. The device presented a linear range from 1 to 10,000 fmol L-1 and a limit of detection of 2.2 and 3.4 fmol L-1 using cpDNA 1A and 3A respectively. The sensibility and accuracy found for the genosensor using cpDNA 1A using biological samples were 93.3 and 80% respectively, indicating the potential of the label-free and portable genosensor to detect SARS-CoV-2 RNA in saliva samples.
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Multispectral imaging is at the forefront of contactless surface analysis. Standard multispectral imaging systems use sophisticated software, cameras and light filtering optics. This paper discloses the building of a customizable and cost-effective multispectral imaging and analysis system. It integrates a web camera, light emitting diodes (LEDs) lighting, a semisphere for even lightening, an open-source Arduino™ development board and a free Python application to automatically obtain and visually analyze multispectral images. The device is hereafter called MEDUSA and its optical performance was tested for repeated Imaging consistency, visible and near infrared band sensitivity and lighting evenness. Four proof of concept tests were run in order to understand the advantageous use of this system, as compared to a simple visual score of diverse samples. Each of three qualitative tests used sets of 12 LED band spectral images to analyze ink changes in a counterfeit bill, surface bruises on Hass avocado fruits and transient changes in petri dish grown bacterial colonies. A fourth test used single band imaging in a set of standard laboratory analyzed plant samples, to quantitatively relate a red band light reflectance to its nitrogen content. These tests indicate that MEDUSA made images may yield qualitative and quantitative spectral information unseen to the naked eye, suggesting potential use in currency counterfeit tests, food quality analyses, microbial phenotyping and agricultural plant chemistry. MEDUSA can be freely reproduced and customized from this research, making it a powerful and affordable analytical tool to analyze a wide range of subtle chemical properties in samples at industrial and science fields.
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RESUMEN El uso de fermentadores es común en diversos procesos biotecnológicos. Actualmente, un fermentador o biorreactor tiene la capacidad de monitorear variables físicas y químicas las cuales son mostradas al operador por medio de una pantalla. Aunado a los materiales de construcción de un biorreactor, hoy en día su adquisición es costosa e inaccesible para fines educativos y de investigación. Para abordar esta problemática, se diseñó y desarrolló la interfaz Fermenta V1.0. orientada a la simulación de un bioproceso realizado por un fermentador, para realizarla se utilizó una pantalla táctil Nextion y Arduino UNO; para su programación, se implementaron los entornos de desarrollo integrados apropiados. La interfaz fue capaz de emular diferentes dispositivos electrónicos como sensores, válvulas solenoides, bombas peristálticas, iluminación y agitación. En esta primera etapa, se establece el punto de partida para facilitar el acoplamiento de la interfaz Fermenta V1.0 con diversos sensores orientados al monitoreo de un fermentador. Con la incorporación de los dispositivos electrónicos a la interfaz, se podrá adecuar al sistema (interfaz-sensores) a un proceso biotecnológico en donde se requiera el uso de un fermentador y la necesidad de monitorear temperatura, oxígeno disuelto, pH, CO2, iluminación, agitación.
ABSTRACT The use of fermenters is common in various biotechnological processes. Currently, a fermenter or bioreactor can monitor physical and chemical variables which are displayed to the operator through a screen. In addition to the construction materials of a bioreactor, nowadays its acquisition is expensive and inaccessible for educational and research purposes. To address this problem, the Fermenta V1.0 interface was designed and developed to simulate a bioprocess performed by a fermenter, using a Nextion touch screen and Arduino UNO; for its programming, the appropriate integrated development environments were implemented. The interface was able to emulate different electronic devices such as sensors, solenoid valves, peristaltic pumps, lighting, and agitation. In this first stage, the starting point is established to facilitate the coupling of the Fermenta V1.0 interface with various sensors oriented to the monitoring of a fermenter. With the incorporation of the electronic devices to the interface, it will be possible to adapt the system (interface-sensors) to a biotechnological process where the use of a fermenter is required and the need to monitor temperature, dissolved oxygen, pH, CO2, lighting, agitation.
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Air, water, and soil are essential for terrestrial life, but pollution, overexploitation, and climate change jeopardize the availability of these primary resources. Thus, assuring human health and food production requires efficient strategies and technologies for environmental protection. Knowing key parameters such as soil moisture, air, and water quality is essential for smart farming and urban development. The MeteoMex project aims to build simple hardware kits and their integration into current Internet-of-Things (IoT) platforms. This paper shows the use of low-end Wemos D1 mini boards to connect environmental sensors to the open-source platform ThingsBoard. Two printed circuit boards (PCB) were designed for mounting components. Analog, digital and I2C sensors are supported. The Wemos ESP8266 microchip provides WiFi capability and can be programed with the Arduino IDE. Application examples for the MeteoMex aeria and terra kits demonstrate their functionality for air quality, soil, and climate monitoring. Further, a prototype for monitoring wastewater treatment is shown, which exemplifies the capabilities of the Wemos board for signal processing. The data are stored in a PostgreSQL database, which enables data mining. The MeteoMex IoT system is highly scalable and of low cost, which makes it suitable for deployment in agriculture 4.0, industries, and public areas. Circuit drawings, PCB layouts, and code examples are free to download from https://github.com/robert-winkler/MeteoMex.
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Apesar da ampla disponibilidade de dispositivos para leitura de tiras reativas para análise de urina, falhas potenciais persistem na rotina baseada na interpretação humana. O objetivo deste estudo foi desenvolver e avaliar o desempenho de um dispositivo baseado em Arduino para a leitura semi-automática de parâmetros de fitas reativas. O parâmetro glicose de um modelo de tira reativa comercial foi analisado pelo sistema, que prevê a concentração do analito submetendo a cor observada na tira a um modelo de regressão, ajustado a um banco de dados de padrões de cores. O sistema foi avaliado através da leitura de 80 tiras com 16 amostras de concentrações aleatórias de glicose. O menor coeficiente de variação após cinco leituras replicadas foi de 4,5% e o mais alto foi de 16,6% (MSE = 68,7 mg / dL; r = 0,979). O dispositivo apresentou resultados satisfatórios mais baixos custos. Para torná-lo útil na rotina laboratorial, seriam necessárias novas experiências com outros parâmetros e outras classes de tiras reativas para análise de urina.
Although many devices are available to read urinalysis reactive strips, potential failure, based on human interpretation, persists in routine tasks. Current study develops and evaluates the performance of an Arduino-based device for the semi-automated reading of reactive strip parameters. The glucose parameter of a commercial reactive strip model was analyzed by the system, which predicts analyte concentration by submitting the color observed in the strip to a regression model, adjusted to a database of color patterns. The system was assessed by reading of 80 strips with 16 samples of random glucose concentrations. The lowest coefficient of variation after five replicated readings was 4.5% and the highest was 16.6% (MSE=68.7 mg/dL; r=0.979). The device featured satisfactory results plus low costs. To make it useful in the laboratory routine, further experiments with other parameters and other classes of urinalysis reactive strips would be necessary.
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Accessibility to potentiostats is crucial for research development in electrochemistry, but their cost is the principal drawback for their massive use. With the aim to provide an affordable alternative for resource-constrained communities, we present a low-cost, portable electrochemical workstation that integrates an open-source potentiostat based on Arduino and a smartphone application. This graphical user interface allows easy control of electrochemical parameters and real-time visualization of the results. This potentiostat can perform the most used electrochemical techniques of cyclic and linear voltammetry and chronoamperometry, with an operating range of ±225 µA and ±1.50 V, and results that are comparable with those obtained with commercial potentiostats. Three applications reported here demonstrate the capacity and the good performance of this low-cost potentiostat as a teaching tool: identification of redox pairs, electrochemical characterization of pencil graphite electrodes, and detection of heavy metals using an electrodeposited film of bismuth on the pencil graphite electrode. Furthermore, detailed schemes of the device and its software are entirely available, expecting to provide an open-source potentiostat easy to replicate to further support education in electrochemical fundamentals and instrumentation.
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Relevant to mobile health, the design of a portable electrocardiograph (ECG) device using AD823X microchips as the analog front-end is presented. Starting with the evaluation board of the chip, open-source hardware and software components were integrated into a breadboard prototype. This required modifying the microchip with the breadboard-friendly Arduino Nano board in addition to a data logger and a Bluetooth breakout board. The digitized ECG signal can be transmitted by serial cable, via Bluetooth to a PC, or to an Android smartphone system for visualization. The data logging shield provides gigabytes of storage, as the signal is recorded to a microSD card adapter. A menu incorporates the device's several operating modes. Simulation and testing assessed the system stability and performance parameters in terms of not losing any sample data throughout the length of the recording and finding the maximum sampling frequency; and validation determined and resolved problems that arose in open-source development. Ultimately, a custom printed circuit board was produced requiring advanced manufacturing options of 2.5 mils trace widths for the small package components. The fabricated device did not degrade the AD823X noise performance, and an ECG waveform with negligible distortion was obtained. The maximum number of samples/second was 2380 Hz in serial cable transmission, whereas in microSD recording mode, a continuous ECG signal for up to 36 h at 500 Hz was verified. A low-cost, high-quality portable ECG for long-term monitoring prototype that reasonably complies with electrical safety regulations and medical equipment design was realized.
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Eletrocardiografia , Telemedicina , Desenho de Equipamento , Humanos , Processamento de Sinais Assistido por Computador , Smartphone , SoftwareRESUMO
Precision aquaculture is a new field that allows farmers to have better control over aquaculture processes, facilitating decision-making and improving efficiency. The implementation and evaluation of a low-cost water-quality monitoring system based on open-source hardware, which is easy to rebuild for scientific applications, is reported in this paper. The proposed system measures temperature, dissolved oxygen, and pH, taking records and sending information through a wireless protocol (ZigBee) to a graphical user interface which can display information numerically and graphically, as well as simultaneously storing the information in a database. These variables are very important for aquaculture, as they have a direct influence on critical culture parameters such as growth and survival. Although it is a low-cost system, it offers good quality data and demonstrates efficiency for its use in precision aquaculture.
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Aquicultura/instrumentação , Qualidade da Água , Gráficos por Computador , Bases de Dados Factuais , Concentração de Íons de Hidrogênio , Oxigênio/análise , Temperatura , Interface Usuário-Computador , Tecnologia sem FioRESUMO
One of the main analytical variable to indicate the evolution and the phases of the composting process is temperature, whose constant monitoring is fundamental for decision making. However, studies usually perform collection of temperature data with a daily frequency due to the operational difficulty in obtaining this information from manually collected samples. Thus, the aim of this study was to determine the ideal frequency of temperature data collection in composting layers. Eight composting layers containing tree prunings + domestic organic residues were installed and four temperature sensors were installed in each layer. The temperature data were collected and recorded from minute to minute by means of a datalogger developed with an Arduino board during 70 days of composting. Thus, the collected temperatures were used as a pilot sample, and therefore the ideal temperature collection rate was estimated for different estimation error limits. No significant difference was found between the different collection times according to the Kruskal-Wallis test at a significance level of 5%. Therefore, the ideal collection frequency can be determined from the error limit of temperature estimation that is acceptable to the researcher.