Method for phase space reconstruction to estimate the short-term future behavior of pressure signals in pipelines

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.•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.•The analysis of the proposed hydraulic system revealed some indications of weak chaos in the time series of the pressure signal obtained experimentally.•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.

Computational thinking and programming with Arduino in education: A systematic review for secondary education

The development of programming skills and computational thinking in the formal educational context is one of the most recent horizons set by many educational systems worldwide. Although the first computational thinking initiatives are being applied from the earliest school ages, this research focuses on the secondary education level. Specifically, the objective is the following: to analyse the implementation of Arduino, as well as the benefits and opportunities it brings to secondary school students. For this purpose, documentary research has been undertaken applying a systematic review according to the PRISMA 2020 framework following the PiCoS strategy. Atlas.ti 9 was used to analyse the information. Out of 316 papers identified, 37 were included in the research. In relation to the results, Arduino is primarily used in technology and physics subjects, although it is also used to develop interdisciplinary STEAM projects. As a rule, it is used to learn programming languages, but likewise as a resource to develop science experiments. LED lights, servomotors and breadboards are among the most commonly used resources together with the Arduino board. and Scratch was the most widely used software. The initiatives implemented have yielded both positive and negative results, for example, one drawback is that some projects are very difficult, and some achievements such as: increased motivation towards the contents addressed or also the development of some soft skills, such as problem solving.

Dual feed progressive cavity pump extrusion system for functionally graded direct ink write 3D printing

Material extrusion Additive Manufacturing (AM), is one of the most widely practiced methods of AM. Fused Filament Fabrication (FFF) is what most associate with AM, as it is relatively inexpensive, and highly accessible, involving feeding plastic filament into a hot-end that melts and extrudes from a nozzle as the toolhead moves along the toolpath. Direct Ink Write (DIW) 3D printing falls into this same category of AM, however is primarily practiced in laboratory settings to construct novel parts from flowable feedstock materials. DIW printers are relatively expensive and often depend on custom software to print a part, limiting user-specificity. There have been recent advancements in multi-material and functionally graded DIW, but the systems are highly custom and the methods used to achieve multi-material prints are openly available to the public. The following article outlines the construction and operation method of a DIW system that is capable of printing that can produce compositionally-graded components using a dual feed progressive cavity pump extruder equipped with a dynamic mixer. The extruder and its capabilities to vary material composition while printing are demonstrated using a Prusa i3 MK3S+ desktop fused filament fabrication printer as the gantry system. This provides users ease of operation, and the capability of further tailoring to specific needs.

Low-Cost Arduino Reverse Transcriptase Loop-Mediated Isothermal Amplification (RT-LAMP) for Sensitive Nucleic Acid Detection

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.

Design and implementation of DATA logging and stabilization system for a UAV

In this paper integration of Micro Electro Mechanical Systems (MEMS) based Inertial Measurement Unit (IMU) and Global positioning System are used for data logging. This paper presents the design and implementation of a data logging system for an Unmanned Aerial Vehicle. The main focus is designing a prototype system for tracking purposes with image-capturing capabilities. The purpose is to develop a recorder that can provide a complete record of the parameters in case of surveillance. The data logger can also be used to determine the cause of a flight crash. The results are gathered to improve the quality of measurements. And also the quality of the sensor's measurements can be improved with sophisticated filtering techniques. This filter was designed using the Mahony filter which provides efficient and effective solutions for IMU. This filter is computationally efficient and requires fewer mathematical computations to produce desired results at lower sampling rates. Additionally, the pitch, roll, and yaw stabilization of the device must be done when the system enters abnormal conditions. However, altitude, camera angle, and motion blur make it a more challenging task.

An IoT Real-Time Potable Water Quality Monitoring and Prediction Model Based on Cloud Computing Architecture

In order to achieve the Sustainable Development Goals (SDG), it is imperative to ensure the safety of drinking water. The characteristics of each drinkable water, encompassing taste, aroma, and appearance, are unique. Inadequate water infrastructure and treatment can affect these features and may also threaten public health. This study utilizes the Internet of Things (IoT) in developing a monitoring system, particularly for water quality, to reduce the risk of contracting diseases. Water quality components data, such as water temperature, alkalinity or acidity, and contaminants, were obtained through a series of linked sensors. An Arduino microcontroller board acquired all the data and the Narrow Band-IoT (NB-IoT) transmitted them to the web server. Due to limited human resources to observe the water quality physically, the monitoring was complemented by real-time notifications alerts via a telephone text messaging application. The water quality data were monitored using Grafana in web mode, and the binary classifiers of machine learning techniques were applied to predict whether the water was drinkable or not based on the data collected, which were stored in a database. The non-decision tree, as well as the decision tree, were evaluated based on the improvements of the artificial intelligence framework. With a ratio of 60% for data training: at 20% for data validation, and 10% for data testing, the performance of the decision tree (DT) model was more prominent in comparison with the Gradient Boosting (GB), Random Forest (RF), Neural Network (NN), and Support Vector Machine (SVM) modeling approaches. Through the monitoring and prediction of results, the authorities can sample the water sources every two weeks.

Cryologger Ice Tracking Beacon: A Low-Cost, Open-Source Platform for Tracking Icebergs and Ice Islands

Icebergs and ice islands (large, tabular icebergs) present a significant hazard to marine vessels and infrastructure at a time when demand for access to Arctic waters is increasing. There is a growing demand for in situ iceberg tracking data to monitor their drift trajectories and improve models used for operational forecasting of ice hazards, yet the high cost of commercial tracking devices often prevents monitoring at optimal spatial and temporal resolutions. Here, we provide a detailed description of the Cryologger Ice Tracking Beacon (ITB), a low-cost, robust, and user-friendly data logger and telemeter for tracking icebergs and ice islands based on the Arduino open-source electronics platform. Designed for deployments of at least 2 years with an hourly sampling interval that is remotely modifiable by the end user, the Cryologger ITB provides long-term measurements of position, temperature, pressure, pitch, roll, heading, and battery voltage. Data are transmitted via the Iridium satellite network at user-specified intervals. We present the results of field campaigns in 2018 and 2019, which saw the deployment of 16 ITBs along the coasts of Greenland and Ellesmere and Baffin islands. The overall success of these ITB deployments has demonstrated that inexpensive, open-source hardware and software can provide a reliable and cost-effective method of monitoring icebergs and ice islands in the polar regions.

Open-source hardware- and software-based cryomicroscopy system for investigation of phase transitions in cryobiological research

The development of inexpensive equipment adapted for the study of a specific biological object is very important for cryobiology. In the presented work, we have proposed a simple system for microscopy utilising open-source platform Arduino. Testing this system showed that it had sufficient sensitivity to determine the physical processes occurring in a cryopreserved sample such as intra- and extracellular water crystallisation and salt eutectic. Utilising this system, we investigated the mechanisms of cryoprotection and cryodamage of testis interstitial cells (ICs) in cryoprotective media, which included cryoprotective agents such as dimethyl sulphoxide (Me2 SO), as well as foetal bovine serum or polymers (dextran, hydroxyethyl starch and polyethylene glycol). It was shown that a serum-/xeno-free medium that included 0.7 M Me2 SO and 100 mg/mL dextran was able to reduce intracellular water crystallisation in cells, change the structure of extracellular ice, and reduce salt eutectic and recrystallisation. All these effects correlated with better IC survival after cryopreservation in the medium. This medium is potentially less toxic as it has lower concentrations of Me2 SO compared to serum-containing media developed for cryopreservation of testicular cells. This would pave a way for the creation of nontoxic serum-free compositions that does not require removal before use of cryopreserved living cells for laboratory practice or in clinics.

Development and application of an inexpensive open-source dendrometer for detecting xylem water potential and radial stem growth at high spatial and temporal resolution

There is currently a need for inexpensive, continuous, non-destructive water potential measurements at high temporal resolution (<1 min). We describe here the development and testing of an entirely open-source dendrometer that, when combined with periodic Scholander pressure chamber measurements, provides sub-minute resolution estimates of water potential when placed on tissues exhibiting little or no secondary growth (petioles, monocotyledon stems). The dendrometer can also be used to measure radial growth of stems and branches when placed on dicotyledon and gymnosperm species. The dendrometer can be interfaced directly with a computer in real time in the lab or greenhouse, or connected to a datalogger for long periods of use in the field on batteries. We tested this device on a herbaceous dicotyledon (Helianthus annuus) (petioles and stems) and a monocotyledon (Zea mays) species (stems) for 1 week during dehydration and re-watering treatments under laboratory conditions. We also demonstrated the ability of the device to record branch and trunk diameter variation of a woody dicotyledon (Rhus typhina) in the field. Under laboratory conditions, we compared our device (hereafter 'contact' dendrometer) with modified versions of another open-source dendrometer (the 'optical' dendrometer). Overall, contact and optical dendrometers were well aligned with one another, with Pearson correlation coefficients ranging from 0.77 to 0.97. Both dendrometer devices were well aligned with direct measurements of xylem water potential, with calibration curves exhibiting significant non-linearity, especially at water potentials near the point of incipient plasmolysis, with pseudo R2 values (Efron) ranging from 0.89 to 0.99. Overall, both dendrometers were comparable and provided sufficient resolution to detect subtle differences in stem water potential (ca. 50 kPa) resulting from light-induced changes in transpiration, vapour pressure deficit and drying/wetting soils. All hardware designs, alternative configurations, software and build instructions for the contact dendrometers are provided.

MagnetoShield: A Novel Open-Source Magnetic Levitation Benchmark Device for Mechatronics Education and Research

This article presents an open-source device illustrating the well-known magnetic levitation experiment. The uniqueness of this particular device lies in its exceptionally small dimensions, affordability and availability, which makes it a perfect design for take-home experiments for education but it can also serve as a referential design for testing various control algorithms in research. In addition, this paper provides a comprehensive hardware design for reproducibility along with the detailed derivation of the mathematical model, system identification and validation. Moreover, the introduced hardware comes with an easy-to-use open-source application programming interface in C/C++ for the Arduino IDE, Simulink and CircuitPython. REXYGEN, another environment similar to Simulink, had also been used to demonstrate the capabilities of the MagnetoShield.

Continuous culture of anaerobic fungi enables growth and metabolic flux tuning without use of genetic tools

Anaerobic gut fungi (AGF) have potential to valorize lignocellulosic biomass owing to their diverse repertoire of carbohydrate-active enzymes (CAZymes). However, AGF metabolism is poorly understood, and no stable genetic tools are available to manipulate growth and metabolic flux to enhance production of specific targets, e.g., cells, CAZymes, or metabolites. Herein, a cost-effective, Arduino-based, continuous-flow anaerobic bioreactor with online optical density control is presented to probe metabolism and predictably tune fluxes in Caecomyces churrovis. Varying the C. churrovis turbidostat setpoint titer reliably controlled growth rate (from 0.04 to 0.20 h-1), metabolic flux, and production rates of acetate, formate, lactate, and ethanol. Bioreactor setpoints to maximize production of each product were identified, and all continuous production rates significantly exceed batch rates. Formate spike-ins increased lactate flux and decreased acetate, ethanol, and formate fluxes. The bioreactor and turbidostat culture schemes demonstrated here offer tools to tailor AGF fermentations to application-specific hydrolysate product profiles.

Development of an Arduino-based, open-control interface for hardware in the loop applications

This article presents a flexible control interface based on low-cost hardware solutions for electric drives which classically come either with a proprietary hardware solution or a high-cost interface solution. The interface presented can be used to connect a standard PC with an electric drive to enable testing simulation and control applications. The control interface is developed based on the open-source Python scripting language and Arduino's open-source and accessible hardware. The new interface communicates with the test stand through its I/O terminals via developed electronic amplifiers and creates a solid base for further development towards more extensive hardware in the loop simulations.

Development of a novel biochar-made porous monolith for enhanced C1 and H2 fermentation

Biochar is a carbonaceous porous material that is produced through the thermal processing of biomass under oxygen-limited environment. Nevertheless, biochar is known to be an inexpensive and sustainable raw material with a wide range of possible applications. Recently, biochar has been discovered as an efficient biological catalyst for anaerobic conversion, mainly due to its highly porous structure with micro and macro channels, which procures a viable living area for attached-grown microorganisms. Whereas it is never applied to improve the biological conversion of gas substances such as C1 (e.g., CO, CO2) and H2, which is a promising research area with increasing commercial interest. However, considering that biological reaction is limited by the target water solubility of gas substrates, special attention is required when combining biochar for gas fermentation. The goal was to create a novel gas sparger where the biofilm grows on biochar, thus improving the interaction with the gaseous substrate. For this purpose, polystyrene foam and powdered biochar were compounded to form a mouldable composite, which was then cast as a porous monolith.•Biochar-made sparger (BS) was investigated for the homoacetogenic conversion of H2 gas via microbial mixed cultures as opposed to a control test equipped with a stone sparger.•BS showed a significantly better performance in terms of biological gas fixation rate (36% more than control) and productivity (8.5 gCOD L-1 d-1).

Low-speed instrumented drill press for bone screw insertion

Screw insertion torque is a widely used/effective method for quantifying fixation strength in orthopedic implant research for different screw geometries, implantation sites, and loads. This work reports the construction of an open-source instrumented benchtop screw insertion device for a total cost of $7545 ($492 + $7053 for equipped sensors), as well as validation of the device and an example use-application. The insertion device is capable of recording the axial load, rotational speed, and applied torque throughout the screw insertion process at 10 samples per second, as demonstrated in the validation test. For this combination of bone analog (20 PCF Sawbones©), screw, and loading, the resolution of the torque sensor was 25% of the maximum measured torque; a different model torque sensor would be required to meet ASTM F543-17, which specifies a resolution of 10% of the maximum torque. This system is optimized for fastener insertion at speeds of 120 rpm or less and axial loading up to 50 N.

Low-cost air, noise, and light pollution measuring station with wireless communication and tinyML

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.

Measuring Heat Stress for Human Health in Cities: A Low-Cost Prototype Tested in a District of Valencia, Spain

Nowadays, the measurement of heat stress indices is of principal importance due to the escalating impact of global warming. As temperatures continue to rise, the well-being and health of individuals are increasingly at risk, which can lead to a detrimental effect on human performance and behavior. Hence, monitoring and assessing heat stress indices have become necessary for ensuring the safety and comfort of individuals. Thermal comfort indices, such as wet-bulb globe temperature (WBGT), Tropical Summer Index (TSI), and Predicted Heat Strain (PHS), as well as parameters like mean radiant temperature (MRT), are typically used for assessing and controlling heat stress conditions in working and urban environments. Therefore, measurement and monitoring of these parameters should be obtained for any environment in which people are constantly exposed. Modern cities collect and publish this relevant information following the Smart City concept. To monitor large cities, cost-effective solutions must be developed. This work presents the results of a Heat Stress Monitoring (HSM) system prototype network tested in the Benicalap-Ciutat Fallera district in Valencia, Spain. The scope of this work is to design, commission, and test a low-cost prototype that is able to measure heat stress indices. The Heat Stress Monitoring system comprises a central unit or receiver and several transmitters communicating via radiofrequency. The transmitter accurately measures wind speed, air temperature, relative humidity, atmospheric pressure, solar irradiation, and black globe temperature. The receiver has a 4G modem that sends the data to an SQL database in the cloud. The devices were tested over one year, showing that radio data transmission is reliable up to 700 m from the receiver. The system's power supply, composed of a Photovoltaic panel and Lithium-ion batteries, provided off-grid capabilities to the transmitter, with a tested backup autonomy of up to 36 days per charge. Then, indicators such as WBGT, TSI, and MRT were successfully estimated using the data collected by the devices. The material cost of a 12-point network is around EUR 2430 with a competitive price of EUR 190 per device.

Technical Solution for Monitoring Climatically Active Gases Using the Turbulent Pulsation Method

This article introduces a technical solution for investigating the movement of gases in the atmosphere through the turbulent pulsation method. A comprehensive control system was developed to measure and record the concentrations of carbon dioxide and methane, temperature, humidity, atmospheric air pressure, wind direction, and speed in the vertical plane. The selection and validation of sensor types and brands for each parameter, along with the system for data collection, registration, and device monitoring, were meticulously executed. The AHT21 + ENS160 sensor was chosen for temperature measurement, the BME680 was identified as the optimal sensor for humidity and atmospheric pressure control, Eu-M-CH4-OD was designated for methane gas analysis, and CM1107N for carbon dioxide measurements. Wind direction and speed are best measured with the SM5386V anemometer. The control system utilizes the Arduino controller, and software was developed for the multicomponent gas analyzer.

An open source 3D printed autosampler for capillary electrophoresis

BACKGROUND

In-house built capillary electrophoresis (CE) systems represent a significant share of laboratory instrumentation. In most of these instruments, sample injection is effected manually with low to moderate precision and requires skilled operators. Although few automated samplers have been previously developed, typically only one sample at a time can be injected. If a series of samples is to be analyzed, manual intervention is required. In the present work, we developed and constructed a fully automated, open source, CE autosampler, able to handle up to 14 different samples that can be used as a modular component of any in-house built CE instrument.

RESULTS

An inexpensive, 3D printed, open source, autosampler for CE was developed. The autosampler consists of two parts: an injection unit with carousel containing sample and electrolyte vials and a flushing unit, containing a miniature pressure/vacuum pump. The autosampler is operated by an Arduino Mega microcontroller and an Arduino code written in the laboratory. The injection sequence is entered through a keypad and LCD display by the user. The instrument can operate autonomously for extended periods of time. It was used for fully automated analysis and/or calibration of up to 14 samples with excellent injection repeatability reaching less than 2.7% RSD for peak areas. The sampler performance was tested with two independently built CE instruments, a CE system with contactless conductivity detection (C4D) and a CE system with laser induced fluorescence (LIF) detector.

SIGNIFICANCE AND NOVELTY

A novel, 3D printed, Arduino-based autosampler for CE was developed. The autosampler allows autonomous hydrodynamic injection of up to 14 different samples with fully programmable injection sequence, including capillary flushing and high voltage and data acquisition control. It provides the missing instrumental sampling setup for laboratory made CE instruments. It can be simply constructed based on the open-source blueprints in any laboratory and be a useful and time-saving add-on to any modular CE instrument.

SALAD: Syringe-based Arduino-operated Low-cost Antibody Dispenser

Lateral Flow Assays (LFA) have been one of the most widely adopted technologies in clinical diagnosis over recent years, especially during the COVID-19 pandemic, due to their feasibility, compactness, and rapid readout. However, the precise dispensing of antibodies-a key part of the fabrication process-requires costly line dispenser equipment, which poses a challenge to researchers with limited budgets. This study aims to resolve this key issue by introducing a Syringe-based Arduino-operated Low-cost Antibody Dispenser (SALAD). By utilizing a microneedle, stepper motor-driven syringe pump, and conveyor belt, SALAD can form micro-droplets to create an even band of antibodies. Our evaluation results showed comparable performance between SALAD and a commercialized model - Claremont ALFRD, with SALAD exceeding in affordability and feasibility. SALAD yielded an even signal, uniform bandwidth, and low background noise, yet optimization in the conveyor belt should be considered to enhance stability. With a low manufacturing cost ($200.61) compared to the commercialized models, our model is expected to provide an affordable approach for LFA researchers.

Enerduino-pro: Smart meter led probe using Arduino

Non-intrusive load monitoring of domestic appliances has received steady interest in the last twenty years, first because of interest from energy companies interested in usage statistics for power balancing and, more recently, in order to assist users in tuning their habits for reduced power consumption. This has increased the need for accurate and economic methods of power measurement that can be efficiently implemented on cheap and easy-to-install platforms. To this end, we present a cheap and efficient device based on Arduino to monitor the usage of domestic appliances in real-time: Enerduino-pro. The design uses low-cost easy-to-assemble open-source electronic components and consists of four main parts: an Arduino UNO microcontroller, one photoresistor to measure instantaneous power absorption plus one optional additional one to measure reactive power, a WiFi shield, and an LED (for debugging purposes only). We describe the device, complete with open software and hardware specifications, and different use cases with proof-of-concept solutions.

Development of an open-source soil water potential management system for horticultural applications, "Open_Irr"

Development of data driven, sensor-based irrigation has become possible with recent advancements in technology, yet due to a cost-barrier to entry, equitable adoption remains out of reach. Therefore, a simple microcontroller based LoRa platform, Open_Irr, was developed in the Arduino IDE to record resistive measures of soil matric potential and automate irrigation events. A single Open_Irr Node may connect with ≤ 16 Watermark® soil sensors and manage 4 irrigation groups, with Node sampling frequency, irrigation settings, and radio transmission settings being end-user adjustable without programming knowledge. Multiple Nodes may connect with a single Gateway to provide a scale-neutral solution for irrigation automation. A preliminary trial was conducted in spring 2022 to validate the performance of the Open_Irr platform in water deficit scenarios. Open_Irr recorded soil matric potentials in line with a commercial Watermark® sensor reader (n = 655); regression analysis yielded a coefficient of determination of 0.91 with Bland-Altman estimated fixed bias of ∼ 2 kPa. The Open_Irr platform was demonstrated to automate dripline irrigation events at several matric potential thresholds through connection to external solenoid valves. This demonstration directly conveys suitability for commercial and academic horticultural applications where automation of irrigation events or imposition of edaphic water stress is desired.

OptoPi: An open source flexible platform for the analysis of small animal behaviour

Behaviour is the ultimate output of neural circuit computations, and therefore its analysis is a cornerstone of neuroscience research. However, every animal and experimental paradigm requires different illumination conditions to capture and, in some cases, manipulate specific behavioural features. This means that researchers often develop, from scratch, their own solutions and experimental set-ups. Here, we present OptoPi, an open source, affordable (∼ £600), behavioural arena with accompanying multi-animal tracking software. The system features highly customisable and reproducible visible and infrared illumination and allows for optogenetic stimulation. OptoPi acquires images using a Raspberry Pi camera, features motorised LED-based illumination, Arduino control, as well as irradiance monitoring to fine-tune illumination conditions with real time feedback. Our open-source software (BioImageProcessing) can be used to simultaneously track multiple unmarked animals both in on-line and off-line modes. We demonstrate the functionality of OptoPi by recording and tracking under different illumination conditions the spontaneous behaviour of larval zebrafish as well as adult Drosophila flies and their first instar larvae, an experimental animal that due to its small size and transparency has classically been hard to track. Further, we showcase OptoPi's optogenetic capabilities through a series of experiments using transgenic Drosophila larvae.

Power tether for long duration multi-copter flight

The possibilities and promises of unmanned aerial vehicles (UAVs) for smart agriculture, 5G cellular integration, package delivery, and persistent surveillance are but a few of the active drivers for advancing UAV technology and systems. The UAVs' dependence on battery power represents a key limitation for practical deployment. As every remote pilot understands, even a modest research payload can limit a UAV's endurance to under 20 min. When horizontal maneuverability is not required, a power tether from the ground can provide near infinite flight time. Commercial tethers exist but can be prohibitively expensive or underpowered for research payloads. This paper describes the detailed design, construction, and operation of a relatively inexpensive open-source alternative. The designed and prototyped tether system delivers 1 kW of power at the tether base which, on an efficient UAV, corresponds to a payload of approximately 4.75 kg. We discuss the tradeoffs, design choices, best practices, and customization options, and provide empirical data for characterizing the power-payload relationship. The power and payload are scalable thanks to the modular design and the tools presented in this paper. The very low cost compared to commercial heavy-lift tether systems and the open-source design enable reproducibility and widespread use for supporting research, development, and emerging services/applications.

Automation of an atomic force microscope via Arduino

The Atomic Force Microscopy is a very versatile technique that allows to characterize surfaces by acquiring topographies with sub-nanometer resolution. This technique often overcomes the problems and capabilities of electron microscopy when characterizing few nanometers thin coatings over solid substrates. They are expensive, in the half million dollar range for standard units, and therefore it is often difficult to upgrade to new units with improved characteristics. One of these improvements, motorization and automation of the measurements is very interesting to sample different parts of a substrate in an unattended way. Here we report a low cost upgrade under 60 $ to a Dimension 3000 AFM based on a control unit using an Arduino Leonardo. It enables to acquire dozens or hundreds of images automatically by mimicking keyboard shortcuts and interfacing the AFM PCI card.

Low-cost and open-source neonatal incubator operated by an Arduino microcontroller

An unacceptably large number of newborn infants die in developing countries. For a considerable number of cases (particularly in preterm infants), morbidity and mortality can be reduced by simply maintaining newborn thermal homeostasis during the first weeks of life. Unfortunately, deaths caused by prematurity remain inordinately common in low- and middle-income countries (LMICs) due to reduced access to incubators in light of the high cost of commercially available devices. We herein describe and test a low-cost and easy-to-assemble neonatal incubator created with inexpensive materials readily available in LMICs. The incubator is based on an Arduino microcontroller. It maintains controlled temperature and relative humidity inside the main chamber while continuously measuring newborn weight progress. Moreover, the incubator has a tilting bed system and an additional independent safety temperature alarm. The performance of the novel low-cost neonatal incubator was evaluated and successfully passed the IEC 60601-2-19 standards. In the present work, we provide all the necessary technical information, which is distributed as open source. This will enable assembly of very low-cost (<250 €) and fully functional incubators in LMICs that should help reduce neonatal mortality.

Arduino based intra-cerebral microinjector device for neuroscience research

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.

Automated behavioral scoring: Do we even need humans?

The development of automated behavior scoring technology has been a tremendous boon to the study of social behavior. However, completely outsourcing behavioral analysis to a computer runs the risk of overlooking important nuances, and researchers risk distancing themselves from their very object of study. Here, I make the case that while automating analysis has been valuable, and overautomating analysis is risky, more effort should be spent automating the collection of behavioral data. Continuous automated behavioral observations conducted in situ have the promise to reduce confounding elements of social behavior research, such as handling stress, novel environments, one-time "snapshot" measures, and experimenter presence. Now that we have the capability to automatically process behavioral observations thanks to machine vision and machine learning, we would do well to leverage the same open-source ethos to increase the throughput of behavioral observation and collection. Fortunately, several such platforms have recently been developed. Repeated testing in the home environment will produce higher qualities and quantities of data, bringing us closer to realizing the ethological goals of studying animal behavior in a naturalistic context.

Autotitrator based on an Arduino Open Source Pump

Acid-base titration is a quantitative analysis that enables knowing the quantity of acidic or basic groups present in a solution sample. It consists in the addition of base or acid to the solution sample while monitoring the pH to reach a neutral pH. The titration can be automated and here we present a low cost Arduino based Open Source Pump (OSPump) modified to act as an automated titrator with an obsolete but reliable Metrohm 713 pH meter. Our device is 50 times less expensive than second hand units from the pH meter manufacturer and inherently open to customization. We present two validation cases of study, including the lipolysis of a vegetable olive oil in water emulsion, characterized by the OSPump Titrator.

Design and manufacture of a soft robot with dual-interaction in virtual reality

This paper examines the design and fabrication of a soft robot that can connect to a virtual reality environment. This study's primary objective is to utilize these technologies concurrently and demonstrate their applicability in various applications, particularly rehabilitation. Therefore, the process of designing and modeling the soft robot is carried out, and an applied model is created using a 3D printer and silicon material, which is then installed on gloves. Using Unity software, a virtual reality environment is created in which programs, commands, and Arduino processors control the movements of the soft robot, allowing the user to move and pick up an object in a real environment while wearing gloves, and to adjust the amount of pressure and angle of its motion based on the size of each virtual object. During the system evaluation phase, a delay in the performance and reaction time of the soft robot installed on the gloves is observed. This delay is reduced by modifying the programming structure, resulting in optimal system functionality. This capability is used to create proper mobility conditions and rehabilitation for the majority of patients with wrist injuries resulting from strokes and accidents, and it may be effective in accelerating patients' recoveries.

Setup of a 3D printed wind tunnel: Application for calibrating bi-directional velocity probes used in fire engineering applications

The research presented here focuses on the development of a 3D printed wind tunnel and the relevant equipment to be used for calibrating bi-directional velocity probes (BDVP). BDVP are equipment to be used for measuring velocity flow by determining the pressure difference of hot gases generated during fires. The manufactured probes require calibration to determine the calibration factor. The calibration is usually performed in wind tunnels which can be difficult to access due to costs, complexity and the various pieces of equipment required. The aim of the current study is to develop and assemble an inexpensive and easy-to-build bench-scale wind tunnel, with a data-logging system and fan control functionalities for fast and effective calibration of BDVP. A 3D printer with a PET-G filament is used, able to produce parts for the wind tunnel system which are durable and easy to handle and assemble. The system additionally includes an Arduino-based measuring unit with a hot-wire anemometer and temperature correction: Rev. P. This takes precise measurements; continuously logging data on a computer through a USB interface and capable of saving data on an SD card. This design provides users with parameters of velocity flow up to 4 m/s with standard deviation of 1.2 % and turbulence intensity of 1 %. The main advantages of this wind tunnel are its simplicity to build and portability.

APELLA: Open-Source, miniaturized All-in-One powered Lab-on-a-Disc platform

We present an unconventional approach to a common Lab-on-a-Disc (LoD) that combines a quadcopter propulsion system, a miniaturized 2.4 GHz Wi-Fi spy camera, 9.74 Watt Qi wireless power, and an Arduino into an open-source, miniaturized All-in-one powered lab-on-disc platform (APELLA). The quadcopter propulsion generates thrust to rotate (from 0.1 to 24.5 Hz) or shake the LoD device, while the spy camera enables a real-time (30 frames per second) and high definition (1280 × 720 pixels) visualization of microfluidic channels without requiring a bulky and heavy stroboscopic imaging setup. A mobile device can communicate with an Arduino microcontroller inside the APELLA through a Bluetooth interface for closed loop and sequential frequency control. In a proof-of-concept study, the APELLA achieved comparable mixing efficiency to a traditional spin stand and can capture rapid microfluidic events at low rotational frequencies (<5Hz). The APELLA is low-cost (c.a. 100 Euro), compact (15.6 × 15.6 × 10 cm³), lightweight (0.59 kg), portable (powered by a 5 V USB power bank), and energy efficient (uses < 6% power of the conventional system), making it ideal for field deployment, education, resource-limited labs.

Reliability Testing of a Low-Cost, Multi-Purpose Arduino-Based Data Logger Deployed in Several Applications Such as Outdoor Air Quality, Human Activity, Motion, and Exhaust Gas Monitoring

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.

Low-Cost Sensors Technologies for Monitoring Sustainability and Safety Issues in Mining Activities: Advances, Gaps, and Future Directions in the Digitalization for Smart Mining

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.

Design and Implementation of ESP32-Based IoT Devices

The Internet of Things (IoT) has become a transformative technology with great potential in various sectors, including home automation, industrial control, environmental monitoring, agriculture, wearables, health monitoring, and others. The growing presence of IoT devices stimulates schools and academic institutions to integrate IoT into the educational process, since IoT skills are in demand in the labor market. This paper presents educational IoT tools and technologies that simplify the design, implementation, and testing of IoT applications. The article presents the introductory IoT course that students perform initially and then presents some of the projects that they develop and implement on their own later in the project.

Development of a simple biogas analyzer module (BAM) for real-time biogas production monitoring

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 (168 h), (ii) complete mixing (168 h), and (iii) bio-stimulation with glycerol (192 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.

A simple computerized Arduino-based control system for insect rotary flight mills

Flight mills are widely used to investigate insect flight behavior. As technology advances, the means to build a computerized control system for a flight mill has become more accessible in terms of both price and availability of components. However, the specialized electronics and programming knowledge required to build such a system can still present an obstacle to interested parties. Here, we describe a simple and inexpensive flight mill control system that can be easily assembled and operated without specialized experience. The hardware and software components are built around an Arduino single-board microcontroller, which outputs raw data in the form of timestamped detections of rotations of the flight mill arm. This control system is suitable both as the basis for new flight mills and for replacing outdated computer controls on existing flight mills. Additionally, it can be used with any rotary flight mill design that uses an electronic sensor to count rotations.

Noninvasive Fuel Flow Monitoring System for Vented Fuel Oil Heaters

In this work, we present hardware and firmware design and preliminary testing results for a noninvasive device for measuring fuel oil consumption in fuel oil vented heaters. Fuel oil vented heaters are a popular space heating method in northern climates. Monitoring fuel consumption is useful to understanding residential daily and seasonal heating patterns and understanding the thermal characteristics of buildings. The device is a pump monitoring apparatus (PuMA) that employs a magnetoresistive sensor to monitor the activity of solenoid driven positive displacement pumps, which are commonly used in fuel oil vented heaters. PuMA accuracy for calculating fuel oil consumption was evaluated in a lab setting and found to vary up to 7% from the measured consumption value during testing. This variance will be explored more in field testing.

A Hardware-Based Configurable Algorithm for Eye Blink Signal Detection Using a Single-Channel BCI Headset

Eye blink artifacts in electroencephalographic (EEG) signals have been used in multiple applications as an effective method for human-computer interaction. Hence, an effective and low-cost blinking detection method would be an invaluable aid for the development of this technology. A configurable hardware algorithm, described using hardware description language, for eye blink detection based on EEG signals from a one-channel brain-computer interface (BCI) headset was developed and implemented, showing better performance in terms of effectiveness and detection time than manufacturer-provided software.

A Spectroscopic Reflectance-Based Low-Cost Thickness Measurement System for Thin Films: Development and Testing

The requirement for alternatives in roll-to-roll (R2R) processing to expand thin film inspection in wider substrates at lower costs and reduced dimensions, and the need to enable newer control feedback options for these types of processes, represents an opportunity to explore the applicability of newer reduced-size spectrometers sensors. This paper presents the hardware and software development of a novel low-cost spectroscopic reflectance system using two state-of-the-art sensors for thin film thickness measurements. The parameters to enable the thin film measurements using the proposed system are the light intensity for two LEDs, the microprocessor integration time for both sensors and the distance from the thin film standard to the device light channel slit for reflectance calculations. The proposed system can deliver better-fit errors compared with a HAL/DEUT light source using two methods: curve fitting and interference interval. By enabling the curve fitting method, the lowest root mean squared error (RMSE) obtained for the best combination of components was 0.022 and the lowest normalised mean squared error (MSE) was 0.054. The interference interval method showed an error of 0.09 when comparing the measured with the expected modelled value. The proof of concept in this research work enables the expansion of multi-sensor arrays for thin film thickness measurements and the potential application in moving environments.

The Open acidification Tank Controller: An open-source device for the control of pH and temperature in ocean acidification experiments

Ocean acidification is the process by which the increase in atmospheric CO₂ causes a corresponding increase in seawater CO₂ and results in lowering the seawater pH. While this process is likely to have substantial impacts on marine ecosystems, research into the effect of ocean acidification has been limited by the high costs of quality tools to perform ocean acidification treatments in the lab. The Open Acidification Tank Controller is designed to reduce the cost of ocean acidification research by providing a device that can monitor and control pH and temperature of aquaria as well as or better than commercially available research-grade devices, but for less than $250 USD per aquarium. The device is centered around an Arduino Mega 2560 and is assembled into a 3D printed housing. It monitors pH using a BNC glass pH probe and temperature using a three-wire waterproof PT100 temperature sensor. The Open Acidification Tank Controller also features web-based parameter reporting, and data storage to a micro-SD card. This device can hold aquarium pH and temperature at given setpoints, ramp between two values over a user-defined time period, or produce a sine-wave fluctuation in values.

Robust Arduino controlled spin coater using a novel and simple gravity chuck design

Spin coaters offer an invaluable method of thin film fabrication. Various implementations, both proprietary and open-source exist, offering vacuum and gravity samples chucks. These implementations vary in their reliability, ease-of-use, cost, and versatility. Here we present a novel easy-to-use open-source gravity-chuck type spin coater with minimal points of failure at a material cost of around 100 USD (1500 ZAR). The unique chuck design makes use of interchangeable brass plate sample masks, each specific to a sample size, these can be made with basic skills and common hand tools. In comparison, replacement chucks for commercial alternatives can cost as much as the entire spin coater we present. Open-source hardware such as this provides an example for individuals in the field on the design and development of hardware where reliability, cost, and flexibility are most important, as is the case for many institutions in developing countries.

Smart textile waste collection system - Dynamic route optimization with IoT

Increasing textile production is associated with an environmental burden which can be decreased with an improved recycling system by digitalization. The collection of textiles is done with so-called curbside bins. Sensor technologies support dynamic-informed decisions during route planning, helping predict waste accumulation in bins, which is often irregular and difficult to predict. Therefore, dynamic route-optimization decreases the costs of textile collection and its environmental load. The existing research on the optimization of waste collection is not based on real-world data and is not carried out in the context of textile waste. The lack of real-world data can be attributed to the limited availability of tools for long-term data collection. Consequently, a system for data collection with flexible, low-cost, and open-source tools is developed. The viability and reliability of such tools are tested in practice to collect real-world data. This research demonstrates how smart bins solution for textile waste collection can be linked to a dynamic route-optimization system to improve overall system performance. The developed Arduino-based low-cost sensors collected actual data in Finnish outdoor conditions for over twelve months. The viability of the smart waste collection system was complemented with a case study evaluating the collection cost of the conventional and dynamic scheme of discarded textiles. The results of this study show how a sensor-enhanced dynamic collection system reduced the cost 7.4% compared with the conventional one. We demonstrate a time efficiency of -7.3% and that a reduction of 10.2% in CO2 emissions is achievable only considering the presented case study.

An interactive and realistic phantom for cricothyroidotomy simulation of a patient with obesity through a reusable design using 3D-printing and Arduino

BACKGROUND AND OBJECTIVES

Proper airway management during emergencies can prevent serious complications. However, cricothyroidotomy is challenging in patients with obesity. Since this technique is not performed frequently but at a critical time, the opportunity for trainees is rare. Simulators for these procedures are also lacking. Therefore, we proposed a realistic and interactive cricothyroidotomy simulator.

METHODS

All anatomical structures were modeled based on computed tomography images of a patient with obesity. To mimic the feeling of incision during cricothyroidotomy, the incision site was modeled to distinguish between the skin and fat. To reinforce the educational purpose, capacitive touch sensors were attached to the artery, vein, and thyroid to generate audio feedback. The tensile strength of the silicone-cast skin was measured to verify the similarity of the mechanical properties between humans and our model. The fabrication and assembly accuracies of the phantom between the Standard Tessellation Language and the fabricated model were evaluated. Audio feedback through sensing the anatomy parts and utilization was evaluated.

RESULTS

The body, skull, clavicle, artery, vein, and thyroid were fabricated using fused deposition modeling (FDM) with polylactic acid. A skin mold was fabricated using FDM with thermoplastic polyurethane. A fat mold was fabricated using stereolithography apparatus (SLA) with a clear resin. The airway and tongue were fabricated using SLA with an elastic resin. The tensile strength of the skin using silicone with and without polyester mesh was 2.63 ± 0.68 and 2.46 ± 0.21 MPa. The measurement errors for fabricating and assembling parts of the phantom between the STL and the fabricated models were -0.08 ± 0.19 mm and 0.13 ± 0.64 mm. The measurement errors internal anatomy embodied surfaces in fat part were 0.41 ± 0.89 mm. Audio feedback was generated 100% in all the areas tested. The realism, understanding of clinical skills, and intention to retrain were 7.1, 8.8, and 8.3 average points.

CONCLUSIONS

Our simulator can provide a realistic simulation experience for trainees through a realistic feeling of incision and audio feedback, which can be used for actual clinical education.

Security Evaluation of Arduino Projects Developed by Hobbyist IoT Programmers

Arduino is an open-source electronics platform based on cheap hardware and the easy-to-use software Integrated Development Environment (IDE). Nowadays, because of its open-source nature and its simple and accessible user experience, Arduino is ubiquitous and used among hobbyist and novice programmers for Do It Yourself (DIY) projects, especially in the Internet of Things (IoT) domain. Unfortunately, such diffusion comes with a price. Many developers start working on this platform without having a deep knowledge of the leading security concepts in Information and Communication Technologies (ICT). Their applications, often publicly available on GitHub (or other code-sharing platforms), can be taken as examples by other developers or downloaded and used by non-expert users, spreading these issues in other projects. For these reasons, this paper aims at understanding the current landscape by analyzing a set of open-source DIY IoT projects and looking for potential security issues. Furthermore, the paper classifies those issues according to the proper security category. This study's results offer a deeper understanding of the security concerns in Arduino projects created by hobbyist programmers and the dangers that may be faced by those who use these projects.

WeatherChimes: An Open IoT Weather Station and Data Sonification System

Many people in the United States are disconnected from their environment: urban residents spend 90% of their time indoors inside confined climate-controlled spaces. In addition to being physically separated from the natural environment, much of human understanding of the world's environment is inferred from data collected by satellites orbiting 22,000 miles away. In contrast, in-situ environmental sensor systems are physically accessible, location specific, and essential for correcting and validating weather measurements. However, present options for in-situ systems are mostly limited to expensive, proprietary commercial data loggers with inflexible data access protocols. WeatherChimes is an open-source Arduino-programmable, low-cost hardware and software suite that enables near real-time access to in-situ environmental sensor data (including light, temperature, relative humidity, and soil moisture) anywhere with a WiFi internet connection. Scientists, educators, and artists alike can use this tool to obtain and interact with environmental data in new and innovative ways, as well as collaborate remotely. Transforming data collection processes of environmental sensors into Internet of Things (IoT) compatible formats opens new doors into accessing, understanding, and interacting with natural phenomena. WeatherChimes not only enables users to observe data online, but can also transform data into auditory signals and soundscapes through sonification processes or creative animations using newly-created computer applications. Lab and field tests have confirmed the sensor and online data logging performance of the system. We describe the application of WeatherChimes in an undergraduate Honors College classroom and STEM (Science, Technology, Engineering, and Math) education workshop series in Sitka Alaska, which was used to not only teach about environmental sensors, but to explore how different aspects of our environment are interrelated (e.g. temperature and humidity) through sonification.

Design and Implementation of a Low-Cost Chlorophyll Content Meter

Chlorophyll meters are portable devices used to assess and improve plants' nitrogen management and to help farmers in the determination of the health condition of plants through leaf greenness measurements. These optical electronic instruments can provide an assessment of chlorophyll content by measuring the light passing through a leaf or by measuring the light radiation reflected from its surface. However, independently of the main principle of operation and use (e.g., absorbance vs. reflectance measurements), commercial chlorophyll meters usually cost hundreds or even thousands of euros, making them inaccessible to growers and ordinary citizens who are interested in self-cultivation, farmers, crop researchers, and communities lacking resources in general. A low-cost chlorophyll meter based on light-to-voltage measurements of the remaining light after two LED light emissions through a leaf is designed, constructed, evaluated, and compared against two well-known commercial chlorophyll meters, the SPAD-502 and the atLeaf CHL Plus. Initial tests of the proposed device on lemon tree leaves and on young Brussels sprouts plant leaves revealed promising results compared to the commercial instruments. The coefficient of determination, R2, was estimated to be 0.9767 for the SPAD-502 and 0.9898 for the atLeaf-meter in lemon tree leaves samples compared to the proposed device, while for the Brussels sprouts plant, R2 was estimated to be 0.9506 and 0.9624, respectively. Further tests conducted as a preliminary evaluation of the proposed device are also presented.

Creation and Analysis of a Respiratory Sensor Using the Screen-Printing Method and the Arduino Platform

The aim of this paper is to present novel highly sensitive and stretchable strain sensors using data analysis to report on human live parameters using the Arduino embedded system as a proof of concept in developing new and innovative solutions for health care. The article introduces the solution of textile sensor origination with electrical resistance measurement using the mobile Arduino microcontroller in the designed/elaborated textile printed sensor. The textile sensor was developed by the screen printing technique based on the water dispersion of carbon nanotubes during printing composition. By stretching and squeezing the T-shirt during breathing, the electrical resistances of the printed sensor were changed. The measured resistance corresponded to the number of breaths of the person wearing the T-shirt. The microcontroller calculated the number of breaths as a number of electrical resistance peaks, which then led to monitoring human live parameters.

Fluorometer Control and Readout Using an Arduino Nano 33 BLE Sense Board

We describe the control and interfacing of a fluorometer designed for aerial drone-based measurements of chlorophyll-a using an Arduino Nano 33 BLE Sense board. This 64 MHz controller board provided suitable resolution and speed for analog-to-digital (ADC) conversion, processed data, handled communications via the Robot Operating System (ROS) and included a variety of built-in sensors that were used to monitor the fluorometer for vibration, acoustic noise, water leaks and overheating. The fluorometer was integrated into a small Uncrewed Aircraft System (sUAS) for automated water sampling through a Raspberry Pi master computer using the ROS. The average power consumption was 1.1 W. A signal standard deviation of 334 µV was achieved for the fluorescence blank measurement, mainly determined by the input noise equivalent power of the transimpedance amplifier. An ADC precision of 130 µV for 10 Hz chopped measurements was achieved for signals in the input range 0-600 mV.

Arduino Automated Microwave Oven for Tissue Decalcification

Decalcification of hard tissues such as bone and teeth is a complex process that requires using chemicals such as acids and chelating agents. Acids act faster than chelating agents, but they have a greater risk of damaging biological samples. Increasing the reaction speed of the chelating agent may solve this issue. There are several strategies to speed up this process, and using microwaves seems to be one of the most effective. However, lab-dedicated microwave ovens are expensive, and their purchase may seem unjustified. Therefore, a low-cost modification of a commercial microwave oven, consisting of an Arduino automation device, has been developed. The setup has proven reliable for continuous work, thanks to implementing an electronic safety circuit. In addition, it may reduce the decalcification time using a chelating agent, achieving optimal results regarding tissue preservation and quality of histological sections.

Student responses to creative coding in biomedical science education

Biomedical science students need to learn to code. Graduates face a future where they will be better prepared for research higher degrees and the workforce if they can code. Embedding coding in a biomedical curriculum comes with challenges. First, biomedical science students often experience anxiety learning quantitative and computational thinking skills and second biomedical faculty often lack expertise required to teach coding. In this study, we describe a creative coding approach to building coding skills in students using the packages of Processing and Arduino. Biomedical science students were taught by an interdisciplinary faculty team from Medicine and Health, Science and Architecture, Design and Planning. We describe quantitative and qualitative responses of students to this approach. Cluster analysis revealed a diversity of student responses, with a large majority of students who supported creative coding in the curriculum, a smaller but vocal cluster, who did not support creative coding because either the exercises were not sufficiently challenging or were too challenging and believed coding should not be in a Biomedical Science curriculum. We describe how two creative coding platforms, Processing and Arduino, embedded and used to visualize human physiological data, and provide responses to students, including those minority of students, who are opposed to coding in the curriculum This study found a variety of students responses in a final year capstone course of an undergraduate Biomedical Science degree where future pathways for students are either in research higher degrees or to the workforce with a future which will be increasingly data driven.