Open Hardware Research Articles

Machine Learning Algorithms: An Experimental Evaluation for Decision Support Systems

Decision support systems with machine learning can help organizations improve operations and lower costs with more precision and efficiency. This work presents a review of state-of-the-art machine learning algorithms for binary classification and makes a comparison of the related metrics between them with their application to a public diabetes and human resource datasets. The two mainly used categories that allow the learning process without requiring explicit programming are supervised and unsupervised learning. For that, we use Scikit-learn, the free software machine learning library for Python language. The best-performing algorithm was Random Forest for supervised learning, while in unsupervised clustering techniques, Balanced Iterative Reducing and Clustering Using Hierarchies and Spectral Clustering algorithms presented the best results. The experimental evaluation shows that the application of unsupervised clustering algorithms does not translate into better results than with supervised algorithms. However, the application of unsupervised clustering algorithms, as the preprocessing of the supervised techniques, can translate into a boost of performance.

Modular Battery Emulator for Development and Functional Testing of Battery Management Systems: The Cell Emulator

Battery Management Systems are fundamental components of the present battery generation. The development and characterization phases of a BMS often require an emulator of the battery cells with which the Battery Management System functions can be assessed with no safety risks as it would instead happen using a real battery. This work describes the design and characterization of a modular cell emulator circuit to be used as platform for the Hardware-in-the-loop test of a Battery Management System. The design constraints and choices are first described. Then, the experimental characterization of the cell emulator is shown and discussed. The proposed circuit shows a voltage resolution of 76 μV, an accuracy of 2.17 mV, and a setting time of 340 μs. Its cost is around 40 USD. The circuit results to be a very good trade-off between performance and cost. The Project is available to the scientific community as open hardware platform freely downloadable. It could be useful to small-size laboratories to self-produce a low-cost battery emulator with good performance for the development and the functional test of custom Battery Management Systems.

An Open-Hardware Insemination Device for Small-Bodied Live-Bearing Fishes to Support Development and Use of Germplasm Repositories.

Simple SummarySmall-bodied live-bearing fishes attract broad attention because of their importance in biomedical research and critical conservation status in natural habitats. Artificial insemination is an essential approach used to establish hybrid lines and for the operation of sperm repositories. The existing mouth-pipetting technique for artificial insemination of live-bearing fishes has not been substantially upgraded since the first implementation in the 1950s. This work developed a low-cost standardized artificial inseminator device (SAID) as open hardware to address issues routinely encountered in insemination by mouth-pipetting, including lack of reproducibility among different users, difficulty in training, and large, unreportable variation in sample volume and pressure during insemination. Community-level enhancements of the SAID prototype could enable standardized insemination with minimal training and facilitate the participation of research communities in the use of cryopreserved genetic resources.Small-bodied live-bearing fishes attract broad attention because of their importance in biomedical research and critical conservation status in natural habitats. Artificial insemination is an essential process to establish hybrid lines and for the operation of sperm repositories. The existing mouth-pipetting technique for artificial insemination of live-bearing fishes has not been substantially upgraded since the first implementation in the 1950s. The goal of this work was to develop a standardized artificial inseminator device (SAID) to address issues routinely encountered in insemination by mouth-pipetting, including lack of reproducibility among different users, difficulty in training, and large unreportable variation in sample volume and pressure during insemination. Prototypes of the SAID were designed as relatively inexpensive (<USD 80) open hardware based on commercially available and 3-D printed components to enable broad community access. A linear actuator was used to accurately control the position of a piston for fluid transfer with a standard deviation of <0.1 mm over a 4 mm range of travel. The volume of sample transfer was precisely controlled with a linear relationship (r2 > 0.99) between the piston position and volume. Pressure generation from eight mouth-pipetting operators and SAID prototypes were assessed by pressure sensors. The pressure control by SAID was superior to that produced by mouth-pipetting, yielding lower pressures (31–483 Pa) and smaller variations (standard deviation <11 Pa). These pressures were sufficient to deliver 1–5 μL of fluid into female reproductive tracts yet low enough to avoid physical injury to fish. Community-level enhancements of the SAID prototype could enable standardized insemination with minimal training and facilitate the participation of research communities in the use of cryopreserved genetic resources.

Determination of tobramycin in eye drops with an open-source hardware ion mobility spectrometer

The analysis of tobramycin was demonstrated successfully as an example for electrospray ionization on an open-source hardware ion mobility spectrometer. This instrument was assembled inexpensively in-house, and required only very few purpose-made components. The quantitative determination of tobramycin required 20 s for a reading. The calibration curve for the range from 50 to 200 μM was found to be linear with a correlation coefficient of r = 0.9994. A good reproducibility was obtained (3% relative standard deviation) and the limit of detection was determined as 8 μM. As the concentration of the active ingredient in the eye drops (ophthalmic solutions) is too high for the sensitivity of the instrument, the samples had to be diluted appropriately.Graphical abstract

Design of a scanning acoustic and photoacoustic microscopy system using open-source hardware and software components

We have designed and started construction of an instrument that will be able to operate as both a scanning acoustic microscope and photoacoustic microscope. To keep costs down, we are using open-source hardware and software components wherever possible. The system is designed to scan specimens that are approximately 2 cm × 2 cm in lateral dimensions with lateral steps of 1 micron or less. When operating as a scanning acoustic microscope, the specimen will be water-coupled to a high-frequency ultrasound transducer operating in pulse-echo mode. When operating as a photoacoustic microscope, short light pulses infrared laser diode located under the specimen will generate ultrasound pulses thermoelastically, which will then be received by a confocal high-frequency transducer. In both cases, the specimen will be raster-scanned under the transducer by a moving stage. The mechanical scanning system was designed and built using a spring-loaded microscope stage, micrometers, stepper motors, a shield board used for 3D printers, an Arduino Mega microcontroller, and a Raspberry Pi 4 microcomputer. A graphical user interface has been written in Python using Tkinter to send the motion control commands to the stage. Future work will include incorporation of the laser and transducer control systems.

Development of a vision based pose estimation system for robotic machining and improving its accuracy using LSTM neural networks and sparse regression

In this work, an eye to hand camera based pose estimation system is developed for robotic machining and the accuracy of the estimated pose is improved using two different approaches, namely Long Short Term Memory (LSTM) neural networks and sparse regression. To improve the accuracy obtained from the Levenberg–Marquardt (LM) based pose estimation algorithm, two distinct supervised data driven approaches are proposed which can take the dynamics into account during robotic machining through utilization of the torque information available from the sensors at each joint. The first one is a LSTM neural network and the second one is a method based on sparse regression. The proposed methods are validated by an experimental study performed using a KUKA KR240 R2900 ultra robot while machining a NAS 979 part, during which the orientation of the cutting tool was fixed, and free form milling, during which the orientation of the cutting tool continuously changed. A target object to be tracked by the camera was designed with fiducial markers to guarantee trackability with ±90°in all directions. The design of these fiducial markers guarantee the detection of at least two distinct non-parallel markers from any view, thus preventing pose estimation ambiguities. Moreover, in order to reduce the errors due to the construction of the camera target and placement of the markers on it, this work proposes a method for optimizing the positions of the corners of the fiducial markers in the object frame using a laser tracker. The proposed methods were compared with an Extended Kalman Filter (EKF) and the experimental results show that both of the proposed approaches significantly improve the pose estimation accuracy and precision of the vision based system during robotic machining while proving much more effective than the EKF approach. The attainable absolute position errors were 5.47 mm, 2.9 mm and 2.05 mm on average for NAS 979 machining and 5.35 mm, 2.17 mm and 0.86 mm on average for free form machining when using the EKF, the proposed LSTM network and the proposed sparse regression approaches, respectively. Moreover, the proposed sparse regression based method provides parsimonious models and better results when compared with the proposed LSTM based approach.

A feminist hacklab’s resilience towards anti-democratic forces

Makerspaces and hacklabs are believed to encourage a positive attitude towards gaining computer skills. Within these communities for peer production, citizens can apply cutting-edge technologies in DIY projects. In recent decades, mushrooming makerspaces and hacklabs were embraced by the tech industry and governments alike. Feminist makerspaces and hacklabs, however, as they are centred around a queer feminist agenda, have raised eyebrows. In order to foster diversity in tech development, they create safer spaces for self-expression. Here, feminist lay(wo)men* (To emphasise that the category ‘Woman’ is constructed and that more people than only those who identify as women are being included, one uses the sign * after the term ‘women’ ), makers, designers, artists and tinkerers experiment with open-source hardware and software. Art and design projects emerging from feminist hacklabs focus on issues of representation and democratic participation in digital media, as well as on ways of reclaiming one’s own body. This article tries to unpack how, after an exhibition on sexual health norms, a feminist hacklab was attacked by local right-wing and conservative politicians. The attack resulted in the defunding of the feminist hacklab. But it also started a transformation process within the collective, as members became aware of critical interferences of diffracting marginalisations. The crisis triggered a discussion on how each member was threatened to very different degrees; for example, there was more at stake for members depending on their legal status in the country. The right-wing and conservative campaign against the feminist hacklab damaged the initiative, but at the same time it pushed the collective to generate increased vehemence and resilience.

CaptuRING: A do‐it‐yourself tool for wood sample digitization

Abstract Standard procedures to obtain high‐quality images of wood samples have become a bottleneck in the digitization of dendrochronology. Digitization is currently dominated by flatbed scanners, but the use of these devices is limited by sample length and surface flatness. Although several solutions based on digital photography have been published, they lack effective digitization processes or are too expensive to be widely adopted. Free open‐source software and hardware has emerged as an alternative to create research tools that combine reduced costs with high reliability. Here we present CaptuRING, an open‐source tool for wood sample digitization combining a do‐it‐yourself hardware based on Arduino® with a DSLR camera and a free open‐source software with an easy‐to‐use graphical user interface. We compared CaptuRing with image acquisition from a standard flatbed scanner Epson® V750PRO. CaptuRING outperforms scanner image resolution and sharpness, while it removes sample size limitations. Moreover, CaptuRing performs this task in less than half of the time needed by Epson® V750PRO flatbed scanner. CaptuRING emerges as a reliable and low‐cost tool to capture high‐resolution images of wood samples boosting current digitization processes. The combination of free open software and hardware empowers dendrochronology to advance in wood sample digitization.

Continuous fiber extruder for desktop 3D printers toward long fiber embedded hydrogel 3D printing

Recent advances in Freeform Reversible Embedding of Suspended Hydrogels (FRESH), a technique that is compatible with most open-source desktop 3D printers, has enabled the fabrication of complex 3D structures using a wide range of natural and synthetic hydrogels, whose mechanical properties can be modified by embedding long fibers into printed hydrogels. However, fiber extruders dedicated for this application are not commercially available or previously reported. To address this, we have designed a continuous fiber extruder (CFE) that is compatible with low-cost, open-source desktop 3D printers, and demonstrated its performance using a Flashforge Creator-pro printer with a Replistruder-2.0 print-head. Key characteristics of the CFE include: (1) it is affordable, accessible and user-friendly to the 3D printing community due to its low fabrication cost and compatibility with open-source hardware and software, (2) it can embed user-defined 2D and 3D features using long fibers into different types of hydrogels, (3) it works with fibers of different mechanical properties and sizes, (4) it can modify mechanical properties of FRESH printed hydrogels via long fiber embedding.

Scalable IoT Architecture for Monitoring IEQ Conditions in Public and Private Buildings

This paper presents a scalable IoT architecture based on the edge–fog–cloud paradigm for monitoring the Indoor Environmental Quality (IEQ) parameters in public buildings. Nowadays, IEQ monitoring systems are becoming important for several reasons: (1) to ensure that temperature and humidity conditions are adequate, improving the comfort and productivity of the occupants; (2) to introduce actions to reduce energy consumption, contributing to achieving the Sustainable Development Goals (SDG); and (3) to guarantee the quality of the air—a key concern due to the COVID-19 worldwide pandemic. Two kinds of nodes compose the proposed architecture; these are the so-called: (1) smart IEQ sensor nodes, responsible for acquiring indoor environmental measures locally, and (2) the IEQ concentrators, responsible for collecting the data from smart sensor nodes distributed along the facilities. The IEQ concentrators are also responsible for configuring the acquisition system locally, logging the acquired local data, analyzing the information, and connecting to cloud applications. The presented architecture has been designed using low-cost open-source hardware and software—specifically, single board computers and microcontrollers such as Raspberry Pis and Arduino boards. WiFi and TCP/IP communication technologies were selected, since they are typically available in corporative buildings, benefiting from already available communication infrastructures. The application layer was implemented with MQTT. A prototype was built and deployed at the Faculty of Engineering of Vitoria-Gasteiz, University of the Basque Country (UPV/EHU), using the existing network infrastructure. This prototype allowed for collecting data within different academic scenarios. Finally, a smart sensor node was designed including low-cost sensors to measure temperature, humidity, eCO2, and VOC.

Pet Food Dosing and Dispenser Design Based on Free Technologies

This paper merges mechatronics, programming and free hardware and software technologies tools. The design consists of a food container connected to a plate with a cover; allowing food to be eaten by the pet and can be dispensed according to user programmed parameters, which are based on age, race and weight of the animal. It consists of a weight sensor in the base plate, indicating when it is reached the required amount, cutting food supplies and in the next appropriate time places only the missing food on the plate. It also has a sensor in the food container for measuring the percentage of existing food and sending a text message to the phone numbers of registered users, as it reaches 20% of total capacity.

Network Optimization Using Learning and Distributed Intelligence through Cognition Based Networks

Network optimisation can be achieved with the incorporation of sophisticated technology and advanced algorithms to achieve efficiency and scalability. Optimisation of the entire network with learning and distributed intelligence through cognitive-based networks is investigated in the paper. A cognition-based network enhances the capacity for network optimization and designing processes to offer better services to the customers appropriately. With the rapid growth of users, the network distribution channels are required to adopt cognitive-based architecture for optimised capacity, capable of providing secure data transmission to a wider user base. 5G network construction with SDN and NFV, along with AI and machine learning algorithms are considered to be the most efficient cognitive-based approach for network optimisation. The application of NFV helps to develop network functions in operating open hardware platforms, reducing Capex, and OpenX and improving network design efficiently. On the other hand, SDN is capable of separating the control plane and the data plan with a defined interface for programming, providing an entire view of the network with centralised control.

Low cost climate station for smart agriculture applications with photovoltaic energy and wireless communication

Measuring climatic conditions is a fundamental task for a wide array of scientific and practical fields. Weather variables change depending on position and time, especially in tropical zones without seasons. Additionally, the increasing development of precision or smart agriculture makes it necessary to improve the measurement systems while widely distributing them at the location of crops. For these reasons, in this work, the design, construction and fabrication of an adaptable autonomous solar-powered climatic station with wireless 3G or WiFi communication is presented. The station measures relative humidity, temperature, atmospheric pressure, precipitation, wind speed, and light radiation. In addition, the system monitors the charge state of the main battery and the energy generated by the photovoltaic module to act as a reference cell for solar energy generation capability and agrivoltaic potential in the installation area. The station can be remotely controlled and reconfigured. The collected data from all sensors can be uploaded to the cloud in real-time. This initiative aims at enhancing the development of free and open source hardware that can be used by the agricultural sector and that allows professionals in the area to improve harvest yield and production conditions.

Improving Hardware Security on Talos II Architecture Through Boot Image Encryption

The OpenPOWER Foundation is an organization that promotes open-source high-performance hardware like the POWER9. OpenBMC is an OpenPower project that strives to produce an open-source firmware stack for Baseboard Management Controllers (BMCs). If hardware falls into the hands of competitors or bad actors, reverse engineering methods can be used to leak or manipulate sensitive information from the boot sequence. This represents a security concern because the root of trust can be invalidated. For example, since the Initial Program Load (IPL) data is frequently not encrypted and is sent over the Low Pin Count (LPC) bus, it is possible to intercept and conduct man-in-the-middle attacks to modify the boot process. The boot image flash chip could also be removed from the Talos II motherboard and examined by competing server architecture manufacturers to reveal detailed boot information. Firmware that developers deem to contain sensitive code or perform innovative operations needs to be protected before being flashed onto the boot image chip. This paper demonstrates a method to encrypt sections of the boot image by encrypting a section of the image before flashing it onto the Talos II. The encrypted image will be decrypted during the boot sequence in the Level 3 cache of the POWER9, proving that it is possible to prevent adversaries from interfering with the IPL flow or obtaining details on firmware from the flash chip. This paper presents a novel method to improve the security of the boot image on Talos II architecture by encrypting the boot firmware image and decrypting it during the boot process. The proof of concept was executed on a Raptor Engineering Talos II system running a POWER9 processor with OpenBMC firmware on the ASPEED AST2500 BMC. This research claims that this unique method increases boot time security through firmware without altering hardware.

Comparison of Arduino Nano and Due processors for time-based data acquisition for low-cost mobile radiation detection system

Arduino is an open-source hardware and software platform that consists of a single-board microcontroller (MCU). Arduino offers low-cost and low-power operation, which allows the design of a mobile battery-operated device and offers easy programming with a wide range of compatible sensors. Hence, Arduino has recently been widely used as an inexpensive solution to build educational and evaluation tools. Here, we combined Arduino processors with custom-developed time-based signal readout electronics for a low-cost mobile radiation detection system; the system utilizes a time-over-threshold technique that provides compact electronics. Arduino processors were used for chip configuration, serial communication, and real-time data acquisition. In this study, we tested two commercial Arduino processors, Nano and Due, in various signal environments and compared their performances. The developed Arduino-based data acquisition system was combined with a 48 × 48 × 20 mm3 GAGG:Ce (Gd3Al2Ga3O12:Ce) scintillation crystal and an 8 × 8 array of 6 × 6 mm2 SiPM. The developed low-cost mobile gamma detection system achieved 9.35% energy resolution at 662 keV and was able to acquire events up to 600 Hz using an Arduino Nano.

Generation of scallop free machined surfaces in CFRPs with minimum waviness and defects using eccentric sleeve grinding

Defect free machining of Fibre Reinforced Polymer (FRP) Composites, crossing the challenges posed by anisotropic non-homogenous fibre-matrix system, is one of the important material processing requirements with a wide scope in industrial applications. Eccentric Sleeve Grinding (ESG) projected in this paper is a unique strategy with progressive-intermittent cutting scheme for achieving minimal damage machined surfaces on FRPs. Progressively varying depth of engagement for active abrasive grains in the cutting zone with an intermittent and periodically repeating cutting pattern achieved through precisely controlled eccentric rotation of grinding wheel is the key highlight of ESG. Through this step-by-step cutting methodology, significant reduction in grinding force has been achieved on Carbon Fibre Reinforced Polymer (CFRP) composites under varying cutting conditions. Coordination of work feed with grinding wheel rotation is an important aspect to be considered for the minimization of scallops on FRP surfaces during ESG. A detailed theoretical model to guide the selection of work feed for a scallop free surface with reduced waviness, roughness and defects, with a demonstration of the associated graphical user interface, has been introduced in this paper. Experiments reported to demonstrate the methodology and capability of intermittent-progressive cutting scheme may provide useful guidance for the adaptation of ESG in similar FRP machining applications. Studies organized in this paper provides an in-depth practical insight towards a futuristic minimal damage grinding strategy for fibre reinforced polymer composites in critical functional applications.

A flexible and low-cost open-source IPMC mezzanine for ATCA boards based on OpenIPMC

This work presents the development of an Intelligent Platform Management Controller mezzanine in a Mini DIMM form factor for use in electronic boards compliant to the PICMG Advanced Telecommunication Computing Architecture (ATCA) standard. The module is based on an STMicroelectronics STM32H745 microcontroller running the OpenIPMC open-source software. The mezzanine has been successfully tested on a variety of ATCA boards being proposed for the upgrade of the experiments at the HL-LHC, with its design and firmware being distributed under open-source hardware license.

Improving the Quantification of Colorimetric Signals in Paper-Based Immunosensors with an Open-Source Reader.

Measuring the colorimetric signals produced by the biospecific accumulation of colorimetric probes and recording the results is a key feature for next-generation paper-based rapid tests. Manual processing of these tests is time-consuming and prone to a loss of accuracy when interpreting faint and patchy signals. Proprietary, closed-source readers and software companies offering automated smartphone-based assay readings have both been criticized for interoperability issues. Here, we introduce a minimal reader prototype composed of open-source hardware and open-source software that has the benefits of automatic assay quantification while avoiding the interoperability issues associated with closed-source readers. An image-processing algorithm was developed to automate the selection of an optimal region of interest and measure the average pixel intensity. When used to quantify signals produced by lateral flow immunoassays for detecting antibodies against SARS-CoV-2, results obtained with the proposed algorithm were comparable to those obtained with a manual method but with the advantage of improving the precision and accuracy when quantifying small spots or faint and patchy signals.

OpenMetBuoy-v2021: An Easy-to-Build, Affordable, Customizable, Open-Source Instrument for Oceanographic Measurements of Drift and Waves in Sea Ice and the Open Ocean

There is a wide consensus within the polar science, meteorology, and oceanography communities that more in situ observations of the ocean, atmosphere, and sea ice are required to further improve operational forecasting model skills. Traditionally, the volume of such measurements has been limited by the high cost of commercially available instruments. An increasingly attractive solution to this cost issue is to use instruments produced in-house from open-source hardware, firmware, and postprocessing building blocks. In the present work, we release the next iteration of our open-source drifter and wave-monitoring instrument, which follows these solution aspects. The new design is significantly less expensive (typically by a factor of 5 compared with our previous, already cost-effective instrument), much easier to build and assemble for people without specific microelectronics and programming competence, more easily extendable and customizable, and two orders of magnitude more power-efficient (to the point where solar panels are no longer needed even for long-term deployments). Improving performance and reducing noise levels and costs compared with our previous generation of instruments is possible in large part thanks to progress from the electronics component industry. As a result, we believe that this will allow scientists in geosciences to increase by an order of magnitude the amount of in situ data they can collect under a constant instrumentation budget. In the following, we offer (1) a detailed overview of our hardware and software solution, (2) in situ validation and benchmarking of our instrument, (3) a fully open-source release of both hardware and software blueprints. We hope that this work, and the associated open-source release, will be a milestone that will allow our scientific fields to transition towards open-source, community-driven instrumentation. We believe that this could have a considerable impact on many fields by making in situ instrumentation at least an order of magnitude less expensive and more customizable than it has been for the last 50 years, marking the start of a new paradigm in oceanography and polar science, where instrumentation is an inexpensive commodity and in situ data are easier and less expensive to collect.

Automation of Hydroponics System using Open-source Hardware and Software with Remote Monitoring and Control

This study aimed to develop and install an open-source hardware and application software for the automation of different actuators and sensors in the hydroponics system established at ARDC-Wengkhar. A prototype automation system was developed using Raspberry Pi 3 installed with open-source hydroponics application software called Mycodo which acted as a main computing hub for the automation. The automation features included the schedule or timer-based switching of different pumps, conditional switching of the ventilation fans based on temperature/humidity, alarm and notifications via email when certain parameters exceed the normal value, data logging and remote access to the system. The prototype was installed in the existing hydroponics structures containing nutrient film technique, deep water culture and vertical tower. The prototype was found efficient, reliable, useful, affordable and expandable as it offers more flexibility and advanced features for any automated hydroponics system.