Open Source Hardware Platform Research Articles

An Open Approach to Autonomous Vehicles

The evolution of autonomous vehicle (AV) technology is rapidly transforming the automotive industry, driving innovations in safety, efficiency, and user experience. This research paper explores the impact of open approaches on the development and deployment of autonomous vehicles. By leveraging open-source software and hardware platforms, such as OpenPilot and Apollo, the study highlights how collaborative, transparent methodologies foster innovation and accelerate technological advancements. The paper examines the technical, regulatory, and ethical challenges associated with open-source AV development, including data management, sensor integration, and compliance with safety standards. Through a comprehensive analysis of successful open-source projects and emerging trends, the research identifies the benefits of open approaches in promoting cross-disciplinary collaboration and addressing complex challenges. The findings underscore the potential of open-source solutions to drive the future of autonomous vehicle technology, offering insights into their role in shaping industry standards and regulatory frameworks

Research on Intelligent Speech Interaction System Based on Residual Neural Network and Baidu Speech Platform

To address the dual needs of convenience and security in human-computer interaction under the context of the Internet of Things (IoT) and Artificial Intelligence (AI), a system has been designed based on Raspberry Pi4B, which integrates voice recognition, speech synthesis, and speaker verification functions. Voice recognition and speech synthesis capabilities leverage Baidu's speech platform technology, while speaker verification employs a Residual Neural Network (ResNet34) model based on the PyTorch framework. With a focus on enhancing the user experience, the system incorporates the snowboy offline voice wake-up engine for voice interaction and utilizes Python's Tkinter library to implement a customized graphical user interface (GUI). After strict testing and verification, this system not only efficiently and friendly meets various voice interaction scenarios in the field of Internet of Things technology, but also utilizes voiceprint recognition technology to ensure the application security of the system. It also provides research value for the innovation of open-source hardware platforms in the field of artificial intelligence.

Iot-based flood monitoring and early warning system for proactive security measures

The project introduces an IoT-based flood monitoring system using Arduino Uno, soil moisture sensor, LCD, buzzer, Wi-Fi module (e.g., ESP8266), and ThingSpeak cloud platform. It monitors soil moisture levels, issuing alerts when a predefined threshold indicative of potential flooding is reached. The soil moisture sensor measures moisture content and is displayed on an LCD screen for real-time monitoring. A buzzer provides audible alerts for high moisture levels. A Wi-Fi module enables wireless communication, transmitting data to the ThingSpeak cloud platform for centralized storage and analysis. Users access real-time and historical data through ThingSpeak's interface. The system configures the Wi-Fi module to connect to a network, securely sending data using a unique API key. ThingSpeak enables visualization, analysis, and alert setup based on soil moisture levels, offering a comprehensive flood monitoring solution. This cost-effective system, integrating open-source hardware and cloud platforms, enhances accessibility and deployment ease and is suitable for various environmental monitoring applications.

New digital low-level RF controls based on the Red Pitaya STEMlab for the TLS Linac system

The Linac system at Taiwan Light Source (TLS) has been in operation for almost a quarter of a century and requires upgrades to improve its reliability. To achieve this, some components of the control system have been replaced with new digital low-level RF control units that use emerging technologies. A new unit is based on the open-source hardware platform which is named “Red Pitaya STEMlab” and offers a compact size and low power consumption. The unit features DAC (Digital-to-Analog Converter) blocks for downloading arbitrary waveforms with external trigger play and ADC (Analog-to-Digital Converter) blocks for waveform acquisition, enabling the development of real-time diagnostic toolkits. The new low-level RF control interface has been fully integrated into the existing EPICS software framework for system integration. The new digital low-level RF control system supports I/Q (in-phase/quadra-ture-phase) data with online amplitude and phase set-tings, and a waveform digitizer for inspecting low-level RF signals from the klystron modulator. Specific graphical applications have been designed and integrated into the existing operation interfaces. The system has been successfully achieved during routine operations. This paper describes the details of these efforts.

Resistor and Capacitor Time Constant Measuring Instrument Using Arduino UNO

The most interesting problem to be discussed in electrical physics is one-way electric circuits. In this work, the researchers constructed an experimental setup for determining the time constant of DC resistors and capacitors using the open-source Arduino UNO hardware platform. Arduino UNO was a signal generator for data collection systems and a simple signal visualization instrument. Experiments were carried out using an analog oscilloscope combined with theoretical calculations. The results show that, on a spreadsheet, the data processing and fitting of the curves for the six Resistor and Capacitor test sets yielded values determined by the component tolerances. The researchers believe that the design of this equipment and software demonstrates the recommended suitability, making it flexible for use in teaching and learning in laboratory contexts.

A technology transfer journey to a model-driven access control system

In the model-driven security domain, access control systems provide an application for handling access of persons through controlled gates. A gate, such as a door, can have a lock mechanism for securing the area from unauthorized access. Most commercial solutions for access control management offer pre-packaged software systems where customization of the authorization logic is either not allowed or subject to payment. Moreover, cross-platform development is a barrier for solution providers due to the high cost of development and maintenance that it implies. To overcome these limitations and further optimize the entire access control systems development process, we propose a model-driven approach that supports automatic code generation to enable communication between an IoT infrastructure and platforms for Facility Access Management. Specifically, the approach combines the benefits of Near-Field Communication (NFC) and Tinkerforge (i.e., an open-source hardware platform) with model-driven techniques. This allows the approach to exploit both behavioral and structural models for the modeling and the consequent code generation of part of the authorization mechanism, thus providing complete coverage of the code generated for the whole system. We implemented and evaluated our approach in a real-world case study within the premises of a fitness center with an IoT infrastructure consisting of several heterogeneous sensors by showing its practical applicability. Experimental results demonstrate the effectiveness of our approach in supporting abstraction and automation concerning traditional code-centric development through code generation features. Consequently, our approach makes the whole development process less time-consuming and error-prone, thus reducing the system’s time to market.

Low-Cost Photoreactor to Monitor Wastewater Pollutant Decomposition.

Actually, the quality of water is one of the most important indicators of the human environmental impact, the control of which is crucial to avoiding irreversible damage in the future. Nowadays, in parallel to the growth of the chemical industry, new chemical compounds have been developed, such as dyes and medicines. The increasing use of these products has led to the appearance of recalcitrant pollutants in industrial wastewater, and even in the drinking water circuit of our populations. The current work presents a photoreactor prototype that allows the performance of experiments for the decomposition of coloured pollutants using photocatalysis at the laboratory scale. The design of this device included the study of the photometric technique for light emission and the development of a software that allows monitoring the dye degradation process. Open-source hardware platforms, such as Arduino, were used for the monitoring system, which have the advantages of being low-cost platforms. A software application that manages the communication of the reactor with the computer and graphically displays the data read by the sensor was also developed. The results obtained demonstrated that this device can accelerate the photodegradation reaction in addition to monitoring the changes throughout the process.

Ethoscopy and ethoscope-lab: a framework for behavioural analysis to lower entrance barrier and aid reproducibility.

High-throughput analysis of behaviour is a pivotal instrument in modern neuroscience, allowing researchers to combine modern genetics breakthrough to unbiased, objective, reproducible experimental approaches. To this extent, we recently created an open-source hardware platform (ethoscope; Geissmann Q, Garcia Rodriguez L, Beckwith EJ et al. Rethomics: an R framework to analyse high-throughput behavioural data. PLoS One 2019;14:e0209331) that allows for inexpensive, accessible, high-throughput analysis of behaviour in Drosophila or other animal models. Here we equip ethoscopes with a Python framework for data analysis, ethoscopy, designed to be a user-friendly yet powerful platform, meeting the requirements of researchers with limited coding expertise as well as experienced data scientists. Ethoscopy is best consumed in a prebaked Jupyter-based docker container, ethoscope-lab, to improve accessibility and to encourage the use of notebooks as a natural platform to share post-publication data analysis. Ethoscopy is a Python package available on GitHub and PyPi. Ethoscope-lab is a docker container available on DockerHub. A landing page aggregating all the code and documentation is available at https://lab.gilest.ro/ethoscopy.

ПІДВИЩЕННЯ ЕФЕКТИВНОСТІ БЕЗПРОВОДОВИХ СИСТЕМ ПЕРЕДАЧІ ДАНИХ В УМОВАХ ЗАСТОСУВАННЯ ЗАСОБІВ РАДІОЕЛЕКТРОННОЇ БОРОТЬБИ

The article discusses some of the technologies that ensure the autonomy of unmanned aerial vehicles (UAVs) on the battlefield, methods of increasing the efficiency of UAV communication channels in the context of electronic warfare (EW). The author analyzes the threats to autonomous UAVs that may arise from the use of electronic warfare, and also presents the characteristics of one of the typical modern electronic warfare complexes. This article discusses the development of a test model of a wireless data transmission channel designed to develop technologies for countering electronic warfare and traininga neural network. The use of this model will allow the development of original domestic algorithms for countering enemy electronic warfare. The requirements of manufacturers to the electronic equipment of autonomous UAVs are analyzed. The possibility of using non-professional SDR radio equipment and open source software and hardware platforms for the develop-ment and verification of these countermeasures algorithms is considered. The algorithm for changing data transmission pa-rameters in the event of interference is determined. The choice of the type of neural network for use in the cognitive radio system of the UAV is substantiated. The idea of applying adaptive coding in UAV communication channels using multicompo-nent turbo codes in combination with neural networks that are simultaneously used for cognitive radio was further developed. Using information from the neural network about subsequent changes in the communication channel will reduce the adaptation time of the coding system, which will reduce the number of errors in data transmission and increase the reliability of commu-nication, especially when using dynamic spectrum access.The article is devoted to the problems of creating methods and models that use software-defined radio (SDR), cognitive radio, and multi-level parametric adaptation of turbo-code structures using artificial intelligence to improve the efficiency of wireless data transmission systems in the context of active use of electronic warfare by ensuring the reliability of information

THE USE OF COGNITIVE RADIO TECHNOLOGY TO IMPROVE THE EFFICIENCY OF WIRELESS DATA TRANSMISSION SYSTEMS IN THE CONDITIONS OF ACTIVE USE OF ELECTRONIC WARFARE

The article discusses the development of a method for improving the efficiency of communication channels of unmanned aerial vehicles (UAVs) in the context of electronic warfare (EW). The threats that can be caused by the use of electronic warfare against autonomous UAVs are analyzed. A review of some technologies that can be used to create original domestic algorithms for countering electronic warfare and improve the autonomy of UAVs on the battlefield is carried out. The possibility of using non-professional SDR radio equipment and open source hardware and software platforms for the development and verification of these countermeasures algorithms is considered. The idea of applying adaptive coding in UAV communication channels using multicomponent turbo codes in conjunction with neural networks, which are simultaneously used for cognitive radio, was further developed. The article is devoted to the problems of creating models and methods for ensuring the integrity of information in wireless data transmission systems in the context of active use of electronic warfare.

A Low-Power IoT Device for Measuring Water Table Levels and Soil Moisture to Ease Increased Crop Yields.

The simultaneous measurement of soil water content and water table levels is of great agronomic and hydrological interest. Not only does soil moisture represent the water available for plant growth but also water table levels can affect crop productivity. Furthermore, monitoring soil saturation and water table levels is essential for an early warning of extreme rainfall situations. However, the measurement of these parameters employing commercial instruments has certain disadvantages, with a high cost of purchase and maintenance. In addition, the handling of commercial devices makes it difficult to adapt them to the specific requirements of farmers or decision-makers. Open-source IoT hardware platforms are emerging as an attractive alternative to developing flexible and low-cost devices. This paper describes the design of a datalogger device based on open-source hardware platforms to register water table levels and soil moisture data for agronomic applications. The paper begins by describing energy-saving and wireless transmission techniques. Then, it summarizes the linear calibration of the phreatimeter sensor obtained with laboratory and field data. Finally, it shows how non-linear machine-learning techniques improve predictions over classical tools for the moisture sensor (SKU: SEN0193).

Disarmadillo: an open source, sustainable, robotic platform for humanitarian demining

<p class="Abstract">The mine action community suffers from a lack of information sharing among stakeholders. Since 2004, Snail Aid has been working on Disarmadillo, a dramatic shift in paradigm: an open source hardware platform for humanitarian demining. Developed mainly thanks to volunteers’ work across more than 15 years, the machine is now going to get a push thanks to the project Disarmadillo+, in collaboration between Snail Aid - Technology for Development and the Italian Institute of Technology. The new version of the machine will be improved in terms of manoeuvrability, modularity, versatility, without compromising its characteristic features. The re-design will take into account the need of keeping the cost low and the technology appropriate to the context where it will work. The ability of the machine to serve two different purposes will also be preserved: the machine will keep on being easily convertible to its original agricultural nature, being developed around a commercial off-the-shelf powertiller. The paper presents the machine and the research work foreseen within the new project</p>

Use of the LunAero Open-Source Hardware Platform to Enhance the Accuracy and Precision of Traditional Nocturnal Migration Bird Counts.

Quantification of nocturnal migration of birds through moon watching is a technique ripe for modernization with superior computational power. In this paper, collected by a motorized telescope mount was data analyzed using both video observations by trained observers and modernized approaches using computer vision. The more advanced data extraction used the OpenCV library of computer vision tools to identify bird silhouettes by means of image stabilization and background subtraction. The silhouettes were sanitized and analyzed in sequence to produce stacked relationships between temporally close contours, discriminating birds from noise based on the assumption that birds migrate in stable paths. The flight ceiling of the birds was determined by extracting relevant correlation coefficient data from doppler radar co-located with the LunAero instrument in Norman, OK, USA using a method with low-computational overhead. The bird paths and flight ceiling were combined with lunar ephemera to provide input for the original method used for nocturnal migration quantification as well as an enhanced version of the same method with more advanced computational tools. We found that the manual quantification of migration activity detected 16,300 birds/km•h heading northwest from 110°, whereas the automated analysis reported a density of 43,794 birds/km•h heading northwest from 106.67°. Hence, there was agreement with regard to flight direction, but the automated method overestimated migration density by approximately three times. The reasons for the discrepancy between flight path detection appeared to be due to a substantial amount of noise in the video data as well as a tendency for the computer vision analysis to split single flight paths into two or more segments. The authors discuss ongoing innovations aimed at addressing these methodological challenges.

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.

Technological collaborations model in Iranian automotive industry: developing an open source hardware platform

Technological collaborations model in Iranian automotive industry: developing an open source hardware platform

Technological collaborations model in Iranian automotive industry: developing an open source hardware platform

Technological collaborations model in Iranian automotive industry: developing an open source hardware platform

On the development of flexible mobile multi-sensor units based on open-source hardware platforms and a reference framework

For some IoT applications, mobile entities are considered as the main source of sensed data, requiring the attachment of sensor modules on them. The endowing of sensing capabilities to such mobile entities can be performed in different ways, but the adoption of a reference hardware framework can bring a series of advantages, specially in dynamic complex scenarios. This article exploits the MSensorMob2 multi-sensor hardware framework for monitoring in areas with disconnection periods, comprising sensing, transmission and reconfiguration functions. Comprehensive analyses on multiple open-source hardware platforms are conducted, assessing their costs, deployment constraints and performance issues when implementing this development framework.

Immersive multitalker remote microphone system

Hearing aids and other listening devices perform poorly in noisy, reverberant environments with many overlapping sound sources. Remote microphones, which are worn by a talker and transmit low-noise, low-reverberation speech directly to a hearing device, can improve intelligibility even in adverse environments. However, most commercial remote microphone accessories can only be used with one talker at a time and remove the interaural cues that listeners use to localize sound sources. Using the Tympan open-source hardware platform, we demonstrate a multitalker remote microphone system that preserves interaural cues and room acoustic effects. A pair of wireless microphones transmits sound from two talkers to the Tympan system. A set of real-time adaptive filters running on the embedded processor match the magnitude and phase of the remote microphone signals to the sound received by the earpiece microphones. The earpiece output has the signal-to-noise ratio of the remote microphones but the spatial cues of the on-ear microphones. Because the remote microphones provide low-noise reference signals, the system can track motion in real time and does not need to perform explicit source localization or separation.

P4Pi

High level, network programming languages, like P4, enable students to gain hands-on experience in the structure of a switch or router. Students can implement the packet processing pipeline themselves, without prior knowledge of circuit design. However, when choosing a P4 programmable target for use in the classroom, instructors face a lack of options. On the one hand, software solutions, such as the behavioral model (BMv2) switch, are overly simplified and offer low performance. On the other hand, existing hardware solutions are closed source and expensive. In this paper, we present P4Pi, a new, low-cost, open-source hardware platform intended for networking education. P4Pi allows students to design and deploy P4-based network devices using the Raspberry Pi board, which has a price tag of less than many academic textbooks. We describe the high-level design of the P4Pi platform, offer some suggestions for how P4Pi could be used in the classroom, and present some additional use-cases for applications and functionality that could be developed using P4Pi.

Correction: Open Source Hardware and Healthcare Collaborative Platforms: Common Legal Challenges

This article details a correction to the article: Biasin, E. and Kamenjašević, E., 2020. Open Source Hardware and Healthcare Collaborative Platforms: Common Legal Challenges. <em>Journal of Open Hardware</em>, 4(1), p. 7. DOI: <a href="https://doi.org/10.5334/joh.31" target="_blank">https://doi.org/10.5334/joh.31</a>