Beyond Open Source Software: Solving Common Library Problems Using the Open Source Hardware Arduino Platform

This chapter examines the use of Open Source Software (OSS) technologies that can be used to improve the learning of Science, Technology, Engineering, and Mathematics (STEM). Explored are the various methods that can be utilized to improve the percentage of STEM majors in the American educational system with resources such as: Open Source as Alternative (OSALT), virtualization, cloud computing, Linux distributions, open source programming, and open source hardware platforms. Increasing the amount of students that pursue STEM majors is important because the projected job growth in the STEM field compared to non-STEM jobs is 33%. OSALT provides cost-effective alternatives to commercial products such as Microsoft Office Suite and Adobe Photoshop. Second, creating Virtual Machines (VMs) is another avenue to teach complex concepts in computer science, engineering, and Information Technology (IT). Third, cloud computing is an inexpensive way for clients to access information from multiple locations and devices. Fourth, universities can use the Operating System (OS) Linux and its various distributions as replacements for commercial operating systems like Windows in order to reduce IT costs. Lastly, open source programming languages like Python and their associated Integrated Development Environments (IDEs) provide comprehensive facilities for software engineers for application development or testing.

Dendrochronological techniques are paramount in forest research. The current climate change scenario and the central role of forests in biogeophysical cycles enforce the importance of novel techniques to get accurate data from trees and their relationship with the environment in faster ways. Recent technological advances and the place of open source software and hardware are making free, user-developed tools for forest research available to the research community. The aim of this Ph.D. thesis is the development of tools for image acquisition and data collection in dendrochronology based on open source software and hardware. Thus, four different tools for dendrochronological research are presented in five different chapters. The first chapter focuses on the development of a do-it-yourself tool based on open source hardware for image acquisition and wood sample digitization at high resolution. We used open hardware equipment from Arduino and Python programming to develop CaptuRING and published the entire free open source tool as: "CaptuRING: A Do-It-Yourself tool for wood sample digitization" in Methods in Ecology and Evolution, 2022; 13:1185-1191. Furthermore, the original software was registered in the Registro General de Propiedad Intelectual (00/2022/737) of Ministerio de Cultura y Deporte (Spain). The second chapter presents "How to build and install your own CaptuRING". This contribution presents a series of videos with a step-by-step guide to promote the use of CaptuRING in the research community. The manuscript and related videos have been submitted for publication. The third chapter describes ρ-MtreeRing. This free and open-source software, which is written in R, analyzes X-ray films from dendrochronological samples to get microdensity values automatically segmented through a graphical user interface. The open source tool and manuscript are published as: "ρ-MtreeRing. A graphical user interface for X-ray microdensity analysis" in Forests. 2021; 12(10):1405. The fourth chapter describes the potential of deep learning methods to automatically segment xylem vessels. We trained three different convolutional neural networks to segment vessels in stained wood microsections using the Keras framework in Python. Our results demonstrate the potential of these techniques to automatically segment xylem vessels and overcome derived problems from image illumination, which hamper segmentation using classical image segmentation methods. The manuscript is published as "Convolutional neural networks for segmenting xylem vessels in stained cross-sectional images" in: Neural Computing & Applications, 2020; 32:17927-17939. The fifth chapter develops an algorithm to delineate annual ring limits in stained wood microsections of a species with diffuse porous wood using convolutional neural networks. We used Python for image processing and the Keras framework for the algorithm training. The results show the ability of this techniques to obtain accurate tree ring segmentation for quantitative wood anatomy, reaching similar or even outperforming conventional manual delimitation in most of the evaluated cases. The results of this chapter will be presented in the manuscript "Deep Learning for ring bordering in stained cross-sectional images". This PhD Thesis presents four open source tools to get accurate information from wood features to unveil how trees respond to the environment. From digitization at macroscopic perspective, automatic data collection and the development of feature segmentation on microscopic samples. The presented four novel dendrochronological tools based on open source software facilitates forest research in the current climate change scenario.

This chapter explores open source hardware. Open source hardware is a relative newcomer in comparison with open source software. As a field it has adopted many assumptions and models from the world of open source software, but its latecomer status gives it the advantage of being able to learn from what has gone before. At this juncture, there are far fewer businesses operating in the world of open hardware, and those businesses are less prominent and successful (although there are signs that this is rapidly changing). There are also far fewer specific open hardware licences than open source software licences, and there are still fundamental questions about the applicability of various different forms of intellectual property right to different aspects of hardware.

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

This article presents the development of a low cost network of wireless sensors that use an open source hardware platform, consisting of an ESP8266 and a digital temperature-humidity sensor to measure the parameters in an area determined by the range of the sensor. The general development of the system includes the use of open source software to receive information through the network. Tests of sensor effectiveness were performed at three different points in an air-conditioned area. The first sensor was placed outside the area, the second in the middle and the last one at the exit of the air conditioning. The results obtained allowed to know the behavior of temperature and humidity in the area and the effectiveness of the sensor network to measure the variables, the results of the measurements are presented in detail. Because the system is highly scalable, inexpensive and easy to build compared to other systems, it is a good choice for a wide variety of applications.

3-D printing technologies have become widely adopted and have spurred innovation and efficiency across many markets. A large contributor to the success of 3-D printing are open source, low cost electronics. On-site circuit manufacturing, however, has not become as widely utilized as 3-D printing. This project attempts to address this problem by proposing and demonstrating an open source circuit board milling machine which is inexpensive, easily manufactured, and accurate. In three interdependent sub-projects, this thesis defines a standard method for designing open source hardware, the design of the bespoke circuit mill, and explores an application of the mill for novel circuit manufacturing. The first sub-project develops a standardized process for designing, prototyping, and distributing open source hardware. Following these steps can help ensure success for each individual part of the project. In order to validate the procedure, a case study is explored of designing low cost parametric glass slide driers. The second sub-project details the design and construction of a circuit prototyping machine. The open source design procedure is implemented to assure maximum effectiveness. A software interface is also designed to control and carry out processing steps on the milling machine. The mill minimizes lead time and production costs of experimental circuitry. The mill also stands as a strong open source tool that can help foster growth in distributed manufacturing of electronics for a wide array of applications. The third and final sub-project explores a flexible and scalable power monitoring system. The electronics are designed according to the open source design procedure and are manufacturable with the circuit milling machine. The power meter can be used to monitor and log power consumption of a wide range of loads, including both AC and DC.

We have attempted to create affordable programmable logical controllers (PLC) that can be used to train millions of students in developing countries. Version 1 of the PLC is based on AtMega16 and costs 600 ($10). Using the free and open source software (FOSS) LD Micro, one can learn ladder logic. To enhance the capabilities, using Raspberry PI, Version 2 of the PLC, costing 1,500 ($25) is made. We can use this device with the FOSS OpenPLC to learn ladder logic. We can also learn function block based programming using the FOSS 4DIAC. As ladder logic and function block based programming are industrial standards, students trained using our approach will be useful to industry.

This paper presents an operational comparison of two open source-based control platforms for a practical, low cost do-it-yourself underwater remotely operated vehicle (ROV) developed by Underwater Technology Research Group (UTeRG), Universiti Teknikal Malaysia Melaka. Research institutes and hobbyist have shown a growing interest in the development of observation class remotely operated vehicle using open-source platform. Two low-cost open-source solutions for such ROV are known as OpenROV, an open-source platform that is introduced by OpenROV company, and the Ardusub, an open-source ROV kit promoted by Blue Robotics Company. Both open-source hardware and software platforms are being used worldwide for the development of small range of electrical powered ROV system’s architecture, with support from the literature in the internet and the extensive experience acquired with the development of robotic exploration systems. The comparison of both open-source platform is discussed in detail, to provide guidance on how to build our own do-it-yourself ROV, with the lowest possible cost.KeywordsOpenROVUnderwater dronesOpen-source

This paper introduces a proof-of-concept 6LoWPAN
\ntestbed to study the integration of programmable network
\ntechnologies in relaxed throughput and low-power IoT devices.
\nOpen source software and hardware platforms are used in
\nthe implemented testbed to increase the possibility of future
\nnetwork extension. The proposed architecture offers end-to-end
\nconnectivity via the 6LoWPAN gateway to integrate IPv6 hosts
\nand the low data rate devices directly. Nowadays, SoftwareDefined
\nNetworking (SDN) and Network Function Virtualization
\n(NFV) are the most promising technologies for dealing with the
\nmassive increase in M2M devices and achieving agile traffic. The
\ndeveloped approach in this paper is entitled tailored Software
\nDefined-Network Function Virtualization (SD-NFV), which is
\naimed at reducing the end-to-end delay and improving the
\nenergy depletion in sensor nodes. Experimental scenarios of
\nthe implemented testbed are conducted using a simple sensing
\napplication and the obtained results indicate that the introduced
\napproach is appropriate for constrained IoT devices. By utilizing
\nSD-NFV scheme in 6LoWPAN network, the data delivery ratio
\nincreased by 5-14%, the node operational time prolonged by
\n70%, the end-to-end latency for gathering sensor data minimized
\nby ≈160%, and the latency for transmitting control messages
\nto a specified node diminished by ≈63% when compared to a
\ntraditional (non SDN-enabled) 6LoWPAN network.

Open source hardware is a type of hardware where the schematics and designs are made unrestricted and available to all. They are often accompanied by open source software. This can bring reliability, ease of debugging, and modular development for rapid prototyping using pre-written libraries. Merits of using open source hardware are discussed and then applied to a portable sensor system based on the open hardware Arduino-derived Jeenode microcontroller board. The system uses an inertial measurement unit (IMU) and seamless integration of other sensors, including a piezo-resistive pressure sensor. It is shown that open source hardware can help to increase rapid development, reduce costs, and encourage further development.

Open source hardware (OSHW) has been created by the design movement and is a promising technology as it applies a compatible concept to a variety of components. Also, OSHW is intended to enable anyone to study specific hardware, makes modifications, and share hardware changes with peers. In this paper, we present the sensor interface application of OSHW. To develop embedded systems using the concept of OSHW, we developed and tested a monitoring module based on the Beaglebone Black for a chip inspection system. The developed module can be used in low power monitoring, and can obtain a more flexible sensor interface in the on-line chip fault inspection and isolation process.

Summary form only given, as follows. The complete presentation was not made available for publication as part of the conference proceedings. You've heard about open source software, but what is open source hardware? Come hear experts from across the industry and in academia discuss the new face of open source, Hardware IP: - What is it? - How are companies and academics using it? - Can Open Source Hardware significantly change the design world?

Design and construction of an automated OSL reader with open source software and hardware

The advent of easy-to-use open source microcontrollers, off-the-shelf electronics and customizable manufacturing technologies has facilitated the development of inexpensive scientific devices and laboratory equipment. In this study, we describe an imaging system that integrates low-cost and open-source hardware, software and genetic resources. The multi-fluorescence imaging system consists of readily available 470 nm LEDs, a Raspberry Pi camera and a set of filters made with low cost acrylics. This device allows imaging in scales ranging from single colonies to entire plates. We developed a set of genetic components (e.g. promoters, coding sequences, terminators) and vectors following the standard framework of Golden Gate, which allowed the fabrication of genetic constructs in a combinatorial, low cost and robust manner. In order to provide simultaneous imaging of multiple wavelength signals, we screened a series of long stokes shift fluorescent proteins that could be combined with cyan/green fluorescent proteins. We found CyOFP1, mBeRFP and sfGFP to be the most compatible set for 3-channel fluorescent imaging. We developed open source Python code to operate the hardware to run time-lapse experiments with automated control of illumination and camera and a Python module to analyze data and extract meaningful biological information. To demonstrate the potential application of this integral system, we tested its performance on a diverse range of imaging assays often used in disciplines such as microbial ecology, microbiology and synthetic biology. We also assessed its potential use in a high school environment to teach biology, hardware design, optics, and programming. Together, these results demonstrate the successful integration of open source hardware, software, genetic resources and customizable manufacturing to obtain a powerful, low cost and robust system for education, scientific research and bioengineering. All the resources developed here are available under open source licenses.

The Move to the Middle: Convergence of the Open-Source and Proprietary Software Industries