Raspberry Pi Single-board Computer Research Articles

ScintPi: A Low‐Cost, Easy‐to‐Build GPS Ionospheric Scintillation Monitor for DASI Studies of Space Weather, Education, and Citizen Science Initiatives

AbstractWe report the proposal and results of a low‐cost, easy‐to‐build GPS‐based sensor for detection and monitoring ionospheric irregularities through the detection of amplitude scintillation. The system is based on the Raspberry Pi single‐board computer combined with an Adafruit Ultimate GPS peripheral, which is capable of measuring (at 10‐Hz rate) the intensity of the L1 signals transmitted by GPS satellites. We introduce and discuss results of short‐ and long‐term observations obtained with a prototype of this system deployed in Presidente Prudente, a low magnetic latitude site in Brazil. The deployment and observations were carried out to test the ability of the system to detect ionospheric scintillations and, therefore, monitor the occurrence of ionospheric irregularities associated with equatorial spread F. Our results show that this low‐cost sensor is indeed capable of detecting scintillation events associated with equatorial spread F. Comparison with simultaneous, collocated measurements made by a commercial scintillation monitor are also presented. The joint observations allowed us to quantify the performance of the low‐cost monitor and to identify sources of potential limitations. While the sensor cannot (and it was not intended to) substitute commercial scintillation monitors, the low cost allows its use in studies of ionospheric irregularities (space weather) that require observations made by distributed arrays of small instruments (DASI). Furthermore, the simplicity of the sensor design stimulates its use in educational and citizen science initiatives.

Low-cost, sub-micron resolution, wide-field computational microscopy using opensource hardware

The revolution in low-cost consumer photography and computation provides fertile opportunity for a disruptive reduction in the cost of biomedical imaging. Conventional approaches to low-cost microscopy are fundamentally restricted, however, to modest field of view (FOV) and/or resolution. We report a low-cost microscopy technique, implemented with a Raspberry Pi single-board computer and color camera combined with Fourier ptychography (FP), to computationally construct 25-megapixel images with sub-micron resolution. New image-construction techniques were developed to enable the use of the low-cost Bayer color sensor, to compensate for the highly aberrated re-used camera lens and to compensate for misalignments associated with the 3D-printed microscope structure. This high ratio of performance to cost is of particular interest to high-throughput microscopy applications, ranging from drug discovery and digital pathology to health screening in low-income countries. 3D models and assembly instructions of our microscope are made available for open source use.

Аналіз можливостей використання одноплатних комп’ютерів Raspberry при викладанні розподільчих та паралельних обчислень

The article considers the possibility of using single-board computers in teaching disciplines related to parallel and distributed computing. To conduct practical training in parallel computing, it is a very personal computer with a multi-core processor and an appropriate operating system, but for computational computing practice it is necessary to organize a computing cluster. To develop a cluster, you need a specific software setup that can make it difficult to use a computer class to teach other disciplines. Also, the purchase of personal computers for a computing cluster can lead to significant material costs. Therefore, it is expedient to explore the possibility of using single-board computers to develop a computing cluster and use it in practical work on distributed computing. The analysis of modern single-board computers and various sources for the development of computing clusters has shown that it is suitable for the single-board computer Raspberry Pi 3 Model B +. A comparative analysis of several Raspberry Pi models and, for comparison, one-board computer of another manufacturer – ASUS Tinker Board. It is revealed that Raspberry Pi 3 Model B + characteristics are optimal in the price / quality ratio for forming a learning computing cluster for distributed and parallel computing. Such a cluster has a relatively high price and very good scalability. Also, the problems that need to be solved when designing a computing cluster are found: there is no standardized chassis for placement of boards, the absence of standard heat removal from single-board computers and the need for a non-standard protected power supply. The organization of such a cluster will greatly improve students' skills in developing distributed computing software and build and configure the cluster systems and will allow the development of such competencies of future programmers. Key words. Parallel and distributed computing, single-board computer, computing cluster, Raspberry Pi, software.

Smart Contract-Based Access Control for the Internet of Things

This paper investigates a critical access control issue in the Internet of Things (IoT). In particular, we propose a smart contract-based framework, which consists of multiple access control contracts (ACCs), one judge contract (JC) and one register contract (RC), to achieve distributed and trustworthy access control for IoT systems. Each ACC provides one access control method for a subject-object pair, and implements both static access right validation based on predefined policies and dynamic access right validation by checking the behavior of the subject. The JC implements a misbehavior-judging method to facilitate the dynamic validation of the ACCs by receiving misbehavior reports from the ACCs, judging the misbehavior and returning the corresponding penalty. The RC registers the information of the access control and misbehavior-judging methods as well as their smart contracts, and also provides functions (e.g., register, update and delete) to manage these methods. To demonstrate the application of the framework, we provide a case study in an IoT system with one desktop computer, one laptop and two Raspberry Pi single-board computers, where the ACCs, JC and RC are implemented based on the Ethereum smart contract platform to achieve the access control.

A low-cost, open-source digital stripchart recorder for chromatographic detectors using a Raspberry Pi

One of the most critical aspects of chromatographic analysis is effective data acquisition and processing. Typical approaches include software platforms designed for specific instruments or commercial data acquisition hardware boards, both of which require expensive licenses to use and operate. To increase the access and affordability of chromatographic data acquisition, especially for systems in which software control has become obsolete or must be written in-house, an open-source digital stripchart recorder has been developed. This system is built upon a Raspberry Pi single-board computer and a plug-in printed circuit board with the necessary integrated circuits for data acquisition. Using an open-source software called Processing, a complete user interface to control the system was developed that enables the acquisition, filtering, and processing of chromatographic data. The system performs comparably to more expensive platforms, with calculated values for peak area, retention time, and plate count all within 3% of the values calculated by a widely used commercial chromatography data software package.

PERANCANGAN SISTEM DETEKSI OBJEK PADA ROBOT KRSBI BERBASIS MINI PC RASPBERRY PI 3

KRSBI Wheeled is One of the competitions on the Indonesian Robot Contest,. It is a football match that plays 3 robot full autonomous versus other teams. The robot uses a drive in the form of wheels that are controlled in such a way, to be able to do the work the robot uses a camera sensor mounted on the front of the robot, while for movement in the paper author uses 3 omni wheel so the robot can move in all directions to make it easier towards the ball object. For the purposes of image processing and input and output processing the author uses a Single Board Computer Raspberry PI 3 are programmed using the Python programming language with OpenCV image processing library, to optimize the work of Single Board Computer(SBC) Raspberry PI 3 Mini PC assisted by the Microcontroller Arduino Mega 2560. Both devices are connected serially via the USB port. Raspberry PI will process the image data obtained webcam camera input. Next, If the ball object can be detected the object's position coordinates will be encoded in character and sent to the Microcontroller Arduino Mega 2560. Furthermore, Arduino mega 2560 will process data to drive the motors so that can move towards the position of the ball object. Based on the data from the maximum distance test results that can be read by the camera sensor to be able to detect a ball object is �5 meters with a maximum viewing angle of 120 �.

Raspberry Pi-Based Low-Cost Connected Device for Assessing Road Surface Friction

Measuring friction between the tyres of a vehicle and the road, often and on as many locations on the road network as possible, can be a valuable tool for ensuring traffic safety. Rather than by using specialised equipment for sequential measurements, this can be achieved by using several low-cost measuring devices on vehicles that travel on the road network as part of their daily assignments. The presented work proves the hypothesis that a low cost measuring device can be built and can provide measurement results comparable to those obtained from expensive specialised measuring devices. As a proof of concept, two copies of a prototype device, based on the Raspberry Pi single-board computer, have been developed, built and tested. They use accelerometers to measure vehicle braking deceleration and include a global positioning receiver for obtaining the geolocation of each test. They run custom-developed data acquisition software on the Linux operating system and provide automatic measurement data transfer to a server. The operation is controlled by an intuitive user interface consisting of two illuminated physical pushbuttons. The results show that for braking tests and friction coefficient measurements the developed prototypes compare favourably to a widely used professional vehicle performance computer.

Low-cost and portable UV holographic microscope for high-contrast protein crystal imaging

Imaging protein crystals and distinguishing them from salt crystals is an important task for protein crystallographers. The conventional tool used for this purpose is a dual-mode microscope composed of bright-field and ultraviolet (UV) induced fluorescence modes. The distinction between a protein and a salt crystal is made based upon the fluorescence response to the UV excitation, where most protein crystals absorb the UV excitation and emit fluorescence, unlike salt crystals. These dual-mode optical microscopes are sensitive; however, they are relatively bulky and expensive as they require UV-grade optics. As an alternative, here we demonstrate that on-chip UV holographic imaging offers a low-cost, portable, and robust technique to image and distinguish protein crystals from salt crystals, without the need for any expensive and bulky optical components. Only composed of a UV light-emitting-diode at 280 nm and a consumer-grade complementary metal–oxide–semiconductor image sensor de-capped and interfaced to a Raspberry Pi single-board computer, the necessary information from the crystal samples (placed very close to the sensor active area) is captured in the form of in-line holograms and extracted through digital back-propagation. In these holographic amplitude reconstructions, protein crystals appear significantly darker compared to the background due to the strong UV absorption, unlike salt crystals which do not show any contrast, enabling us to clearly distinguish between them. We believe that the on-chip UV holographic microscope could serve as a low-cost, sensitive, and robust alternative to conventional lens-based UV-microscopes used in protein crystallography.

Condition Monitoring of Active Magnetic Bearings on the Internet of Things

A magnetic bearing is an industrial device that supports a rotating shaft with a magnetic field. Magnetic bearings have advantages such as high efficiency, low maintenance, and no lubrication. Active magnetic bearings (AMBs) use electromagnets with actively controlled coil currents based on rotor position monitored by sensors integral to the AMB. AMBs are apt to the Internet of Things (IoT) due to their inherent sensors and actuators. The IoT is the interconnection of physical devices that enables them to send and receive data over the Internet. IoT technology has recently rapidly increased and is being applied to industrial devices. This study developed a method for the condition monitoring of AMB systems online using off-the-shelf IoT technology. Because off-the-shelf IoT solutions were utilized, the developed method is cost-effective and can be implemented on existing AMB systems. In this study, a MBC500 AMB test rig was outfitted with a Raspberry Pi single board computer. The Raspberry Pi monitors the AMB’s position sensors and current sensors via an analog-to-digital converter. Several loading cases were imposed on the experimental test rig and diagnosed remotely using virtual network computing. It was found that remote AMB condition monitoring is feasible for less than USD 100.

Real-time implementation of Kalman filter to improve accuracy in the measurement of time of flight in an ultrasonic pulse-echo setup.

In this paper, we demonstrate a hardware implementation of Kalman filter to enhance accuracy in the measurements of time-of-flight in an ultrasonic pulse echo technique (operated at 10 MHz). Pulser-receivers and other respective circuit units are designed using off-the-shelf electronic components. The advanced reduced instruction-set computing machine processor based Raspberry Pi single board computer is used to implement the Kalman filter and control various processes. Additionally, a graphical user interface is designed using Qt software, under the Debian open source operating system. The software has capability to measure and display the time-of-flight and ultrasonic propagation velocity in a liquid under test. The designed system with the Kalman filter exhibited an extremely small error of about 0.01% in the time-of-flight measurements compared with other systems. The functionality of the developed approach to measure time of flight and thereby ultrasonic velocity with significant improvement has been discussed in this article. It was experimentally verified that by improving other parameters such as the separation between the transducer and the reflector and cell structure, significant improvement in the accuracy of ultrasonic velocity in the liquid under test is achieved.

A Compatible OpenFlow Platform for Enabling Security Enhancement in SDN

Software-defined networking (SDN) is a representative next generation network architecture, which allows network administrators to programmatically initialize, control, change, and manage network behavior dynamically via open interfaces. SDN is widely adopted in systems like 5G mobile networks and cyber-physical systems (CPS). However, SDN brings new security problems, e.g., controller hijacking, black-hole, and unauthorized data modification. Traditional firewall or IDS based solutions cannot fix these challenges. It is also undesirable to develop security mechanisms in such an ad hoc manner, which may cause security conflict during the deployment procedure. In this paper, we propose OSCO (Open Security-enhanced Compatible OpenFlow) platform, a unified, lightweight platform to enhance the security property and facilitate the security configuration and evaluation. The proposed platform supports highly configurable cryptographic algorithm modules, security protocols, flexible hardware extensions, and virtualized SDN networks. We prototyped our platform based on the Raspberry Pi Single Board Computer (SBC) hardware and presented a case study for switch port security enhancement. We systematically evaluated critical security modules, which include 4 hash functions, 8 stream/block ciphers, 4 public-key cryptosystems, and key exchange protocols. The experiment results show that our platform performs those security modules and SDN network functions with relatively low computational (extra 2.5% system overhead when performing AES-256 and SHA-256 functions) and networking performance overheads (73.7 Mb/s TCP and 81.2Mb/s UDP transmission speeds in 100Mb/s network settings).

MULTIFUNCTIONAL ROBOTIC COMPLEX BASED ON A SINGLE-BOARD COMPUTER

The purpose of the work is to create a modular multifunctional robotic complex based on the single-board computer Raspberry Pi and Arduino microcontroller. In order to solve the problems of fast transfer and processing of data, a client/server software code has been developed that minimizes potential losses. The server is universal and can modify its code for a specific task by spending a minimum amount of time. An image processing algorithm is created that reduces the amount and time for correctness checking that affects the speed of cascade construction. The fastest and optimal algorithm for cascade construction is developed, which allows to reduce the time of repair by 3 times. Optimized software communication between a single-board computer and a microprocessor for faster processing of information.

Implementation of an axisymmetric drop shape apparatus using a Raspberry-Pi single-board computer and a web camera

This paper describes the implementation of an axisymmetric drop shape apparatus for the measurement of surface or interfacial tension of a hanging liquid drop, using only cheap resources like a common web camera and a single-board microcomputer. The mechanics of the apparatus is composed of stubs of commonly available aluminium bar, with all other mechanical parts manufactured with an amateur 3D printer. All of the required software, either for handling the camera and taking the images, or for processing the drop images to get the drop profile and fit it with the Bashforth and Adams equation, is freely available under an open source license. Despite the very limited cost of the whole setup, an extensive test has demonstrated an overall accuracy of ±0.2% or better.

Method of mobile robot indoor navigation by artificial landmarks with use of computer vision

The article describes an algorithm of the mobile robot indoor navigation based on the use of visual odometry. The results of the experiment identifying calculation errors in the distance traveled on a slip are presented. It is shown that the use of computer vision allows one to correct erroneous coordinates of the robot with the help of artificial landmarks. The control system utilizing the proposed method has been realized on the basis of Arduino Mego 2560 controller and a single-board computer Raspberry Pi 3. The results of the experiment on the mobile robot navigation with the use of this control system are presented.

An open-source approach to automation in organic synthesis: The flow chemical formation of benzamides using an inline liquid-liquid extraction system and a homemade 3-axis autosampling/product-collection device

Several open-source hardware and software technologies (RAMPS, Python, PySerial, OpenCV) were used to control an automated flow chemical synthesis system. The system was used to effect the synthesis of a series of benzamides. An inexpensive Raspberry Pi single board computer provided an electronic interface between the control computer and the RAMPS motor driver boards.

Development of a Hardware and Software System for Meteorological Observations

Article is devoted to development of a hardware and software system for monitoring of weather conditions. The hardware of this complex is the Arduino platform, which are connected sensors of temperature, humidity, atmospheric pressure, speed and direction of wind, level of ultra-violet radiation, which allow to watch environment parameters. Data are transferred to the remote server which is constructed on the basis of the single board computer Raspberry Pi, by means of a radio channel. For ensuring functioning of a complex, the software was written and it consisting of three programs. The first program was written to on Si similar language for operation of the Arduino controller. The second from programs was written for functioning of the server, it consists of MySQL DBMS, a script for data record in a basis and the PhpMyAdmin servers for administration of a DB. The third was written in the C# programming language and represents the application Windows forms. The made experiment showed that the complex allows to carry continuously meteorological observations, at the same time data remain in the database and the consumer software allows to carry their processing.

Portable cyber-physical system for indoor and outdoor gas sensing

A design, development and testing process for a cyber-physical system capable of versatile gas sensor measurement is described. Two approaches for the system are proposed; a stationary system for calibration and testing in laboratory environments and a portable system with wireless capability. The device utilizes a well-established Arduino microcontroller as well as a Raspberry Pi single board computer. The functionality is realized with C and Python programming languages. The operability is validated by system performance evaluation in the mixture of air and hydrogen gas, using both commercial and experimental Taguchi-type metal oxide semiconductor sensors. The experimental sensors are fabricated by inkjet printing platinum decorated tungsten oxide nanoparticles onto an electrode pattern on a silicon substrate which is then wire bonded to a chip carrier. The measurement platform demonstrated in our paper provides rapid prototyping capabilities for evaluating novel gas sensor materials in realistic measurement scenarios

Harnessing open-source technology for low-cost automation in synthesis: Flow chemical deprotection of silyl ethers using a homemade autosampling system

An inexpensive homemade 3-axis autosampler was used to facilitate the automation of an acid catalysed flow chemical desilylation reaction. Harnessing open-source software technologies (Python, OpenCV), an automated computer-vision controlled liquid-liquid extraction step was used to provide effective inline purification. A Raspberry Pi single-board computer was employed to interface with the motors used in the autosampler and actuated fluidic valves.

A Low Cost, Edge Computing, All-Sky Imager for Cloud Tracking and Intra-Hour Irradiance Forecasting

With increasing use of photovoltaic (PV) power generation by utilities and their residential customers, the need for accurate intra-hour and day-ahead solar irradiance forecasting has become critical. This paper details the development of a low cost all-sky imaging system and an intra-hour cloud motion prediction methodology that produces minutes-ahead irradiance forecasts. The SkyImager is designed around a Raspberry Pi single board computer (SBC) with a fully programmable, high resolution Pi Camera, housed in a durable all-weather enclosure. Our software is written in Python 2.7 and utilizes the open source computer vision package OpenCV. The SkyImager can be configured for different operational environments and network designs, from a standalone edge computing model to a fully integrated node in a distributed, cloud-computing based micro-grid. Preliminary results are presented using the imager on site at the National Renewable Energy Laboratory (NREL) in Golden, CO, USA during the fall of 2015 under a variety of cloud conditions.

WiseEye: Next Generation Expandable and Programmable Camera Trap Platform for Wildlife Research.

The widespread availability of relatively cheap, reliable and easy to use digital camera traps has led to their extensive use for wildlife research, monitoring and public outreach. Users of these units are, however, often frustrated by the limited options for controlling camera functions, the generation of large numbers of images, and the lack of flexibility to suit different research environments and questions. We describe the development of a user-customisable open source camera trap platform named ‘WiseEye’, designed to provide flexible camera trap technology for wildlife researchers. The novel platform is based on a Raspberry Pi single-board computer and compatible peripherals that allow the user to control its functions and performance. We introduce the concept of confirmatory sensing, in which the Passive Infrared triggering is confirmed through other modalities (i.e. radar, pixel change) to reduce the occurrence of false positives images. This concept, together with user-definable metadata, aided identification of spurious images and greatly reduced post-collection processing time. When tested against a commercial camera trap, WiseEye was found to reduce the incidence of false positive images and false negatives across a range of test conditions. WiseEye represents a step-change in camera trap functionality, greatly increasing the value of this technology for wildlife research and conservation management.