Two open source designs for a low‐cost operant chamber using Raspberry Pi™

2019 ◽  
Vol 111 (3) ◽  
pp. 508-518
Author(s):  
Katelyn Gurley
Electronics ◽  
2018 ◽  
Vol 7 (12) ◽  
pp. 404 ◽  
Author(s):  
Daniel Costa ◽  
Cristian Duran-Faundez

With the increasing availability of affordable open-source embedded hardware platforms, the development of low-cost programmable devices for uncountable tasks has accelerated in recent years. In this sense, the large development community that is being created around popular platforms is also contributing to the construction of Internet of Things applications, which can ultimately support the maturation of the smart-cities era. Popular platforms such as Raspberry Pi, BeagleBoard and Arduino come as single-board open-source platforms that have enough computational power for different types of smart-city applications, while keeping affordable prices and encompassing many programming libraries and useful hardware extensions. As a result, smart-city solutions based on such platforms are becoming common and the surveying of recent research in this area can support a better understanding of this scenario, as presented in this article. Moreover, discussions about the continuous developments in these platforms can also indicate promising perspectives when using these boards as key elements to build smart cities.


Author(s):  
Chaitra Hegde ◽  
Zifan Jiang ◽  
Pradyumna Byappanahalli Suresha ◽  
Jacob Zelko ◽  
Salman Seyedi ◽  
...  

AbstractWith the recent COVID-19 pandemic, healthcare systems all over the world are struggling to manage the massive increase in emergency department (ED) visits. This has put an enormous demand on medical professionals. Increased wait times in the ED increases the risk of infection transmission. In this work we present an open-source, low cost, off-body system to assist in the automatic triage of patients in the ED based on widely available hardware. The system initially focuses on two symptoms of the infection fever and cyanosis. The use of visible and far-infrared cameras allows for rapid assessment at a 1m distance, thus reducing the load on medical staff and lowering the risk of spreading the infection within hospitals. Its utility can be extended to a general clinical setting in non-emergency times as well to reduce wait time, channel the time and effort of healthcare professionals to more critical tasks and also prioritize severe cases.Our system consists of a Raspberry Pi 4, a Google Coral USB accelerator, a Raspberry Pi Camera v2 and a FLIR Lepton 3.5 Radiometry Long-Wave Infrared Camera with an associated IO module. Algorithms running in real-time detect the presence and body parts of individual(s) in view, and segments out the forehead and lip regions using PoseNet. The temperature of the forehead-eye area is estimated from the infrared camera image and cyanosis is assessed from the image of the lips in the visible spectrum. In our preliminary experiments, an accuracy of 97% was achieved for detecting fever and 77% for the detection of cyanosis, with a sensitivity of 91% and area under the receiver operating characteristic curve of 0.91. Heart rate and respiratory effort are also estimated from the visible camera.Although preliminary results are promising, we note that the entire system needs to be optimized before use and assessed for efficacy. The use of low-cost instrumentation will not produce temperature readings and identification of cyanosis that is acceptable in many situations. For this reason, we are releasing the full code stack and system design to allow others to rapidly iterate and improve the system. This may be of particular benefit in low-resource settings, and low-to-middle income countries in particular, which are just beginning to be affected by COVID-19.


Sensors ◽  
2021 ◽  
Vol 21 (17) ◽  
pp. 5812
Author(s):  
Andres Henao ◽  
Philippe Apparicio ◽  
David Maignan

During the last decade, bicycles equipped with sensors became an essential tool for research, particularly for studies analyzing the lateral passing distance between motorized vehicles and bicycles. The objective of this article is to describe a low-cost open-source sensor called one metre plus (1m+) capable of measuring lateral passing distance, registering the geographical position of the cyclist, and video-recording the trip. The plans, codes, and schematic design are open and therefore easily accessible for the scientific community. This study describes in detail the conceptualization process, the characteristics of the device, and the materials from which they are made. The study also provides an evaluation of the product and describes the sensor’s functionalities and its field of application. The objective of this project is to democratize research and develop a platform/participative project that offers tools to researchers worldwide, in order to standardize knowledge sharing and facilitate the comparability of results in various contexts.


Electronics ◽  
2019 ◽  
Vol 8 (6) ◽  
pp. 652 ◽  
Author(s):  
José R. García-Martínez ◽  
Juvenal Rodríguez-Reséndiz ◽  
Edson E. Cruz-Miguel

The velocity profiles are used in the design of trajectories in motion control systems. It is necessary to design smoother movements to avoid high stress in the motor. In this paper, the rate of change in acceleration value is used to develop an S-curve velocity profile which presents an acceleration and deceleration stage smoother than the trapezoidal velocity profile reducing the error at the end of the duty-cycle pre-established in one degree of freedom (DoF) application. Furthermore, a new methodology is developed to generate a seven-segment profile that works with negative velocity and displacement constraints applying an open source architecture in a hybrid electronic platform compounded by a system on a chip (SoC) Raspberry Pi 3 and a field programmable gate array (FPGA). The performance of the motion controller is measured through the comparison of the error obtained in real-time application with a trapezoidal velocity profile. As a result, a low-cost platform and an open architecture system are achieved.


Electronics ◽  
2019 ◽  
Vol 8 (8) ◽  
pp. 822 ◽  
Author(s):  
Lawrence Oriaghe Aghenta ◽  
Mohammad Tariq Iqbal

Supervisory Control and Data Acquisition (SCADA) is a technology for monitoring and controlling distributed processes. SCADA provides real-time data exchange between a control/monitoring centre and field devices connected to the distributed processes. A SCADA system performs these functions using its four basic elements: Field Instrumentation Devices (FIDs) such as sensors and actuators which are connected to the distributed process plants being managed, Remote Terminal Units (RTUs) such as single board computers for receiving, processing and sending the remote data from the field instrumentation devices, Master Terminal Units (MTUs) for handling data processing and human machine interactions, and lastly SCADA Communication Channels for connecting the RTUs to the MTUs, and for parsing the acquired data. Generally, there are two classes of SCADA hardware and software; Proprietary (Commercial) and Open Source. In this paper, we present the design and implementation of a low-cost, Open Source SCADA system by using Thinger.IO local server IoT platform as the MTU and ESP32 Thing micro-controller as the RTU. SCADA architectures have evolved over the years from monolithic (stand-alone) through distributed and networked architectures to the latest Internet of Things (IoT) architecture. The SCADA system proposed in this work is based on the Internet of Things SCADA architecture which incorporates web services with the conventional (traditional) SCADA for a more robust supervisory control and monitoring. It comprises of analog Current and Voltage Sensors, the low-power ESP32 Thing micro-controller, a Raspberry Pi micro-controller, and a local Wi-Fi Router. In its implementation, the current and voltage sensors acquire the desired data from the process plant, the ESP32 micro-controller receives, processes and sends the acquired sensor data via a Wi-Fi network to the Thinger.IO local server IoT platform for data storage, real-time monitoring and remote control. The Thinger.IO server is locally hosted by the Raspberry Pi micro-controller, while the Wi-Fi network which forms the SCADA communication channel is created using the Wi-Fi Router. In order to test the proposed SCADA system solution, the designed hardware was set up to remotely monitor the Photovoltaic (PV) voltage, current, and power, as well as the storage battery voltage of a 260 W, 12 V Solar PV System. Some of the created Human Machine Interfaces (HMIs) on Thinger.IO Server where an operator can remotely monitor the data in the cloud, as well as initiate supervisory control activities if the acquired data are not in the expected range, using both a computer connected to the network, and Thinger.IO Mobile Apps are presented in the paper.


2018 ◽  
Vol 50 (6) ◽  
pp. 2523-2530 ◽  
Author(s):  
James D. O’Leary ◽  
Olivia F. O’Leary ◽  
John F. Cryan ◽  
Yvonne M. Nolan

2020 ◽  
Author(s):  
John P. Efromson ◽  
Shuai Li ◽  
Michael D. Lynch

AbstractAutosampling from bioreactors reduces error, increases reproducibility and offers improved aseptic handling when compared to manual sampling. Additionally, autosampling greatly decreases the hands-on time required for a bioreactor experiment and enables sampling 24 hrs a day. We have designed, built and tested a low cost, open source, automated bioreactor sampling system, the BioSamplr. The BioSamplr can take up to ten samples from a bioreactor at a desired sample interval and cools them to a desired temperature. The device, assembled from low cost and 3D printed components, is controlled wirelessly by a Raspberry Pi, and records all sampling data to a log file. The cost and accessibility of the BioSamplr make it useful for laboratories without access to more expensive and complex autosampling systems.


PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0251812
Author(s):  
Arunkumar Arumugam ◽  
Cole Markham ◽  
Saurabh S. Aykar ◽  
Barbara Van Der Pol ◽  
Paula Dixon ◽  
...  

Growth in open-source hardware designs combined with the decreasing cost of high-quality 3D printers have supported a resurgence of in-house custom lab equipment development. Herein, we describe a low-cost (< $400), open-source CO2 incubator. The system is comprised of a Raspberry Pi computer connected to a 3D printer controller board that has controls for a CO2 sensor, solenoid valve, heater, and thermistors. CO2 is supplied through the sublimation of dry ice stored inside a thermos to create a sustained 5% CO2 supply. The unit is controlled via G-Code commands sent by the Raspberry Pi to the controller board. In addition, we built a custom software application for remote control and used the open-source Grafana dashboard for remote monitoring. Our data show that we can maintain consistent CO2 and temperature levels for over three days without manual interruption. The results from our culture plates and real-time PCR indicate that our incubator performed equally well when compared to a much more expensive commercial CO2 incubator. We have also demonstrated that the antibiotic susceptibility assay can be performed in this low-cost CO2 incubator. Our work also indicates that the system can be connected to incubator chambers of various chamber volumes.


2016 ◽  
Author(s):  
Maxime Leblanc-Latour ◽  
Craig Bryan ◽  
Andrew Pelling

ABSTRACTOpen-source lab equipment is becoming more widespread with the popularization of fabrication tools such as 3d-printers, laser cutters, CNC machines, open source microcontrollers and open source software. Although many pieces of common laboratory equipment have been developed, software control of these items is sometimes lacking. Specifically, control software that can be easily implemented and enable user-input and control over multiple platforms (PC, smartphone, web, etc.). The aim of this proof-of-principle study was to develop and implement software for the control of a low-cost, 3d-printed microscope. Here, we present two approaches, which enable microscope control by exploiting the functionality of the social media platform Twitter or player actions inside of the videogame Minecraft. The microscope was constructed from a modified web-camera and implemented on a Raspberry Pi computer. Four aspects of microscope control were tested, including single image capture, focus control and time-lapse imaging. The Twitter-embodiment enabled users to send “tweets” directly to the microscope. Image data acquired by the microscope was then returned to the user through a Twitter reply and stored permanently on the photo-sharing platform Flickr, along with any relevant metadata. Local control of the microscope was also implemented by utilizing the video game Minecraft, in situations where Internet connectivity is not present or stable. A virtual laboratory was constructed inside the Minecraft world and player actions inside the laboratory were linked to specific microscope functions. Here, we present the methodology and results of these experiments and discuss possible limitations and future extensions of this work.


Author(s):  
John J. Chelsom ◽  
Jay H. Chelsom

We describe a series of experiments which test the performance and scalability of an XML records system deployed on a Beowulf cluster of open source XML databases. Using the open source cityEHR health records system as an example, we first ran experiments to determine the feasibility and optimal size of database instances running on Raspberry Pi and low-cost Intel computers. We describe the implementation of a Data Access Layer for create, read, query and delete operations, using XForms submissions, which encapsulates all database access. We then present the results of testing the scalability and performance of this implementation on clusters of one to sixteen physical database nodes. We conclude that Beowulf clustering provides an effective and cost-efficient mechanism for scaling XML records systems.


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