scholarly journals Democratising Design in Scientific Innovation: Application of an Open Value Network to Open Source Hardware Design

2016 ◽  
Author(s):  
Maria Frangos ◽  
Joshua M. Pearce ◽  
Tiberius Brastaviceanu ◽  
Ahmed Akl Mahmoud ◽  
Abran Khalid
Author(s):  
Jean-François Boujut ◽  
Franck Pourroy ◽  
Philippe Marin ◽  
Jason Dai ◽  
Gilles Richardot

AbstractOpen source design of hardware products is an emerging phenomenon that takes more and more importance today's in the society. However, open source (hardware) design implies a tremendous change in both design practices and philosophy because it is partly related to the movements of creative commons and the sharing economy. From this perspective one could think that participation is crucial in the success of open source design projects. In this paper, we analyse 9 case studies in the light of 3 hypotheses. If many studies highlight the potential of the crowd as a resource for design tasks, our study shows that for open source design communities the participation is not massive. In this study, we used an activity-based approach to build our model. As open source design processes are fairly unstructured and based on voluntary participation, it is impossible to adopt a classical task-based model. With the help of this model, we were able evaluate the overall size of the active community, the participation rate with regards to the activities. This study paves the way to deeper and extensive studies on how to support communities engaged in open source design of hardware products.


2017 ◽  
Vol 2 (1) ◽  
pp. 80-87
Author(s):  
Puyda V. ◽  
◽  
Stoian. A.

Detecting objects in a video stream is a typical problem in modern computer vision systems that are used in multiple areas. Object detection can be done on both static images and on frames of a video stream. Essentially, object detection means finding color and intensity non-uniformities which can be treated as physical objects. Beside that, the operations of finding coordinates, size and other characteristics of these non-uniformities that can be used to solve other computer vision related problems like object identification can be executed. In this paper, we study three algorithms which can be used to detect objects of different nature and are based on different approaches: detection of color non-uniformities, frame difference and feature detection. As the input data, we use a video stream which is obtained from a video camera or from an mp4 video file. Simulations and testing of the algoritms were done on a universal computer based on an open-source hardware, built on the Broadcom BCM2711, quad-core Cortex-A72 (ARM v8) 64-bit SoC processor with frequency 1,5GHz. The software was created in Visual Studio 2019 using OpenCV 4 on Windows 10 and on a universal computer operated under Linux (Raspbian Buster OS) for an open-source hardware. In the paper, the methods under consideration are compared. The results of the paper can be used in research and development of modern computer vision systems used for different purposes. Keywords: object detection, feature points, keypoints, ORB detector, computer vision, motion detection, HSV model color


2020 ◽  
Author(s):  
K. Thirumalesh ◽  
Salgeri Puttaswamy Raju ◽  
Hiriyur Mallaiah Somashekarappa ◽  
Kumaraswamy Swaroop

2021 ◽  
Vol 13 (15) ◽  
pp. 8182
Author(s):  
José María Portalo ◽  
Isaías González ◽  
Antonio José Calderón

Smart grids and smart microgrids (SMGs) require proper monitoring for their operation. To this end, measuring, data acquisition, and storage, as well as remote online visualization of real-time information, must be performed using suitable equipment. An experimental SMG is being deployed that combines photovoltaics and the energy carrier hydrogen through the interconnection of photovoltaic panels, electrolyser, fuel cell, and load around a voltage bus powered by a lithium battery. This paper presents a monitoring system based on open-source hardware and software for tracking the temperature of the photovoltaic generator in such an SMG. In fact, the increases in temperature in PV modules lead to a decrease in their efficiency, so this parameter needs to be measured in order to monitor and evaluate the operation. Specifically, the developed monitoring system consists of a network of digital temperature sensors connected to an Arduino microcontroller, which feeds the acquired data to a Raspberry Pi microcomputer. The latter is accessed by a cloud-enabled user/operator interface implemented in Grafana. The monitoring system is expounded and experimental results are reported to validate the proposal.


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