FPGA remote laboratory: experience of a shared laboratory between UPNA and UNIFESP

Mayoz, Cándido Aramburu; Beraldo, Ana Lúcia da Silva; Villar-Martinez, Aitor; Rodríguez-Gil, Luis; Seron, Wilson; Orduña, Pablo

doi:10.1109/taee46915.2020.9163773

Cited by 25 publications

(9 citation statements)

References 11 publications

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“…The methodology is based on the previous collaborative experience between the Public University of Navarra and LabsLand [8]. LabsLand is a company that provides access to educational laboratories and equipment, online.…”

Section: Methodsmentioning

confidence: 99%

Learning CAN bus communication with a remote laboratory

Villar

Rodríguez-Gil

Orduña

2022

2022 IEEE Global Engineering Education Conference (EDUCON)

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CAN bus is a very important communications protocol. Its usage is extended to many applications and it is key to know some fundamentals in an introductory course to industrial communications. A collaborative experience between the Public University of Navarra has permitted students of Industrial Technologies Engineering and Electrical and Electronic Engineering to access a remote laboratory where they can progress in the development of a project where they must implement a CAN bus client and server for monitoring the parameters of a vehicle. More than twenty parameters can be monitored and the remote laboratory is 24 hours a day accessible, which permits students to work at home and progress more in the multiprotocol project they develop at the university. The interface and some code examples are shown, along with some statistics that demonstrate the utilization of the tool by the students with the aid of some evaluation measurements taken by the lecturer. Finally, a survey was performed to the students in order to understand better the potential of the remote laboratory assisted teaching as well as to know where to improve it in the next future.

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Section: Methodsmentioning

confidence: 99%

Learning CAN bus communication with a remote laboratory

Villar

Rodríguez-Gil

Orduña

2022

2022 IEEE Global Engineering Education Conference (EDUCON)

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“…Therefore, students learn to develop hybrid system and understand that it is possible that some phases relating to the object recognition process can be performed with software implementation and others with hardware architectures. This would not only contribute to improving student training for topics as relevant to Industry 4.0 as computer vision, but it would also provide students with highly practical specialized knowledge once they are working in the industry [35].…”

Section: Related Workmentioning

confidence: 99%

An FPGA‐based tool for supporting the design, modeling, and evaluation of hybrid object recognition systems on computer engineering courses

Guzmán‐Ramírez,

Garcia,

Pacheco

et al. 2024

Comp Applic In Engineering

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The field of computer vision is characterized by computationally intensive algorithms and techniques with strict real‐time requirements. Field programmable gate arrays (FPGAs) are based on a concurrent paradigm which allows the design of efficient hardware architectures and has positioned FPGAs as an ideal device for implementing compute‐intensive applications. For this reason, FPGA technology has had a great impact in areas such as computer vision, where one of the main objectives for researchers working in this field is to create efficient automatic object recognition systems. Therefore, the need to provide undergraduates with the necessary skills to design FPGA‐based object recognition systems is evident. With this aim in mind, it is essential that specialization courses related to the design of these systems include the required resources for the student to apply the theoretical knowledge in solving practical problems. In this article, we present a development tool designed to help students, teachers, and researchers during the design‐modeling‐implementation process of object recognition systems based on FPGAs. The proposed tool operates under a modular approach as this facilitates the working on any of the phases of a recognition system and it is considered as a hybrid because the other phases can be developed using a software language. An empirical evaluation involving undergraduates enrolled in a Computer Engineering program was conducted to create a hardware architecture for the DAISY descriptor that uses the homogeneous features of objects immersed in images to produce an efficient representation. By considering similar descriptors such as Scale‐Invariant Feature Transform (SIFT) and Histogram of Oriented Gradients (HOG), DAISY is computed by convolving orientation maps instead of using weighted sums of gradient norms, which offers the same kind of invariance at a lower computational cost for the dense case. The results obtained during such an evaluation indicated that students consider this FPGA‐based tool to be an alternative to receiving practical training on designing systems for solving problems related to the area of object recognition.

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“…Remote laboratories composed of reconfigurable FPGA devices were presented in [15], deployed and shared by institutions in Spain and Brazil to facilitate student access to this technology.…”

Section: Related Workmentioning

confidence: 99%

Remote Laboratory for E-Learning of Systems on Chip and Their Applications to Nuclear and Scientific Instrumentation

et al. 2021

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Configuring and setting up a remote access laboratory for an advanced online school on fully programmable System-on-Chip (SoC) proved to be an outstanding challenge. The school, jointly organized by the International Centre for Theoretical Physics (ICTP) and the International Atomic Energy Agency (IAEA), focused on SoC and its applications to nuclear and scientific instrumentation and was mainly addressed to physicists, computer scientists and engineers from developing countries. The use of e-learning tools, which some of them adopted and others developed, allowed the school participants to directly access both integrated development environment software and programmable SoC platforms. This facilitated the follow-up of all proposed exercises and the final project. During the four weeks of the training activity, we faced and overcame different technology and communication challenges, whose solutions we describe in detail together with dedicated tools and design methodology. We finally present a summary of the gained experience and an assessment of the results we achieved, addressed to those who foresee to organize similar initiatives using e-learning for advanced training with remote access to SoC platforms.

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FPGA remote laboratory: experience of a shared laboratory between UPNA and UNIFESP

Cited by 25 publications

References 11 publications

Learning CAN bus communication with a remote laboratory

Learning CAN bus communication with a remote laboratory

An FPGA‐based tool for supporting the design, modeling, and evaluation of hybrid object recognition systems on computer engineering courses

Remote Laboratory for E-Learning of Systems on Chip and Their Applications to Nuclear and Scientific Instrumentation

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