Bitters, N. C., & Sundaram, R. (2021, March), Integrated Project Platform for Student Research and Curriculum Development  Paper presented at 2021 ASEE North Central Section Conference, University of Toledo, Ohio. 10.18260/1-2--36343

\bibitem{asee_peer_36343}
  Bitters, N. C., \& Sundaram, R. (2021, March), \emph{Integrated Project Platform for Student Research and Curriculum Development}
  Paper presented at 2021 ASEE North Central Section Conference, University of Toledo, Ohio.
  10.18260/1-2--36343

Niklas Cyril Bitters and Ramakrishnan Sundaram.  "Integrated Project Platform for Student Research and Curriculum Development".  2021 ASEE North Central Section Conference, University of Toledo, Ohio, 2021, March.  ASEE Conferences, 2021.  https://peer.asee.org/36343 Internet.  11 Feb, 2025

\bibitem{asee_peer_36343}
  Niklas Cyril Bitters and Ramakrishnan Sundaram.
  "Integrated Project Platform for Student Research and Curriculum Development".
  \emph{2021 ASEE North Central Section Conference, University of Toledo, Ohio, 2021, March}.
  ASEE Conferences, 2021.
  https://peer.asee.org/36343 Internet.  11 Feb, 2025

@INPROCEEDINGS{asee_peer_36343
author = "Niklas Cyril Bitters and Ramakrishnan Sundaram"
title = "Integrated Project Platform for Student Research and Curriculum Development"
booktitle = "2021 ASEE North Central Section Conference"
year = "2021"
month = "March"
address = "University of Toledo, Ohio"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/36343}
number = {10.18260/1-2--36343}
}

TY  - CPAPER
AB  - This paper describes the setup of an integrated project platform to support student research and curriculum development in the burgeoning topics of artificial intelligence and machine learning.  The platform, which was proposed and developed by one of the authors as part of his master’s thesis research,  targets the modules for object classification and collision avoidance which are crucial stages in the design of intelligent and autonomous vehicles. Object classification consists of the appropriate neural network architecture for training and learning object characteristics from data sets. Collision avoidance utilizes a single camera to estimate the distance of the vehicle from the object. The hardware and software requirements of the integrated project platform are met by cost-effective resources.  In addition to serving as a testbed for student research in the design and operation of intelligent and autonomous vehicles, project activities on this platform will enable students to gain valuable laboratory and project experiences through the incorporation of exercises on this platform in appropriate graduate and undergraduate courses offered as part of the electrical and computer engineering (ECE) curriculum. For instance, graduate ECE courses in signal and image processing, neural networks, wireless system applications, and embedded system design would be suitable choices for project activities on this platform. Typical courses in the undergraduate ECE program are programming in C/C++/Python, digital logic design, circuits, electronics, test and measurement analysis. The platform can also engage and promote student participation across the ECE program in competitive design events for the next generation of intelligent and autonomous vehicles.
AU  - Niklas Cyril Bitters
AU  - Ramakrishnan Sundaram
CY  - University of Toledo, Ohio
DA  - 2021/03/19
PB  - ASEE Conferences
TI  - Integrated Project Platform for Student Research and Curriculum Development
UR  - https://peer.asee.org/36343
DO  - 10.18260/1-2--36343
ER  -