Salt Lake City, Utah
June 23, 2018
June 23, 2018
July 27, 2018
Electrical and Computer
Diversity
19
10.18260/1-2--29706
https://strategy.asee.org/29706
1280
Nick Barendt is an Adjunct Senior Instructor in the Department of Electrical Engineering and Computer Science at Case Western Reserve University, in Cleveland, Ohio. He earned his Bachelor of Science and Master of Science in Electrical Engineering and Applied Physics at Case Western Reserve University, in Cleveland, Ohio, in 1995 and 1998, respectively. He has worked in a variety of industries, including Industrial Automation, Robotics, Data Acquisition, and Test and Measurement. He has lead technology teams, professional service firms, and startups. He consults with industry and academia on business and technology. He is a Senior Member of the IEEE.
Nigamanth Sridhar is the Dean of the College of Graduate Studies and Professor in Electrical Engineering and Computer Science at Cleveland State University. His research interests are largely focused on computer science education, with specific attention to issues of equity in computer science courses taught in the K-12 school system. This work is supported by grants from the NSF and the Cleveland Foundation. He holds a Ph.D. in Computer Science from Ohio State University.
Kenneth A. Loparo is the Nord Professor of Engineering in the Department of Electrical Engineering and Computer Science and holds academic appointments in the Departments of Biomedical Engineering and Mechanical and Aerospace Engineering in the Case School of Engineering. He has received numerous awards including the Sigma Xi Research Award for contributions to stochastic control, the John S. Diekoff Award for Distinguished Graduate Teaching, the Tau Beta Pi Outstanding Engineering and Science Professor Award, the Undergraduate Teaching Excellence Award, the Carl F. Wittke Award for Distinguished Undergraduate Teaching and the Srinivasa P. Gutti Memorial Engineering Teaching Award. He was Associate Dean of Engineering from 1994 -1997 and chair of the Department of Systems Engineering from 1990 -1994 and the Department of Electrical Engineering and Computer Science from 2013-2017.
Loparo is a fellow of a Life Fellow of the IEEE and a fellow of AIMBE, his research interests include stability and control of nonlinear and stochastic systems with applications to large-scale systems; nonlinear filtering with applications to monitoring, fault detection, diagnosis, prognosis and reconfigurable control; information theory aspects of stochastic and quantized systems with applications to adaptive and dual control and the design of distributed autonomous control systems; the development of advanced signal processing and data analytics for monitoring and tracking of physiological behavior in health and disease.
This paper describes a one-semester course developed to address a gap in undergraduate engineering education – preparing students for creating and maintaining Internet-of-Things (IoT) products and services. The principles that drove the course content and organization are explained, along with a novel courseware delivery mechanism and organization to facilitate repeatability, as well as some additional tools the authors have found useful. The two-part organization of the IoT course content – building a complete IoT system, and then investigating system properties, behaviors, and concerns of that system – is explained in some depth. A detailed course outline illustrates the wide variety of technologies students gain hands-on experience with during the course, including embedded, web/cloud, mobile, analytics, load testing, security. A novel application of DevOps tools to incrementally deliver multi-platform (systems) solutions each week is discussed. Finally, lessons learned from several offerings of the course are presented, along with challenges, opportunities and successes, and directions for future work.
Barendt, N., & Sridhar, N., & Loparo, K. A. (2018, June), A New Course for Teaching Internet of Things: A Practical, Hands-on, and Systems-level Approach Paper presented at 2018 ASEE Annual Conference & Exposition , Salt Lake City, Utah. 10.18260/1-2--29706
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