The Internet-of-Things (IoT) refers to the connection of numerous sensors and devices through a process that involves Edge and Cloud computing. The world connected through IoT will incite new waves of technological revolution that modify our homes, highways, work places, communities, and economy. Examples include smart buildings/grids and smart urban traffic control.
Specifically, intelligent and autonomous mobiles such as drones and cars that optimally navigate within roads or air are emerging rapidly. We will experience a semi-autonomous world while moving from the current non-autonomous state to a fully autonomous one—a transition period that may take years if not decades. On the highways of future, to minimize the risk of accidents, autonomous vehicles should optimally drive in conjunction with non-autonomous vehicles via control signals received from Cloud or Edge processing units—a procedure that exploits big data collected from numerous sensors. Location-based data reduction, and data-propelled driving behavior assessment via deep learning should be tackled to move the implementation of autonomous mobiles one step closer to reality.
This talk looks at both sides of the coin: first, it discusses fundamental problems in positioning sensor design to enable high performance simultaneous vehicle-to-vehicle (V2V) connectivity and localization. Next, it assesses implementation problems for the operation of autonomous vehicles in a semi-autonomous world.
Host: Prof. Elke Rundensteiner, Computer Science
Biography: Professor Reza Zekavat received his PhD from Colorado State University in 2002, when he joined Michigan Tech. He is the author of the textbook "Electrical Engineering: Concepts and Applications" published by Pearson, and the editor of the book “Handbook of Position Location: Theory, Practice and Advances,” published by Wiley/IEEE. He holds a patent on an active Wireless Remote Positioning System. Zekavat has also co-authored two books “Multi-Carrier Technologies for Wireless Communications,” published by Kluwer, and “High Dimensional Data Analysis,” published by VDM Verlag.
Zekavat is the founder of the wireless positioning lab at Michigan Tech. The lab equipment and research has been supported by the National Science Foundation, the Army Research Labs, and National Instruments. Zekavat’s research interests are in wireless localization, big data and internet of things, blind signal separation, feature extraction, and neural networking. He is active on the technical program committees for several IEEE international conferences, serving as a committee chair or member. He has served on the editorial board of many Journals including IET Communications, IET Wireless Sensor System, Springer International Journal on Wireless Networks, and GSTF Journal on Mobile Comm.; he has been on the Executive Committee of multiple IEEE conferences.