Abstract:
The emergence of Internet of Things (IoT) coupled with artificial intelligence has changed the way we carry out everyday business to become smarter, productive and much safer. There have been many recent revolutions that IoT brought to a wide range of business and industrial sectors including smart cities, healthcare, emergency response, intelligent transportation, industrial automation and agriculture. Drones also have invaded our skies to provide unprecedented opportunities and see things like never before. In this tutorial, I am going to provide a quick update on the status quo of how IoT impacted our lives and what are the opportunities yet to unfold at the current progress pace. Then, I will elaborate on one application enabled by the convergence of IoT and machine learning in the agriculture domain using autonomous drones. Agriculture is ripe with opportunities to incorporate AI analytics, specifically novel and ever-growing deep learning analytics. Visual information for analysis can be collected autonomously using appropriately equipped and programmed mobile robots (drones & ground robots). The tutorial will shed the light on the technical details involving yield estimation using deep learning and Mask R-CNN for object detection and tracking, weed detection, crop disease classification, and fruit ripeness prediction. Pending resource availability, we will do some quick hands-on to better understand the processing pipeline and dataflow across the dataflow stack.
Professor: Khalid Elgazzar, CRC, IEEE Senior Member
Ontario Tech, Canada
Biography:
Dr. Khalid Elgazzar, is a Canada Research Chair and assistant professor with the Faculty of Engineering and Applied Science at Ontario Tech University, Canada and an holds and adjunct assistant professor at Queen’s University where he also received his PhD degree in Computer Science from the School of Computing in 2013. He is the founder and director of the IoT Research Lab at Ontario Tech University. Prior to joining Ontario Tech, he was an assistant professor at University of Louisiana at Lafayette and an NSERC postdoctoral fellow at Carnegie Mellon School of Computer Science. Dr. Elgazzar named the recipient of the outstanding achievement in sponsored research award from UL Lafayette in 2017 and the distinguished research award from Queen’s University in 2014. He also received several recognition and best paper award at top international venues. Dr. Elgazzar is a rising world leader in the areas of Internet of Things (IoT), computer systems, real-time data analytics, and mobile computing. Dr. Elgazzar is currently an associate editor for Springer Peer-to-Peer Networking and Applications Journal and Wireless Communications and Mobile Computing. He also chaired a number of IEEE conferences and symposia on mobile computing, communications and IoT. Dr. Elgazzar is Senior IEEE Member and an active volunteer in technical program committees and organizing committees in both IEEE and ACM events.