Speaker "Sam Siewert" Details Back



Drone Net - Multi-modal sensor network for sUAS shared air space safety and security


The challenge and opportunity presented by use of UAS "drones" in the national airspace has historic significance. The FAA estimates that by 2020 the drone market will be $98 billion with 7 million drones added annually. How drones ranging from professional service to hobby will safely share airspace is unclear. Preliminary research at Embry Riddle to develop a drone detector, which can be placed on rooftops and networked with other detectors and information services, has shown that multi-spectral electro-optical/infrared detection is quite effective. Our team is using Big Data with machine vision and machine learning systems in an EO/IR, acoustic and active RADAR sensor fusion system. The Big Data and machine vision and learning architecture provides real-time object detection for aircraft and drones using salient object detection algorithms both on embedded instruments and networked to Cloud based high performance computing. We'll present the intelligence, power efficiency and real-time processing advantages our architecture provides compared to traditional systems.


Dr. Sam Siewert has studied at University of California Berkeley, University of Notre Dame, University of Houston and University of Colorado Boulder and has a BS in Aerospace and Mechanical Engineering and MS/Ph.D. in Computer Science. He has worked in the computer engineering industry for twenty four years before starting an academic career in 2012. Half of his time was spent on NASA space exploration programs and the other half of that time on commercial product development for high performance networking and storage systems. In 2014 Dr. Siewert joined Embry Riddle Aeronautical University Prescott as full time faculty and retains an adjunct professor role at University of Colorado Boulder. Research interests include big data, real-time theory, machine vision and machine learning. Dr. Siewert was a co-founder of the Embedded Systems Engineering program at University of Colorado.