Space Internet of Things (IoT): Technological Advances and Challenges
Prof. G.K. Giakos
Manhattan College, NYC
DEIB - Carlo Erba Room (Building 7)
Piazza Leonardo da Vinci, 32
May 10th, 2023
11.00 am
Contacts:
Cesare Svelto
Research Line:
Optical measurements and laser instrumentation
Manhattan College, NYC
DEIB - Carlo Erba Room (Building 7)
Piazza Leonardo da Vinci, 32
May 10th, 2023
11.00 am
Contacts:
Cesare Svelto
Research Line:
Optical measurements and laser instrumentation
Sommario
On May 10th, 2023 at 11.00 am G.K. Giakos, Professor and director of the Laboratory for Cognitive Imaging and Neuromorphic Engineering (CINE), at Manhattan College, NYC, will hold a seminar on "Space Internet of Things (IoT): Technological Advances and Challenges" in DEIB Carlo Erba Room.
Adoption of new interconnected, distributed space ecosystem, consisting of a suite of breakthrough technologies, would lead to the often termed as Space Internet of Things (IoT). These technologies encompass networks of satellites, nanosatellites, space orbital platforms, robots, scientific instrumentation, imaging and spectroscopic systems for object detection, tracking, identification, debris motoring, situational awareness. Space IOT network architectures are aiming at fast transmission, processing, and storage of large amount of data in Space, at reduced latency, low operational power, and robust security.
Space IoT require high-performance, reliable computing platforms that meet size, weight, and power constraints and can function in challenging environmental and operational conditions, including extreme temperature, high radiation, power loss, and disrupted communications and impaired navigation capabilities. Deploying faster, smarter, autonomous, and more power-efficient satellites in space is a significant advantage—for both situational awareness and space commercialization. On the other hand, computing processors have severe limitations, in terms of processing power, power consumption, speed and memory constraints, and agility. A brain inspired architecture enabled by the significant advances in Machine Learning (ML) and Deep Learning (DL) techniques, would emerge to play a major role in the automation of future space systems and space IoT. Such bioinspired architecture would combine both computation and memory emulating neurons and synapses, paving the way to meet the requirements of next-generation Artificial Intelligence (AI) systems Specifically, combining AI with bioinspired computing, like neuromorphic computing (NC), it would pave the way for overcoming constraints on power and speed to enable energy efficient and agile information, capable to process near-real time large volume, heterogeneous set of data. Examples highlighting importance of neuromorphic computing in Space IoT, towards the development of advanced and new capabilities energy efficient agile Space platforms capable to fast processing of big data, at reduced storage, low power, memory, and bandwidth will be presented and discussed.
Adoption of new interconnected, distributed space ecosystem, consisting of a suite of breakthrough technologies, would lead to the often termed as Space Internet of Things (IoT). These technologies encompass networks of satellites, nanosatellites, space orbital platforms, robots, scientific instrumentation, imaging and spectroscopic systems for object detection, tracking, identification, debris motoring, situational awareness. Space IOT network architectures are aiming at fast transmission, processing, and storage of large amount of data in Space, at reduced latency, low operational power, and robust security.
Space IoT require high-performance, reliable computing platforms that meet size, weight, and power constraints and can function in challenging environmental and operational conditions, including extreme temperature, high radiation, power loss, and disrupted communications and impaired navigation capabilities. Deploying faster, smarter, autonomous, and more power-efficient satellites in space is a significant advantage—for both situational awareness and space commercialization. On the other hand, computing processors have severe limitations, in terms of processing power, power consumption, speed and memory constraints, and agility. A brain inspired architecture enabled by the significant advances in Machine Learning (ML) and Deep Learning (DL) techniques, would emerge to play a major role in the automation of future space systems and space IoT. Such bioinspired architecture would combine both computation and memory emulating neurons and synapses, paving the way to meet the requirements of next-generation Artificial Intelligence (AI) systems Specifically, combining AI with bioinspired computing, like neuromorphic computing (NC), it would pave the way for overcoming constraints on power and speed to enable energy efficient and agile information, capable to process near-real time large volume, heterogeneous set of data. Examples highlighting importance of neuromorphic computing in Space IoT, towards the development of advanced and new capabilities energy efficient agile Space platforms capable to fast processing of big data, at reduced storage, low power, memory, and bandwidth will be presented and discussed.
Biografia
G.K. Giakos is professor and director of the Laboratory for Cognitive Imaging and Neuromorphic Engineering (CINE), at Manhattan College, NYC. His research is articulated in imaging technology innovation, through the integration of engineering, bioinspired vision, and artificial intelligence. He has been recognized for "his leadership efforts in advancing the professional goals of IEEE" by receiving the 2014 IEEE-USA Professional Achievement Award" in "recognition of his efforts in strengthening links between industry, government and academia". He has been elected Fellow of the IEEE and he is a Distinguished Fellow of the ONR. Dr. Giakos was recognized by the IEEE I&M Society as Top 70 Most Published Author of All Time (2021). His team is the first to explore polarimetric imaging using near infrared
(NIR) photon illumination for label-free lung cancer detection; his team pioneered the characterization of CZT semiconductors for flat panel radiography. Dr. Giakos invented a new class namely, the “Polarimetric Dynamic Vision Sensor p(DVS)s”. His Dissertation was on the "Detection of Longitudinal EM Waves in Open Media" under the direction of T. Koryu Ishii. He has been awarded with 20 patents and authored more than 250 peer-review papers. Fulbright Scholar award (2020-2022). He was elected Fellow of the Asia-Pacific Artificial Intelligence Association (2021). He promoted collaborations with US Air Force, Office of Naval Research, DOD, NASA, National Academy of Sciences, Lockheed Martin, Philips, Case Western, University Hospitals, Cleveland Clinic, Varian Medical Systems He serves as Chair of the New York Chapter of the IEEE Instrumentation and Measurement Society.
(NIR) photon illumination for label-free lung cancer detection; his team pioneered the characterization of CZT semiconductors for flat panel radiography. Dr. Giakos invented a new class namely, the “Polarimetric Dynamic Vision Sensor p(DVS)s”. His Dissertation was on the "Detection of Longitudinal EM Waves in Open Media" under the direction of T. Koryu Ishii. He has been awarded with 20 patents and authored more than 250 peer-review papers. Fulbright Scholar award (2020-2022). He was elected Fellow of the Asia-Pacific Artificial Intelligence Association (2021). He promoted collaborations with US Air Force, Office of Naval Research, DOD, NASA, National Academy of Sciences, Lockheed Martin, Philips, Case Western, University Hospitals, Cleveland Clinic, Varian Medical Systems He serves as Chair of the New York Chapter of the IEEE Instrumentation and Measurement Society.
