BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:Australia/Melbourne BEGIN:DAYLIGHT DTSTART:20251005T030000 TZOFFSETFROM:+1000 TZOFFSETTO:+1100 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=10 TZNAME:AEDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20250406T020000 TZOFFSETFROM:+1100 TZOFFSETTO:+1000 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=4 TZNAME:AEST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20250711T020912Z UID:C24D03F1-83F0-4004-99E9-1CA1EC6E8009 DTSTART;TZID=Australia/Melbourne:20250708T150000 DTEND;TZID=Australia/Melbourne:20250708T160000 DESCRIPTION:Abstract:\n\nGiven the lack of generic assessments for the posi tion and shape behavior of particles under acoustic levitation\, a system was conceived to study these behaviors using both classical and advanced A I-based methods. Two acoustic levitators were designed and successfully le vitated particles\, while a camera-based visual system was developed to ca pture their movement. A classical image pixel filter-based particle tracki ng system and an aspect ratio-based shape analysis system were created. Th is system was validated using an Artificial Neural Network (ANN)-based sha pe classification algorithm and a YOLO v4-enabled position tracking system . The results showed nearly 100% accuracy in particle motion tracking with the classical method\, and 90% accuracy in particle detection through YOL O-v4. The shape analysis system\, utilizing the ANN\, achieved highly accu rate tracking of particle orientation and aspect ratio\, ensuring precise behavior monitoring. This integration with the levitation control system p rovided real-time feedback\, allowing for enhanced control and manipulatio n of the levitated particles\, with the ability to analyze particle dynami cs and ensure stable levitation.\n\nAbout the Speaker:\n\nVinay Adithya Su brahmanya is a Mechatronics Engineer with extensive expertise in automatio n\, AI-driven solutions\, and industrial applications. He is currently eng aged in cutting-edge research involving acoustic levitation and particle b ehavior analysis\, combining classical image processing and AI techniques to develop novel systems for particle tracking and shape analysis. Vinay h as previously worked as a Territory Account Manager at MathWorks\, where h e played a pivotal role in driving technology adoption and strategic sales for automation and control solutions. With a solid background in engineer ing\, business development\, and project management\, Vinay’s work focus es on creating innovative solutions to complex problems in manufacturing\, automation\, and smart systems. He is also passionate about exploring AI applications in real-world engineering challenges\, contributing to advanc ements in smart factory systems and material handling.\n\nCo-sponsored by: Deakin University\n\nSpeaker(s): Vinay\n\nRoom: KE3.208\, Bldg: KE\, Pigd ons road\, Geelong\, Victoria\, Australia\, 3216 LOCATION:Room: KE3.208\, Bldg: KE\, Pigdons road\, Geelong\, Victoria\, Aus tralia\, 3216 ORGANIZER:hamid.abdi@deakin.edu.au SEQUENCE:2 SUMMARY: "Acoustic Levitation: Unveiling Particle Dynamics and Advanced Con trol through Hybrid AI" URL;VALUE=URI:https://events.vtools.ieee.org/m/490372 X-ALT-DESC:Description: <br /><div id="x_model-response-message-contentr_b4 6139d1d75e148d" class="elementToProof">\n<div class="elementToProof">\n<p> <strong>Abstract:</strong></p>\n</div>\n<div class="elementToProof">\n<p>G iven the lack of generic assessments for the position and shape behavior o f particles under acoustic levitation\, a system was conceived to study th ese behaviors using both classical and advanced AI-based methods. Two acou stic levitators were designed and successfully levitated particles\, while a camera-based visual system was developed to capture their movement. A c lassical image pixel filter-based particle tracking system and an aspect r atio-based shape analysis system were created. This system was validated u sing an Artificial Neural Network (ANN)-based shape classification algorit hm and a YOLO v4-enabled position tracking system. The results showed near ly 100% accuracy in particle motion tracking with the classical method\, a nd 90% accuracy in particle detection through YOLO-v4. The shape analysis system\, utilizing the ANN\, achieved highly accurate tracking of particle orientation and aspect ratio\, ensuring precise behavior monitoring. This integration with the levitation control system provided real-time feedbac k\, allowing for enhanced control and manipulation of the levitated partic les\, with the ability to analyze particle dynamics and ensure stable levi tation.</p>\n</div>\n<div class="elementToProof">\n<p><strong>About the Sp eaker:</strong></p>\n</div>\n<div class="elementToProof">\n<p>Vinay Adithy a Subrahmanya is a Mechatronics Engineer with extensive expertise in autom ation\, AI-driven solutions\, and industrial applications. He is currently engaged in cutting-edge research involving acoustic levitation and partic le behavior analysis\, combining classical image processing and AI techniq ues to develop novel systems for particle tracking and shape analysis. Vin ay has previously worked as a Territory Account Manager at MathWorks\, whe re he played a pivotal role in driving technology adoption and strategic s ales for automation and control solutions. With a solid background in engi neering\, business development\, and project management\, Vinay&rsquo\;s w ork focuses on creating innovative solutions to complex problems in manufa cturing\, automation\, and smart systems. He is also passionate about expl oring AI applications in real-world engineering challenges\, contributing to advancements in smart factory systems and material handling.</p>\n</div >\n</div>\n<div class="elementToProof">\n<p>&nbsp\;</p>\n</div> END:VEVENT END:VCALENDAR