BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/Los_Angeles BEGIN:DAYLIGHT DTSTART:20190310T030000 TZOFFSETFROM:-0800 TZOFFSETTO:-0700 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:PDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20191103T010000 TZOFFSETFROM:-0700 TZOFFSETTO:-0800 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:PST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20200128T022901Z UID:5E67C2D9-EECB-44BD-90EF-60BA8CF3943C DTSTART;TZID=America/Los_Angeles:20190917T183000 DTEND;TZID=America/Los_Angeles:20190917T210000 DESCRIPTION:In this talk\, we focus on designing an IoT-based fire and smok e detection system using edge and cloud computing infrastructure along wit h deep learning. First\, an overview of IoT-based fire and smoke detection in smart cities will be discussed. Then a framework of an IoT-based syste m for fire and smoke detection is presented. An efficient model using deep learning for the IoT framework is proposed. This presentation covers appl icability of our proposed model in detection of fire and smoke for edge an d cloud computing.\n\nFinally\, we discuss the effectiveness of the propos ed model and make recommendations using industry best practices.\n\nSpeake rs of this talk are:\n\nTitle: IoT-based Fire and Smoke Detection in Smart Cities using Deep Learning\n\nSpeaker: Subhankar Dhar\, Dev Bhattacharya and Avid Farhoodfar\n\nTalk duration: 60 mins\n\nSubhankar Dhar subhankard har@gmail.com\n\nBio:\n\nSubhankar Dhar is a Professor with the School of Information Systems and Technology at San José State University. He is al so an affiliate faculty member of the Center for Smart Technology\, Comput ing\, and Complex Systems (STCCS) and Silicon Valley Center for Entreprene urship.\nHe advises early stage high tech startups and mentors entrepreneu rs. Subhankar's research interests are data science\, big data analytics\, mobile\, and cloud computing as well as wireless networks. In addition\, he is also interested in smart cities. He teaches a variety of courses inc luding computer networks\, distributed systems\, database systems\, and we b-based computing. His publications have appeared in reputed international journals and gave presentations to various international conferences. He serves as a member of the editorial board of International Journal of Busi ness Data Communications and Networking. He is a reviewer of papers for va rious international journals\, conferences and scholarly publications. He also served as a member of the organizing committee of various internation al conferences including IEEE ANTS\, IEEE Smart World Congress\, Workshop on Large Scale Complex Network Analysis. Subhankar has several years of in dustrial experience in software development\, consulting for high-tech ind ustries including product planning\, design\, and information systems mana gement. Subhankar has a Ph.D. in Statistics from the Univesity of South Fl orida and is a senior member of IEEE.\n\nDev Bhattacharya dev_bhattacharya @ieee.org\n\nBio:\n\nDev Bhattacharya\, is currently a chair of Consumer E lectronics Society of IEEE section of Santa Clara Valley. He is a technica l leader in various IoT systems and has over 20 years of experience in lea ding the system\, hardware and firmware development of complex IoTs and em bedded systems based on various sensors and devices.\n\nDev has a master ’s degree of Science in computer and systems engineering from Rensselaer Polytechnic Institute and has successfully led and managed development of system architecture\, system hardware\, firmware of consumer grade and co mplex embedded system products with sensors\, networking\, wireless and mu lti-media from concept to volume production at various companies including Cisco\, Intel\, Logitech\, Moog Crossbow and Rockwell Collins.\n\nAvid Fa rhoodfar avid.farhoodfar@gmail.com\n\nBio:\n\nAvid Farhoodfar\, PhD\, is c urrently a Faculty in the Computer Science Department at Sofia University at Palo Alto\, California. Formerly an Assistant chair in the Engineering Management Department\, as well as Faculty in the Electrical and Computer Engineering Department at the International Technological University (ITU) in San Jose.\n\nFor her doctorate in Condensed Matter Physics and Materia l Sciences at Queen’s University\, Dr. Farhoodfar modeled matter in quan tum size\, developing a modeling system using Quantum Monte Carlo approxim ation and Sherman Morrison optimization techniques.\n\nThe speakers of thi s talk are:\n\nCo-sponsored by: avid.farhoodfar@gmail.com\n\nAgenda: \n6:3 0pm - 7:00pm: Registration\, Food\, Networking\n7:00pm - 8:00pm: Talk\n8:0 0pm - 8:30pm: Q&A and Networking\n\nBldg: Nvidia Buliding E \, 2800 Scott Blvd \, Santa Clara\, California\, United States\, 95050 LOCATION:Bldg: Nvidia Buliding E \, 2800 Scott Blvd \, Santa Clara\, Calif ornia\, United States\, 95050 ORGANIZER:dev_bhattacharya@ieee.org SEQUENCE:20 SUMMARY:IEEE Consumer Electronics IoT-based Fire and Smoke Detection in Sma rt Cities using Deep Learning URL;VALUE=URI:https://events.vtools.ieee.org/m/198956 X-ALT-DESC:Description: <br /><p>In this talk\, we focus on designing an Io T-based fire and smoke detection system using edge and cloud computing inf rastructure along with deep learning. First\, an overview of IoT-based fir e and smoke detection in smart cities will be discussed. Then a framework of an IoT-based system for fire and smoke detection is presented. An effic ient model using deep learning for the IoT framework is proposed. This pre sentation covers applicability of our proposed model in detection of fire and smoke for edge and cloud computing.</p>\n<p>Finally\, we discuss the e ffectiveness of the proposed model and make recommendations using industry best practices.</p>\n<p>&nbsp\;</p>\n<p><strong>Speakers of this talk are :</strong></p>\n<p>&nbsp\;</p>\n<p style="font-weight: 400\;"><strong>Titl e: IoT-based Fire and Smoke Detection in Smart Cities using Deep Learning& nbsp\;</strong></p>\n<p style="font-weight: 400\;"><strong>Speaker: Subhan kar Dhar\, Dev Bhattacharya and Avid Farhoodfar</strong></p>\n<p style="fo nt-weight: 400\;"><strong><span style="font-weight: 400\;">Talk duration: 60 mins</span></strong></p>\n<p style="font-weight: 400\;">&nbsp\;</p>\n<p style="font-weight: 400\;"><strong>Subhankar Dhar&nbsp\; &nbsp\; &nbsp\;s ubhankardhar@gmail.com</strong></p>\n<p style="font-weight: 400\;">&nbsp\; </p>\n<p style="font-weight: 400\;">Bio:</p>\n<p style="font-weight: 400\; ">Subhankar Dhar is a Professor with the School of Information Systems and Technology at San Jos&eacute\; State University. He is also an affiliate faculty member of the Center for Smart Technology\, Computing\, and Comple x Systems (STCCS) and Silicon Valley Center for Entrepreneurship.&nbsp\;<b r />He advises early stage high tech startups and mentors entrepreneurs. S ubhankar's research interests are data science\, big data analytics\, mobi le\, and cloud computing as well as wireless networks. In addition\, he is also interested in smart cities. He teaches a variety of courses includin g computer networks\, distributed systems\, database systems\, and web-bas ed computing. His publications have appeared in reputed international jour nals and gave presentations to various international conferences. He serve s as a member of the editorial board of International Journal of Business Data Communications and Networking. He is a reviewer of papers for various international journals\, conferences and scholarly publications. He also served as a member of the organizing committee of various international co nferences including IEEE ANTS\, IEEE Smart World Congress\, Workshop on La rge Scale Complex Network Analysis. Subhankar has several years of industr ial experience in software development\, consulting for high-tech industri es including product planning\, design\, and information systems managemen t. Subhankar has a Ph.D. in Statistics from the Univesity of South Florida and is a senior member of IEEE.&nbsp\;&nbsp\;</p>\n<p style="font-weight: 400\;">&nbsp\;&nbsp\;</p>\n<p style="font-weight: 400\;"><strong>Dev Bhat tacharya&nbsp\; &nbsp\; &nbsp\; &nbsp\;dev_bhattacharya@ieee.org</strong>< /p>\n<p style="font-weight: 400\;">Bio:</p>\n<p style="font-weight: 400\;" >Dev Bhattacharya\, is currently&nbsp\;a chair of Consumer Electronics Soc iety of IEEE section of Santa Clara Valley. He is a technical leader in va rious IoT systems and has over 20 years of experience in leading the syste m\, hardware&nbsp\;and firmware development of complex IoTs and embedded s ystems based on various sensors and devices.</p>\n<p style="font-weight: 4 00\;">Dev has a master&rsquo\;s degree of Science in computer and systems engineering from Rensselaer Polytechnic Institute and has successfully led and managed development of system architecture\, system hardware\, firmwa re of consumer grade and complex embedded system products with sensors\, n etworking\, wireless and multi-media from concept to volume production at various companies including Cisco\, Intel\, Logitech\, Moog Crossbow and R ockwell Collins.</p>\n<p style="font-weight: 400\;">&nbsp\;</p>\n<p style= "font-weight: 400\;"><strong>Avid Farhoodfar&nbsp\; &nbsp\; avid.farhoodfa r@gmail.com</strong></p>\n<p style="font-weight: 400\;">Bio:</p>\n<p style ="font-weight: 400\;">Avid Farhoodfar\, PhD\, is currently&nbsp\;a Faculty in the&nbsp\;Computer Science Department at Sofia University at Palo Alto \, California. Formerly an Assistant chair in&nbsp\;the Engineering Manage ment Department\, as well as&nbsp\;Faculty in the&nbsp\;Electrical and Com puter Engineering Department at the&nbsp\;International Technological Univ ersity (ITU) in San Jose.</p>\n<p style="font-weight: 400\;">For her docto rate in Condensed Matter Physics and Material Sciences at Queen&rsquo\;s U niversity\, Dr. Farhoodfar modeled matter in quantum size\,&nbsp\;developi ng a modeling system&nbsp\;using Quantum Monte Carlo approximation and She rman Morrison optimization techniques.</p>\n<p>The speakers of this talk a re:</p>\n<p>&nbsp\;</p><br /><br />Agenda: <br /><p>6:30pm - 7:00pm: Regis tration\, Food\, Networking<br />7:00pm - 8:00pm: Talk<br />8:00pm - 8:30p m: Q&amp\;A and Networking</p>\n<p>&nbsp\;</p> END:VEVENT END:VCALENDAR