BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:NZ BEGIN:DAYLIGHT DTSTART:20190929T030000 TZOFFSETFROM:+1200 TZOFFSETTO:+1300 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=9 TZNAME:NZDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20190407T020000 TZOFFSETFROM:+1300 TZOFFSETTO:+1200 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=4 TZNAME:NZST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20190528T220233Z UID:361B50E0-F181-45F7-9A3C-4B2FA276E804 DTSTART;TZID=NZ:20190523T130000 DTEND;TZID=NZ:20190523T140000 DESCRIPTION:Ambient intelligence: convergence of artificial intelligence\, machine learning\, biometrics\, cloud-computing\, and internet-of-thing\n\ nAdaptability and advanced services for ambient intelligence require an in telligent technological support for understanding the current needs and th e desires of users in the interactions with the environment for their dail y use\, as well as for understanding the current status of the environment also in complex situations. This infrastructure constitutes an essential base for smart living. Various technologies are nowadays converging to sup port the creation of efficient and effective infrastructures for ambient i ntelligence.\n\nArtificial intelligence can provide flexible techniques fo r designing and implementing monitoring and control systems\, which can be configured from behavioural examples or by mimicking approximate reasonin g processes to achieve adaptable systems. Machine learning can be effectiv e in extracting knowledge form data and learn the actual and desired behav iours and needs of individuals as well as the environment to support infor med decisions in managing the environment itself and its adaptation to the people's needs.\n\nBiometrics can help in identifying individuals or grou ps: their profiles can be used for adjusting the behaviour of the environm ent. Machine learning can be exploited for dynamically learning the prefer ences and needs of individuals and enrich/update the profile associated ei ther to such individual or to the group. Biometrics can also be used to cr eate advanced human-computer interaction frameworks.\n\nCloud computing en vironments will be instrumental in allowing for world-wide availability of knowledge about the preferences and needs of individuals as well as servi ces for ambient intelligence to build applications easily.\n\nThis talk wi ll analyse the opportunities offered by these technologies to support the realization of adaptable operations and intelligent services for smart liv ing in an ambient intelligent infrastructures.\n\nCo-sponsored by: Poul Ni elsen\n\nSpeaker(s): Vincenzo Piuri\, \n\nRoom: 802\, Bldg: WT\, 14/2 Wake field St\, CBD\, Auckland\, North Island\, New Zealand\, 1010 LOCATION:Room: 802\, Bldg: WT\, 14/2 Wakefield St\, CBD\, Auckland\, North Island\, New Zealand\, 1010 ORGANIZER:p.nielsen@auckland.ac.nz SEQUENCE:0 SUMMARY:IEEE I&M seminar at AUT by Vincenzo Piuri URL;VALUE=URI:https://events.vtools.ieee.org/m/199627 X-ALT-DESC:Description: <br /><div dir="ltr">\n<p>Ambient intelligence: con vergence of artificial intelligence\, machine learning\, biometrics\, clou d-computing\, and internet-of-thing</p>\n<p>Adaptability and advanced serv ices for ambient intelligence require an intelligent technological support for understanding the current needs and the desires of users in the inter actions with the environment for their daily use\, as well as for understa nding the current status of the environment also in complex situations. Th is infrastructure constitutes an essential base for smart living. Various technologies are nowadays converging to support the creation of efficient and effective infrastructures for ambient intelligence.</p>\n<div dir="ltr ">\n<p>Artificial intelligence can provide flexible techniques for designi ng and implementing monitoring and control systems\, which can be configur ed from behavioural examples or by mimicking approximate reasoning process es to achieve adaptable systems. Machine learning can be effective in extr acting knowledge form data and learn the actual and desired behaviours and needs of individuals as well as the environment to support informed decis ions in managing the environment itself and its adaptation to the people's needs.</p>\n<p>Biometrics can help in identifying individuals or groups: their profiles can be used for adjusting the behaviour of the environment. Machine learning can be exploited for dynamically learning the preference s and needs of individuals and enrich/update the profile associated either to such individual or to the group. Biometrics can also be used to create advanced human-computer interaction frameworks.</p>\n<p>Cloud computing e nvironments will be instrumental in allowing for world-wide availability o f knowledge about the preferences and needs of individuals as well as serv ices for ambient intelligence to build applications easily.</p>\n<p>This t alk will analyse the opportunities offered by these technologies to suppor t the realization of adaptable operations and intelligent services for sma rt living in an ambient intelligent infrastructures.</p>\n</div>\n</div> END:VEVENT END:VCALENDAR