BEGIN:VCALENDAR
VERSION:2.0
PRODID:IEEE vTools.Events//EN
CALSCALE:GREGORIAN
BEGIN:VTIMEZONE
TZID:America/New_York
BEGIN:DAYLIGHT
DTSTART:20260308T030000
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3
TZNAME:EDT
END:DAYLIGHT
BEGIN:STANDARD
DTSTART:20261101T010000
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11
TZNAME:EST
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20260801T170751Z
UID:D0EE3E99-71AE-4518-843D-1BC5DDB2E3B9
DTSTART;TZID=America/New_York:20260820T190000
DTEND;TZID=America/New_York:20260820T200000
DESCRIPTION:This presentation highlights a data-driven smart agriculture sy
 stem that tracks soil health and crop yields. Modern day agriculture utili
 zes many digital methods and tools for precision farming and smart resourc
 e use. The system is designed to be remotely powered with longrange wirele
 ss communication and have effective machine learning for farming decisions
 .\n\nEnvironmental and soil data is collected through a smart controller a
 nd displayed on a webbased dashboard. A moisture prediction model was cons
 tructed with 2\,000 accurate field observations. It is capable of anomaly 
 detections\, moisture forecasts and a soil energy composite index. The pro
 ject is in active development. The completed phases along with the future 
 directions and goals will be discussed. This data agriculture system is an
  important contribution in developing sustainable methods in smart farming
 .\n\nSpeaker(s): Huzaifa Muhammad \n\nAgenda: \n7:00PM - Introduction of I
 EEE Hamilton Section\n\n7:15PM - Presentation\n\n8:00PM - Q&A\n\n8:15PM - 
 Refreshments\n\nRoom: Community Room 2\, 3070 Neyagawa Blvd\, \, Oakville\
 ,\, Ontario\, Canada\, L6M 0P4
LOCATION:Room: Community Room 2\, 3070 Neyagawa Blvd\, \, Oakville\,\, Onta
 rio\, Canada\, L6M 0P4
ORGANIZER:sneh@rchilli.com, eduardo.gomez.hennig@ieee.org
SEQUENCE:16
SUMMARY:Data-Driven Smart Agriculture System: IoT & Machine Learning for Pr
 ecision Farming 
URL;VALUE=URI:https://events.vtools.ieee.org/m/570758
X-ALT-DESC:Description: <br /><p>This presentation highlights a data-driven
  smart agriculture system that tracks soil health and crop yields. Modern 
 day agriculture utilizes many digital methods and tools for precision farm
 ing and smart resource use. The system is designed to be remotely powered 
 with longrange wireless communication and have effective machine learning 
 for farming decisions. <br><br>Environmental and soil data is collected th
 rough a smart controller and displayed on a webbased dashboard. A moisture
  prediction model was constructed with 2\,000 accurate field observations.
  It is capable of anomaly detections\, moisture forecasts and a soil energ
 y composite index. The project is in active development. The completed pha
 ses along with the future directions and goals will be discussed. This dat
 a agriculture system is an important contribution in developing sustainabl
 e methods in smart farming.&nbsp\;</p><br /><br />Agenda: <br /><p>7:00PM 
 - Introduction of IEEE Hamilton Section</p>\n<p>7:15PM - Presentation</p>\
 n<p>8:00PM - Q&amp\;A</p>\n<p>8:15PM - Refreshments</p>
END:VEVENT
END:VCALENDAR