Energy Efficiency in Smart Buildings through IoT Sensor Integration

#IEEE #YP #Energy #Efficiency #IoT
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IEEE South Saskatchewan in collaboration with North Saskatchewan would like to invite you to attend this free Webinar


Internet of Things (IoT) deployments offer a much higher value proposition if these can function in the context of smart buildings. Such advanced information and communication technology (ICT) applications in commercial buildings, schools, libraries, shopping centers, etc. offer low cost but highly effective monitoring and control opportunities.  Sensors deployed in key locations can monitor the building environment in real-time, collect information for intelligent decision making, and facilitate various services. An IoT sensor platform has been developed that provides a unified communication platform which can integrate information from disparate sources and provide one control hierarchy. It is a powerful, low-cost, open-architecture software platform that can monitor and control major electrical loads (e.g., HVAC, lighting and plug loads), as well as solar PV systems, energy storage units and other IoT sensors in commercial buildings. The platform can provide new or legacy buildings with a building automation system (BAS) or connect with existing BAS systems in large and small commercial buildings. This platform leverages machine learning algorithms to draw insights from a deployed building’s historical operating data and occupant preferences to save energy (kWh) while increasing occupant comfort. This also allows buildings to reduce peak demand (kW) through direct communication with utilities using demand response protocols such as openADR. 



  Date and Time

  Location

  Hosts

  Registration



  • Date: 11 Aug 2020
  • Time: 05:00 PM to 06:00 PM
  • All times are (UTC-06:00) Saskatchewan
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  • Regina, Saskatchewan
  • Canada S4S 0A7
  • Building: Online

  • Contact Event Hosts
  • Co-sponsored by IEEE North Saskatchewan
  • Starts 27 July 2020 12:00 PM
  • Ends 11 August 2020 04:30 PM
  • All times are (UTC-06:00) Saskatchewan
  • No Admission Charge


  Speakers

Prof. Dr. Rahman Prof. Dr. Rahman of Advanced Research Institute at Virginia Tech, USA

Topic:

Energy Efficiency in Smart Buildings through IoT Sensor Integration

Biography:

Prof. Dr. Saifur Rahman is the founding director of the Advanced Research Institute (www.ari.vt.edu) at Virginia Tech, USA, where he is the Joseph R. Loring Professor of Electrical and Computer Engineering. He also directs the Center for Energy and the Global Environment (www.ceage.vt.edu). He is a Life Fellow of the IEEE and an IEEE Millennium Medal winner. He was the founding Editor-in-Chief of the IEEE Electrification Magazine and the IEEE Transactions on Sustainable Energy. He has published over 140 journal papers and has made over four hundred conference and invited presentations. In 2006, he served on the IEEE Board of Directors as the Vice President for Publications. He is a Distinguished Lecturer for the IEEE Power & Energy Society (PES) and has lectured on renewable energy, energy efficiency, smart grid, electric power system operation and planning, etc. in over 30 countries. He was IEEE Power and Energy Society President 2018-2019 and is now a candidate for IEEE President-Elect 2021.

He is the founder of BEM Controls, LLC, a Virginia (USA)-based software company providing building energy management solutions. He chaired the US National Science Foundation Advisory Committee for International Science and Engineering, 2010-2013. He conducted several energy efficiency, blockchain and sensor integration projects for Duke Energy, Tokyo Electric Power Company, US National Science Foundation, US Department of Defense, State of Virginia and US Department of Energy. He has a PhD in electrical engineering from Virginia Tech. 

Address:Arlington, Virginia, United States





Agenda

Webinar from 5:00 to 6:00 (Saskatchewan Local Time)



Admission: Free. Registration required.
For any additional information, please contact: moeeed@ieee.org



  Media

Webinar - Screenshot 1.35 MiB