Smart Connected Homes and Connected Communities – IBPSA-USA Research Committee

Date of Recording:
Short Description
Long Description

Internet of things has revolutionized the way devices, actuators, buildings occupant, building operators, and utilities interact. In This era, there is an immense need and opportunity for a building energy management system that can monitor, control, coordinate, and shape the power consumed by end-use devices. Effective integration of these assets in buildings has critical role in providing load flexibility to improve building energy efficiency and support grid resiliency. In this presentation, we will present a cloud-based software framework that has been deployed in a smart neighborhood to optimize the energy consumption of the water heaters and HVAC systems in a community of occupied residential buildings. We will also discuss different optimization methodologies that can be used for optimizing the buildings’ energy use.

Learning Objectives:

  • The role of Internet of Things and software in the success of building-to-grid integration.
  • Optimizing the energy usage of building loads to provide grid services.
  • Impact of applying optimization in connected homes.
  • Data-driven and Machine Learning algorithms on building data.


Helia Zandi is currently a research scientist in Modeling and Simulation group, in Computation Science and Engineering Division at Oak Ridge National Laboratory (ORNL). She is involved and leads a variety of projects for developing advanced control systems to support demand response and grid resiliency. Current research interest includes machine learning, image processing, robotics, cyber-physical system, smart grid, Internet of Things, Building-to-grid integration, and grid responsive control systems.

smart homes, IoT, internet of things, smart neighborhood, HVAC, water heaters, cloud-based software framework, machine learning, ML