The U.S. Department of Energy (DOE) has recently awarded PassiveLogic additional funding to create a digital twin ontology that can be used across the industry to describe buildings, their systems, and occupants. This standard enables system level control for buildings and is the underpinning for PassiveLogic’s Autonomous Buildings platform. The $1.15M grant has been awarded through the DOE’s competitive SBIR (Small Business Innovation Research) program whose goal is to foster research, development, and commercialization of new advanced technologies in the energy industry.

The grant is supported by the SBIR/STTR Program.

More specifically, this latest grant is the second phase of funding to develop the “deep data fusion” aspect of the digital twin standard. It is a continuation of PassiveLogic’s phase I grant in which the primary goal was to demonstrate the feasibility of an end-to-end Digital Twin workflow consisting of two major parts. Part I consists of a simple to use on-premises autonomous control platform for the purposes of deep data fusion and automation. Part II consists of a serializable data standard for a physics-based Digital Twin ontology description that provides a comparable, reconstructable, simulatable, and queryable digital copy of any building.

Deep data fusion at the individual building level enables energy efficiency, deep analytics, building autonomy, and the future of smart cities. This SBIR grant will provide valuable funding for the research and development of this disruptive early-stage technology, while enabling the DOE to meet its energy efficiency goals by standardizing building data science insights, thus improving the efficiency and autonomy of buildings — an 8.7 Quad potential savings opportunity. PassiveLogic is looking forward to extending this partnership with the DOE to realize improved energy efficiency throughout our built environment.