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Seamless Interoperability in Building Automation Using Self-Mapping and Discovery of Sensors, Actuators, and Data

Lead Performer: Oak Ridge National Laboratory - Oak Ridge, TN
DOE Funding: $260,000
Cost Share: N/A
Project Term: 10/1/13 - 9/30/14

Project Objective

The goal of this project is to facilitate the rapid, cost-effective integration of building automation systems by exposing the functions of sensors, actuators, and other data sources through a uniform software interface. This project extends an existing, open integration framework for building automation in two ways: (1) support the automatic discovery of automation equipment resident on a building automation network and (2) include automation tools that facilitate rapid construction of new device drivers, automatic retrieval of existing device drivers, and attachment of the device to the integration framework. This proposed solution will leverage existing capabilities for device discovery in protocols, such as BACnet, and augment them with (1) a database and retrieval system for device drivers and (2) technology for generating, fully or in part, the source code for device drivers directly from information obtained during discovery. The outcome of the research will be a substantial reduction in the effort required to integrate new and legacy devices into an open integration framework, and a corresponding reduction in the cost of retrofitting small to medium commercial buildings with new, energy-saving control systems.

Project Impact

Buildings are responsible for more than 40% of U.S. energy consumption. This level of energy consumption by buildings is due in part to design and operating principles that assume maximum occupancy and a worst-case “design day.” Indeed, ORNL estimates that better control of heating, ventilation, and air-conditioning (HVAC) units alone has the potential to reduce whole-building energy consumption by up to 10% (0.5–1.7 quads of the 17 quads of energy consumed by US commercial buildings).


DOE Technology Manager: Joe Hagerman
Lead Performer: Teja Kuruganti, Oak Ridge National Laboratory