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Patrick Gilhooly is a Customer Onboarding Engineer at Buildings IOT and a member of the OAP working group and advisory council. Patrick is based out of Ontario, Canada, and a graduate of the University of Waterloo. Before joining Buildings IOT, Patrick held project engineering positions at Bombardier Inc, SAP, and HTS Engineering.
Within an intelligent built environment, data integration means identifying, transforming, analyzing, and utilizing data from disparate sources to improve the performance of a building owner's most valuable asset.
Data models visually represent the data gathered throughout a connected IT system, either in whole or in part to facilitate its storage with easy access from a database. In built environments, the importance of data modeling comes down to the ability of elements within this system to communicate. To better communicate, common definitions should show from where the data comes and what it represents. To ensure understanding and lessen confusion, rules are used to describe elements within the system.
Data infrastructure can be thought of as a network of roads along which data travels. Poor infrastructure is like trying to drive on roads with missing street signs, toll booths, traffic lights that don’t work, dilapidated bridges, and random roadblocks. These obstacles can make traffic grind to a halt, or even get lost on the way to its destination.
Smart buildings require communication. Open-source data tagging standards make that communication seamless and ensure interoperability of components, regardless of who developed the software or manufactured the devices. Introducing standard ways in which to describe various elements within a building, along with their relationships to each other, makes integration of new technologies easier—and more useful—than ever before.
In smart buildings, devices, software, and building equipment must work together seamlessly. This requires unifying several naming and tagging standards currently used for building automation. While a seemingly simple issue, many data modeling approaches create roadblocks to real-world application of building data. But there is a better way. The Ontology Alignment Project lets you harness the full potential of building data, allows smart solutions to evolve and grow, and supports better performance and efficiency.
The Internet of Things (IoT) is transforming built structures into energy-efficient environments that enhance the experiences of those who occupy them. This goes beyond mere comfort control or cost-cutting. Digital environments enhance the operational efficiency, energy savings, comfort, and health of building owners, managers, and occupants. Smart buildings connect people, support collaboration, and increase productivity while conserving resources. To make this possible, data must be standardized and flow efficiently through gateways with sufficient capabilities and capacity.
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