Video: Unifying data from diverse systems and sources to enable wholebuilding analytics FDD and KPI analysis
An introduction to the concept of an IDL and the factors involved in achieving the necessary functionality to acquire and normalize data to support real-world applications.
- Identify key characteristics of an IDL.
- Differentiate sources of data that can be used in the MBCx process.
- Understand the role of semantic data/tagging in normalizing data from different sources.
- Provide basic understanding of Project-Haystack as a data tagging standard.
The challenge for the commissioning professional is that they need the data from a variety of protocols and web services. In this session, we will provide an introduction to the concept of an IDL (Independent Data Layer) and discuss the factors involved in achieving the necessary functionality to acquire and normalize data to support real-world applications.
Today’s facilities are increasingly populated with smart devices and equipment systems. These systems come from a variety of manufacturers and communicate using a wide range of methods from field busses based on standard protocols i.e., BACnet, OPC UA, MODBUS and others, to webservices that offer a wide range of open, yet different APIs (Application Programming Interfaces). The challenge for the commissioning professional is that they need the data from all, or most of, these systems in order to accomplish their job of ensuring proper operation of complex building systems. The effort required to connect to and acquire usable data from diverse systems is one of the major cost and complexity barriers to implementing cost effective MBCx and data-driven retro-commissioning. Addressing this issue has led to a focus on software that can unify and normalize diverse data sources and act as an independent data service making the data available to any and all applications that need it via a standard, open interface. In this session we will provide an introduction to the concept of an IDL – independent data layer and discuss the factors involved in achieving the necessary functionality to acquire and normalize data to support real world applications.
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Roger Quesnel, SkyFoundry