I have written before of UNC’s Enterprise Building Management System (EBMS). EBMS talks to legacy systems in more than a 100 buildings on the UNC campus. EBMS uses a half dozen variants of web services to monitor and operate building systems using nearly every brand and every internal protocol. All data is normalized and brought into an industry standard database, currently we are adding 42 million transactions a day to that database.
Phase II of EBMS is finishing up before the end of the year. The system is going through final tuning and acceptance testing; the developers from Cyrus Technologies are still sleep deprived but have that light in their eyes that coders get when the end of a death march is in sight.
While commissioning the system, we found errors in our old proprietary system, including sensors that had always supplied bad data. Building integrators had “solved problems by the expedient of not displaying bad data. In at least one case, this bad data explained years of expensive maintenance and replacements. When EBMS is complete, our operators will have a single web-based console for all of these buildings.
We are just beginning to get other sources of data into the EBMS database. EBMS now includes historical weather data. Metering data for all utilities in the building is just starting to flow in. Even though we have in-house utilities providing electricity, and steam, and chilled water to the buildings, we have had as much difficulty getting live information as if we were getting information from a third party. The barriers have been political, or perhaps more fairly cultural. Still, the information is now flowing in.
One of the final steps for the developers was setting up an OLAP framework for looking at the data. Online Analytic Procession (OLAP) is using multi-dimensional analysis of data to find underlying patterns. OLAP is typically used in business reporting for sales, marketing, management reporting, business process management (BPM), budgeting and forecasting, and financial reporting. OLAP has not traditionally been available for building operational data. We now have an OLAP framework in place for 100 buildings.
This week, we are interviewing candidates for a new position, for a new role in this, or perhaps any, organization. We are hiring a full time data analyst, looking for experience in quality management or marketing rather than in mechanical systems. This positions full time job will be to look for anomalies and patterns in the operational data.
Perhaps we are moving toward predictive maintenance based upon analysis. Perhaps we are finding sub-optimal building response arriving from technology choices made years ago. Perhaps we will be able to understand the relationships between different departments and how buildings perform for them. We are entering the era of knowledge-based operations.