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SCIwatch is said to address the problem of “energy drift,” which causes commercial buildings to lose an average of 17 percent in energy efficiency every one to two years. With average electricity costs running $2.00 per square foot, this energy leakage is costing billions of dollars in unnecessary spending each year, stated SCI. Energy drift can be triggered by a variety of problems ranging from clogged filters to more complex issues that include electrical, mechanical, and HVAC system faults. In addition, anomalies in building tolerances, seasonal climate change, or varying tenant occupancy rates can contribute to the problem of energy seepage.
As a predictive energy analytics platform using patent-pending neural network technologies, SCIwatch is said to feature a unique architecture that combines:
• A universal interface to almost any building management system, metering, or external data source;
• A certified baseline of energy consumption and spending by each facility over time;
• A data warehouse storing all operations source data and anomaly detection histories and associated costs;
• A fault-prediction diagnostic engine that identifies and tracks changes to baselines and anomalies across mechanical and electrical systems; and
• A comprehensive work order module that issues and tracks job tickets to completion, broken down by building and individual systems.
“The days of recommissioning buildings every few years are essentially over,” said David Wolins, chief executive officer at SCI. “With the introduction of SCIwatch, we have figured out a way to package and greatly simplify the complex tasks of analyzing a facility’s energy consumption and systems operations. As a result, commercial buildings can now be monitored persistently and comprehensively to detect anomalies before they can erode energy efficiency and system uptime.”
For more information, visit www.scientificconservation.com.
Publication date: 07/13/2009