Advanced methods of interpreting large volumes of data have brought innovations in areas such as healthcare/pharmaceuticals, meteorology, marketing, e-commerce, government services, national security, and financial services. Despite success in other areas, though, big data is only beginning to have an impact on building automation and energy efficiency. In a 2013 blog, my colleague Bob Gohn discussed big data in the context of buildings. In this blog, I’ll take a look at some of the solutions emerging in this area and how the buildings industry will be affected.
Currently, the most common use for big data in buildings is fault detection and predictive maintenance. Advances in sensor technology have enabled unprecedented views into the status and functionality of building systems such as heating, ventilation, and air conditioning (HVAC). Sensors are capable of regularly measuring every aspect of the system’s performance by analyzing the data to identify equipment that needs to be replaced or may be about to fail. Bringing technicians onsite to service equipment can be a major expense for building owners. This type of data analytics allows a diagnosis to be made before the technician arrives, while also providing information on replacement parts and other relevant items. Data analytics solutions can also build a list of the known problems in a building and derive each piece of equipment’s usage and cost, enabling a quantitative return on investment (ROI)-based assessment of which upgrade or investment should be implemented first.
As building automation and data analytics continue to advance, new applications within the buildings industry are emerging. Advanced building energy management systems (BEMSs) harness large quantities of data to provide a visualization of the overall energy consumption of a building or portfolio of buildings. These systems also have the ability to leverage historical data to provide recommendations for how to best reduce consumption. Next-generation BEMSs have the capability to adjust building system parameters automatically to maximize occupant comfort and energy efficiency. One example of this type of advanced system is SHIFT Energy’s Intelligent Live Recommissioning (ILR) solution, which provides ongoing re-adjustments. Another cutting-edge solution is offered by Ecorithm, whose program also includes richly detailed graphics to visualize processed data across a building’s floor plan, identifying areas of waste and recommending corrections.
Designed with Data
Big data is also playing an increasingly important role in the design of resource efficient buildings. Building information modeling (BIM) programs allow architects to analyze key performance metrics such as natural ventilation, daylighting, solar heat gain, overall energy usage, and even how people will likely interact with spaces. These programs utilize vast amounts of data from existing buildings to visualize how a conceptual building may perform. Such analysis can speed the construction of new buildings by leveraging the data-rich plans from previous projects, modified to fit the specific characteristics of the new site. This also allows designers to cut costs by eliminating the duplication of work from past projects. Reducing the time and cost required to construct new buildings is an essential factor in addressing rapidly growing urban populations that lack sustainable buildings and infrastructure.
Despite these achievements, the buildings industry is not yet exploiting available data to the extent that other industries are. Looking forward, advances in building design, construction, and management can leverage big data and advanced analytics to reduce costs and improve efficiency. As buildings and cities become increasingly automated and digitalized, data analytics will play a growing role in energy efficient buildings.
Tags: Big Data, Building Systems, Data Analytics, Energy Efficient Buildings, Smart Buildings Program
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