Using data analytics to improve building efficiency

The amount of electricity needed to operate a commercial building is staggering. According to the Department of Energy, commercial buildings account for nearly 20 percent of all the energy consumption in the United States. Offices, schools and retailers are notable offenders, representing half of all commercial building energy use. Many of these building occupants practice wasteful energy practices, including skyscrapers leaving their lights on through the night or running central heating and cooling units when no one is present. The good news is that these buildings' systems collect a great deal of information, which means that Hadoop big data tools can be deployed to find solutions.

Data Informed recently outlined how data analytics resources could be used to help building managers find more efficient means to run critical operations. Using the information gathered by heating systems, lighting controls and energy meters, big data tools can customize automated functions to create an optimal environment for an individual building. Managers can eliminate wasteful practices and reduce the amount of money spent on utilities.

Big data software can also be used to identify problems in various systems. By comparing the output of internal systems to those of similar building types and sizes, managers can determine if their equipment is as energy efficient as it should be. Additionally, managers could use data analytics software to assess the state of their equipment and identify problems that may result in hardware failures down the road. By spotting those issues early and adjusting maintenance schedules to address them, building managers can avoid costly breakdowns and equipment replacements.

"If we can measure it, we can track it," Panoptix operations director Mark Henderson told the source. "If we can track it, we can determine performance. If we can determine performance, we can make adjustments."

Using Hadoop big data tools, commercial building managers can significantly improve the operating efficiency of their structures. By keeping energy consumption levels down and identifying faulty equipment, they can ensure that buildings are operating optimally with the lowest possible expenses.

Categorized by :
Big Data

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