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In recent years, interest in reducing carbon emission levels and increasing energy efficiency has led to the exponential growth of smart building technologies.
Most significantly, IoT has expanded the possibilities of interconnecting devices and building management systems for better energy management. Truly realizing its potential, however, requires organizing and analyzing the large data sets generated by building automation systems.
Managing and maintaining big data in real time is the key to improving building energy management. And the benefits of big data analytics go beyond saving money on electrical bills; it can deliver comfort to building users and increase the lifespan of building equipment, enhancing the value of commercial buildings.
Big data has transformed smart building operations by offering extraordinary insight into building conditions and equipment behavior. Some of the most powerful applications of big data for building energy management include:
Analyzing the data provided by building automation systems is essential for understanding consumption and tracking progress toward efficiency goals. Significantly, it also makes that data actionable by allowing you to identify energy waste, such as unnecessary lighting, heating, or cooling of unoccupied rooms.
Energy demand, also known as energy load, is the total amount of energy required in a building at a certain time interval. By providing historical and real-time energy usage information, big data can be used to predict demand and consumption.
The data generated by building automation systems contain valuable information about temperature, power, control signals, the status of equipment, and occupant behavior. By analyzing the relationships between energy loads, consumption patterns, and a range of building components, it is easier to enhance building design for optimal energy efficiency.
Big data can provide real-time updates on the operational status of building equipment and detect faults in the infrastructure. With continuous monitoring and data analysis, anomalous data patterns can be identified automatically, alerting you to system failures and allowing you to easily anticipate the effect of those failures on other equipment.
Failures in metering equipment can lead to inaccurate billing of energy consumption and services. Such failures—whether accidental or the result of tampering—can lead to fraudulent manipulation of energy services by building occupants. Data mining can detect irregularities to identify potential fraud or account defaulting.
These applications of big data are slowly revolutionizing building energy management practices. Yet, many contractors fail to deploy smart building IoT solutions with robust analytics platforms and take advantage of their benefits. Many commercial buildings still rely only on pneumatic controllers that require operators handle energy-consuming building operations manually.
The reluctance to adopt advanced data analytics in buildings is rooted in cost. Though the cost of sensors has decreased substantially over the last decade, the cost of deploying a comprehensive smart building solution is still perceived as high. However, the long-term benefits of collecting, organizing, and analyzing big data for improved building energy management deliver a return on investment that far outweighs the initial expense.
The ability to extract meaningful information from large data sets is critical to improving operational efficiencies and reducing energy consumption. As such, an analytics-enhanced building management system is required to produce actionable insights.
A building analytics platform can offer:
Advanced energy management features: An integral part of energy management is optimizing energy and operational efficiency with minimal human intervention. A building analytics platform provides valuable insights on energy conservation opportunities, including those related to equipment runtimes, heating and cooling hours, and zone setpoints. With the right platform, key building operations and maintenance of equipment can be more easily automated.
Equipment monitoring: Monitoring actual energy usage by building systems and specific equipment against expected usage and energy goals is critical to evaluate efficiency across building systems and real estate portfolios. Analytics platforms can illuminate mechanical issues or operational problems that may be interfering with performance.
Real-time reports: The ability to customize reporting according to your requirements is essential to cutting through noise and creating a clear picture of current building conditions, energy goals, and other prioritized variables. Real-time data reports that distill complex big data in a user-friendly format allow stakeholders to get the information they need when they need it.
Fault detection and diagnostics: The data received from existing BMS alarm systems cannot proactively detect faults in building systems or equipment. An analytics platform uses advanced algorithms to identify and diagnose faults before occupants complain. This also streamlines maintenance and facilitates rapid corrections.
Not all building analytics platforms are created equal, and realizing the potential of big data for building energy management requires the right platform.
onPoint is designed to transform big data into actionable intelligence. With onPoint, contractors can receive continuous, actionable insights to improve comfort, enhance operations, and save energy. This secure edge-to-cloud service combines the power of machine learning with deep building domain knowledge. It allows you to optimize systems automatically and identify opportunities for greater automation, and provides the tools you need to address pain points. The result? You get closer to your energy efficiency goals faster.
Big data is essential for making building energy management better. But it is analytics that turn raw data into the knowledge you need to create smarter commercial buildings.
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