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Building analytics are data analytics gleaned from smart building technologies such as networked sensors, building management systems (BMSs), integrated workplace management systems (IWMSs) and internet of things (IoT) edge devices. These technologies continually provide facility owners and managers with valuable data about the condition and performance of building infrastructure systems.
By reviewing and analyzing data retrieved from smart building technologies, smart building analytics can help manage a facility’s systems—heating, ventilation and air conditioning (HVAC), lighting, plumbing and security/access—during and after the pandemic. In addition, building analytics can help businesses:
Building automation systems are leveraging information technology to build an “informed infrastructure” that supports demand management goals. Informed infrastructure is the merging of building hardware and building analytics software, enabling users to monitor, measure, analyze, communicate and operate building controls in ways that could not have been imagined a few years ago.
A demand management platform can be used to continuously import information and signals from customers’ infrastructure outside the enterprise, process that data into actionable information, communicate recommended actions to the building, “read” the building as part of the continuous process and feed select information back beyond the enterprise.
This platform provides the ability to establish predefined strategies for a variety of physical assets, such as entire buildings and specific spaces in buildings, as well as underlying equipment and energy meters in buildings. Importantly, it allows building managers to vary consumption across building components for various parameters, such as comfort, occupancy, equipment type, time of day, pricing and so on. Such a platform enables the automatic synchronization of energy consumption with these parameters by adopting predefined ways of load-shedding based on customer contracts. This provides the ability to automatically recognize when demand should be reduced or shifted in a predefined fashion.