Automated building systems view spaces differently
As artificial intelligence (AI) is integrated with building systems and Internet of Things (IoT) devices, it has the potential to improve occupant experience, increase operational efficiency, and optimize space and asset utilization. In the recent IBM Institute for Business Value (IBV) study, “The human-machine interchange,” 76 percent of Chief Operating Officers reported that increasing automation in facility and asset management will have a positive impact on operational efficiency. Although cost-control measures and flexibility remain key objectives, creating compelling, emotionally rich experiences is the new frontier.
Optimizing building performance with AI and IoT
Buildings are becoming far more than walls, roofs and masonry. Thanks to AI, building systems are now able to autonomously integrate the proliferation of data from IoT devices and occupant behavior to apply learning, optimize performance, and improve environmental efficiency. A vast array of information from digital devices, beacons, and tweets provides insights about the operations, use, and condition of everything from the building’s infrastructure, physical environment, climate, water and energy usage, to an occupant’s experience and satisfaction.
IoT and platforms embedded with AI and learning make it possible to develop innovative new services for engaging with building occupants. These systems have the potential to radically reduce costs through automation and optimization of operations.
Of the executives surveyed in the IBV study, 70 percent report that intelligent machines will provide new categories of insight that enhance decision making. The new services also can improve occupant satisfaction by providing more personalized customer service.
A comprehensive building optimization system leverages all aspects of building and facility management. These types of systems allow for monitoring the use of space, water, and the usage and allocation of energy. Taking this monitoring one step further, building equipment data collected from IoT sensors that is tagged by location or asset type, and associated with business rules, can trigger algorithms to not only detect but also predict and respond to anomalies. These optimized ecosystems of building technologies identify opportunities for efficiency controls through predictive maintenance. They identify possible root causes so actions can be prioritized, assigned, monetized, and prevented. Recommendations that appear on dashboards or adjustments can be routed directly to the IoT device for action.
Identifying opportunities using analytics and AI
After equipment performance information is collected through sensors and meters, a library of benchmark data is applied, analytics are performed, and potential operational improvements are identified. To automate insights into actions as they optimize assets with IoT, many companies are advancing their use of predictive analytics to AI or learning systems.
By taking advantage of powerful analytics and AI, building owners can significantly cut energy consumption and achieve ambitious cost-saving targets. For example, by combining data for heating and cooling with Weather Company micro-location forecasts, an HVAC system can deliver more efficient heating and cooling.
Analytics can also be used to prevent energy waste by isolating inefficient energy use. Sensor-controlled systems can monitor dispensing and water use. Cognitive maintenance systems can help preserve the health of critical building equipment and assets by anticipating asset failure and guiding timely interventions.
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