The Internet of Things is enabling a more automated approach to energy efficiency. Using IoT-devices and BMSs as data streams, advanced intelligent energy management platforms can automatically optimize daily energy usage within facilities and participate in demand response events through predictive analytics and cloud control. This is the approach that’s been taken at the University of South Florida (USF), in Tampa. Using this strategy, which doesn’t require oversight from onsite staff, the university reduced HVAC energy consumption by roughly 12% over a thirteen-month period, compared to baselines. This session will outline implementation, results and lessons-learned from USF’s IoT energy strategy.
1. Learn how predictive analytics can uncover opportunities for energy savings
2. Learn how to determine if their building is IoT-ready
3. Examine real-world energy savings results from USF
4. Learn how cloud-based software can reduce upfront capital investments