The Adaptive Automation product, says the company, focuses on commercial buildings and does for a building what a self-driving system does for a car. It enables building management systems (BMSs) to operate while adapting to changing building conditions autonomously, ensuring continuous and maximized system performance without human intervention.
"Building infrastructure and management technology has not kept pace with the increasing complexity of the built environment," says Jonathan Chu, Verdigris' CTO. "The sheer number of possible operating configurations and nonlinear interdependencies make it difficult to understand and optimize a building with manual analysis and simple engineering formulas. You need a dynamic, machine-assisted approach."
While traditional building automation systems are designed to monitor and control based on periodically modeled and retuned setpoints - which can be quarters, years, or even longer intervals apart leading to drift in building performance - Adaptive Automation is designed to take advantage of technology advances in IoT sensors, pervasive wireless communications networks, and artificial intelligence to continuously learn and predict building patterns.
These capabilities, say the company, make it possible to make dozens of adjustments daily to deliver optimally efficient building performance. Whether the changes are seasonal, or due to new equipment or occupant end-use, the building management system's optimization engine adapts automatically.
Adaptive Automation's machine learning based approach, says the company, makes it both scalable and cost-effective to implement in buildings as small as 20,000 square feet and as large as several million square feet.
Adaptive Automation is available to US-based building owners and operators by application or invitation.
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