Building Automation System in an Edge Package.
When Edge Analytics Controllers are fed real-time data from intelligent sensor network from Current, powered by GE, retail spaces and other commercial building environments are transformed for the better.
Who is BASSG?
BASSG is a Software and Services partner to controls contractors, energy management and engineering firms. It has been providing DevOps support to the open-protocol building automation system industry for over 10 years. Its deep domain knowledge and strong industry relationships have positioned BASSG at the cutting edge of informatics for commercial buildings It has launched Anka Labs to bring machine-learning-ready edge analytics controllers (EACs) to market at a price point that makes it affordable to place one wherever needed to create a data flow revealing Key Performance Indicators (KPIs) for comfort, energy use or business goal achievement. These hybrid devices put a full stack of resources and applications for graphics, trending, alarming, control logic and advanced analytics at the edge, making a flexible, responsive smart building truly possible.
BASSG + Current, powered by GE
The partnership between BASSG and Current, powered by GE, is focused on bringing commercial buildings into the age of autonomy through edge computing informed by sensor data from Current’s intelligent infrastructure. Edge Analytics Controllers can integrate Current sensor data with live thermal and air quality data from building equipment, as well as with meter, submeter, and human feedback data. Each hybrid device is equipped to analyze the data per historical trends, optimize the points it has under control, and visualize results for facilities staff. Through drag-and-drop graphics and easy block programming interfaces, energy managers, commissioning advisors, controls contractors and other trusted stakeholders are empowered to create obvious, easy-to-maintain workflows for air control, chilled water, hot water, demand response, integration of renewables and other building infrastructure networks. The resulting controls architecture is an ideal basis for the creation of source training data for machine learning.
Contact us to learn more.