Microsoft and partner technologies will save businesses significant costs with smarter buildings
We’ve got smartwatches, smartphones and smarthomes, but where are all the smartbuildings? Here’s an interested stat for you; in the US alone, businesses are collectively forced to dedicate $100 billion on energy bills to power their offices on a yearly basis. Done right, smartbuildings can save those businesses $20-25 billion from that annual fee.
Microsoft and partner company OSIsoft, a world leader in enterprise infrastructure and the management of real-time data and events, will be hosting an hour-long webinar on November 13th to talk about how businesses can benefit from investing in intelligent buildings. In addition to how the planet will be better off environmentally, especially considering that on a global scale, buildings contribute 40% to overall carbon emissions.
Hosted by Microsoft’s Director of Facilities and Energy, Darrell Smith, and OSIsoft’s Industry Principal of Facility Analytics, David C. Doll, the rundown of the events will include discussing how their solutions can result in achieving increased energy efficiency via state-of-the-art Predictive Analytics and Fault Detection and Diagnostics (FDD) technologies, in addition to discussing some of the important details to know before investing in this sort of facility management infrastructure.
(OISoft PI System architechture)
Those that catch the webinar will also learn about techniques to go beyond current building management systems that monitor a buildings mechanical and electrical equipment such as ventilation, lighting, power, fire, and security systems to also include energy management, demand response and microgrids.
The webinar starts Thursday, November 13 at 8AM Pacific, or 11AM Eastern. You can register via OSIsoft here which we recommend you do if you or your company are looking to save significant energy costs and have a lower environmental footprint as a result.Further reading: Business, Enterprise, Microsoft, Partners, Smartbuildings, Webinar