SkyFoundry has announced that SkySpark® analytics software has now been deployed to over 8200 buildings consisting of over 475 Million square feet, across facilities of all types. SkySpark automatically analyzes data from equipment systems and smart devices to identify issues and opportunities for improved performance and reduced operating costs. It is used in a wide range of applications including energy management, systems optimization, monitoring-based commissioning and fault detection.
“We see these results validating a number of key facts – For building owners, this continued, rapid growth validates the financial benefits of applying analytics to improve the performance of virtually all types of buildings and equipment systems. It’s also validation of the effectiveness of SkyFoundry’s worldwide partner channel.
This network of independent systems integrators and specialty engineering firms give owners the greatest freedom of choice in the market, allowing them to choose the organizations they want to work with for deployment, service, and ongoing consulting and support services.” Stated John Petze, Principal at SkyFoundry.
Originally released to the market in October of 2010, SkySpark has seen rapid market adoption and become recognized as an industry-leading analytics solution in the intelligent buildings market. Recently, the company has seen significant growth in other segments of the Internet of Things (IoT) market.
SkySpark is a fully programmable analytics application that allows owners to utilize the knowledge of their own facilities staff in conjunction with the deep expertise of SkyFoundry partners to implement analytic programs that fit the unique characteristics and requirements of individual facilities.
SkyFoundry is a company that provides software solutions for the “the Internet of things”, helping customers derive value from their investments in smart systems. The company’s SkySpark analytics platform identifies opportunities for operational improvements and cost reduction in control and equipment systems by automatically analyzing data to “find what matters™”.