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CopperTree Analytics Higher Education

Discovering and Onboarding Proprietary BAS Data

Discovering and Onboarding Proprietary BAS Data

A research university based in the USA relies on an amalgam of different BAS technologies for its 600-acre urban campus. The private university is a pioneer in healthcare, research and has state-of-art laboratories.

Our Challenge

CopperTree Analytics was contracted to create a custom Dashboard for the University’s engineering team to evaluate the performance of their systems, as well as provide consulting services using the Kaizen Analytics Platform.

The University Campus has different buildings with a mixture of legacy, standard and proprietary software. Each building focuses on different disciplines and hence their Energy requirements and setups are diverse. The data from each needed to be onboarded to Kaizen to deliver analytics.

The BAS was isolated and connecting with their system required meeting security requirements and connecting to the BAS behind a firewall.

Additionally, the site had a mix of standard and proprietary software. The data of the proprietary software needed to be queried through different endpoints and protocols. The custom software created additional challenges as the encoding of the data was unique in the BAS system.

Our Solution

To communicate with the BAS, CopperTree deployed a custom connector which would meet their security requirements. Further, to discover points from the custom BAS system, CopperTree created a custom script based on documentation provided by the vendor and established API connections to onboard the point names, their descriptions, units, and present value. CopperTree also stitched data from different sources together and matched encoding requirements of the proprietary platform. Then, the data was pumped into the Kaizen platform for analytics.

Our Results

The data from the buildings were onboarded to Kaizen to help the engineering team perform analytics. Further, with CopperTree’s ability to query from different protocols, reduced cost associated with upgrading systems for analytics. The data on Kaizen was subsequently used for FDD by generating insights and creating custom reports.

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