Data mining and smart lighting solutions

White paper about analyzing insights from installed projects to increase customer adoption.

Request a copy

First name

Last name

Company name

Job title

Country

By completing this form, I confirm that I have read the privacy statement and understood and accept the terms of use.

I would like to receive informational emails with related content in the future from DNV, for example but not limited to invitations to webinars, seminars, newsletters, or access to research that DNV thinks is relevant to me. I can unsubscribe or change my email preferences at any time using the links in the footer of the emails I receive from DNV.

Smart Lighting Solutions (SLS), which rely on sensor networks, capture an immense amount of data. To fully leverage this data, users should analyze and manage the data as a strategic asset. One powerful feature of SLS is the ability to report energy consumption data in short time sets. The granular nature of this data affords the buildings operator an opportunity to modify occupant behavior to achieve savings goals. Far from “set it and forget it,” the data captured from actual building use is dynamic and changes over time. When properly analyzed, datasets from SLS produce better energy consumption outcomes. These outcomes lower operating costs, which frees up cash flow and helps mitigate the financial risks associated with the initial capital expenditure.

Data mining and smart lighting solutions

SHARE:

Request a copy