Leveraging Cloud-based Building Management Systems for Multi-site Facilities

PublishTime：2022-04-21

●Introduction
■In a perfect world, facilities managers would always choose to optimize building performance. Consumingless energy, improving occupant comfort and productivity, reducing equipment failures and repair emergencies—these are all ideal goals.
■But in the real world, especially for enterprises with multiple distributed facilities, building optimization can seemlike a pipe dream. Resources and budgets are already stretched to the limit just keeping buildings in operation. Most organizations have a large stock of older buildings with varying degrees of building automation controls, or often only simple thermostats. Growth, mergers, and acquisitions create even more headaches.
■In this environment, activities like managing the big picture, sharing best practices, and proactively fine-tuning building systems have simply been impractical, if not impossible, for mostorganizations.
■Recently, the development of the Cloud and other technologies has created a new opportunity for facilities managers to take control of operations on a large scale. By using the Cloud—which provides connectivity, data storage, and applications without major investments—it is now possible and cost-effective for companies of all sizes to view and manage their facilities landscape in a consistent, centralized way.
■This paper explains how enterprises with distributed facilities can use the Cloud cost-effectively for improved building management that reduces energy and maintenance costs, improves efficiency and asset management, and provides greater occupant comfort and productivity

Brand of Product：	SCHNEIDER
Part#：
Product Category：	Cloud-based Building Management Systems More
Application：	[ Multi-site Facilities ] More
Data Type：	White Paper More
Safety & Environment Standards：	More
Operating Temperature：	Please see the document for details
Qualification Grade：	More
Qualification Approval：	More
Package：
Language：	English Chinese Chinese and English Japanese
Date of Creation：	2016/3/29
Version Number：	Rev 0
Data Encoding：	998-2095-11-05-15AR0
Data Size：	619 KB

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