Middleware Solution for Standardization and Analysis of Disparate Facility Infrastructure
Craig Compiano | Modius, Inc.
The fundamental purpose of this demonstration project is to illustrate how an enterprise-wide facility and infrastructure management portal can be implemented – and maintained – within a Department of Defense (DoD) environment. Although the OpenData Internet of Things (IoT) platform has been proven within commercial environments, it has not been deployed or evaluated within the security and operational environment of a DoD site. Each Service uses a different system for collecting and managing utility data, but all have encountered challenges with networking thousands of new devices (i.e. smart meters) in a reliable, efficient and cost-effective way. As more meters come on-line, the available data is becoming a valuable resource that is currently under-utilized. To convert this resource into improved management of energy and water consumption, the data must be translated into information that is accessible, reliable and meaningful at the enterprise and installation levels. This project will demonstrate that the widely disparate and distributed metering data can be collected, normalized and time synchronized to provide operations & maintenance (O&M) and facility teams, and related command structures with a cohesive view of all energy related consumption for baselining. Measurement and Verification (M&V), and on-going operational management.
Modius OpenData is a full-stack IoT platform that is based on a two-tier distributed architecture. This proven technology can be integrated to all commonly found devices (both new and legacy) and building management system products on the market to create an enterprise wide normalized view of all building infrastructure. Having a normalized view of data eliminates (or greatly reduces) the need for data cleansing and enables the rapid deployment of analytics. The “first tier” of the two-tier OpenData solution provides for distributed, user configurable integration to disparate and physically distributed meters, and the secure encrypted transmission of the meter data to the “second tier” - a centralized analytics database with integrated analytics and visualization tools. This two-tier model addresses fundamental issues of scalability and security for compliance with RMF requirements of cross-network systems. Machine learning has been applied to many similar use-cases but not with ease of repeatability and cost effectiveness offered by OpenData. After transitioning the software, the OpenData platform can serve as a permanent M&V tool for subsequent analysis of future proposed technologies and offerings provided by third-parties.
The benefits to DoD will include:
- A DoD site team can implement the technology independently therefore reducing the cost of deploying an automated metering systems.
- DoD Energy Managers and O&M personnel can gain better insight into energy usage.
- The benchmark “5%” energy reduction (as promulgated in the Office of the Deputy Undersecretary of Defense Meter Policy Memo dated April 16, 2013) will be validated as a way to substantiate return on investment for implementation of OpenData at other sites.
- Machine Learning technologies will be implemented and tested within the DoD framework to provide automated “over watch” of this highly complex, distributed and mission-critical infrastructure to ensure mission objectives.