Navigator Cloud-Based Predictive Analytics
Casey Jones | Siemens Government Technologies, Inc.
Naval Station Great Lakes trains 40,000 recruits annually to become U.S. Navy sailors and hosts advanced training for 16,000 sailors annually. Any delay to training drastically impacts U.S. Navy readiness; therefore, facility repairs and condition is a high priority. Support to the public works shops personnel to assist trouble-shooting equipment and predicting failure would improve the resiliency of Naval Station Great Lakes to meet its mission to train recruits to be sailors. The technology (Navigator) is a remotely hosted cloud-based (Amazon Web Services) data management energy and sustainability platform that integrates and centralizes energy and facility data, from Advanced Metering Infrastructure (AMIs), Heating, Ventilation and Air Conditioning (HVAC), building automation, Utility Meter Data Management systems, Asset Management Systems, and other sources of facility data, into a convenient user interface. It can be securely accessed from any location with an internet connection and is designed to assist with optimizing the performance of buildings. Powerful predictive analytics rulesets provide the necessary information to find and act on performance optimization and energy savings measures. Reports allow users to normalize by floor area and weather to accurately compare variables affecting energy consumption and costs between and among individual facilities. Navigator is a thin client enterprise application providing energy and facility data to any user of the application. All data is hosted and archived by Siemens in a secure environment using data encryption with regular backups and no storage limit for historical data.
The research team will demonstrate a remotely hosted, cloud-based application that integrates and centralizes energy and facility data from multiple sources into a convenient user interface that can be securely accessed from any location with an internet connection. Fault Detection and Diagnostics (FDD) will be developed using predictive analytics that will alert facilities managers’ maintenance about issues before they affect the building occupants, allowing for prioritization, repair parts to be procured and the work to be scheduled to minimize impact to operations. Repair work orders will be generated in Maximo or a similar work order management system through integration. The research team will also provide a Cybersecurity assessment based on the DoDI 8510 Risk Management Framework (RMF) for Department of Defense Information Technology. The server farm is operated in a demilitarized zone, meaning that the application is protected by firewalls against the internet as well as the Siemens intranet. The application and data are hosted on separate servers. The database server is not accessible from the internet but only via the Navigator application, which is located on the application server. Secure communication with the Navigator application server is guaranteed by a state-of-the-art encrypted connection (128-bit SSL).