NEW YORK and PALO ALTO, Calif., June 20, 2016 /PRNewswire/ -- Prescriptive Data, a subsidiary of leading real estate developer Rudin Management, today unveiled Nantum, a cloud-based smart building platform and control panel built on MongoDB, the database for giant ideas.
Designed to function as the "brain" of a building, Nantum integrates existing sensor data from disparate building systems to provide a holistic view of how a building is operating. It can then prescriptively recommend real-time system adjustments, identify operational inefficiencies, target preventative maintenance and provide 24/7, 365 building re-commissioning in real time. As a result, buildings with Nantum realize advanced sustainability performance, improved operational efficiencies, reduced expenses and an enhanced tenant experience.
An early version of the product was designed using a combination of Oracle database and Microsoft SQL Server by a team of 55 developers over 18 months. The version took 15 minutes to run a process that required expensive on-premise servers, which was not useful for building engineers. Using MongoDB 3.2 Enterprise Advanced and Amazon Web Services, as well as MongoDB's Consulting Services, Prescriptive Data and its team of 16 developers were able to recreate a brand new platform, and begin adding buildings into Nantum in less than four months. Today, the system operates in real time with new features being added onto the platform, like automation services.
"Until now, building system data has been trapped in silos, making building operations management time consuming and expensive. Nantum is the realization of our vision for a next-generation operating system to manage Class A commercial properties and more," said John Gilbert, executive vice president and chief operating officer, Rudin Management. "We chose MongoDB for its ability to easily integrate data coming from various hardware in different formats in real time, its ability to scale almost infinitely and for its ease of development."
Predictive Analytics Manage Energy Usage
Nantum learns from past data from various sources to predict daily energy usage and generates recommendations to optimize the way a building runs. Utilizing a patented machine learning engine, the system manages energy demand by analyzing building occupancy, electric demand, outside weather and other factors to automatically adjust indoor temperatures to optimal levels, saving millions of dollars in energy cost, reducing load on the energy grid and improving tenant comfort.
The system is currently providing energy savings of between 10 and 13 percent in the Rudin building portfolio, ranging from 40 to 50 cents per square foot depending on the number of hours the building operates on an annual basis.
In addition, the system generates cost-optimized ramp-up and ramp-down schedules and enables building operators to respond quickly to spikes and other anomalies with immediate alerts. With fewer issues, engineers will be more available to provide higher value services to tenants and owners.
Rudin Management has implemented Nantum in 17 of their New York City buildings, including 15 commercial buildings and two residential towers, totaling approximately 10 million square feet overall. Nantum will be demonstrated at Realcomm IBcon 2016 in Silicon Valley, June 21-24.
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About MongoDB
By offering the best of traditional databases as well as the flexibility, scale and performance today's applications require, we let innovators deploy applications as big as they can possibly dream. From startups to enterprises, for the modern and the mission-critical, MongoDB is the database for giant ideas. For more information, visit www.mongodb.com.
About Prescriptive Data
Prescriptive Data is a new technology company founded by the Rudin Family, one of New York City's largest private owners, operators and developers. Prescriptive Data's mission is to create a unified and secure operating platform for the built environment. Building energy analytics and automation services are the first applications come out the Nantum platform
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SOURCE MongoDB