Prescriptive Data recently elaborated details of Nantum, a cloud-based platform that delivers intelligent automation for the management of real estate. Nantum integrates sensor data from a multitude of sources to deliver actionable business intelligence about the performance of a building with respect to metrics such as energy consumption, occupancy and expense utilization. Specifically, the Nantum platform ingests and aggregates sensor data sources that include subway and traffic data to proactively understand the occupancy of buildings as a means toward optimizing the delivery of energy. Nantum’s machine learning analytics can predict seasonal and local variations in occupancy as a result of variables such as weather, holidays and notable news-related events. Moreover, the Nantum platform natively integrates with infrastructures for the delivery of energy within buildings to intelligently automate the usage of energy in different buildings and their constituent floors and rooms. Built using MongoDB 3.2 Enterprise Advanced, Prescriptive Data’s Nantum platform delivers real-time analytics to building operators via a dashboard containing actionable business intelligence as illustrated below:
Whereas an earlier version of the application was built using Oracle and Microsoft via an on-premise deployment, the current version is delivered via the cloud using MongoDB Enterprise Advanced in conjunction with Amazon Web Services. The existing platform delivers prescriptive analytics that empower building operators to make decisions using machine learning-generated algorithms. Building operators can elect to implement the recommendations from Nantum’s smart building platform or customize them as desired. Importantly, the platform delivers recommendations about building management based on real-time data and iteratively optimizes the accuracy of its prescriptive analytics using machine learning technology. Expect to hear more about Nantum as it brings it smart building analytics to more buildings across the U.S. via the intersection of MongoDB-based big data, the AWS cloud, predictive analytics and real-time data feeds that produce interactive data visualizations for building owners and operators.