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2019 GTC San Jose

S9855 - Machine Learning for Automated Context Discovery of Commercial Buildings

Session Speakers
Session Description

Intelligent buildings help create and maintain a safer, more secure, productive, and comfortable environment. A modern-day commercial building may have hundreds of air conditioners, thermostats, and other devices connected to thousands of sensors for measuring critical parameters like temperature, airflow and pressure. As a result, configuring or commissioning new buildings can take weeks or months. During equipment installation, installers typically embed contextual information around the sensors in the sensor name. We'll discuss the neural net-based models we developed to recognize and extract patterns in the sensor-naming convention and its time-series data to predicts tags necessary for fault detection and diagnostics. We'll describe our findings showing that our context-discovery process accurately recommends important information to system integrators with 80-90 percent confidence.


Additional Information
Building Design
AI Application Deployment/Inference Building Design Predictive Maintenance/Monitoring
General
All technical
Talk
50 minutes
Session Schedule