The Importance of Analysis-Ready Data to Power Line Fire Safety Planning

Logo
Presented by

Dr. Mike Flaxman, Spatial Data Science Practice Lead, OmniSci & Brian Kummer, Director West, OmniSci

About this talk

Conventional vegetation management by power utilities has been based on 3-year revisit scheduling and largely ground-based monitoring. These efforts have not been minor - utilities spend rather many millions of dollars per year. But recent events in California have made it clear that they are completely insufficient. OmniSci offers power utility companies an alternative solution based on continuous monitoring data and fire science. Our GPU-accelerated analytics platform integrates disparate datasets, including near-real time satellite, LIDAR and weather and micro-demographics data, in order to assess risk dynamically. Thanks to the power of cloud ETL and GPU-accelerated geoprocessing, we are able to put analysis-ready data interactively in front of key utility managers. During this session, we will discuss how GPU-accelerated analytics can help visualize vegetation risk and help utility companies take action on wildfire prevention. From vegetation management, to balancing the electrical grid, to smart meter analysis, fleet management, and beyond, GPU-accelerated analytics is a breakthrough technology that allows utility and vegetation management companies to visualize their massive IoT and telematics datasets. This unprecedented level of data visualization improves vegetation management plans - including invasive vegetation management - and wildfire prevention methods to help utility companies reduce costs, catastrophes, and to keep the lights on. We will show this capability through a demonstration of California fire history and risk to infrastructure dataset on the OmniSci GPU-accelerated analytics platform .
Related topics:

More from this channel

Upcoming talks (0)
On-demand talks (55)
Subscribers (2526)
HEAVY.AI provides advanced analytics that empower businesses and the government to visualize high-value opportunities and risks hidden in their big location and time data.