Kewen Gu

Kewen Gu is a Machine Learning Engineer in the Sustainability Software division of IBM, focusing on building AI solutions for businesses using weather, remote-sensing Imagery and client related data sets. He has extensive experience working with very large data sets including scaling runs using PySpark, Kubernetes, Argo. Currently, he is focused on building and deploying two main AI solutions in the IBM Environment Intelligence Suite - a) Outage Prediction which predicts where and how many outages a Utility should expect during a storm. b) Vegetation Management, which uses 3D Imagery to determine where a Utility needs to trim trees that are closest to power lines.

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Sessions

11-02
10:10
40min
How to Empower Utility Vegetation Management: A Blend of AI and LiDAR Data
Kewen Gu, Anjani Prasad Atluri

The great majority (more than 2/3) of power outages are caused by contact from vegetation to an active power line, with the added risk of fire and public safety. The goal for utility companies is to manage the vegetation near their above-ground infrastructure in order to reduce these types of contact during inclement weather. This session will discuss an AI-driven vegetation management solution, using LiDAR and satellite imagery to determine the highest risk areas of a utility's service area. Our approach is able to give insights across a service territory, by line down to the foot level as far as how close a branch may be to a power line. This work will enable them to shift from cycle-based to condition-based trimming. We will go over the data used, the various technical challenges, and our approach to scale the solution.

Radio City (Room 6604)