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Enview automatically detects grow-in and fall-in vegetation that could pose risk to power lines. Results are displayed on an intuitive and secure Web Portal.

Enview Launches AI-Powered Solution to Automatically Detect Vegetation Near Power Lines

Utilities are using Enview to detect encroaching vegetation that threatens power lines and can cause wildfires.

 Enview, a team of Silicon Valley-based data scientists and engineers, is working to solve one of the biggest challenges facing utilities—quickly identifying threats before they become incidents.

Major incidents, like last year's historic wildfire season, and the cascading failure which caused the Northeast Blackout of 2003, may result from contact between vegetation and power lines. The ability to identify the exact location and clearances of high-risk vegetation early, and at scale, helps operators prioritize and address the problem areas.

Enview automatically detects grow-in and fall-in vegetation that could pose risk to power lines. Results are displayed on an intuitive and secure Web Portal.
"The scale of this challenge is staggering. It simply is not reasonable to expect the traditional manual processes used by many utilities to prevent these emergent threats," says Enview Founder & CEO Dr. San Gunawardana. "The results are catastrophic and we're seeing that play out not only here in California, but also worldwide. New technology can help solve these challenges. It's why we've designed and built a solution using the latest in artificial intelligence, machine vision, and cloud computing to enable accurate and extremely fast identification of at-risk spans."

Today many utilities are using LiDAR to map and visualize their power lines. Enview, which is offered through a software subscription, enables utilities to leverage LiDAR data but with much faster results and with much less manual labor. The Enview solution automatically classifies and analyzes the data to produce intuitive and accessible data visualizations that are field-ready, meaning that they can be delivered directly to the workforce in the field for immediate response.

"Ever since we completed our 2003 Northeast Blackout investigation, LiDAR-driven programs have helped utilities identify threats, but LiDAR is currently constrained by taxing levels of manual data manipulation. As an industry, we have to look to new advancing technologies like AI that enable us to automatically see what we can't see and to do so in days and weeks, not months," says Stephen Cieslewicz, a nationally recognized expert in Utility Vegetation Management.

In a recent article she wrote for the California Public Utilities Commission (CPUC), Elizaveta Malashenko, CPUC's Safety and Enforcement Division Director, has called for the use of technology to solve the challenge energy companies are facing in preventing incidents.

"There are technical solutions that can help utilities and regulators get ahead of the problem. These rely on "big data" solutions, advanced analytics, machine learning paired with data streams coming from sensors, aerial patrols, LiDAR, and other advanced surveying techniques. Expanded use of advanced technologies can enable utilities to do much more robust risk management than what can be done with boots on the ground," Malashenko says.

Utilities around the world are using Enview to identify potential threats before they become incidents. Enview will be demoing their UVM solution after the utility wildfire event at the CEATI Vegetation Management Conference Dec. 4-5 in Berkeley, California. 


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