Skip to main content

Utility Corridor Management using Machine Learning

At Data Tapestry, our team's expertise spans a variety of specialties. While we've been able to apply NLP techniques, forecasting, and predictive analytics to many problems, most recently our team had to work with image data and the complexities that it presents. We combined resources with unmanned imaging experts at Skytec, LLC to create a solution for overgrowth and vegetation management in utility corridors. 

Damages in these areas due to overgrowth can occur without warning. Tower damage and power outages can cost millions of dollars in repairs and regulatory fines. It is even more important to detect these encroachments since an electricity arc or flashover can occur within less than 15 feet of power lines, thereby damaging equipment or causing fire to nearby vegetation. Unfortunately, manual efforts to monitor overgrowth can be extremely manpower intensive, expensive, and inefficient.

Our Solution

Imaging experts at Skytec provide aerial photos of utility corridors via unmanned and manned aircraft systems. Additional enhancement layers are added to the image to improve the visibility of the landscape and other objects. Next, our team will pre-process the images so towers, trees, roads, and buildings can be easily distinguished. Once the images have been processed, we train a multi-label classifier on labeled input images over several iterations. After that, we apply functions to calculate the difference in vegetation indexes over time. Then we execute an algorithm for calculating the distance between towers and other objects over time to determine if action needs to be taken. The result is the identification of vegetation and other objects within the corridor that could be potentially hazardous. 

If you are interested in learning more or seeing how this solution can be applied in your business, email us at or visit our website


Post a Comment

Popular posts from this blog

Transforming and Accessing Data through Custom Built Pipelines

One of the biggest hurdles in data analysis is just getting access to data in the first place. At Data Tapestry, we offer end-to-end analytics services beginning with data acquisition, performing analytics, and providing end user products. Keith Shook walks us through how to maintain data security and integrity when dealing with a variety of situations. Tell us a little about your background and your role at Data Tapestry. Currently, I’m a senior data engineer, but I actually started off as an intern ingesting data into Postgres and SQL databases. I then shifted into visualization using D3, a javascript library, but we found that Tableau was much more efficient. Since then, I’ve gained a variety of experience using scala, Hive, AWS, and building clusters.   Can you walk us through a project you’ve worked on? Data engineering is pretty straightforward as far as the process goes. You get the data, ingest it into the database, and then hand it off to the data scientist. You have to be fle
Here at Data Tapestry we are here to help organizations looking to understand their data and make improvements to their organization’s customer service, turnover, or solve one of the many other challenges facing organizations today. Some of our specialties include NLP analytics, developing data system architecture tailored for analytics, predictive analytics, and applying applications to simplify data. With some of our current and previous clients we have been able to come up with solutions to assist with turnover by automating the process of analyzing employee exit surveys, analyzing employee efficiency, and utility corridor management using machine learning. We have also worked on a project for integration of financial and contract management systems to improve allocation to company’s KPI, as well as parking assignments for universities during sports seasons to name a few. We are able to tackle a variety of software customizations as well as analyze data and provide solutions to comm