You Don’t Have the Data You Need to Effectively Maintain Your Right-Of Way? Here’s How You Can Get It!

Power transmission line right-of-way

Right-of-Way (ROW) monitoring is often a game of inches that takes place over weeks, months, or even years. Having a clear ROW is important, but performing the necessary inspections can be a burden that siphons your maintenance crew’s valuable time and effort. However, intrusions on your right-of-way can cause damage to above-ground infrastructure, interfere with crew maintenance efforts, and cause disruptions to nearby landowners and the public at large.

Current methods for ROW monitoring aren’t giving operators the information they need to identify potential problems before they become critical maintenance issues. As a result, management teams are making reactive decisions that disrupt schedules and divert company resources.

The good news? There is a better way of doing things.

To get the information your company needs to start proactively managing your right-of-way, you need to leverage predictive analytics.

To thoroughly inform a predictive analytics model, you need to make regularly scheduled inspections, consistent high-resolution imagery, and high-quality data the cornerstones of your ROW monitoring program.

Developing a Baseline for Predictive Analytics

The path to predictive analytics starts with building a baseline set of data with an initial inspection. By following-up with subsequent inspections on a routine basis, you can gather the necessary datasets you need to track changes on your ROW.

However, to perform this kind of analysis, you need to be working with consistent and highly-precise imagery that doesn’t radically deviate from one inspection to the next. To derive high-quality data from the large volumes of raw images, we use machine-learning algorithms with a small degree of human verification. Using an automated system can effectively analyze the subtle changes between new and historical data, notifying you of trends and potential problems. While a human can help to better contextualize the anomalies that the algorithm has flagged.

Taking a proactive management stance allows you to better understand the issues occurring on your right-of-way, as well as give you higher confidence that maintenance efforts are driven by complete and accurate information. Regularly scheduled inspections, consistent high-resolution imagery, and high-quality data – these three criteria must be a core part of your ROW monitoring operation to unlock the full value of predictive analytics.

Proactive Management for a Clear Right-of-Way

Here are common intrusions in a right-of-way and how predictive analytics can help you better address them:

  • Vegetation encroachment: Think of a tree as a long, drawn-out explosion that is slowly making its way into your ROW and toward your asset. In the world of power transmission lines, it only takes one lucky branch to jumpstart a serious incident. During a recent power line inspection, we were able to detect tall-growth vegetation that was well-within the ROW area. With consistent imagery from inspection-to-inspection, a predictive analytics model could track the gradual growth of vegetation and flag it before it becomes a red-flag maintenance issue.
  • Erosion, cracks, and ground depressions: Ground deformations cause serious damage to oil & gas pipelines, making them high priorities for pipeline integrity management. Geological anomalies of this nature are difficult to spot via manual inspection, one of our clients – a pipeline operator in Mexico – wasn’t catching these issues during their routine ground inspections along the pipeline. Our aerial system and machine-learning analysis were able to detect cracks forming in the seismically active ground.
  • Unauthorized human activity: Effectively tackling human entry into a restricted right-of-way area is about finding hotspots of activity that indicate easy access to the pipeline. With the ability to detect anomalies such as footprints and vehicle tracks, and a log of consistent datasets for comparison, computer vision software can identify common-areas of unauthorized human activity that should be addressed.
  • Construction and development: Construction sites are easy to spot, but their gradual expansion into your right of way might not be. Not to mention, wayward excavation and backfill can remain well-hidden amongst the surrounding terrain. The subtle changes in the landscape and gradual growth of work sites are something predictive analytics are well-suited for measuring. In Alberta, we identified improper construction backfill from the previous summer, which was concealed by heavy snowfall at the time of inspection. The client, a pipeline operator, was able to get in touch with the construction company and have the issue rectified.

Now that you know the value of predictive analytics, you’re probably wondering how it’s possible to increase the frequency of inspection, quality of data, and consistency of imagery – without increasing the complexity and cost of your operation.

Aerial Inspection with Drones = The Right Quantity and Quality of Data

Performing frequent inspections requires a system that is swift, easy, and cost-effective to deploy – because consistent data requires a highly-repeatable method for collection. Drones are fantastically suited for this use case. Be it a pipeline or power line, having fully-autonomous aerial systems scan your right-of-way makes it easier to regularly monitor these long, remote corridors without having to run a complex operation.

Historically, aerial inspection of the right-of-way is performed by manned aircraft, but this method isn’t practical for getting the volume and quality of data you need to start addressing problems proactively. Frequently dispatching planes or helicopters can quickly increase the cost and complexity of your operation, while data collection from these vehicles is often low resolution and inconsistent from flight-to-flight. Not to mention, critical accidents involving these vehicles in pipeline and power line monitoring operations aren’t unheard of.

Drones can perform these inspections more effectively and yield higher-quality data. Highly-autonomous aerial systems are able to take-off from a launch station, fly its mission, collect data, land back on the station, transmit data for processing, and recharge for the next flight all without human intervention. All the while, the vehicle is flying a precise, programmable flight path that ensures data remains consistent from flight-to-flight.

Aside from the consistency of data, highly-programmable missions allow you to tailor your flight path for the perfect intersection of image collection and safety. For instance, in the case of a power transmission line application, the aerial system can fly at a set altitude above the right-of-way that maintains a safe operational buffer between the transmission line, towers, and terrain below – while still allowing for optimal image capture of the asset and surrounding right-of-way.

Additionally, automated failsafes can be modified to take the presence of high voltage transmission infrastructure into consideration – such as geofencing to maintain a safe distance from the asset and avoidance maneuvers that limit descent until the vehicle is well-clear of the power line.

Improving the maintenance of your right-of-way requires a shift from reactive to proactive management. Through regularly scheduled inspections, consistent high-resolution imagery, and high-quality data – you can unlock the predictive analytics that drive this paradigm shift. Highly-autonomous aerial systems are the ideal vehicle for meeting these requirements, which will empower you to better identify subtle anomalies and developing issues on your ROW.

Want to improve the quality of your right-of-way monitoring program?

Contact our team to discuss your unique challenges and technical requirements.