Which is more expensive, maintaining your oil and changing it regularly or allowing your engine to run out of oil and ultimately fail? The answer is obvious. While preventative maintenance does cost both time and money, you ultimately save a considerable amount of time and money by not dealing with catastrophic failure. The fact is that regular inspections prevent things from breaking.
Our infrastructure is no different. Proper preventative maintenance can keep things from falling and as we all know, when infrastructure fails, the results can be unimaginable. Failures to inspect have resulted in a huge loss of life as well as costly and time-consuming repairs. Several major fires in the United States started because of improperly maintained right of ways where vegetation was allowed to grow into the powerlines. After a major disaster like these, we typically do a post-mortem and find out that these events were preventable if only we knew about the issues in advance. The question then becomes, how do we find out, AND most importantly, how do we catalog and manage these issues?
We have been using GIS to manage these issues for a long time. It is a major part of any asset management program. We send out field personnel, they perform their routine inspections and preventative maintenance, we catalog those efforts in our GIS using some proprietary tools or something like Esri’s Survey123 or Collector. When we are done with our inspections, we sync that information back to our GIS database that is accessible by the rest of our team using a dashboard, a portal, or directly through the server. All the information is in one place, with a properly structured system for managing the work that is performed every day. This is a well-established way of doing things that we have been doing for a long time that works great (most of the time).
So, what happens when things are not easy to access for inspections? What happens when accessing those areas becomes dangerous such as a utility pole or transmission tower? Wooden utility poles specifically often rot at the top first. That type of rot is difficult to inspect from the ground. To see that traditionally, you would need to climb that pole to get a look. Doing so is dangerous and time consuming not to mention there are over 185 million distribution poles in the United States alone. That is an absurd amount of assets that could potentially fail with catastrophic results.
One of the ways we have started to address this issue is with the use of drones. Drones are the perfect tool for hard to reach asset inspections. Under Part 107, the commercial drone pilot regulations in the United States, we can fly about a half-hour at a time, line of sight, which is typically a mile per flight. In a half-hour, we can safely inspect a heck of a lot more poles than if we had to walk each one let along climbing them. Drone adoption continues to grow in various asset management domains such as electric utility, oil and gas, water/wastewater, and telecommunication. It truly is a tremendous tool for high value hard to reach assets.
With that said there is a downside. Drones have allowed us to get to these difficult areas and they allow us to collect massive amounts of imagery showing any issues in stunning clarity. The question is, how do you now manage all this information you have collected with the drone? It’s still independent and not well integrated into your GIS systems. How do you get all that data into your asset management system so that imagery can become action? That is ultimately what we want to do. We want to turn imagery into action. Identifying the problem is only half the battle.
So how do we do this? How do we fully integrate the drone into our GIS and asset management program? We believe the answer is, we take the things that have worked on the ground for GIS asset management and we bring that to the drone. To do this, we need to first bring the GIS with us when we fly. We have found that the best way to do this, in our opinion, is by using augmented reality. In this context, think of augmented reality in the same way you would a 2D map on your mobile device or computer. Live video becomes your base map. Now you can fly around your map and go to the different things in it to inspect them. Just like you would with Esri Collector, you can select an attribute, you can see all your attribute information and you can begin to edit that information, as necessary. Attach images, select pre-defined ranges or domains or use related tables to manage the inspection. The beauty of handling your drone data this way is that you have embedded the GIS into the exact process you would have performed with that drone anyways. By doing it this way, you have saved 12 steps that used to be required after you land. All of that is baked into the workflow. Now instead of putting data on a hard drive, loading data on a server, finding a way to correlate that back to a location in your GIS, joining that information in some way to the geometry, and then entering your field notes, Its already complete. You can do it all right there. To us, this is the most logical way to approach drone inspections.
So, in summary, drone adoption in inspection continues to grow rapidly and rightfully so as we discussed today. It’s a clear and obvious choice for certain applications. We believe that there still is a major adoption challenge and unrealized potential because these systems to date have not been properly integrated into organizations' workflows. Our hope is that we have shown you, or at least provided some food for thought on how those challenges may be overcome in the future. Even if it's not our solution to the problem specifically, we hope that in the future that clients will demand that their drone asset inspection workflows are managed in their GIS in a way that is similar to the rest of their operations. As our systems grow more and more sophisticated our workflows must adapt to that. We need to ensure that boots on the ground have proper context with the existing information we have, that they have a way to manage the content they are collecting that reduces the amount of potential human error, and importantly that their workflow facilitates better communication with everyone involved so that better decisions can be made quickly to prevent as many catastrophic failures as we can.
Christian Stallings is one of the Co-Founders of BirdOne and the CEO