The utilities industry is at an interesting point in which things seem to be moving in two different directions simultaneously. In many ways, it is the same as it has always been. Many of the power systems we rely upon for our daily energy usage are largely the same as they have been for decades. Of course there have been updates to the technology to keep up with changing demand patterns and improving tools, but the need for inspection, maintenance, and replacement follow many of the same beats. Organizations are still having to keep track of all of their assets, a challenge the industry has been dealing with since its inception.
At the same time, many of the things that have caused gradual change across the sector are starting to shift more rapidly, and it’s being reflected in the way work is being done. Demand has always increased gradually over time as populations have risen, more people have migrated from rural areas to urban centers, and new technology that requires power has become more commonplace. Urbanization is now starting to increase more rapidly, though, and the recent AI boom is putting exponentially more demand on our energy utilities. Throw in greater focus on how our energy systems are affecting the planet and the adjustments that are being made with that in mind, and it is a uniquely tumultuous time in the industry.
All of these changes have made the sector need to adjust the way it works, and one of the major effects has been the need for more accurate accounting of the assets owned by the company. The good news is the technology to map these sprawling networks of assets is rapidly improving along with the industry, and mobile mapping is a critical part of this puzzle. Whereas traditional survey methods of manually mapping this network were largely inefficient and time-consuming, mobile mapping has made much of this work more efficient, and the improving technology in that space, in terms of both hardware and software, is coming at the perfect time for the utilities industry.
Consider the path that mobile mapping hardware has taken in recent years. Systems to be attached to cars or trains are better than ever for performing these mapping and asset tracking workflows, bringing better performance and more ease of use. These systems are consistently improving with every release, including by adding more sensors to give a wider breadth of coverage and more dense point cloud. Thanks to lidar sensors in general becoming smaller, the mobile mapping systems are also getting lighter and more portable at the same time. Additionally, as IMU integrations and SLAM capabilities improve, these systems no longer need to rely on consistent GNSS connection and can capture accurate data at highway speeds, a game-changer for this space.
As all of these improvements have streamlined the actual data collection workflow, the software that processes all of this data and turns it into actionable insights has improved right alongside it. Much of this improvement connects with the very same AI booms that are changing the demands around our energy utilities in the first place. While it’s been generative AI that has captured the attention and imagination of most of the world, it’s machine learning and computer vision types of AI that are changing the mobile mapping and utilities space.
With these new algorithms, software is now available that can quickly and painlessly not only process the point cloud data, but also automatically extract features. For a utilities industry that needs to classify thousands of assets like poles, wires, transformers, and more from massive datasets, this kind of tool is truly game-changing. Even beyond the simple mapping, many of these tools can also identify potentially defective assets, making the process of maintaining these assets significantly simpler.
Even with all of these AI-powered capabilities often getting most of the attention, arguably the most powerful software improvements have come around the fusion of data from different data sources. As noted, mobile mapping is becoming a crucial piece of this utility mapping workflow, but it’s still not the only way to collect data. Some parts of these networks may not be particularly close to a road, making a handheld mobile mapping system or tripod-based scanner more useful. And of course, getting scan data and imagery from above is still crucial. Traditionally, bringing all of this data together into one cohesive deliverable has been easier said than done, but it’s becoming a significantly easier ask.
For the managers of these networks who are facing the simultaneous pressures of aging infrastructure and evolving energy demands, these advances couldn't come at a better time. The combination of faster, more accurate hardware and AI-powered software processing means comprehensive network documentation is no longer a luxury reserved for major capital projects; it's becoming an operational necessity that's finally within reach. The ability to maintain current, precise inventories while identifying potential issues before they become costly failures directly addresses the industry's core challenges of reliability, safety, and cost management in an increasingly complex operational environment.
On the other side of the equation, by embracing these improving technologies, the service providers contracted to complete most of this work are positioning themselves not just as data collectors but as strategic partners in utility asset management. The efficiency gains from high-speed collection systems and automated processing translate directly into competitive advantages.
As utilities increasingly recognize the value of accurate, up-to-date asset intelligence in their decision-making processes, service providers equipped with these advanced mobile mapping capabilities will find themselves essential to their clients' operational success. The technology has evolved from a nice-to-have service to a fundamental business tool, and those who master it first will define the industry standard for years to come.