The air is cool as the sun hangs low in the sky. Nighttime draws near. Amidst the rustling of the trees in the wind, there’s a faint buzz. It grows louder. It draws closer. Overhead, a drone flies past. 

The drone is inspecting a pipeline right-of-way. Ahead of the drone stretches a corridor of flat land saddled by wild countryside. This is the third and final inspection of the day.

From a remote office in a distant city, a pilot-in-command monitors the vehicle as it autonomously performs day-to-day inspections.

As the drone completes this leg of the mission, it lands at a ground station, begins to recharge for the next flight and transmits the captured imagery for analysis. A machine learning algorithm conducting change detection analysis parses through the imagery and identifies two anomalies in a small area. The first is a ground depression—that indicates recent excavation and fill—directly above the pipe. The second anomaly is a set of tire tracks.

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