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And it’s these two uses that will continue to drive the growth of drones for industrial use for many years to come. PrecisionHawk was one of a few companies to partner with the FAA on its Pathfinder Program, and the company’s work is informing current FAA regulations and BVLOS policy. The Economics of Using Drones for BVLOS Inspections,” they educate businesses and help them evaluate when it’s best to use traditional ground and manned aviation, line-of-sight drones, or BVLOS drone inspection approaches. That’s why, early on, they pivoted from open source-based aircraft to DJI drones since DJI is and has been for four years the dominant player in the space.

As drone technology matures, it is important to know what it means for you as the steward of your firm’s information technology and software. Drones present both a big data and an IoT challenge Up to now, the focus of commercial drone use has been on accurate data collection and visualization—not IT process integration. When dealing with drone data you may need to expand your current data governance policies because of new risks associated with aerial data itself (like privacy concerns) and the location and operations of the drone (because a drone is legally an aircraft and operates under certain regulations). As you start integrating drone data, you should familiarize yourself with the most common types of processed “processed” data from drones—not the raw data, but the data produced by imaging software and the ones you’ll most likely come across if you’re in IT.

The Economics of Using Drones for BVLOS Inspections is a white paper sponsored by PrecisionHawk, the leading provider of drone technology for the enterprise, which provides a foundation for businesses to evaluate when it’s best to use traditional ground and manned aviation, line of sight drones, or BVLOS (for “beyond visual line of sight”) drone inspection approaches. Representatives we spoke with in those industries point to four main drivers motivating them to explore BVLOS operations: * Safety, as in preventing fatal helicopter crashes or accidents from having to manually climb towers to take readings; * Costs, or reducing dependence on a $1,500-per-rotor-hour helicopter and personnel and even cutting the time and expense of the multiple flights needed in flying drones within visual line of sight (VLOS); * Data inconsistency and lack of quality, since manual data collection sometimes involves photos taken from a helicopter traveling at speed and at different heights for each flight—which leads to inconsistency—or hand-written notes taken while visually inspecting with binoculars—which leads to imprecise or poor quality data; * Time to value, meaning that BVLOS flight can cover a wide area and collect high-quality data much more quickly than traditional means, so, for example, insurance claims of total loss can be indemnified faster. The 21-page report also provides a guide for when—and how—to deploy drones to inspect assets, use cases for how drone missions compare with traditional methods, and insight from PrecisionHawk’s customers about how they’re refining their inspection strategy

Last year saw a wider rollout of the FAA’s LAANC program (the Low Altitude Authorization and Notification Capability that provides access to controlled airspace near airports), the launch of the UAS Integration Pilot Program from the FAA, and some significant developments for new regulatory frameworks for drones in Europe and in India. Some predict 2019 will be the year the FAA finally implements a requirement for remote identification for all drones, recreational and commercial, flying in the U.S. UTM should help enable some of the most talked-about use cases for drones, from package delivery to aerial taxi services, but don’t expect this first iteration of remote ID to live up to the headlines or vendor expectations of a global autonomous drone network – as that would ignore the arduous political processes in each country or region to make UTM even possible. Along with the new imaging sensor integration announcements in 2019 (such as smaller, more lightweight LiDAR), expect to see imaging software advancements as companies seek to combine RGB, thermal imaging, orthomosaic, and data from IoT sensors.