Aerial view of an industrial facility with rows of cylindrical storage tanks

What is industrial drone inspection?

Industrial drone inspection, defined

Industrial drone inspection is the use of unmanned aerial vehicles (UAVs) to inspect large industrial assets, such as bridges, pipelines, wind turbines, power lines and storage tanks.

Industrial drones carry cameras and sensors that capture information that inspectors can’t, making them an indispensable tool for maintenance organizations in asset-intensive industries.  

Unlike recreational drones, industrial drones carry advanced equipment such as high-resolution cameras, thermal cameras and LiDAR sensors. Industrial drone inspections help organizations advance and modernize their maintenance capabilities by easily integrating data into computerized maintenance management system (CMMS), enterprise asset management (EAM) and digital twin software and platforms.  

Industrial drone inspection has become common wherever organizations need to maintain large, physical assets as part of their core business processes. Data gathered by drones helps inform many modern maintenance strategies, including predictive maintenance, asset management planning and automated regulatory compliance.

The market for drones that can be used for inspection in general—not just to inspect industrial assets—is large and growing. According to a recent report from Global Newswire, the market is projected to grow from USD 14 billion in 2024 to almost USD 36 billion in 2029.

The five steps of the industrial drone inspection process

Industrial drone inspection is the process of drone operators flying drones near industrial assets to collect detailed visual and non-visual data to maintain those assets better.

Most drone inspections—not just those involving industrial assets—are conducted through a simple, five-step process.

1. Planning

The first step for any organization seeking to implement drone inspection is to clearly define its objective.

Maintenance planners must determine which assets require drone inspection, which defects they’re trying to identify and what types of data they want to collect.

2. Flight preparation

After creating a drone inspection plan, drone operators prepare the unmanned aerial vehicle (UAV) and verify that its onboard systems are functioning correctly.

The second phase of the drone inspection process usually includes steps such as calibrating navigation systems, checking battery health, testing cameras and sensors and confirming GPS accuracy.

3. Data collection

During the data collection phases, drones use cameras and sensors to capture data and images according to their flight plan.

Many modern drones have autonomous flight software that enables them to maintain consistent distances from sensitive structures such as storage tanks, pressure vessels and refineries and take photographs from multiple angles. This repeatability aspect allows maintenance teams to compare results from identical viewpoints across multiple inspections.

4. Data processing

After the flight, software processes the information the drone collected into a usable data visualization, such as orthomosaic imagery, a point cloud dataset or a three-dimensional map (3D map).

Photogrammetry software can reconstruct an image of an asset from overlapping photographs during this phase, while other software can translate laser measurements into highly accurate digital representations of structure and terrain.

5. Analysis and reporting

The last stage of the drone inspection process involves engineers, inspectors and maintenance specialists analyzing the data the drone collected to identify potential defects in physical structures.

Most modern organizations integrate the results of drone inspections directly into a CMMS platform where software automatically creates and maintains a maintenance record and inspection history for each asset.

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Visual versus non-visual industrial drone inspection

Modern industrial drones are primarily set up to conduct two types of inspections: visual and non-visual:

  • Visual inspections: Drones carrying standard high-definition cameras conduct visual inspections by capturing images and video of an asset’s exterior. Examples of problems frequently detected during a visual inspection include cracks, corrosion, loose hardware, dents, paint or coating damage and missing components.
  • Non-visual inspections: Drones performing non-visual inspections use specialized sensors to collect data that the naked eye cannot detect. These sensors can reveal hidden defects in structures and variations in temperature. Data collected during non-visual inspections is often used to create a highly detailed digital model of an asset to assist in maintenance planning.

Here’s a side-by-side comparison.

 

Visual inspection

 

Non-visual inspection

 

Equipment

Uses high-resolution, red-green-blue (RGB) cameras that mimic the human eye

Uses complex non-visual devices including thermal cameras, thermal sensors, LiDAR sensors, gas detectors and multispectral cameras

Uses

Detects visible defects and surface damage including cracks in bridges, blade erosion on wind turbines and loose antennas on cell towers

Detects defects or asset conditions invisible to the naked eye, including methane leaks at an oil and gas refinery, overheating in a storage tank and variations in underground terrain in a mine

Output

Photos and videos

Thermal imagery, point clouds, 3D models and 3D maps

Strengths

Best for leak detection, powerline inspection and other processes that help identify superficial damage such as corrosion, cracks and missing parts

Best for identifying changes in temperature or terrain, structural problems and gas leaks

Inspection standards for industrial drones

Industrial drone inspections are subject to requirements set by industry-specific organizations and national governing bodies, such as the Federal Aviation Administration (FAA). To ensure regulatory compliance, organizations often demonstrate their procedures to the relevant governing bodies.

Aspects of industrial drone operation covered during these demonstrations typically include the following elements:

  • Flight planning
  • Procedures for maintaining data quality
  • Inspection intervals
  • Documentation
  • Personnel requirements
  • Record retention

Formal inspection bodies

The formal inspection bodies that regulate drone inspection are divided into two categories: rules that govern drone flight and rules that govern infrastructure inspection.

Worldwide, national aviation authorities regulate drone flight, while the International Civil Aviation Organization (ICAO) increasingly standardizes the overall regulatory framework.

In the United States, the FAA regulates all drone flight, sets rules for safe flight, controls air traffic and establishes oversight of commercial drone operations.

Infrastructure inspection standards—which organizations operating industrial inspection drones must also comply with—vary by industry. Here are a few of the regulatory bodies responsible for monitoring industrial drone inspections in the United States:

Benefits of industrial drone inspection

Drone inspection benefits many industries, but perhaps none more than those industries that operate large, complex industrial assets. Industrial drone inspections enable organizations to inspect their physical assets faster, more safely and more accurately than was possible in the past when relying on human resources.

By improving the quality and frequency of inspection data, industrial drone inspections enable maintenance teams to make smarter decisions throughout the entire asset lifecycle. Here are some of the most common benefits of industrial drone inspection at the enterprise level:

  • Improved worker safety: Industrial drone inspection helps minimize employee exposure to hazardous work environments. Instead of climbing towers, working over water or employing rope access to scale structures, inspectors can collect the same data while remaining safely on the ground.  
  • Better data quality: Modern drones capture thousands of high-resolution images from viewing angles that are difficult or impossible for humans to access. Digital inspection records also eliminate much of the subjectivity associated with handwritten inspection notes.
  • Increased frequency: Flying industrial drones allows organizations to inspect their assets more frequently and with fewer resources. While a visual inspection by a human requires personnel, safety equipment and scheduling, industrial drone inspections require just a drone and a pilot and often have less rigorous scheduling demands.
  • Reduced downtime: Downtime costs companies millions. According to a recent report from IBM, 33% of enterprises surveyed said that just an hour cost them between USD 1 and 5 million. Industrial drone inspections can be performed without shutting down most equipment, minimizing disruptions and allowing maintenance teams to prioritize repairs instead of inspections during scheduled downtime.
  • Stronger asset management: Industrial drones collect detailed, accurate data that can help build a more comprehensive understanding of asset health than data gathered by human inspections alone. Combined with modern tools such as CMMS, EAM software and digital twin technology, drone inspection supports long-term asset lifecycle management (ALM) strategies and enables better asset investment planning (AIP).

Examples of industrial drone inspection by industry

Industrial drone inspections are used across nearly every asset-intensive industry, including transportation, oil and gas and mining. Here are some of its most common use cases:

  • Bridge inspection: Industrial drones inspect nearly every aspect of bridge infrastructure, including decks, suspension cables, expansion joints, steel beams and underside structures. Visual inspection with high-definition cameras helps engineers identify corrosion, cracking and structural issues while minimizing traffic disruptions and reducing the cost of resources.
  • Oil and gas facilities: The oil and gas industry relies extensively on industrial drones to inspect complex infrastructure such as pipelines, refineries, flare stacks and pressure vessels. Thermal imaging often reveals insulation failures and abnormalities in temperature that can indicate a problem. Photogrammetry, the construction of 3D models from 2D imagery, helps create accurate digital models of physical assets.
  • Wind farms: Wind turbine inspections on wind farms traditionally required technicians to descend from blades or use specialized cranes, both potentially dangerous activities. Today, industrial drones flown near turbines can quickly detect lightning damage, surface erosion, edge wear and other issues without putting maintenance workers at risk.
  • Electrical transmission systems: In utilities asset management (UAM), inspecting power lines frequently poses a safety hazard for technicians. Utilities companies are increasingly using drones to inspect many of their physical assets, including power lines, towers, poles and substations. Thermal cameras help identify overheating electrical connections and high-resolution imagery reveals damaged insulators, corrosion and vegetation encroachment.
  • Mines: Mining companies increasingly rely on industrial drones for inspection and surveying purposes. LiDAR and photogrammetry produce accurate 3D maps, orthomosaic imagery and point cloud datasets that help mining operators improve safety, optimize production planning and maintain critical infrastructure.

The future of industrial drone inspection

Demand for drone inspection is increasing worldwide, with industrial drone inspection considered to be one of the fastest-growing application areas. As infrastructure ages and safety regulations increase, asset-intensive industries such as oil and gas, mining and transportation are turning to industrial drones to improve safety, reduce costs and conduct more frequent inspections.

Here’s a look at three major trends shaping the industry.

AI-enabled autonomy

Drones are becoming more autonomous through increasingly advanced artificial intelligence (AI) applications. For industrial drones in particular, AI is having an impact on how they are flown and how they gather and analyze data.

Here’s a look at some of the areas where new AI capabilities are enabling advancements in industrial drone technology:

  • Planning flights
  • Collecting and analyzing data
  • Avoiding obstacles in real time
  • Returning to charging stations when batteries are low
  • Conducting scheduled inspections without human input

Beyond visual line of sight (BLVOS) capabilities

Beyond visual line of sight (BVLOS) operations are drone flights that require manual operation when drones are too far away for pilots to see them. Driven by the need to inspect assets that span hundreds of miles, industrial drones are being designed to enable pilots to operate them from farther and farther away.

Organizations seeking to operate drones in this way must first receive approval from relevant governing bodies. In the United States, FAA approvals of BVLOS drone operations increased from 1,229 in 2020 to 26,870 in 2023, according to a recent report form the Inspector General. This increase indicates a dramatic rise in demand.

Here are some examples of assets BVLOS drone flights help pilots inspect:

  • Pipelines that travel hundreds of miles
  • Electrical transmission lines, railways, bridges and highways in remote areas
  • Large mining operations
  • Energy infrastructure that sits miles offshore

Integration with asset management systems

Modern drone inspection platforms are becoming increasingly integrated into asset management systems so they can improve long-term maintenance strategies, simplify workflows and inform capital planning decisions.

These software systems integrate data from industrial drone inspections:

Instead of generating inspection reports, future systems will likely automate work orders, update asset histories and enhance predictive maintenance. They will also prioritize repairs based on defects drones have detected.

 

Mesh Flinders

Staff Writer

IBM Think

Ian Smalley

Staff Editor

IBM Think

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