Flyability’s new High-Accuracy Mapping feature brings survey-grade Elios 3 point-cloud processing into Inspector Online. It helps industrial teams connect drone inspection evidence with the spatial data needed to understand, measure and manage complex assets.
A drone inspection can show that an asset has a crack, corrosion, blockage or deformation. A high-accuracy point cloud helps teams understand exactly where it is, how it relates to the surrounding structure and whether its condition changes over time. That distinction explains why Flyability’s newly released High-Accuracy Mapping feature matters. Available as of October 6 in Inspector Online, formerly Flyability Cloud, the capability lets Elios 3 users process LiDAR survey data online using the same FARO Insight-powered SLAM technology that underpins Flyability’s established FARO Connect desktop workflow. Rather than exporting data for local processing in separate software, users can generate, review and share point clouds within the same online environment that houses their inspection data. For asset owners, this capability turns confined-space drone flights into a more complete record of asset condition that helps to support decisions about maintenance, repair planning, surveying and risk reduction.
From Visual Evidence To Spatial Context
Visual inspection of assets remains essential across the industrial enterprise. Video and still images can document anomalies and give inspectors the context needed to identify issues. But imagery alone does not always answer the next set of questions: How large is the problem? Where is it located within the asset? How far is it from another structural feature? Has the shape of the environment changed?
A point cloud gives teams a digital representation of a physical space. It contains millions of measured points that collectively describe walls, pipes, beams, tunnels, tanks or other surfaces. When processed accurately, that data can support distance measurements, volume calculations, deformation assessments, design comparisons and repeatable condition monitoring.
For example, consider a drone flight inside a wastewater tunnel. An inspection video may reveal sediment accumulation, surface damage or intrusions. A high-accuracy point cloud can add measurable spatial context, such as the tunnel diameter, the extent of a buildup, the location of a defect relative to a joint or access point, or changes between inspections.
That level of context is especially useful in confined, inaccessible and GPS-denied environments, settings where Flyability specifically designed its Elios 3 to operate. Traditional inspection methods can require rope access, scaffolding, shutdowns, entry permits or worker exposure to hazards. A drone can reduce the need for people to enter those areas, while LiDAR data can help teams produce a digital record that extends beyond visual documentation.
The Role Of Faro Insight
Flyability’s newly released High-Accuracy Mapping uses FARO Insight’s SLAM technology, including the same underlying processing engine, presets and settings used in FARO Connect its established desktop workflow for processing Elios 3 LiDAR data. The cloud-based capability processes data through FARO Sphere XG, while Flyability says Inspector Online keeps the results connected to the wider inspection workflow. That relationship is important because point-cloud quality depends heavily on how raw LiDAR data is processed. The software must align thousands of sensor observations into a coherent model of the environment, manage drift and support reliable spatial relationships across the mapped area.
By using FARO Insight technology in Inspector Online, Flyability aims to offer users a more accessible path to the same category of high-accuracy SLAM processing they may already associate with the FARO Connect workflow. The company’s validation report compared the two workflows using identical datasets, SLAM settings, presets, survey targets and alignment references.
For users, the practical question is not whether cloud or desktop processing is inherently better. It is which workflow matches the requirements of the job. A team that needs to process datasets offline, apply advanced filtering or deliver a specific format may continue to use FARO Connect. A team that needs to process survey data online, share it quickly and preserve a direct link between 3D mapping and inspection evidence may find High-Accuracy Mapping in Inspector Online more suitable.
What High Accuracy Means
To help users understand what to expect from High-Accuracy Mapping, Flyability published a validation report comparing its new Inspector Online workflow with FARO Connect. The report does not position FARO Connect as the sole measure of accuracy. Instead, it uses external survey references, including terrestrial laser scans, total-station measurements and GNSS references, to assess how closely each point cloud matches the physical environment.
The comparison matters because High-Accuracy Mapping and FARO Connect provide two ways to process the same Elios 3 flight data. Both use FARO Insight-powered SLAM technology. But FARO Connect processes data locally in desktop software while High-Accuracy Mapping processes it online in Inspector Online. Flyability’s central question was practical: Can users move to the online workflow while maintaining point-cloud accuracy comparable to the established desktop option?
The report also showed why mapping accuracy depends on the asset itself. SLAM works by estimating the drone’s location as it moves while simultaneously building a 3D model of the surrounding space. Environments with distinct features, such as corners, structural supports, equipment and changes in shape, give the system useful reference points. In these structured spaces, the system can more easily maintain its position throughout the flight.
By contrast, long, uniform or highly symmetrical assets, including certain tunnels, pipes and sewers, provide fewer distinguishing features. As the drone travels farther through a repetitive environment, small position-estimation differences can build up. This accumulated difference between the point cloud and the real asset is called drift.
That pattern appears in Flyability’s testing. In a structured environment, High-Accuracy Mapping recorded 0.12% overall drift, compared with 0.10% for FARO Connect. Both workflows closely aligned with the external references. In a more symmetrical environment, High-Accuracy Mapping recorded 0.19% mean drift, while FARO Connect recorded 0.67%.
The most difficult tests involved sewer-like environments with highly repetitive geometry. As expected, both workflows showed more drift as the environment became harder for SLAM to interpret. In the challenging test, High-Accuracy Mapping recorded 0.81% overall drift and FARO Connect recorded 0.63%. In the most difficult test, the results were nearly the same: 4.2% and 4.1%, respectively.
The report’s conclusion is not that one workflow will produce the same result in every asset. Rather, it shows that High-Accuracy Mapping delivered results comparable to FARO Connect across the tested environments, including spaces that are inherently difficult to map. For users, that means the decision between the two workflows can focus more on operational needs, such as cloud access, collaboration, offline processing and export requirements, than on a presumed tradeoff in mapping quality.
Why Online Processing Changes The Workflow
High-Accuracy Mapping does not eliminate the need for desktop software in every surveying workflow. Instead, it adds a cloud-based alternative for teams that prioritize direct access, simplified collaboration and integration with their inspection records.
Historically, inspection teams that wanted to create high-accuracy point clouds from Elios 3 survey data processed flights in FARO Connect, the company’s dedicated desktop application. That approach remains available and can be the better fit for certain advanced requirements, including offline processing, sophisticated point filtering, automated ground-control-point target detection and export formats such as E57, LAS, LAZ and PLY.
Within Inspector Online, users can upload Elios 3 survey data, select processing settings, generate a point cloud and review that output alongside flight trajectories, inspection imagery and measurements. They can then share the results online and export the point cloud as a LAS file.
This matters because data handoffs often create friction. A field team may capture the flight, a survey specialist may process the data on a separate workstation, an engineer may need to review it in another program, and an asset owner may receive only a static export or summary. Each handoff can add time, create version-control problems or disconnect the point cloud from the images and observations that explain what the team found.
A shared online workspace can streamline that process. The field operator can deliver the data into Inspector Online; technical stakeholders can access a point cloud and its related inspection evidence; and decision-makers can review the findings without necessarily requiring a specialized local setup for every step. For inspection providers, that can improve the delivery of client work. For asset owners, it can make inspection records more usable after the flight is complete. For engineering teams, it can help preserve the relationship between a measurement in a point cloud and the visual evidence that gives that measurement operational meaning.
Building Better Inspection Records
The launch reflects a broader shift in industrial drone operations. The value of a drone flight increasingly comes from the quality and usability of the resulting data, not only from the ability to reach difficult locations.
Inspection teams need evidence that can inform real decisions. They need to communicate findings to operations personnel, maintenance managers, engineers, safety teams and outside contractors. They also need records that remain useful months or years later, when someone needs to compare an emerging defect with earlier conditions. High-accuracy mapping can support that longer-term view. A point cloud provides a spatial baseline that teams can use to understand an asset as it existed on a specific date. When paired with visual inspection data, it can make anomalies easier to locate, quantify and revisit during future work.
Flyability’s 3D Survey Add-On makes the new feature available for Elios 3 users in Inspector Online. It supports processing of Rev 6 and Rev 7 LiDAR data, with Rev 7 offering a higher-performance sensor configuration that Flyability says provides improved point density, range, precision and global accuracy. Actual mapping results will still depend on the environment and flight conditions.
For teams considering the feature, the most important takeaway is not simply that point clouds can be generated online. It is that an inspection can become a more connected digital deliverable. Instead of separating visual findings from surveying outputs, users can bring both into a single record of what the drone saw, where it was and what the data reveals about the asset.
To learn more, watch Flyability’s High-Accuracy Mapping webinar here.