Introducing Tower Assessments 3D

January 10, 2019
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There are thousands of network towers across Finland. Each tower is typically 70–100m high requiring technicians to scale the mast via rope rigging. Unsurprisingly, despite best efforts, every year people are hurt in such operations due to weather and equipment.

Until a technician can get a closer look at the tower, there’s little indication as to what problem they may need to fix. This means multiple trips, increased downtime and elevated personal risk.

Drones, with their high-resolution cameras, and AI driven software can serve as a unique tool to provide an initial inspection for the technicians. So today we’re announcing Tower Assessments 3D (TA-3D), a future proof service for energy and network providers that want to reduce costs but obtain more data points on their assets.

Meet TA-3D: an entirely new way for network operators to better manage their towers by conducting fast, accurate, independent tower assessments.

The majority of inspections network providers conduct are routine and don’t require a technician to scale the tower. The ability to do this remotely with a drone greatly increases the operational efficiency of the service providers, allowing them to identify towers with issues more quickly and minimising the amount of time they spend hanging from ropes from the side of towers.

Extract More Valuable Data Over Time

Reduce site visits and improve design, build or maintenance workflows by understanding the real world as-built condition of your towers. Measure, inspect and compare records online — or automate manual processes by leveraging Fly-by Guys machine learning & object recognition technology.

What our inspections detect:

  • Rust detection
  • Radiation Hazards
  • Hardware measurement
  • Panel detection
  • Fall zone
Panel detection (left), Rust detection (centre) & radiation detection (right)

Why We Think This Is Big for the Network Industry

Partnering with Fly-by Guys will significantly reduce tower climbs and reliance on access equipment by utilising drone based technology to detect problems that sometimes might not be visible. This therefore reduces operational expenses through digital assessments of up-to-date information.

Technicians can make informed decision prior to going onsite, saving time. Network owners can position maintenance resources to be data driven and let AI proactively find faults before high costs are incurred.

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