We are partnering with AISPECO to develop edge computing algorithms for the improvement and automation of the image capture process for overhead line inspections.
One key challenge of transitioning to virtual overhead line inspections is the quality and consistency of image capture. In real-life conditions, images are often not good enough quality caused by improper exposure, blur and framing. Sometimes operators are even forced to rely the lines to get useful data for virtual inspections, leading to inefficiencies and high costs.
The objective of the Smart Falcon project is to develop a solution that is able to identify in real-time when a target structure or part of the structure is in-frame, and automatically trigger a camera shot.
The solution will also evaluate in real-time the quality of the image to determine if it meets the standards required, and otherwise, another image is taken automatically without the need to circle back.
Funding For Project
Project SMART FALCON:AUTONOMOUS DATA COLLECTION PLATFORM (LT07-1-EIM-K02-007).
The project is co-financed by the Norwegian Financial Mechanisms and the Republic of Lithuania, under the Business Development, Innovation and SMEs program .