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Edge computing algorithms to enhance overhead line inspections – Smart Energy

eSmart Systems is partnering with AISPECO to develop edge computing algorithms for the improvement and automation of the image capture process for overhead line inspections.

The company, which provides AI services and solutions for the inspection and maintenance of critical energy infrastructure, is partnering on the project with AISPECO, which manufactures advanced geo-spatial platforms.

The project – dubbed Smart Falcon – is aiming to support utilities capture images of their assets in a more efficient and reliable manner, with the goal of reducing image capture costs by ensuring the right images are captured the first time. High-quality, consistent images, according to the partners, will contribute to a significantly more efficient AI-assisted inspection process.

The objective of Smart Falcon 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.

According to eSmart, 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.

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AISPECO will develop a versatile gimbal and steering system for helicopters’ rig and – in later stages – for planes, drones and cars.

Kathrin Sunde, head of innovation and sustainability, cited how image capture processes are not as efficient as they should be, necessitating image capture teams to refly the course and retake images. The Smart Falcon project thus aims to prevent this with improved efficiency, increased image quality and reduced process costs for overhead line inspections.

The computing project is co-financed by the Norwegian Financial Mechanisms and the Republic of Lithuania, under the Business Development, Innovation and SMEs program.

This UrIoTNews article is syndicated fromGoogle News

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