K
Kathleen Martin
Guest
For industrial inspections, data is king. Drones, equipped with a variety of sensors, can gather an overwhelming amount of it. Businesses don’t just need any data. They need the right data at the right time. Qii.AI, a Toronto, Ontario Canadian startup, helps companies hone in on what is important and relevant to them, and then to sort through it all.
Qii.AI’s artificial intelligence (AI)-machine learning (ML)-enabled platform coalesces mission-specific drone visual and digital inspection data into actionable intelligence for decision makers by providing targeted reports and 3D digital twins and disseminating them to all relevant stakeholders in near real time.
“Our mantra at Qii.AI is ‘Label, Train, and Manage’,” explained the company’s CEO Michael H. Cohen, a 20-year commercial pilot and former Boeing airline Captain, who initially started the company in 2014 to perform building inspections in Canada.
This initial use case employed drones with thermal cameras to image buildings at night for energy loss. Cohen’s team was the first to obtain waivers for tablet-driven autonomous night flights in both Canada and the United States.
“We were collecting about three to five gigabytes for each building,” Cohen recalled. He and his partners soon realized that they had an internal business need for data management and data analytics in these remote digital inspections – and that their clients did too.
“If you have 5000 photographs, the user just wants to see the best ones. How do you sort through those? You create ways in which algorithms can look at camera position, the lighting and various attributes to narrow those 5000 images down to the 20 that provide a holistic, 360 degree view of the asset,” he said.
Those algorithms require accurate comparable data-sets to narrow outputs to relevant images. Uniquely, Qii.AI engages their customers in the AI process, putting AI at the edge and allowing users to label the data. Cohen and his team call this “user-defined” labeling.
Continue reading: https://dronelife.com/2022/01/29/qii-ai-platform-for-drone-inspection-data-label-train-and-manage/
Qii.AI’s artificial intelligence (AI)-machine learning (ML)-enabled platform coalesces mission-specific drone visual and digital inspection data into actionable intelligence for decision makers by providing targeted reports and 3D digital twins and disseminating them to all relevant stakeholders in near real time.
“Our mantra at Qii.AI is ‘Label, Train, and Manage’,” explained the company’s CEO Michael H. Cohen, a 20-year commercial pilot and former Boeing airline Captain, who initially started the company in 2014 to perform building inspections in Canada.
This initial use case employed drones with thermal cameras to image buildings at night for energy loss. Cohen’s team was the first to obtain waivers for tablet-driven autonomous night flights in both Canada and the United States.
“We were collecting about three to five gigabytes for each building,” Cohen recalled. He and his partners soon realized that they had an internal business need for data management and data analytics in these remote digital inspections – and that their clients did too.
“If you have 5000 photographs, the user just wants to see the best ones. How do you sort through those? You create ways in which algorithms can look at camera position, the lighting and various attributes to narrow those 5000 images down to the 20 that provide a holistic, 360 degree view of the asset,” he said.
Those algorithms require accurate comparable data-sets to narrow outputs to relevant images. Uniquely, Qii.AI engages their customers in the AI process, putting AI at the edge and allowing users to label the data. Cohen and his team call this “user-defined” labeling.
Continue reading: https://dronelife.com/2022/01/29/qii-ai-platform-for-drone-inspection-data-label-train-and-manage/
