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How Hyperspectral Imaging is Revolutionizing Industrial Recycling

📅 Date:

✍️ Author: Francis Doumet

🔖 Topics: Recycling

🏢 Organizations: Metaspectral

Another benefit of this pixel-level accuracy is that it allows for powerful IFTTT (If This Then That) rules when sorting objects mechanically in an industrial recycling facility. For example, a rule can be set up to remove an object from a PET stream if it is wrapped in a non-PET label for more than 80% of its surface area, since removing the label mechanically will likely fail, and shredding the object as is will end up contaminating the otherwise pure PET.

Finally, pixel-by-pixel level hyperspectral systems can identify the proverbial needle in a haystack. In the world of plastics recycling, PVC is a dangerous contaminant that spoils production if detected even at levels of 1 part per million. Dubbed the Poison Plasticby Greenpeace, the disposal of PVC results in the release of toxic, chlorine-based chemicals. Hyperspectral systems can detect such rare yet hazardous substances and identify them for removal with high accuracy before they result in non-reversible contamination.

Read more at Metaspectral Blog

Metaspectral Raises $4.7 Million to Launch Fusion, a Cloud-Based AI Platform

📅 Date:

🔖 Topics: Funding Event

🏢 Organizations: Metaspectral, SOMA Capital

Metaspectral, a software company advancing computer vision using deep learning and hyperspectral imagery, has completed a $4.7 million seed round from SOMA Capital, Acequia Capital, the Government of Canada, and multiple notable angel investors including Jude Gomila and Alan Rutledge.

The company plans to use this investment to scale up its team to support the continued development and refinement of the Fusion platform which is set to publicly launch this Fall. Fusion makes it easy for those with or without technical expertise to train and deploy deep learning models that analyze hyperspectral imagery in real-time. Hyperspectral images contain information from across the electromagnetic spectrum, making it possible to identify the chemical composition and other invisible properties of materials with computer vision.

Read more at Metaspectral Blog