A16: Best Practices (IT Equipment Recovery): Difference between revisions
No edit summary |
No edit summary |
||
| Line 9: | Line 9: | ||
• '''Asset Type''': Executable | • '''Asset Type''': Executable | ||
• '''AI Breadth''': | • '''AI Breadth''': N.A | ||
• '''Learning Ability''': | • '''Learning Ability''': N.A | ||
• '''Related technologies''': | • '''Related technologies''': N.A | ||
• '''Applicable Research Area''': Collaborative AI | • '''Applicable Research Area''': Collaborative AI | ||
| Line 19: | Line 19: | ||
• '''Applicable Technical Category''': Optimisation | • '''Applicable Technical Category''': Optimisation | ||
• '''License Information | • '''License Information''': N.A | ||
• '''Related to circularity and sustainability''': | • '''Related to circularity and sustainability''': Yes | ||
• '''Audience''': Electrical and Electronic waste management companies and workers | • '''Audience''': Electrical and Electronic waste management companies and workers | ||
Latest revision as of 08:56, 28 April 2025
• Short Description: Redesign of technical processes in the refurbishment of IT equipment with the use of AI tools, thereby increasing the recovery of second-hand equipment, critical components and materials, reducing costs and creating added value. The results are presented in the form of updated technical instructions to provide electrical and electronic waste management companies and workers, where the focus is on reuse through the advantages of AI.
• Reference, URL: https://revertia.com/en/
• Applicable Business Category: Manufacturing
• Application in relevant Projects/Initiatives:Yes, Circular TwAIn
• Asset Type: Executable
• AI Breadth: N.A
• Learning Ability: N.A
• Related technologies: N.A
• Applicable Research Area: Collaborative AI
• Applicable Technical Category: Optimisation
• License Information: N.A
• Related to circularity and sustainability: Yes
• Audience: Electrical and Electronic waste management companies and workers
Go back to the AI portfolio of reference implementations
