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  3. RAIght way
Afthab Shirazabout 11 hours agoContributorJudging locked: Event build

RAIght way

We tell cleanup crews where to go without ever needing to search themselves.

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Project description
Cities have countless examples of infrastructure damage: potholes, graffiti, broken signs and so on. In order to figure out what to fix, councils must drive and search for issues manually, costing money and time. England and Wales spend £4.4 billion annually on these kind of issues, with £240 million purely due to finding out late. With the rise of autonomous vehicles, streets are already being recorded at scale. Our product uses NVIDIA Cosmos (running on W&B Inference) to search hours of this data for damage, pinpoint where using the provided GPS data, use Nemotron to score them and decide which crews should be dispatched, then we use NVIDIA cuopt to find the optimal pathway for crews to perform maintenance. Our entire stack is built on Vast infrastructure.
Project links
  • GitHub repository
  • Project website
  • Demo video
Tools used
  • VAST Data logoVAST Data
  • CoreWeave (Weights & Biases) logoCoreWeave (Weights & Biases)
  • NVIDIA logoNVIDIA
  • SpaceXAI (Cursor) logoSpaceXAI (Cursor)
Tools used
  • VAST Data logoVAST Data
  • CoreWeave (Weights & Biases) logoCoreWeave (Weights & Biases)
  • NVIDIA logoNVIDIA
  • SpaceXAI (Cursor) logoSpaceXAI (Cursor)