Rua

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  HomePage

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  Dashboard

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  Toronto Map Viewer

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  Report Incident

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  Hardware - Arduino

Road and street safety is one of the more pivotal aspects that need to be considered in urban planning and city infrastructure. All four of us are natives to the city of Toronto, though living in different neighbourhoods, but we have noticed one thing in common. All roads or streets no matter where you go in the city, can tend to have some sort of debris, garbage, broken streetlights, vandalism, or potholes, and we wanted to come up with a way to help the City of Toronto’s Transportation Department to optimize a way to report these incidents and resolve them as quickly and efficiently as possible. The four of us then embarked on a 36-hour long project to fix this problem using our passions and skills in Agentic AI, Hardware, and Software Engineering. Our team has a very diverse skillset including a member who was experienced with embedded hardware and had passions for integrating AI with the physical world. To pursue these passions, a CV and hardware element was brought to this project to directly interact with the physical world (in this case, street infrastructure) and combined with modern agentic frameworks to pursue societal change. Our tech stack features a robust collection of technologies and innovations as outlined below.

Built With

• arduino
• css
• fastapi
• huggingface
• javascript
• mapbox
• opencv
• python
• pytorch
• supabase
• tailwind
• typescript