Inspiration
According to CanadaHelps, more than half of charities are unable to meet current levels of demand, meanwhile a study conducted by the University of Waterloo found that almost 500 million kilograms of apparel & home items are disposed per year. Consumers have the opportunity to help address this gap in the system but, with limited time to sort through items, limited time to learn about the variety of organizations with differing needs, limitations and locations and limited motivation to donate, these items either continue to collect dust or end up in landfills.
What it does
Trove is an app (desktop and mobile) that directly connects consumers to a large database of local organizations that are in need of donations. Rather than having the users manually research the requirements of each organization, users simply have to scan their items and are immediately matched with a local organization based on urgency and distance. The scanning feature provides users with a sense of urgency by highlighting the need in their area and the rewards feature incentivizes and gamifies the process to encourage incorporating decluttering and donating to everyday life.
How we built it
First, we mapped out the required features and use roadmap using a flowsheet. Then, we drafted a set of prompts that would lead to our desired functionalities. We compiled all of our prompts into Bolt AI and refined upon our product by testing different user cases and addressing bugs and errors along the way.
Challenges we ran into
Accomplishments that we're proud of
Getting the scanning feature to work. This required researching the use of CNN Machine Learning Models ad refining the classifications.
What we learned
What's next for Trove
Built With
- bolt
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