TMG Lostandfound

Revolutionizing the way lost items are found and claimed.

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Inspiration

I lost the original copy of my Birth certificate.

What it does:

  • It uses image recognition to help people find thier lost items.
  • Matches user stories to recommended lost items by using semantic search .
  • People can easily turn in and claim lost items by contacting the phone numbers off the users who submitted an item reports.

How we built it

  • It was built on Taipy, MongoDB atlas , Google Cloud Platform

Challenges we ran into

  • Taipy did not provide line numbers to ease error debuging .
  • Changes in the database reflect on the Taipy UI only after reseting the server.
  • Not alot of information is avialable on MongoDB and Google Cloud vertex AI.

Accomplishments that we're proud of

  • We proud of helping people reconnect with thier lost belongings.
  • We are proud of fostering a sence of shared responsibility within every community.

What we learned

  • I learned to use Taipy to create a form for users to submit lost item reports, capture details like item description, location, date of loss, and finder's contact information, implement image upload functionality, and create a search interface for users to find lost items based on various criteria.

  • I learned to use MongoDB Atlas to implement Vector Search to enable semantic search capabilities for item descriptions and image recognition.

  • I also learned to use the Google Cloud pre-trained models to generate vector embeddings for lost item descriptions and images.

What's next for TMG Lostandfound

  • Protect users from being spamed by introucing google recaptcha.
  • Identify danger zones (areas with the most frequent missing item reports) and add to google maps.
  • Use internationalization to support people who speak different languages

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