Un-Smuggle

We help customs officers to track animals inside the luggage easer and faster. Also communicate safely by storing ans sharing the information not on public chat services.

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Inspiration

As we received a list of the current Wildlife problem at the Zoo-Hackathon in Vienna.The important things for us was to find an easy to use application for the customs officer by helping them with "logic" on there smartphone. To make everything more clear, we define the problems:

  1. Detect the suspect luggage for animals inside (by detecting movement)
  2. Add luggage to a checklist for easy prioritising the large amount ever day on the airport
  3. Safe Communication

What it does

Our primary target animal we want to find are the Glass Eels. As we got told in the intro this is a huge problem right no on the airports. In the beginning the customs officer has a list of all luggages sorted by predicted potential for animals detected. In the Top of the list, there are Suspect Luggages. The list also has the x-ray images from the boarding control. The movement of the animals we want to detect by taking 2 images in 5 seconds time distance. From each luggage to specify we can detect the moment by image differentiation. Also luggages with no X-Ray images are suspect for example corruption.

How I built it

  • User Interview
  • Empathise map to define the problems
  • Brain storming and Ideas --> Combine best solution
  • Visual prototype (Adobe xd)
  • Test and Implement (functional on iOS/swift)

Challenges I ran into

Team finding and also finding a topic all new team members wanted to work on, and also the short time...

Accomplishments that I'm proud of

In less than 20 hours solve the challenge with a team (4) that has never known one another before.

What I learned

Wildlife problems and how serious they are.

What are next (possible) steps for Un-Smuggle

  • More detailed talks with customs officers and wildlife experts to evaluate more in detail the project
  • Check and test the X-Ray boarding control with examples
  • Develop a web control panel and the mobile application.
  • Collect the Data each time Custom for Machine learning.

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