QuetzAI was born out of the need to make information in museums accessible to all ages. This information is often specialized and therefore many people do not retain the information on display efficiently.
QuetzAI reads QRs that contain the information of an historical object and do an abstractive summary of the information according to the visitor's age. Finally, after 10 objects scanned, there is the possibility to put on practice the new knowledge acquired by a trivia activity, where the questions are generated dynamically according to the scanned information and visitor's age.
We built a web application using HTML, CSS and JavaScript for the user interface, but the magic happens behind. There is a Relational Data Base where we store the visitor's information and object's information, using queries where Gemini creates abstractive summaries based on visitor's age, and storing this at the DB, and finally using these summaries to create personalized questions where visitors can put their knowledge on practice.
The most tough challenge we had, is how can we iterate between summaries to generate the questions and as AI developers is one of our firsts approaches to the web development.
Definitely we are proud of our system because we conceive it to be inclusive for all people of all ages who are interested about history and be an approach por people who doesn't, in such a way that helps museums to do their goal: impart knowledge.
We learned a lot about generative AI, web development, user experience and data base management.
An awesome question! This web application is generalized, letting museums of all the world and all tematices use this app, so their visitors can learn more having fun in the process.