When revising, there can be the temptation to reach for your phone and before you know it you've spent 2 hours scrolling and 20 minutes revising.

LockedIN is designed to eliminate that temptation by locking users out of distracting apps until they complete their study sessions. The sessions are structured around the Pomodoro Technique, using focused periods of study followed by scheduled breaks.

However, simply blocking access to apps isn’t always enough to ensure that work actually gets done. LockedIN addresses this by introducing accountability: before starting a study session, users upload scans or photos of the work they intend to complete. Once the session is finished, they must scan their completed work before access to their apps is restored.

To verify completion, LockedIN uses Google Gemini's image recognition to compare the submitted work and generate a confidence score indicating how likely it is that the work has been completed. This method is incredibly flexible for a variety of work including exam papers, question sheets, written notes and digital work.

The app is currently nearing the end development for version 1, with the iOS release planned for early September.

There is a theory that for any 2 given Wikipedia pages, they are no more than 6 clicks away from each other. This concept has been popularised through Wikipedia Speedruns and Six Degrees of Wikipedia. I too was interested in this idea, so wrote a python program to parse, consolidate and store each wikipedia page's title and links from the Wikimedia-XML dumps in CassandraDB.

I was then able to write a number of search algorithms including Branch and Bound and Iterative Deepening Depth-First Search from which I could enter 2 pages and find the shortest possible route.

This project was very fun but also very time consuming (It was taking over 12 hours on my computer to parse and store the data!) but the results were really interesting.