Scheduling Assistant
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Figma Prototypes of User Interface, Notifications System and AI-Assisted Scheduling Suggestions
Current System Architecture (for prototype)

Meet TimeSlice!

Your new AI planning assistant.

TimeSlice is a mobile app that helps busy college students, professionals, and neurodivergent individuals with daily scheduling. Using machine learning and a robust notifications system, TimeSlice helps people make the most out of every day by recognizing patterns in routines and habits over time, improving schedules based on users' unique needs.

An entire day is sliced into "time blocks" of all a users' tasks and events, ranging from meetings and study periods to meal times and commutes. Users can schedule blocks of "free time" as well to indicate when their schedule is open to new acitivity suggestions. Over time, TimeSlice's unique scheduling assistant recognizes when users may not be maximizing their available time, and offers suggestions for activities to meet individual career, academic, and personal goals. It also suggests breaks in between study blocks (basded on the Pomodor study method) when users forget to schedule "break" blocks during productive activities.

Using push notifications, users are reminded when time blocks are about to end or begin. The app checks in with users at the end of a time block to ask if the task has been complete. IF not, users have the option to accpet and AI-based suggestion to extend the time block and continue finishing the task, absed on how long the AI predicts users will need to finish. It then uses smart scheduling to push all consecutive time blocks ahead by that extra time interval, allowing users to forget the stress of constantly rearranging their schedules so they can focus on completing the acitivty at hand.

A note on current progress

TimeSlice is under development and still in the prototyping stage. Stay tuned for more updates on its progress by clicking "watch" at the top of this repository! :)

Here's some of our prototypes made in Figma.

Inspiration

Task prioritization and time management is a daily challenge. Existing scheduling apps like Google Calendar and Outlook are useful for planning future events, but for busy folk (especially those who face the extra challenge that often comes with neurodivergence), they aren't accessible enough. In these traditional scheduling apps, each event or task must be edited and shifted around manually. Routines can't be set, and manually reentering the same tasks each day proves to be more time-consuming than helpful. This interface simply isn't convenient for daily use. TimeSlice was built to make busy lives more manageable.

What it does

Machine learning and a robust notification system bring daily schedules to life. Forget about the chore of setting daily schedules and remembering to check them...TimeSlice's built-in scheduling assistant recognizes patterns in your daily habits and uses smart suggestions to guide you in your daily scheduling. Forget to schedule time for lunch? No need to worry--the app will catch this and suggest pushing time blocks down to make room for a lunch break. The more you continue to use the app, the more it will recognize flaws in your time estimation and suggest longe or shorter time blocks for routine activities.

How we built it

We designed this app using Figma protoypes, and built it using FlutterFlow's app development interface. We then designed its backend in Python using flask and SQL Alchemy for local database storage and designing our API.

Challenges we ran into

Although this project has a strong foundation, we were not able to completely finish and deploy a fully-functional prototype due to time limits. We prioritized spending time strengthening our business model, designing its systems architecture, and innovating the core features that make this product unique.

Accomplishments that we're proud of

Both Lisa and I learned how to create our own backend APIs, design Figma prototypes, manage Github Repositories using git, the Azure deployment process, basic Javascript principles and integrating API requests through the frontend. We finally began to understand how the front and backend of applications work together as a whole. We also learned how to create systems architecture diagrams and mobile app storyboards, which proved to be extremely helpful in the development of the app's core design! This is something we are super excited to use in our future projects. We successfully created a shared repository using source control to push, pull, and merge edits together remotely and locally. At the end of the day, we're both really eager to continue putting these skills to use, and hopefully making this project a real product in the near future!

The Future of TimeSlice

We intend to continue developing this app into a full-fledged mobile application with a scalable database. Although time was limited in the Hackathon, we plan to integrate our proposed AI model using an unsupervised learning algorithm, and transfer our temporary SQL Alchemy data to a larger SQL database. The project will be converted from its FlutterFlow prototype to React Native, and made available in both IOS and Android.