Inspiration

Individuals with ADHD struggle with organizing their day and tend to focus on completing B tasks; those that are interesting, easy, fun, or quick to do. On the other hand, A tasks (those that are laborious, boring, and required a lot of time to complete) are either completed after B task are done or not done at all. We wanted to create an app which can help alleviate the task of prioritization of organization, and create a personalized work schedule.

What it does

Planwise is an iOS app that’s connected with your google calendar and creates a schedule to compete all your tasks in order of priority. Collects data from user such as, what is the project/task, when its due, the weight of the project, time it will take to complete and how important it is to the user. Based on this, a schedule to complete this task is integrated into the google calendar.

How we built it

  • Chatbot
  • Backend
  • xcode

Chatbot: We have used Google's diloglfow to create a chatbot and to integrate it with google assistant. Backend: Used Google Datalab to write a prioritization algorithm. We have used Google Cloud Shell, Calendar API and mongoDB to store the tasks created and to update the prioritized tasks in Google Calendar. Xcode: Used xcode to design the UI pages of the IOS app.

Challenges we ran into

  • Setting up the google console account, vm was new. Handling google cloud shell was more time consuming.
  • Learning Xcode was completely new and challenging.

Accomplishments that we're proud of

We are happy that this app will be helpful to those in need and it can also be used by the students to plan everything smartly.

What we learned

We got hands-on on the google cloud, APIs, xcode, dialogflow. And also working with new people was also a very good experience.

What's next for Plan wise

  • The planning fallacy is a law of nature that can reduce the impact of this app. The planning fallacy is a term used by psychologists to describe our tendency to underestimate the amount of time it will take to complete a task. We plan to have a database of historical data on the duration it takes to complete the task on average to a majority of the population and recommend this time to the user, if their estimate is out of the appropriate range.
  • Learning the user's behaviour or work style will help in better planning.
  • Smart recommendation system for efficient planning.

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