Mobile Application

Presque Vu

Mobile application that stores people-based contextual reminders.

  • Mobile
  • User Experience Design
  • Development
  • Server-side scripting
  • Context Awareness
  • Productivity

Mobile and Pervasive Computing Services
Spring 2014 Carnegie Mellon University
Team : Jennifer Morioka, Pratyush Tewari, Ramya Mallya
Role: Ideation, Storyboarding, Wireframing, Navigation flow, User Research, Software Architecture, Development


PresqueVu is a context aware reminder application that triggers reminders based on your proximity to a designated person.

Project Scope

The total duration of this project was 5 weeks. Over this period we engaged in the end to end design process and built a working prototype to demonstrate our concept. The project required us to take into consideration all aspects of a well rounded mobile service ie, viability, business model, usability, privacy and security and so on. While not all of these were built into our prototype, we presented a project report that covered all of these aspects. Our project got special mention for being one of the best 4 projects at the final poster show.

Problem Space

The market is saturated with time-based reminder application. Recently, with applications like Google Now, people can now set location-based reminders, which trigger reminders when they arrive at specific geographic locations. However, none of these applications effectively solve the problem of forgetting what you wanted to tell someone when you meet them. PresqueVu aims to fill that void, by allowing people to set person-based reminders that are triggered when the designated person is in proximity.

Concept Validation

We interviewed 6 people to determine if our concept was viable. The most common responses wer that people would feel uncomfortable sharing their location with others, and that they saw this as being a single feature of a larger productivity application. The most common use cases that our interviewees determined was to remind them about what they needed to discuss with co-workers in a work setting, and to remind them about previous conversations with the same person that they wanted to follow up on.
We used these responses to guide the design of our concept.

Story Boarding

We used Storyboarding to define what a typical usage scenario for our application would be.

Sketches and Paper Prototypes

We sketched out navigation flows, which later translated into paper prototypes.

User Testing

We tested our paper prototypes using Think Alouds and interviews with six participants. Feedback gathered from this research informed our final UI design.

Final UI Design

Application Architecture

We sketched out the architecture of our application, to make sure it was technically viable and determined the essential components that would go into our design.

Privacy and Security Concerns

We brainstormed various approaches to ensure that our application respected the privacy of it's users. We decided to add a feature that informs users about reminders that have been set based on her, and allows her to accept or reject them. Instead of showing the exact location, we decided to only notify users that the people whom they have set reminders based on, are less than a 5 minute walk away. By adopting the above approaches, we dealt with the privacy concerns that had emerged in our concept validation phase. In order to ensure that users' information was secure, we propose encrypting all location information that was being sent to the server.

Business Model

We propose a Freemium model to generate profit from PresqueVu. Users would only be allowed to set a fixed number of reminders for free, and would need to buy upgrades to set more reminders.

Final Prototype

The final working prototype was a web application built using Express framework for Node.js that used for client-server communication. We used Google+ login, and Google Maps Distance API in our implementation.