Nov 2015
McMaster University Engineering Capstone
"Strangers" was an Android application that my three peers and I developed during the HackDuke hackathon at Duke University. The project's objective was to create an engaging platform for individuals to interact and converse with strangers, utilizing APIs from Facebook, Firebase, and IBM. Within the span of 24 hours, our team meticulously planned and designed the app, implementing a feature that scanned a user's recent Facebook posts and matched them with someone of the opposite personality. The app's overarching goal was to foster connections among individuals from diverse backgrounds and promote an appreciation for the diversity of personalities within the community.
Future plans for the application entailed developing a more intuitive interface with enhanced branding. Additionally, we aimed to implement a feature that would passively block offensive content or any material that violated our terms of use. This social experiment was intended to assist us in gauging the interactions between individuals with contrasting personalities and gaining insight into potential issues or advantages that might arise.
In this project, my role involved working with the Watson Personality Insights API to create a comprehensive character profile for the individuals involved. The profile encompassed details regarding their personality traits, needs, and values. This marked my inaugural experience in working with a web API, presenting me with a considerable learning curve. To navigate this challenge effectively, I sought guidance from a mentor affiliated with Google, who provided instruction on fundamental commands and familiarized me with IBM's security protocols.
This project presented a considerable challenge for me as I had limited prior knowledge about the topics I needed to delve into. It pushed me beyond my comfort zone.
While developing Strangers with my team, I acquired substantial firsthand experience and received mentorship in utilizing the Google Android SDK and mastering the fundamentals of front-end application development. The data sourced from Facebook was formatted as a JSON file, which we subsequently reconfigured within our app to optimize compatibility with IBM's Bluemix servers. Within the Bluemix environment, I gained proficiency in coding with Node.js and interfacing with Watson, the computation engine responsible for analyzing the data packets transmitted to Bluemix and generating personality profiles in response. This data was employed to pair users, directing them to a Firebase script that facilitated the swift establishment of a messenger feed between two individuals.