Phase 4 Contributions#
My contributions in phase 4 consisted of uniting project components by implementing our cosine similarity and times series autoregressive machine learning models, refining our software architecture, and enhancing the UI to produce our finished application. With the UI layer, I improved the design of the home page by using selectboxes for user profile selection in each persona. With this, I enhanced the personalization of each user’s experience by customizing the display of their name and tweaking the navigation to improve the experience through personalization. Additionally, I focused on improving the interactive feedback with the My Profile page, allowing users to view their profile details, edit their username or first name, and delete their profile. I smoothed out the features for each persona, specifically aiding in the prospective student feature of joining a university mailing list. On top of this, we fixed many minor bugs or features that were not up to our standard throughout the application.
Additionally, with the improvement of features across the application, I added routes to suit my needs and updated the REST API Matrix with new routes. I adjusted the database and revised the relational mapping to reflect the changes as we reviewed and optimized the schema. I composed the README to explain the purpose of our project, the intended users, and how someone could set up and use our project. Lastly, I contributed to the team blog post by describing our software architecture and the final version of the database model. Overall, my contributions aided in our app’s complete implementation, testing, and improvement, focusing on the UI, REST API, and database layer.
Experiences#
Our group had the opportunity to lead a reflection on our speaker, Sophie Meszaros, who detailed her work in addressing local challenges and delivering better services to citizens through data spaces. The development of smart communities in which tech solutions improve the management and efficiency of urban environments represents a future with a sustainable society. This idea ties in greatly with our project, which aims to enhance individuals’ lives through a data-driven application that simplifies decision-making. The similarity lies in the goal of affecting individuals’ lives and building applications for the impact we wish to have.
Another experience with touring EnergyVille allowed me to look into achieving sustainable energy. Diving deep into their physics-based approach regarding collective heating systems and the data collected from their heating and cooling experiments displayed a real-life look into the impact data can have on improving designs.
Reflection#
As my time in the dialogue has ended, I cannot help but think back on the incredible experiences during the trip. I am deeply grateful that I had the opportunity to study abroad and develop this project, Best Life, which focused on my passion for improving the lives of others. The creation of our application has not only furthered my skills as a computer science student, growing my knowledge of Python, Flask, Streamlit, SQL, and more, but also enhanced my teamwork abilities. Through the collaboration with Maya, Max, and Zoya, we have effectively communicated and worked with the joint goal of creating Best Life to aid in the complex decision-making process, allowing users to be well-informed when making choices to improve their or others’ lives.
Thank you to Professor Fontenot, Professor Gerber, and our TA Sydney for creating an engaging and impactful experience. Your time and guidance in improving our applications through continuous feedback have contributed significantly to my learning and enthusiasm in this field.