Robert Beane

Evolutionary Traveling Sales Person Project

Key Technologies:

AWS

Lambda Functions

DynamoDB

IAM Roles

REST APIs

(Download the full write up here or visit the GitHub Repository )

Purpose
The purpose of this application was to allow for an evolutionary process to find the best solution to the “Traveling Salesperson Problem,” a problem that figures out the shortest route from a given set of locations and distances. This was accomplished by using the skills we learned throughout the Processes, Programming, and Languages: Programming for Cloud Computing course offered by the University of Minnesota – Morris. These skills included many technologies offered by Amazon's Web Services (AWS) including Lambda functions, DynamoDB Databases, and some others.

Solution
The application’s architecture consists of an HTML web app that displays the evolutions at work. Behind the scenes, several Lambdas using JavaScript are called upon via a REST API which then returns the requested data to the web app. Meanwhile, certain lambdas are also responsible for adding certain “routes” to the DynamoDB database which is used throughout the application. IAM roles are also utilized to give permissions to the lambdas to write and read from the databases.

UMM Laundry Project (Software Design)

Key Technologies/Techniques:

Typescript

Java

HTML

CSS

Angular

Agile

(Download the full write up here or visit the GitHub Repository )

Purpose
The purpose of the laundry project was to provide an easy to use web app for students to see the status of laundry machines. Students would be able to see how much time was left on their load of laundry, see what machines were open, and which machines were having problems. Students could also report a machine if it was having problems. The student could also sign up for email notifications for when their load was complete.

Solution
By using Angular, we were able to make a user friendly experience to display the app. We also used CSS to make the web app super responsive so that it looked great on any device. The web app also used some pretty simple cookies to save a students preferred laundry location so that when ever they opened the app, it would auto direct to that facility. The backend consisted of a MongoDB database while running on a Java Spark server. The server/site was then hosted on DigitalOcean while utilizing CloudFlare to get HTPPS. Agile methodologies were used throughout the development of the web app. My personal contributions were focused on the user experience (dark mode, CSS changes, responsiveness, etc.) I also implemented the cookie system and HTTPS via CloudFlare.

Analysis of the ‘London Bike Sharing Dataset’ (Data Mining)

Key Technologies:

Python

Pandas

scikit-learn

(Download the full write up here or visit the GitHub Repository )

More info coming soon