Computer Engineering Commons^™

Reach - A Community Service Application, Samuel Noel Magana

Computer Engineering

Communities are familiar threads that unite people through several shared attributes and interests. These commonalities are the core elements that link and bond us together. Many of us are part of multiple communities, moving in and out of them depending on our needs. These common threads allow us to support and advocate for each other when facing a common threat or difficult situation. Healthy and vibrant communities are fundamental to the operation of our society. These interactions within our communities define the way we as individuals interact with each other, and society at large. Being part of a community helps …

Digital Forensics Challenge, Zoe Lie, Sydney Marie Mendoza

Computer Engineering

No abstract provided.

Bpm: Blz Package Manager, Kenneth Huang

Computer Engineering

bpm (BLZ Package Manager) is a package manager for the open-source programming language BLZ, built in Java. It allows users of the BLZ programming language to create and upload their own packages, as well as downloading necessary dependency packages for their packages. To do this, the program communicates with the “cardiovascular”, a web server designed for users to upload and download BLZ packages.

The program has three primary functions. The first one, “init”, initializes a package directory for use with the package manager. Part of this initialization is creating a “heartbeat” meta file, which holds information about the package’s name, …

Keylime, Joshua Michael Magera

Computer Engineering

New freshmen arrive at Cal Poly every year, experience Week of Welcome, and, if they haven’t been to Firestone Grill within the first week, they can consider themselves an anomaly. But how long until those freshmen find the amazing sandwiches and breakfast burritos served at Gus’s Grocery or hear about the free burger promo at Sylvester’s? The goal of this senior project was to create an app, KeyLime, that makes it easy for college students to find new eateries and fresh deals that are local, affordable, and tasty. KeyLime aims to target college students and create a space for restaurants …

Labeling Paths With Convolutional Neural Networks, Sean Wallace, Kyle Wuerch

Computer Engineering

With the increasing development of autonomous vehicles, being able to detect driveable paths in arbitrary environments has become a prevalent problem in multiple industries. This project explores a technique which utilizes a discretized output map that is used to color an image based on the confidence that each block is a driveable path. This was done using a generalized convolutional neural network that was trained on a set of 3000 images taken from the perspective of a robot along with matching masks marking which portion of the image was a driveable path. The techniques used allowed for a labeling accuracy …

Keylime, Matthew Orgill

Computer Engineering

This project creates an iOS mobile app geared specifically toward the students of California Polytechnic State University. The app aims to provide the ability for users to discover new restaurants to checkout in the central coast area. These restaurants can be filtered to the user’s choosing based on the price of food, rating the restaurant has received, distance away from the user, and type of food. In addition, featured deals that local restaurants currently offer can be found on the app. Each restaurant can be favorited by the user to allow for better filtering of discovering new restaurants and to …

Grammar-Based Procedurally Generated Village Creation Tool, Kevin Matthew Graves

Computer Engineering

This project is a 3D village generator tool for Unity. It consists of three components: a building, mountain, and river generator. All of these generators use grammar-based procedural generation in order to create a unique and logical village and landscape each time the program is run.

Identifying Hourly Traffic Patterns With Python Deep Learning, Christopher L. Leavitt

Computer Engineering

This project was designed to explore and analyze the potential abilities and usefulness of applying machine learning models to data collected by parking sensors at a major metro shopping mall. By examining patterns in rates at which customer enter and exit parking garages on the campus of the Bellevue Collection shopping mall in Bellevue, Washington, a recurrent neural network will use data points from the previous hours will be trained to forecast future trends.