Digital Commons Network^™

Deploying A Distributed Cloud-Based Microservice Application Benchmark Suite, Sai Dhruthik Murthy, Srish Maulik, Joydeep Mukherjee

College of Engineering Summer Undergraduate Research Program

Cloud services have lately transitioned from a single monolithic application to several loosely coupled microservices. This design shift from a single complex monolithic application to tens or hundreds of single-purpose microservices has enabled modern cloud services to be deployed, scaled, and managed in a more efficient way. Microservices can be deployed inside their own lightweight containers hosted on a cloud platform, and they can be individually developed, updated, tested, and elastically scaled. Each microservice can also be developed in its own suitable language, with only a common API for microservices to communicate with each other. Due to these benefits, large …

Advanced Localization Technologies For Autonomous Robotic Apple Harvesting, Gabriel K. Basus

College of Engineering Summer Undergraduate Research Program

No abstract provided.

Gamified Machine Embroidery, Sai Rama Balakrishnan, Vince Thanh Doan

College of Engineering Summer Undergraduate Research Program

This project aims to improve accessibility to the embroidery field by developing an application that captures the utility of a embroidery software (controlling an embroidery machine to produce embroidered output) and combines it with the playfulness of a game, to put those advanced controls in the hands of novices.

Agentic Ai In Search & Rescue, Belal Elshenety

College of Engineering Summer Undergraduate Research Program

No abstract provided.

Ai For Search And Rescue: Probabilistic Reasoning, Emi Dinh, Sydney Lynch, Swayam Chidrawar

College of Engineering Summer Undergraduate Research Program

No abstract provided.

Measurement Automation & Measurement System Research Endowment, Brian Bivinetto, Beneda Loya, Shiron Bendrihem

College of Engineering Summer Undergraduate Research Program

Road travel safety is always the most important issue in transportation systems. In general, several factors cause road accidents, such as human error, vehicle mechanical failure, roadway limitations (e.g. pavement, lane geometry, etc.), and inclement weather conditions. The major focus of today’s transportation developments is related to making highway transportation safer, smarter, and greener to enhance livability. Many accidents are caused when drivers lack a better understanding of the surrounding traffic conditions because the driver not only needs to control his/her vehicle but also needs to be aware of the movements of the vehicles around him/her. A driver cannot be …

Wearable Sensor-Based Gait And Balance In Elementary And Middle Schools, Sofie Zalatimo, Catherine Semaan

College of Engineering Summer Undergraduate Research Program

No abstract provided.

Significance Of Noninvasive Endothelial Dysfunction And Other Cardiovascular Measurements In Various Communities, Sofi Z. David, Lily Wilcox, Kalia Richard

College of Engineering Summer Undergraduate Research Program

This pilot study aims to raise awareness of endothelial dysfunction in underrepresented communities, where cardiovascular disease is prevalent. By delivering educational presentations and materials, the study seeks to increase participants' understanding and interest in endothelial dysfunction, potentially leading to proactive health behaviors. The results will inform future initiatives to enhance public knowledge and reduce the burden of cardiovascular disease in these communities.

In the future, there will also be a 3 vs 5-minute hyperemia study. Thirty participants without a history of cardiovascular disease will undergo testing using the Cordex SmartCuff™ device. If the three-minute hold proves to accurately measure endothelial …

Impact Of Composites Material Research On Underrepresented Communities, Neil Bedagkar

College of Engineering Summer Undergraduate Research Program

The purpose of this research is to qualify and quantify the amount of research into composite materials applicable to certain engineering industries, then examine the impact these industries have on communities of a lower socioeconomic status. Of a random sample of papers from ScienceDirect over the last 24 years, it was found that the amount of research applicable to industries cascades as follows: the most is applicable to the construction industry, followed by automotive, defense, renewable energy, and biomedical. The effects of each industry have been examined and are presented as well.

Digital Twin For Shelf Intelligence: Ai-Driven Inventory Management For Minimizing Food Waste, Charlotte Maples, Marvin Velazquez

College of Engineering Summer Undergraduate Research Program

This project aims to develop a solution for improving grocery store inventory management by leveraging AI-driven image recognition. Traditional inventory methods, which rely on manual counting or barcode scanning, are inefficient, labor-intensive, and prone to human error. Over an 8-week period, we designed and developed a basic iPad app capable of identifying specific types of fruit and automatically updating inventory records in real time. By utilizing the iPad’s camera and machine learning algorithms, the app demonstrates the potential to streamline inventory tracking, reduce manual labor, and improve accuracy in managing perishable goods. Future work will focus on expanding the app’s …

Sal-E: Responsive Space Pathfinder Mission, Liam Duckworth, Berfredd Quezon

College of Engineering Summer Undergraduate Research Program

The main objective of the SAL-E mission is to grow the Cal Poly CubeSat Lab’s (PolySat) capabilities in rapid spacecraft design, as well as to provide the current generation of students with the opportunity to design, test, integrate, and communicate with a satellite. This summer we will be focusing on a few aspects of the spacecraft design and preparing our test facilities for Fall. Specifically, we will be ordering electronics boards that were designed in Spring, testing the boards as they arrive, developing software to interface with the payloads, begin integrated testing, updating the control system in our thermal vacuum …

Optimizing Medical School Enrollment, Justin Koida, Nicholas Quattrocchi

College of Engineering Summer Undergraduate Research Program

The increasing physician shortage, coupled with an aging population, presents significant challenges for healthcare systems. With higher education facing a projected enrollment cliff, and a decline in youth math and reading scores, identifying the most qualified medical school applicants is imperative. With thousands of applications received annually for only 300 spots at Western University of Health Sciences (WesternU), it is crucial to streamline the selection process while minimizing applicant attrition and melt.

In our research project, we develop a predictive model to identify candidates for interviews based on success data from students at WesternU. We utilized a dataset provided by …

Ai Integration For Intellisar, Eric Lee

College of Engineering Summer Undergraduate Research Program

IntelliSAR aims to integrate AI techniques into Search and Rescue (SAR) operations, building on the foundation laid by previous SURP initiatives. IntelliSAR’s core elements include a front-end for SAR forms, a comprehensive command center dashboard, and AI-driven components designed to enhance SAR decision-making. During summer, our efforts focused on streamlining the user interface by integrating various machine learning models into a unified, interactive dashboard. Our models predict critical factors such as missing persons’ behavior, potential locations, and resource requirements, with the goal of optimizing response times and improving the effectiveness of SAR teams.

Analyzing The Determinants Of College Graduates’ Salaries In The Us: A Data Analytics Approach, David Nunez, Puneet Agarwal Ph.D., Samuel Gray

College of Engineering Summer Undergraduate Research Program

In this project, we will explore a range of factors that influence the salaries of US college graduates. Demographic variables such as gender, race, and ethnicity; educational variables such as fields of study; and professional variables, including job and employer characteristics, will be examined to understand their impact on salaries. Our research will extend to a spatial and temporal analysis, offering a deeper understanding of how these factors vary across different states and over time, revealing critical disparities linked to gender, race, and ethnicity. The study will provide valuable insights that can help individuals make well-informed decisions regarding their career …

Computer Vision In A Robotic Arm, Jack Maxwell

College of Engineering Summer Undergraduate Research Program

We used a machine learning-based object detection algorithm to give a robotic arm the ability to "see" with its camera.

Exploring Human Responses In Conversations With Ai Entities, Phillip Semenov, Miguel Coronado

College of Engineering Summer Undergraduate Research Program

This study argues that while AI systems have become increasingly advanced, they still evoke distinct emotional responses compared to human interactions, potentially limiting their effectiveness in emotionally-driven environments. We used the Emotiv Insight brain-computer interface to monitor participants' emotional responses during controlled interactions with both AI systems and other humans. Key emotional metrics, such as arousal, focus, and stress, were recorded in real time, providing a detailed picture of the emotional dynamics at play in each type of interaction. Participants exhibited higher levels of excitement, stress, and focus during interactions with humans compared to AI systems, while other emotions like …

Computational Modeling Of High Yttrium Refractory High Entropy Alloy Microstructures, Kaleb C. Ryan, Marissa M. Baker

College of Engineering Summer Undergraduate Research Program

Refractory high entropy alloys (RHEAs) are advanced metals made up of five or more principal elements in roughly equal amounts. The microstructural effects of alloying with yttrium as a principal element for RHEAs are currently not well understood. This project compared RHEA microstructures from literature with simulations using the High Entropy Alloy Predicting Software (HEAPS), which computes 10 screening criteria to predict the microstructure of a RHEA composition. The accuracy of HEAPS predictions was assessed by comparing them with experimentally validated microstructures found in literature. A combination of criteria was found to have a 95.8% accuracy rate, and a new …

Wearable Sensing Systems And Data Analytics For Pressure Sensing Socket Prostheses, Stacey Le, Mio Nakagawa

College of Engineering Summer Undergraduate Research Program

Prosthetics have been widely used as the primary solution for lower limb amputations, but residual limb volume fluctuations have posed challenges to the effectiveness and comfortability of these devices. In this project, we aim to observe pressure distribution patterns in the prosthetic socket during gait using sensing technology and investigate the performance of different machine learning algorithms on determining good or bad fit.

Deep-Learning Based Microstructure Reconstruction And Generation, Cameron J. Maloney, Lucas Taliaferro

College of Engineering Summer Undergraduate Research Program

Characterizing the microstructural behavior of materials is crucial for understanding their properties and performance. Traditional imaging methods, such as optical microscopy and electron microscopy, are effective but costly and time-consuming. Computational approaches can reduce costs and time while expanding the accessibility of microstructural analysis through the generation of new microstructure images. Traditional computational approaches, namely descriptor-based approaches, are slow but effective in low-data scenarios. Modern approaches use machine learning (ML), which is faster but often requires a lot of data to approach the performance of descriptor-based methods. This research leverages a special data-efficient Generative Adversarial Network (GAN) architecture to artificially …

Surrogate Models For Stress-Strain Mapping Of Microscale Physics, Samuel Roach, Dr. Eric Ocegueda

College of Engineering Summer Undergraduate Research Program

•Learn the difference between different neural networks within machine learning (ML) •Develop a working understanding of the ML tool Pytorch and machine learning operator: Recurrent Neural Operator •Use MATLAB to create and process time dependent stress/strain matrices to display the hyper-parameters for different RNOs •Apply RNO to train the strain-stress mapping of tri-laminate and granular cases

Attitude Control Of A Flexible Flapping Wing Uav Based On Fuzzy Logic, Reed M. Paulson, Tyson Chen, Diego Del Real, Nico Morrison

College of Engineering Summer Undergraduate Research Program

This project revolves around creating an a attitude controller for a hovering flexible flapping wing UAV that is based on a flying hummingbird. We based our model from a paper by Banazadeh and Taymourtash1 , First replicating the open-loop results using the nonlinear dynamic model and the equations of motion (seen below) while considering aerodynamic loads. Once replicated, we then used fuzzy logic to model the dynamic model. Subsequently, we designed a fuzzy controller to stabilize the hovering mode. We then considered and detailed future work needed to make further progress in this area.

Exploration Of Esp32 Vulnerabilities And Malware, Charles T. Moreno

College of Engineering Summer Undergraduate Research Program

The rapid expansion of the Internet of Things (IoT) has revolutionized industries by enabling connected smart devices to monitor, communicate, and automate tasks in real-time. Central to the functioning of many IoT systems are microcontrollers like the ESP32, a versatile and low-cost microcontroller known for its integrated Wi-Fi and Bluetooth capabilities. The ESP32's powerful processing, energy efficiency, and adaptability make it a popular choice for IoT applications ranging from smart home devices to industrial automation. However, as IoT adoption grows, so too do the security challenges posed by vulnerabilities in these devices, particularly within ESP32-based systems. For this project, I …

Enhancing Place-Based Interaction With Emotion Ai And Augmented Reality, Jake Maier, Ivan Martinez

College of Engineering Summer Undergraduate Research Program

This project explores the integration of augmented reality (AR) and Emotion AI technologies to enhance user experiences in physical environments. By seamlessly merging virtual elements with real-world contexts, we aim to deepen individuals’ interactions and perceptions of their surroundings. Leveraging AR technology enables users to access contextual information, engage with interactive content, and navigate spaces with heightened immersion and understanding. Additionally, Emotion AI enhances these experiences by detecting and responding to users’ emotional states, fostering personalized and emotionally resonant interactions. We aim to integrate digital content within physical environments using mixed-reality headsets equipped with eye-tracking capabilities and consumer-grade wireless EEG …

Seismic Resilience Of Timber Homes, Melia R. Costa

College of Engineering Summer Undergraduate Research Program

The vast majority of residential buildings in California are wood-frame structures. A home is typically a very large investment for families, and damage to the home can be detrimental to a family’s economic success. Thus, reducing the economic impacts of an earthquake on residential timber housing is crucial. A full scale, two-story section of a residential timber house is in construction in the Parson’s Geotechnical and Earthquake Engineering Laboratory on the Cal Poly campus in San Luis Obispo, California. Once built it will be put through earthquake simulation tests on a shake table with various magnitudes of seismic activity. Next, …

Drive To Succeed: Empowering Underserved Communities Through Autonomous Driving Education, Amanda I. Chan

College of Engineering Summer Undergraduate Research Program

Autonomous vehicle (AV) technology represents the leading edge of innovation in transportation and holds immense potential to transform industries across the globe, with California at the forefront. However, access to education and technical training in this field has often been out of reach for students in underserved communities. The “Drive to Succeed” project endeavors to bridge this gap by introducing autonomous driving technology to high school students in communities where access has traditionally been limited. We propose an outreach program specifically designed to address the underrepresentation of marginalized groups in technology sectors and cultivate the next generation of engineers from …

Shake Table Testing Of Full-Scale Fully Equipped Timber Assembly In Residential Timber Homes, Derek A. Quintanilla

College of Engineering Summer Undergraduate Research Program

No abstract provided.

Distributed Multi-Robot Localization And Coordination Framework For Mobile Robots, Dmitri Dobrynin, Indigo T. Garcia

College of Engineering Summer Undergraduate Research Program

This project aims to develop an experimental framework for multiple mobile robots, both in simulation and real-world hardware, using ROS 2 as the primary operating system. Utilizing TurtleBot 3 platforms, the team will establish a robust setup that enables tasks such as distributed localization, autonomous navigation, path planning, and formation control for mobile robots. Leveraging simulation environments like Gazebo, the project will replicate real-world setups in a simulated environment for testing and development. All tasks, communication, and sensor integration will be implemented using ROS 2, ensuring seamless coordination and interoperability among the robots. The project involves integrating various sensors and …

Leveraging Tradespace-Exploration For A Senior Project Team Formation Application, Miguel Saenz

College of Engineering Summer Undergraduate Research Program

This project revolves around the development of an app in MATLAB that leverages the VASSAR rule-based system and a genetic algorithm to form groups of teams for the Mechanical Engineering Senior Design project class. We leveraged the iterative design process to eventually attain a functional app with a reasonable runtime that works provided correctly formatted rulesheets describing student project preference and member preference.

African Californios.Org: Reconstructing The African Past Of Spanish & Mexican California, Anthony Colin Herrera

College of Engineering Summer Undergraduate Research Program

AfricanCalifornios.org is a research project dedicated to highlighting the significant contributions of Afro-descendants in Spanish and Mexican California. Historical colonial census records reveal that 19% of California's population had African ancestry, yet many individuals concealed their identities to enhance their social standing. This project uses modern NLP and Data Science techniques to construct family trees, shedding light on their overlooked stories. The work has been published and presented at the 2024 Alliance of Digital Humanities Organizations conference.

Design Of Ballistics Armor Using Additive Manufacturing Of Kevlar Composites, Jedidiah D. Jimenez, Roha Y. Ali, Jack C. Bride

College of Engineering Summer Undergraduate Research Program

This project evaluates the effectiveness of various geometries created using advanced additive manufacturing (AM) of Kevlar fiber, chopped carbon fiber-reinforced filament for ballistic protection applications. This study expands on sandwich panel designs with woven Kevlar face sheets and investigates an optimal fiber reinforced filament core structure design. A unit cell workflow was developed in nTop to take advantage of its custom cell modeling and FEA capabilities. Unit cell types were simulated and tested from the hexagonal honeycomb, gyroid TPMS, and re-entrant auxetic cell families. Core structure thickness and cell size were additive manufacturing parameters that were varied to assess the …