Computer Engineering Commons^™

Safehome, Meryem Esa, Siddarth Raj

Interdisciplinary Design Senior Theses

The SafeHome app was developed to address the significant communication challenges in refugee camps, where outdated methods such as flyers and intercoms limit the efficiency and reliability of information dissemination. Through extensive research and user-centric design, we developed a dual-interface application on the Firebase platform, featuring a web-based portal for camp administrators and a mobile application for refugees. The results showed effective functionality and enhanced communication, with refugees now able to receive timely updates, access crucial resources, and store personal documents securely. The successful implementation of SafeHome underscores the potential of leveraging technology to solve real-world challenges and enhance the …

A Hardware Platform For Wireless Beehive Monitoring, Erik Wrysinski, Jonathan Stock, Collin Paiz, Daniel Blanc

Computer Science and Engineering Senior Theses

Traditional beehive monitoring systems suffer from many challenges. These monitoring devices are expensive to set up, difficult to implement, and lack cross compatibility with each other. Preexisting beehive monitoring solutions face all of these shortcomings. Our beehive monitoring platform aims to overcome these issues by using inexpensive, off-theshelf, open-source hardware paired with a computer vision machine learning model to accurately monitor the ingress and egress of bees into and out of the hive. This data is presented to the beekeeper in a simple GUI which allows them to track hive activity over time, and by extension, the overall health of …

A Study Of Processing Beehive Monitoring Data In Edge And Cloud, Yen-Jung Lu, Jason Fong, Cheng Zhang, Chan Nam Tieu

Computer Science and Engineering Senior Theses

Bees are vital pollinators for numerous crops and plants, playing an essential role in maintaining the world’s ecosystem and food security. Without bees, the global food supply would be threatened, potentially leading to food shortages and increased food prices. Current beehive monitoring solutions in the market are often prohibitively expensive, some commercial beehive monitoring solutions can cost upwards of thousands of dollars. This makes them inaccessible to many small-scale beekeepers. To help protect bee health and ensure the survival of thousands of plant species worldwide, this project aims to create an accessible solution for individuals to monitor the health and …

Flowview: A Web Application For Hydrologic Predictions, Marcus Chavez, Sean Leininger, Joseph Pham Nguyen

Computer Science and Engineering Senior Theses

The Santa Clara Valley Water District, or Valley Water, provides water management resources to the two million residents in Santa Clara County. A few of their services include supplying safe water, ownership of streams, and flood protection. However, given the evolving conditions of the climate throughout the state of California, Valley Water seeks to include machine learning analytics as part of its water management services. Additionally, the increased access to the Internet has expanded the use of web applications, which provide a flexible platform to integrate the

predictions of machine learning models. In this paper, we design and implement a …

Warn: Wi-Fi Attack Recognizer And Notifier, Sudhish Sewpaul, Roshan Sevalia, Jaden Ngo, Tate Musante

Computer Science and Engineering Senior Theses

The Wi-Fi Attack Recognizer and Notifier (WARN) aims to establish a wireless network monitoring system for detection of attacks on Wi-Fi IoT devices. Millions of homes use smart home devices, and many of these are for security. However, these devices are vulnerable to attacks that can disable them or compromise their data confidentiality. WARN is capable of detecting two of these attacks: deauthentication and key reinstallation (KRACK). Deauthentication attacks hoax devices into disconnecting themselves from a network, and KRACK manipulates the authentication protocol of Wi-Fi devices to see unencrypted data. WARN uses Raspberry Pis equipped with long range Wi-Fi antennas …

Automated Retail Checkout By Computer Vision: Arc-Ai, Griffin Ellis

Computer Science and Engineering Senior Theses

There is some opportunity to apply AI and computer vision techniques to the problems in the retail industry. This paper presents a possible solution to the problem of accurate automated check-out in a retail store setting, a difficult problem due to the possibility of occlusion of hand-held products by the customer and the possible similarity of different products. This solution will identify objects being purchased frame-by-frame, propose tracks that follow individual objects across multiple frames, then determine when and where the object was brought over the region of interest, which will be determined at the start of the task. At …

Avalanche Predictions Based On Ml, William Olson, Matthew Davenport, Ben Airola

Computer Science and Engineering Senior Theses

Our Avalanche Prediction Model utilizes machine learning to analyze weather and climate data in order to provide users in the Northern California back-country with accurate probabilities of avalanche occurrences. Snow forecasts only provide information relating to how much snow will fall. Current avalanche danger ratings only provide the potential level for injury there is if an avalanche will occur. Our system, Avy Safe ML, let’s users survey geographic terrain and see direct probability indicators for precise geo-locations of mountain faces and ranges. These indicators are represented as variably-shaded geo-polygons that indicate avalanche risk classifications. Our data visualization allows access to …

Twigeenglish, Brian Burnett, Jillian Coveney, Kristin Tong, Nanki Sekhon

Computer Science and Engineering Senior Theses

TwigeEnglish is an educational platform aimed to teach English in a fun and interactive way. It comprises a mobile application for students and a web application for pre-determined administrators. The mobile application offers three key features which include: a pictionary-like game, a dictionary flash card game, and a user-friendly interface for uploading photos to be used in both games. The web application will primarily focus on providing administrators with an interface to manage the student-photo database. With moderation powers, administrators can seamlessly review and make decisions to approve or deny the inclusion of photos in the active pictionary and dictionary …

Round Trip Time Measurement Over Microgrid Power Network, Yasin Emir Kutlu, Ruairí De Fréin, Malabika Basu, Ali Malik

Conference papers

A focus of the Power Systems and Networking communities is the design and deployment of Microgrid (MG) integration systems that ensure that quality of service targets are met for load sharing systems at different endpoints. This paper presents an integrated Microgrid testbed that allows Microgrids endpoints to share their current, voltage and power values using a Network Published Shared Variable (NPSV) approach. We present Round Trip Time (RTT) measurements for time sensitive Microgrid control traffic in the presence of varying background traffic as an example quality of service measurement. Numerical results are presented using a range of different background traffic …

Whether-Weather, Lucas Voron, Graham Purvis, Malcolm Weaver, Josh Kelleran

Computer Science and Engineering Senior Theses

The WhetherWeather project is a comprehensive weather and traffic forecasting system that provides real-time insights and predictions. It utilizes Python programming language and various data sources, including Inrix data for traffic information and weather data from Meteostat. The system employs machine learning techniques, specifically XGBoost, to train models on historical data. Once trained, the models can accurately forecast traffic conditions based on weather data. To visualize the results, a Flask API is available, allowing users to access the system's functionalities through a web interface. For more information and to access the WhetherWeather website, visit WhetherWeather.org.

Singular Value Decomposition And Transformer-Based Image Super Resolution, Andy Qin, Chen Zhang, Timothy Cui

Computer Science and Engineering Senior Theses

Image super-resolution (ISR) is a prominent field in computer vision that aims to enhance the quality and resolution of low-resolution images. It finds widespread applications in various domains, including surveillance, satellite imagery, medical imaging, and media. The primary objective of ISR is to improve the visual quality and level of detail in low-resolution images. In this paper, we propose the Singular Value Decomposition and Transformer-based Image Super Resolution (SVDTIR) model, which combines both traditional and deep learning approaches to achieve image super-resolution. The SVDTIR model consists of three stages: image pre-processing, which employs the singular-value decomposition (SVD) algorithm to decompose …

Climate Cloud, Atiyut Khemkhon, Dylan Lin

Computer Science and Engineering Senior Theses

The increasing frequency and intensity of drastic climate change events have underscored the urgency for a comprehensive understanding of climate dynamics and the development of effective mitigation and adaptation strategies. In this context, our thesis addresses the critical issue of drought category prediction in Western America using machine learning techniques. We recognize the interconnectedness of efforts aimed at combating climate change and strive to make a meaningful contribution to the broader understanding of climate change, even if our impact may seem comparatively smaller. By leveraging the power of machine learning algorithms and utilizing a wide range of climatic and environmental …

Underwater Robot Path Planning In An Intermittent Communication System, Hunter Gallant

Dartmouth College Master’s Theses

Sunflower, a novel cross-medium localization system between an aerial drone and an underwater robot, has not yet been implemented in a multi-robot exploration system. This project’s aim was to simulate various configurations of multi-robot systems, and to create an algorithm, called AdjustPath, to improve exploration and avoid inter- robot collisions. With three, five, seven, and ten simulated underwater robots, there was significant improvement when the AdjustPath algorithm was used. Knowing this, future hardware using the Sunflower system could use this proposed algorithm to increase efficiency and avoid more collisions.

Ai-Powered Iot Monitoring And Security For Smart Homes, Paul Boldyrev, Timothy Hradil, Matthew Ding

Computer Science and Engineering Senior Theses

Smart home devices are becoming increasingly popular across the United States. Unfortunately, in order to keep the cost of these devices down, manufacturers tend to place cybersecurity measures lower on their list of priorities. As a result, these devices have become targets for security breaches like the Mirai Botnet and distributed denial of service (DDoS) attacks. The cybersecurity solutions currently available on the market are either expensive, difficult to set up, or follow a static set of rules for attack detection. In this thesis, we propose a novel approach to detecting attacks on Internet of Things (IoT) devices through the …

Cometrics: A New Software Tool For Behavior‑Analytic Clinicians And Machine Learning Researchers, Walker S. Arce, Seth G. Walker, Morgan L. Hurtz

Department of Electrical and Computer Engineering: Faculty Publications

Cometrics is a Microsoft Windows compatible clinical tool for the collection and recording of frequency- and duration-based target behaviors, physiological signals, and video data. This software package is designed to record in-vivo observational and physiological data. In addition, we have included features that allow observers to capture video from real-time camera feeds and import saved video for retroactive data collection. By using Microsoft Excel-based spreadsheets, also called keystroke files, assessment and treatment sessions are exported into a single document using the click of a button. Integrated interobserver agreement metrics allow comparisons across primary and reliability observers, with the output exported …

Model-Driven Analysis Of Ecg Using Reinforcement Learning, Christian O'Reilly, Sai Durga Rithvik Oruganti, Deepa Tilwani, Jessica Bradshaw

Publications

Modeling is essential to better understand the generative mechanisms responsible for experimental observations gathered from complex systems. In this work, we are using such an approach to analyze the electrocardiogram (ECG). We present a systematic framework to decompose ECG signals into sums of overlapping lognormal components. We use reinforcement learning to train a deep neural network to estimate the modeling parameters from an ECG recorded in babies from 1 to 24 months of age. We demonstrate this model-driven approach by showing how the extracted parameters vary with age. From the 751,510 PQRST complexes modeled, 82.7% provided a signal-to-noise ratio that …

Poly-Gan: Regularizing Polygons With Generative Adversarial Networks, Lasith Niroshan, James Carswell

Conference Papers

Regularizing polygons involves simplifying irregular and noisy shapes of built environment objects (e.g. buildings) to ensure that they are accurately represented using a minimum number of vertices. It is a vital processing step when creating/transmitting online digital maps so that they occupy minimal storage space and bandwidth. This paper presents a data-driven and Deep Learning (DL) based approach for regularizing OpenStreetMap building polygon edges. The study introduces a building footprint regularization technique (Poly-GAN) that utilises a Generative Adversarial Network model trained on irregular building footprints and OSM vector data. The proposed method is particularly relevant for map features …

Interactive Architecture - Intervention Of Virtual Business On Commercial Space, Yihao George Xu

Masters Theses

Traditional mall-based restaurants, such as P.F. Chang’s in the Providence Place Mall, have primarily focused on site-based dining and bar services. However, the food provided by this chain restaurant often lacks depth, and customers seldom learn the story behind the dishes. This thesis explores the integration of mixed reality technology within the physical environment of P.F. Chang’s, an American Chinese restaurant chain with over 300 locations, aiming to transform it into an authentic Shanghai food culture experience. This experience combines virtual and physical stimuli to evoke various periods of Chinese history, providing a unique encounter for customers.

The proposed transformation …

Unveiling Pain: Wearables For Objective Pain Measurement, Hanqing Tang

Masters Theses

">">Pain perception is a subjective experience that differs significantly among individuals, often leading to inconsistencies in assessment and management. A critical issue within this context is the gender bias in pain evaluation, which contributes to unequal treatment and perpetuates gender inequality within the healthcare system. This thesis presents an in-depth investigation of the problem and proposes the development of a wearable device for objective pain assessment. Physiological parameters — Electrocardiography (ECG) can be collected from cardiac sound signals auscultated by fabrics via nanometre-scale vibrations. Machine learning methods can accurately classify heart rate and acute pain intensity of participants. …

Slowly Changing Dimensions And Fast Changing Facts - The Story Of The Traditional Data Warehouse, Vishnu Pendyala

Open Educational Resources

This presentation, "Slowly Changing Dimensions and Fast Changing Facts - The Story of the Traditional Data Warehouse," explores how to generate actionable insights from organizational performance data. It begins by discussing the challenges of generating insights directly from existing databases and introduces the concept of data cubes for efficient aggregate storage. The core of the presentation focuses on dimensional modeling, particularly the Star Schema, as a solution for analytical processing needs that cannot be met by transactional systems. It details the characteristics of fast-changing fact tables (long, lean, numeric) and slowly changing dimension tables (descriptive, wide, containing strings and numbers). …