Electrical and Electronics Commons^™

A Multiscale Ai Framework For Forest And Agriculture Health Monitoring: Drone-Based Object Recognition And Segmentation For Automated Ecological Assessment, Sruthi Keerthi Valicharla

Graduate Theses, Dissertations, and Problem Reports (ETD)

Forest and agricultural ecosystems are increasingly at risk due to invasive species, pests, and diseases, necessitating scalable, automated, and intelligent monitoring solutions. Traditional field based forest and agriculture health assessments are limited by cost, time, and spatial coverage. This dissertation presents a multiscale deep learning framework that automates forest and agriculture health monitoring using drone imagery and computer vision techniques. The system operates across three spatial levels: forest level, tree level, and leaf level, combining object detection, segmentation, and classification models to support large scale ecological assessment.

At the forest level, high-altitude drone imagery is processed using object detection and …

Neural Network-Based Image Compression, Atefeh Khoshkhahtinat

Graduate Theses, Dissertations, and Problem Reports (ETD)

The rapid advancement of information technology and the exponential growth of digital communication have significantly increased the demand for efficient data compression techniques that reduce storage requirements, minimize bandwidth consumption, and accelerate data transmission—without substantially compromising data quality. This dissertation addresses these challenges by investigating and developing advanced learned image compression (LIC) methods, with a particular focus on lossy compression for both natural images and scientific imagery obtained from NASA’s Solar Dynamics Observatory (SDO) mission. Traditional image compression standards—such as JPEG, JPEG2000, BPG, and HEVC—rely on manually engineered transforms and heuristic rules, which often lack the adaptability required to accommodate …

Design, Control, And Evaluation Of A Photovoltaic Snow Removal Strategy Based On A Bidirectional Dc-Dc Converter For Photovoltaic–Electric Vehicle Application, Salma Elakkad, Mohamed Hesham, Hany Ayad Bastawrous, Peter Makeen

Electrical Engineering

A novel self-heating technique is proposed to clear snow from photovoltaic panels as a solution to the issue of winter snow accumulation in photovoltaic (PV) power plants. This approach aims to address the shortcomings of existing methods. It reduces PV cell wear, resource loss, and safety risks, without the need for additional devices. A self-heating current is applied to the solar panel to melt the snow covering its surface, which is then allowed to slide off the panel due to gravity. The proposed system consists of a bidirectional DC-DC converter, which removes the snow cover by heating the solar PV …

Design & Development Of Fr1 Band Antenna For V2x Communication, Sujanth Narayan Kg

Theses and Dissertations

The developing trends in the automotive industry are evolving towards connected and autonomous vehicles that provide various advantages namely enhanced safety & security, congestion less traffic, smart mobility, and environmental sustainability at a lower cost with greater cause to the society. Vehicle to Everything (shortly V2X) Communication plays a significant role in autonomous driving. Salient features of V2X provide improved better driving experience and traffic efficiency even during fast moving scenarios.

V2X technologies are being carried out in sub 6 GHz range mainly at the 5.9 GHz band called the Dedicated Short-Range Communication (DSRC) based on IEEE 802.11p providing support …

Exploring Smart Thermostat, Don P. Dang

2024 Fall Honors Capstone Projects - Archive

This study examines the security, privacy, and compatibility challenges associated with smart thermostats in smart home systems. Smart thermostats, as part of the growing Internet of Things (IoT) ecosystem, face vulnerabilities such as unauthorized access, data breaches, and inconsistent security protocols. Using a mixed-methods approach, this research evaluates encryption techniques, communication protocols (Zigbee, Z-Wave, Wi Fi), and user behaviors that impact system security and efficiency. Key findings indicate that 35% of users are concerned about hacking risks, while 25% express data privacy concerns. Many users lack awareness of security measures, such as firmware updates and password management, which increases vulnerabilities. …

Open-Source Cubesat Flight Board, Braydon M. Burkhardt

Electrical Engineering

The Helmsman Flight Board is an open-source main flight computer and electrical power system for educational and entry-level CubeSats. The board incorporates commercial off-the-shelf (COTS) components in conjunction with simplified monitoring and management circuitry, supporting easy adoption, modifiability, and affordability while crucially enabling the emerging aerospace industry’s rapid ‘design-build-test’ methodology in student satellite teams. Its design includes essential CubeSat subsystems such as battery management, command and data handling, attitude determination, on-board processing, and is built to support real-time embedded operating systems. Key features include an Arm Cortex-M7 based STM32, radiation-resistant memory for OS storage, bulk Flash memory, real-time clock, two …

Artificial Intelligence Computational Techniques Of Flywheel Energy Storage Systems Integrated With Green Energy: A Comprehensive Review, Abdelmonem Draz, Hossam Ashraf, Peter Makeen

Electrical Engineering

In recent years, the operation of the electric power grid has become more efficient and resilient due to the integration of renewable energy sources (RESs). Solar and wind energy are being incorporated aggressively into the main grid, while other RESs like biomass and geothermal energy are also on the rise. However, the intermittent nature of these RESs necessitates the use of energy storage devices (ESDs) as a backup for electricity generation such as batteries, supercapacitors, and flywheel energy storage systems (FESS). This paper provides a thorough review of the standardization, market applications, and grid integration of FESS. It examines the …

Developing A Bioengineered Nanoparticle For Improving Oral Absorption Of Iron Supplements., Mila Biswas

Open Access Theses & Dissertations

Iron deficiency (ID) and iron deficiency anemia (IDA) are widespread nutritional issues, affecting millions globally. Conventional iron supplements often suffer from low absorption rates and gastrointestinal side effects. We investigated β-glucan derivatives as potential carriers to enhance iron absorption and mitigate these drawbacks. This study explored a novel β-glucan-based carrier system loaded with ferrous sulfate heptahydrate. In-vitro studies demonstrated sustained iron stability for over six hours in simulated gastric fluids due to the carrier's affinity for stomach mucin. Particle size analysis and scanning electron microscopy (SEM) images confirmed this specific binding. Additionally, drug release studies revealed a pH-dependent release profile, …

Chipless 3d Microfluidic Rf Sensing, Sheikh Dobir Hossain

Open Access Theses & Dissertations

Effective management of the cold chain is essential to uphold the quality and safety of products vulnerability to physical factors like temperature, humidity, pressure, etc., including perishable foods, pharmaceuticals, and vaccines. Chipless Radio Frequency Identification (RFID) sensors have become increasingly favored as a viable technology for tracking, inventory, and sensing industries due to their wireless and non-line of sight (NLOS) situations, straightforward fabrication, cost efficiency, and adaptability to challenging environmental conditions. However, there is still a need for advancements in RFID sensors to make them promise for cold chain applications. Integration of flexibility and non-volatile memory into the existing RFID …

Extracting Permittivity And Permeability Using The Position-Insensitive And Calibration-Independent Method On A Rectangular Waveguide, James Conrad Denemark

Theses and Dissertations

Classic methods for extracting material characteristics require known measurements to accurately calibrate the network analyzer. Previous work demonstrated a position-insensitive and calibration-independent (PiCi) transmission/reflection method to extract a material’s permittivity. This thesis proposes a method with the same function, manipulated to use one empty measurement and then two samples of different thicknesses. The PiCi method is first adopted for rectangular waveguide which resulted in inaccurate permittivity data when compared to the calibrated solution. Once detector mismatch corrections were applied, the PiCi method produced accurate results. Using a 2-D numerical root search, permittivity and permeability material characteristics are now successfully extracted …

Leveraging P4 Programmable-Hardware Switches For In-Network Pmu Packet Recovery, Evan Michael Bonar

Electrical Engineering and Computer Science Undergraduate Honors Theses

Phasor Measurement Unit (PMU) systems are essential for real-time power grid monitor- ing but often face data loss due to network delays, equipment malfunctions, or transmis- sion errors. Traditional centralized recovery solutions introduce significant latency and scalability challenges. This thesis presents a P4-based in-network recovery mechanism that embeds detection and recovery directly into the data plane of P4-enabled programmable switches, significantly reducing recovery time and infrastructure complexity. Using the Aurora 610 switch, the system detects missing packets via sequence number analysis and recovers magnitudes with an efficient register-based algorithm.

Evaluation demonstrates high accuracy and low latency, achieving a mean absolute …

Dynamic Optimization Of Directed Energy Deposition Build Conditions Using Real-Time Monitoring Via Closed-Loop Control, Callan Herberger

Open Access Theses & Dissertations

Directed Energy Deposition (DED) is an additive manufacturing process that is being rapidly adopted by industry and is well suited for the fabrication of complex components in various metal alloys. DED provides unique benefits such as design flexibility, the potential for in-situ alloying, and an open environment that allows for unobstructed monitoring within the build chamber. Despite these benefits, fully exploiting additive manufacturing's (AM) potential remains a complex task for designers. This dissertation presents a framework for controlling Directed Energy Deposition process variables through in-situ monitoring. An exploration into modifying AM build conditions through the development and implementation of a …

Uncovering The Light Network Load Performance Penalty Of The Network Link Outlier Factor (Nlof), Michelle Lara

Open Access Theses & Dissertations

This thesis evaluates the effectiveness of the Network Link Outlier Factor with Most Likely Link (NLOF: MLL) algorithm under varying network load conditions. Repeated simulation experiments using Mininet were conducted for four different network-wide load levels: 100 Mbps, 500 Mbps, 1 Gbps, and 5 Gbps. Using statistical inference, our experimental results indicate that NLOF: MLL is ineffective under light load conditions (i.e., 100Mbps load) due to the limited network flow data available for its learning process. This limitation highlights a key challenge in applying the algorithm to lightly loaded networks. A preliminary algorithm was proposed to address this light-load performance …

Advancing Grid Modernization Through Data-Driven Resilience Modeling And Hosting Capacity Of Distributed Energy Resources, Oscar Samuel Acosta

Open Access Theses & Dissertations

This Ph.D. dissertation focuses on advancing the integration of distributed energy resources (DERs) through concepts surrounding their impacts on power system stability, resilience, and hosting capacity (HC). This dissertation addresses crucial topics in renewable energy deployment, transient fault response, and dynamic modeling. The work begins with the development of renewable energy source (RES) models tailored for offsetting residential heating, ventilation, and air conditioning~(HVAC) and commercial cooling loads. These models utilize solar photovoltaic (PV) and wind energy systems to produce scalable frameworks adapted across diverse climates and building types in application of a partial-load targeting methodology. The dissertation then transitions from …

Hardware Applications Of High-Speed Fault Detection Algorithms, Daniel Zintsmaster

All Theses

The growing need for a sustainable electric energy infrastructure has driven research into control, protection, and optimization of power systems. A key challenge is that the changing grid must operate at increasingly higher speeds, but many current hardware devices cannot meet these demands. This thesis focuses on power system protection, aiming to design a hardware solution that can detect and isolate faults in microseconds, ensuring faster, more reliable grid operations. The first hardware developed was for a low-voltage direct current (LVdc) microgrid, which faces challenges due to a lack of protection schemes and novel speed requirements. This thesis presents protection …

Three-Dimensional Environmentally Sustainable Neuromorphic Computing System Based On Natural Organic Memristor, Mohammed Rafeeq Khan

Graduate Theses and Dissertations (2019 - present)

A three-dimensional neuromorphic (3D) computing architecture based on environmentally sustainable natural organic honey memristors is proposed in this thesis. A set of comprehensive and experimental results indicate that the proposed systems exhibit remarkable inference accuracy, consistently surpassing the 90% threshold, even with different challenges such as device variations and nonlinearity. This study also considers four different conductance drift situations, the effects of analog-to-digital converter (ADC) quantization, and multiple algorithms, such as VGG8 and DenseNet-40. The deliverable of this thesis will test the stability of the proposed systems and explore their potential applications and scalability in real-world situations.

Smartphone Haptics Can Uncover Differences In Touch Interactions Between Asd And Neurotypicals, Ivonne Monarca, Franceli L. Cibrian, Isabel López Hurtado, Monica Tentori

Engineering Faculty Articles and Research

Utilizing touch interactions from smartphones for gathering data and identifying digital markers for screening and monitoring neurological disorders, such as Autism Spectrum Disorder (ASD), is an emerging area of research. Smartphones provide multiple benefits for this kind of study, including unobtrusive data collection via built-in sensors, integrated haptic feedback systems, and the capability to create specialized applications. Acknowledging the significant yet understudied presence of tactile processing differences in individuals with ASD, we designed and developed Feel and Touch, a mobile game that leverages the haptic capabilities of smartphones. This game provides vibrotactile feedback in response to touch interactions and collects …

Automated Solutions For Hydroponic Plant Growth, Sydney Mcclure, Adam Lachguar

Sustainability Conference

Within the past year, Project H.O.M.E. has been focusing on the design and development of a semi-automatic hydroponic system specifically for sustaining plant life in Martian-like conditions. Given the significance of extended space-based travel, where the duration of human life in space is a crucial factor, growing food becomes imperative. This project has integrated electrical engineering and computer science, with features like automated pH testing and sensor-based evaluations. Key functionalities, including timed watering and automatic adjustments, were coded to enhance plant care. Initially, the project’s comprehensive research and strategic planning resulted in detailed blueprints and computer-aided design models for the …

Sustainable Mobility: Machine Learning-Driven Deployment Of Ev Charging Points In Dublin, Ruairí De Fréin, Alexander Mutiso Mutua Mr

Articles

Electric vehicle (EV) drivers in urban areas face range anxiety due to the fear of running out of charge without timely access to charging points (CPs). The lack of sufficient numbers of CPs has hindered EV adoption and negatively impacted the progress of sustainable mobility. We propose a CP distribution algorithm that is machine learning-based and leverages population density, points of interest (POIs), and the most used roads as input parameters to determine the best locations for deploying CPs. The objects of the following research are as follows: (1) to allocate weights to the three parameters in a $6$ km …

Investigation On The Impact Of Loading Effect Of Fruit Juices On The Performance Of Pulsed Electric Field Generators, Devi S

Theses and Dissertations

Pulsed Electric Field (PEF) treatment is one of the efficient non-thermal food processing techniques which is being preferred as a replacement for thermal pasteurization methods. The effectiveness of PEF treatment was measured in terms of reduction in the microbial load in the food, extension of shelf life of the food and retention of nutritional properties of the food. The successful implementation of the PEF treatment depends upon various aspects such as design of pulse generator, parameters of pulse generator, shape and size of the treatment chamber and most importantly the characteristics of each food items. Design and fabrication of a …