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2020

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Full-Text Articles in Electrical and Computer Engineering

Technique Design Of Filter On Surface-Acoustic Waves, Dilmurod Abdujalilovich Davronbekov, Zafar Tulyaganovich Khakimov Dec 2020

Technique Design Of Filter On Surface-Acoustic Waves, Dilmurod Abdujalilovich Davronbekov, Zafar Tulyaganovich Khakimov

Acta of Turin Polytechnic University in Tashkent

The article describes the design of filters on surface acoustic waves (SAWs), which are selective elements and are widely used in blocks, devices and signal processing systems in telecommunications, including wireless communication systems such as cellular, trunking and others. Designs of filters for surfactants are considered, which are divided into two large groups - by functional purpose and by a systematic approach to the synthesis of performance characteristics of filters for surfactants. Optimization algorithms and methods for synthesizing surfactant filters have been developed and improved. An improved technique for the synthesis of a filter based on surface acoustic waves is …


Solar Photovoltaic Performance Monitoring: A Bibliometric Review, Research Gaps And Opportunities, Javed Sayyad, Paresh Nasikkar Dec 2020

Solar Photovoltaic Performance Monitoring: A Bibliometric Review, Research Gaps And Opportunities, Javed Sayyad, Paresh Nasikkar

Library Philosophy and Practice (e-journal)

Electrical power generation has been revolutionized by growing demand and use of Renewable Energy (RE) sources such as Solar Photovoltaic (SPV) as the main electricity source in modern times. The main objective of this bibliometric analysis is to understand the scope of the literature available for SPV performance characterization. This detailed reviewed was performed on the documents related to SPV research considering all the subject categories from Scopus and Web of Science (WoS) databases. The patterns for the particular set of keywords were broke down with the recuperated outcomes from Scopus database in the language, publication type, year of publication, …


Protecting Health Data In A Pandemic: A Systematic Adversarial Threat Analysis Of Contact Tracing Apps, Leah Krehling Dec 2020

Protecting Health Data In A Pandemic: A Systematic Adversarial Threat Analysis Of Contact Tracing Apps, Leah Krehling

Electronic Thesis and Dissertation Repository

In this thesis centralized, decentralized, Bluetooth, and GPS based applications of digital contact tracing were reviewed and assessed. Using privacy principles created by a contingent of security and privacy experts from across Canada, a metric of assessing an application’s privacy was created. An attack tree was built to assess the security of the contact tracing applications. Eighteen attacks were theorized against contact tracing applications currently in use. An application’s vulnerability to the attacks was measured using a scoring system developed for this purpose. The results of the security scores were used to create a metric for assessing the security of …


Longitudinal Partitioning Waveform Relaxation Methods For The Analysis Of Transmission Line Circuits, Tarik Menkad Dec 2020

Longitudinal Partitioning Waveform Relaxation Methods For The Analysis Of Transmission Line Circuits, Tarik Menkad

Electronic Thesis and Dissertation Repository

Three research projects are presented in this manuscript. Projects one and two describe two waveform relaxation algorithms (WR) with longitudinal partitioning for the time-domain analysis of transmission line circuits. Project three presents theoretical results about the convergence of WR for chains of general circuits.

The first WR algorithm uses a assignment-partition procedure that relies on inserting external series combinations of positive and negative resistances into the circuit to control the speed of convergence of the algorithm. The convergence of the subsequent WR method is examined, and fast convergence is cast as a generic optimization problem in the frequency-domain. An automatic …


Novel Memristor Based True Random Number Generator, Scott Stoller Dec 2020

Novel Memristor Based True Random Number Generator, Scott Stoller

Boise State University Theses and Dissertations

Random numbers are an important, but often overlooked part of the modern computing environment. They are used everywhere around us for a variety of purposes, from simple decision making in video games such as a coin toss, to securing financial transactions and encrypting confidential communications. They are even useful for gambling and the lottery.

Random numbers are generated in many ways. Pseudo random number generators (PRNGs) generate numbers based on a formula. True random number generators (TRNGs) capture entropy from the environment to generate randomness. As our society and our devices become more connected in the digital world, it is …


A Multimodal Neuroimaging Approach For Classification And Prediction Of Alzheimer's Disease Using Machine Learning, Parisa Forouzannezhad Nov 2020

A Multimodal Neuroimaging Approach For Classification And Prediction Of Alzheimer's Disease Using Machine Learning, Parisa Forouzannezhad

FIU Electronic Theses and Dissertations

Alzheimer’s disease (AD) is one of the most common neurodegenerative disorders among the elderly population. It is progressive, irreversible in nature, and is considered the main cause of dementia. AD has become a world health problem affecting developed and developing nations alike, with the number of diagnosed AD patients increasing rather dramatically as both the life span of humans and the earth’s population continue to increase. Therefore, AD diagnosis in its earliest manifestations, preferably at the presymptomatic stage is critical for the timely planning of treatment and therapeutic interventions. We introduce new machine learning algorithms to detect and predict Alzheimer’s …


Challenges To Adopting Hybrid Methodology: Addressing Organizational Culture And Change Control Problems In Enterprise It Infrastructure Projects, Harishankar Krishnakumar Oct 2020

Challenges To Adopting Hybrid Methodology: Addressing Organizational Culture And Change Control Problems In Enterprise It Infrastructure Projects, Harishankar Krishnakumar

Dissertations and Theses

IT infrastructure projects have long been an overlooked field superseded by the more popular software development silos and cross-functional project teams when it comes to enterprise Agile transformations. This paper presents a systematic literature review by leveraging a qualitative research methodology based on empirical evidence provided in contemporary scholarly research articles to explore how certain variables such as organizational culture- including team structure, leadership hierarchy, geolocation, etc. along with an organization’s change management processes affect the adoption of a Hybrid/Agile project management methodology, focusing on reported challenges and critical success factors that define such large-scale enterprise transformations. The salient features …


Forecasting Vegetation Health In The Mena Region By Predicting Vegetation Indicators With Machine Learning Models, Sachi Perera, Wenzhao Li, Erik Linstead, Hesham El-Askary Sep 2020

Forecasting Vegetation Health In The Mena Region By Predicting Vegetation Indicators With Machine Learning Models, Sachi Perera, Wenzhao Li, Erik Linstead, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Machine learning (ML) techniques can be applied to predict and monitor drought conditions due to climate change. Predicting future vegetation health indicators (such as EVI, NDVI, and LAI) is one approach to forecast drought events for hotspots (e.g. Middle East and North Africa (MENA) regions). Recently, ML models were implemented to predict EVI values using parameters such as land types, time series, historical vegetation indices, land surface temperature, soil moisture, evapotranspiration etc. In this work, we collected the MODIS atmospherically corrected surface spectral reflectance imagery with multiple vegetation related indices for modeling and evaluation of drought conditions in the MENA …


High Wind Alerts: A System Created With Observations From The X-Band Teaching And Research Radar, Lauren Warner Aug 2020

High Wind Alerts: A System Created With Observations From The X-Band Teaching And Research Radar, Lauren Warner

The Journal of Purdue Undergraduate Research

Following the August 13, 2011, Indiana State Fair stage collapse tragedy, caused by a wind gust from an approaching thunderstorm, Purdue University enforced a wind speed restriction of 30 mph (13 m s-1) for tents at outdoor events. During these events, volunteers stand outside with handheld anemometers, measuring and reporting when the wind speeds exceed this limit. In this study, we report testing of a new system to automate high-wind alerts based on observations from a Doppler radar, the X-band Teaching and Research Radar (XTRRA), near Purdue’s campus. XTRRA scans over campus at low elevations approximately every 5 minutes. Using …


Material Evaluation And Structural Monitoring Of Early-Age Masonry Structures, Kyle Dunphy Aug 2020

Material Evaluation And Structural Monitoring Of Early-Age Masonry Structures, Kyle Dunphy

Electronic Thesis and Dissertation Repository

During the initial construction period, “early-age” masonry walls are susceptible to lateral loads induced by wind or earthquake, which may result in damages or catastrophic failures. To mitigate such consequences at construction sites, temporary bracings are adopted to provide lateral support to masonry walls until they are matured enough to serve as the inherent lateral system of the structure. However, current temporary bracing guidelines provide oversimplified design due to the lack of available information on the material properties of early-age masonry. Moreover, there are no existing techniques for monitoring masonry walls to detect cracks due to construction activities. …


Network Resource And Performance Optimization In Autonomous Systems: A Connected Vehicles And Autonomous Networks Perspective, Ibrahim Shaer Aug 2020

Network Resource And Performance Optimization In Autonomous Systems: A Connected Vehicles And Autonomous Networks Perspective, Ibrahim Shaer

Electronic Thesis and Dissertation Repository

This thesis covers two topics that optimize a network-related problem subject to environment-specific constraints; placing vehicular applications and executing network traffic assignment changes. The first topic introduces an optimization model, Resource and Delay-aware V2X service Placement (RDP), and a baseline approach that only considers the resource requirements of vehicular services. Both are responsible for placing vehicular services used by vehicular applications in an edge computing environment. Under different simulation scenarios, the results obtained by RDP satisfy the delay requirements of vehicular applications as opposed to the baseline approach. The second topic examines the efficient execution of inter-domain traffic changes under …


A New Approach For Homomorphic Encryption With Secure Function Evaluation On Genomic Data, Mounika Pratapa Aug 2020

A New Approach For Homomorphic Encryption With Secure Function Evaluation On Genomic Data, Mounika Pratapa

Electronic Thesis and Dissertation Repository

Additively homomorphic encryption is a public-key primitive allowing a sum to be computed on encrypted values. Although limited in functionality, additive schemes have been an essential tool in the private function evaluation toolbox for decades. They are typically faster and more straightforward to implement relative to their fully homomorphic counterparts, and more efficient than garbled circuits in certain applications. This thesis presents a novel method for extending the functionality of additively homomorphic encryption to allow the private evaluation of functions of restricted domain. Provided the encrypted sum falls within the restricted domain, the function can be homomorphically evaluated “for free” …


Circus In Motion: A Multimodal Exergame Supporting Vestibular Therapy For Children With Autism, Oscar Peña, Franceli L. Cibrian, Monica Tentori Aug 2020

Circus In Motion: A Multimodal Exergame Supporting Vestibular Therapy For Children With Autism, Oscar Peña, Franceli L. Cibrian, Monica Tentori

Engineering Faculty Articles and Research

Exergames are serious games that involve physical exertion and are thought of as a form of exercise by using novel input models. Exergames are promising in improving the vestibular differences of children with autism but often lack of adaptation mechanisms that adjust the difficulty level of the exergame. In this paper, we present the design and development of Circus in Motion, a multimodal exergame supporting children with autism with the practice of non-locomotor movements. We describe how the data from a 3D depth camera enables the tracking of non-locomotor movements allowing children to naturally interact with the exergame . A …


A 2.56 Gbps Serial Wireline Transceiver That Supports An Auxiliary Channel And A Hybrid Line Driver To Compensate Large Channel Loss, Xiaoran Wang Aug 2020

A 2.56 Gbps Serial Wireline Transceiver That Supports An Auxiliary Channel And A Hybrid Line Driver To Compensate Large Channel Loss, Xiaoran Wang

Electrical Engineering Theses and Dissertations

Serial transceiver links are widely used for high-speed point-to-point communications. This dissertation describes two transceiver link designs for two different applications.

In serial wireline communications, security is an increasingly important factor to concern. Securing an information processing system at the application and system software layers is regarded as a necessary but incomplete defense against the cyber security threats. In this dissertation, an asynchronous serial transceiver that is capable of transmitting and receiving an auxiliary data stream concurrently with the primary data stream is described. The transceiver instantiates the auxiliary data stream by modulating the phase of the primary data without …


Admittance Method For Estimating Local Field Potentials Generated In A Multi-Scale Neuron Model Of The Hippocampus, Clayton S. Bingham, Javad Paknahad, Christopher Bc Girard, Kyle Loizos, Jean-Marie C. Bouteiller, Dong Song, Gianluca Lazzi, Theodore W. Berger Aug 2020

Admittance Method For Estimating Local Field Potentials Generated In A Multi-Scale Neuron Model Of The Hippocampus, Clayton S. Bingham, Javad Paknahad, Christopher Bc Girard, Kyle Loizos, Jean-Marie C. Bouteiller, Dong Song, Gianluca Lazzi, Theodore W. Berger

Engineering Faculty Articles and Research

Significant progress has been made toward model-based prediction of neral tissue activation in response to extracellular electrical stimulation, but challenges remain in the accurate and efficient estimation of distributed local field potentials (LFP). Analytical methods of estimating electric fields are a first-order approximation that may be suitable for model validation, but they are computationally expensive and cannot accurately capture boundary conditions in heterogeneous tissue. While there are many appropriate numerical methods of solving electric fields in neural tissue models, there isn't an established standard for mesh geometry nor a well-known rule for handling any mismatch in spatial resolution. Moreover, the …


The Effects Of Radiation On Memristor-Based Electronic Spiking Neural Networks, Sumedha Gandharava Dahl Aug 2020

The Effects Of Radiation On Memristor-Based Electronic Spiking Neural Networks, Sumedha Gandharava Dahl

Boise State University Theses and Dissertations

In this dissertation, memristor-based spiking neural networks (SNNs) are used to analyze the effect of radiation on the spatio-temporal pattern recognition (STPR) capability of the networks. Two-terminal resistive memory devices (memristors) are used as synapses to manipulate conductivity paths in the network. Spike-timing-dependent plasticity (STDP) learning behavior results in pattern learning and is achieved using biphasic shaped pre- and post-synaptic spikes. A TiO2 based non-linear drift memristor model designed in Verilog-A implements synaptic behavior and is modified to include experimentally observed effects of state-altering, ionizing, and off-state degradation radiation on the device. The impact of neuron “death” (disabled neuron …


Inventory Management Of The Refrigerator's Produce Bins Using Classification Algorithms And Hand Analysis., Sarah Virginia Morris Aug 2020

Inventory Management Of The Refrigerator's Produce Bins Using Classification Algorithms And Hand Analysis., Sarah Virginia Morris

Electronic Theses and Dissertations

Tracking the inventory of one’s refrigerator has been a mission for consumers since the advent of the refrigerator. With the improvement of computer vision capabilities, automatic inventory systems are within reach. One inventory area with many potential benefits is the fresh food produce bins. The bins are a unique storage area due to their deep size. A user cannot easily see what is in the bins without opening the drawer. Produce items are also some of the quickest foods in the refrigerator to spoil, despite being temperature and humidity controlled to have the fruits and vegetables last longer. Allowing the …


Boost Converter Inductor Sizing Effects On The Performance Of Mppt Algorithms, Alan Nonaka Aug 2020

Boost Converter Inductor Sizing Effects On The Performance Of Mppt Algorithms, Alan Nonaka

Master's Theses

With solar power and other renewables set to take over the market in the coming decades, maximum power point tracking will be essential to optimizing power output. One underserved topic of research is the effect of inductor current ripple on performance of Maximum Power Point Tracking (MPPT) algorithms. Many new topologies are focused on decreasing the ripple from PV source to increase efficiency and power output. However, not much has been done to show ripple degrading performance of MPPT algorithms. This study uses a boost converter topology to test the performance of constant duty cycle step Perturb and Observe (PO), …


Intelligent Algorithm For Trapezoidal Interval Valued Neutrosophic Network Analysis, Florentin Smarandache, Said Broumi, Deivanayagampillai Nagarajan, Malayalan Lathamaheswari, Mohamed Talea, Assia Bakali Aug 2020

Intelligent Algorithm For Trapezoidal Interval Valued Neutrosophic Network Analysis, Florentin Smarandache, Said Broumi, Deivanayagampillai Nagarajan, Malayalan Lathamaheswari, Mohamed Talea, Assia Bakali

Branch Mathematics and Statistics Faculty and Staff Publications

The shortest path problem has been one of the most fundamental practical problems in network analysis. One of the good algorithms is Bellman-Ford, which has been applied in network, for the last some years. Due to complexity in the decision-making process, the decision makers face complications to express their view and judgment with an exact number for single valued membership degrees under neutrosophic environment. Though the interval number is a special situation of the neutrosophic, it did not solve the shortest path problems in an absolute manner. Hence, in this work, the authors have introduced the score function and accuracy …


Enhanced Control Algorithms In Permanent Magnet Synchronous Machines, Haibo Li Aug 2020

Enhanced Control Algorithms In Permanent Magnet Synchronous Machines, Haibo Li

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Permanent magnet synchronous machines (PMSMs) are gaining increasing popularity in various applications due to their advantages, such as high efficiency, high power density, and superior control performance. A well-designed machine control algorithm is indispensable for a PMSM system to secure its good performance.

In this work, enhanced control algorithms in PMSMs are developed. Online machine current trajectory tracking, source power management, hardware overcurrent regulation, and machine current sensor fault detection and isolation (FDI) are included in the developed algorithms. The online machine current trajectory tracking ensures the maximum torque per ampere (MTPA) or maximum torque per voltage (MTPV) control in …


An End-To-End Trainable Method For Generating And Detecting Fiducial Markers, J Brennan Peace Aug 2020

An End-To-End Trainable Method For Generating And Detecting Fiducial Markers, J Brennan Peace

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Existing fiducial markers are designed for efficient detection and decoding. The methods are computationally efficient and capable of demonstrating impressive results, however, the markers are not explicitly designed to stand out in natural environments and their robustness is difficult to infer from relatively limited analysis. Worsening performance in challenging image capture scenarios - such as poorly exposed images, motion blur, and off-axis viewing - sheds light on their limitations. The method introduced in this work is an end-to-end trainable method for designing fiducial markers and a complimentary detector. By introducing back-propagatable marker augmentation and superimposition into training, the method learns …


A Novel Path Loss Forecast Model To Support Digital Twins For High Frequency Communications Networks, James Marvin Taylor Jr Jul 2020

A Novel Path Loss Forecast Model To Support Digital Twins For High Frequency Communications Networks, James Marvin Taylor Jr

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

The need for long-distance High Frequency (HF) communications in the 3-30 MHz frequency range seemed to diminish at the end of the 20th century with the advent of space-based communications and the spread of fiber optic-connected digital networks. Renewed interest in HF has emerged as an enabler for operations in austere locations and for its ability to serve as a redundant link when space-based and terrestrial communication channels fail. Communications system designers can create a “digital twin” system to explore the operational advantages and constraints of the new capability. Existing wireless channel models can adequately simulate communication channel conditions with …


Optimized Machine Learning Models Towards Intelligent Systems, Mohammadnoor Ahmad Mohammad Injadat Jul 2020

Optimized Machine Learning Models Towards Intelligent Systems, Mohammadnoor Ahmad Mohammad Injadat

Electronic Thesis and Dissertation Repository

The rapid growth of the Internet and related technologies has led to the collection of large amounts of data by individuals, organizations, and society in general [1]. However, this often leads to information overload which occurs when the amount of input (e.g. data) a human is trying to process exceeds their cognitive capacities [2]. Machine learning (ML) has been proposed as one potential methodology capable of extracting useful information from large sets of data [1]. This thesis focuses on two applications. The first is education, namely e-Learning environments. Within this field, this thesis proposes different optimized ML ensemble models to …


A Machine Learning Approach To Delineating Neighborhoods From Geocoded Appraisal Data, Rao Hamza Ali, Josh Graves, Stanley Wu, Jenny Lee, Erik Linstead Jul 2020

A Machine Learning Approach To Delineating Neighborhoods From Geocoded Appraisal Data, Rao Hamza Ali, Josh Graves, Stanley Wu, Jenny Lee, Erik Linstead

Engineering Faculty Articles and Research

Identification of neighborhoods is an important, financially-driven topic in real estate. It is known that the real estate industry uses ZIP (postal) codes and Census tracts as a source of land demarcation to categorize properties with respect to their price. These demarcated boundaries are static and are inflexible to the shift in the real estate market and fail to represent its dynamics, such as in the case of an up-and-coming residential project. Delineated neighborhoods are also used in socioeconomic and demographic analyses where statistics are computed at a neighborhood level. Current practices of delineating neighborhoods have mostly ignored the information …


Numerical Simulation Of Thermoelectric Transport In Bulk And Nanostructured Sisn Alloys, Venkatakrishna Dusetty Jul 2020

Numerical Simulation Of Thermoelectric Transport In Bulk And Nanostructured Sisn Alloys, Venkatakrishna Dusetty

Masters Theses

The current high demand for sustainable and renewable energy sources to solve world energy crisis has enormously increased interest in looking at alternative sources of energy. All the machines used in manufacturing process, electricity generation, residential applications, transportation etc., rejects energy in the form of heat into environment. Thermoelectric materials can convert thermal-to-electrical and electrical-to-thermal energy and can be utilized in waste-heat harvesting, more efficient cooling to reduce energy usage and CO2 emissions. Significant research efforts have been devoted over the past decade to thermoelectric materials, with particular emphasis being placed on combining materials selection with nanostructuring. The overarching …


Artificial Intelligence Towards Future Industrial Opportunities And Challenges, Gizealew Dagnaw Jul 2020

Artificial Intelligence Towards Future Industrial Opportunities And Challenges, Gizealew Dagnaw

African Conference on Information Systems and Technology

The industry 4.0 will bring reflective changes to our society, including an important digital shift in the manufacturing sector. At present, several manufacturing firms are trying to adopt the practices of industry 4.0 throughout their supply chain. The Fourth Industrial Revolution and the artificial intelligence at its core are fundamentally changing the way we live, work and interact as citizens. The complexity of this transformation may look overwhelming and to many threatening. Recently, the dramatic growth of new generation information technologies has prompted several countries to seek new strategies for industrial revolution. The globalization and the competitiveness are forcing companies …


Interdisciplinary Education Outreach With Traffic Sensor Build Kits, Sarah V. Hernandez, Mariah B. Crews Jul 2020

Interdisciplinary Education Outreach With Traffic Sensor Build Kits, Sarah V. Hernandez, Mariah B. Crews

Civil Engineering Teaching and Learning

The goal of this project was to attract K-12 students to transportation engineering careers through STEM outreach programs. To accomplish this goal, the object of the project was to design and implement maritime freight oriented educational outreach activities centered on traffic sensing technologies for middle, high school, and first-year college students. In MarTREC Project 5011 (Evaluating the Performance of Intermodal Connectors), the research team designed a low-cost, easily implementable LiDAR and Bluetooth sensor bundle that was capable of detecting, characterizing, and tracking freight trucks as they traveled to and from inland waterway port areas. The sensor provided data necessary to …


Vector Magneto-Optical Generalized Ellipsometry On Magnetic Slanted Columnar Heterostructured Thin Films, Chad Briley Jul 2020

Vector Magneto-Optical Generalized Ellipsometry On Magnetic Slanted Columnar Heterostructured Thin Films, Chad Briley

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Modern material growth techniques allow for nano-engineering highly complex three dimensionally nanostructured materials. These nano-engineered materials possess highly anisotropic physical properties that are significantly different from that of their bulk counterparts. The magnetization properties of nano-engineered materials can be modified through a close range interaction known as magnetic exchange. These materials are referred to as magnetic exchange-coupled materials. Exchange-coupled magnetic materials are composite magnetic materials where the magnetization of one material is influenced by the magnetization state of the neighboring materials.

The author describes the creation of a representative sample set of exchange-coupled nanoengineered magnetic materials. These materials are created …


Raysun's Infrared Raisin Dryer, Lucas Kensinger, Saraith Aispuro, Joe Vanacore Jun 2020

Raysun's Infrared Raisin Dryer, Lucas Kensinger, Saraith Aispuro, Joe Vanacore

General Engineering

The RaySuns senior project team was tasked with lowering the drying costs of raisins for River Ranch Raisins. In doing so, we explored several options for cutting costs: utilizing automation and exploring new drying technologies were our primary focus. We eventually planned a modular infrared heating mechanism which would be easy to automate in future projects. After manufacturing and testing an infrared heating mechanism, it was found that infrared drying could significantly cut costs versus the previous natural gas fired dryer tunnels while leaving room for automation. The infrared dryer was also shown to have the potential to create high-quality …


Automated Drone Calibration System, Jackie Kelly Jong-Mee Paik, Zach Nathan Richter, Tyler Wilson Van Den Berg, Ryan Alexander Zhan, Matthew Ward Carlson Jun 2020

Automated Drone Calibration System, Jackie Kelly Jong-Mee Paik, Zach Nathan Richter, Tyler Wilson Van Den Berg, Ryan Alexander Zhan, Matthew Ward Carlson

Mechanical Engineering

The final design review of the Inspired Flight Calibration Team senior project will detail the process used to complete a verification prototype of a drone calibration device and discuss lessons learned and suggestions for improving this device. Going from brainstorming and conceptual prototyping all the way through verification prototyping and testing, we were able to design a gyroscopic device that met Inspired Flight’s needs for the flight sensor calibration of their drones. The mechanical design involved comprehensive CAD models and hands-on manufacturing. The mechatronics side of the project worked heavily with electrical wiring and writing custom software to communicate and …