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A Parametric Evaluation Of Iot Applications To Freight Transportation Using Model-Based Systems Engineering, Paul George Crawford
A Parametric Evaluation Of Iot Applications To Freight Transportation Using Model-Based Systems Engineering, Paul George Crawford
Theses and Dissertations
Industrial Internet of Things or IIoT consists of computing and communication at the operational edge of a value chain. Applications span manufacturing, energy, and transportation, among others. In the transportation context, IIoT translates to connected vehicle architecture and ITS applications. Current trends in communication allow more applications and devices to contribute to functions traditionally allocated to transportation ITS infrastructure. This poses challenges to design engineers to prototype emerging technologies in the existing transportation context and reduce integration, validation, and time to market. Model-based systems engineering is crucial step for IIoT deployment since it allows for a feature-rich digital representation of …
Development Of A Deformation-Based Structural Health System With Contactless Sensors And Machine Learning For Health Characterization And Failure Prediction, Juan Camilo Avendano Arbelaez
Development Of A Deformation-Based Structural Health System With Contactless Sensors And Machine Learning For Health Characterization And Failure Prediction, Juan Camilo Avendano Arbelaez
Theses and Dissertations
This dissertation presents the design and development of a structural health monitoring (SHM) system specifically tailored for transportation infrastructure components, such as bridges. The proposed system collects data by using contactless sensors and performs health characterization and failure prediction. It is capable of simulating multiple load conditions on structures, identifying possible failure points, and detecting and predicting failure scenarios. Both hardware and software implementations of a model of a bridge were performed as a pilot project in order to validate the proposed system. Computer simulation in ANSYS and the application of gradient boosting neural networks were performed to produce a …
Application Of Classification In Machine Learning: An Analysis Of Highway-Rail Grade Crossing Systems Safety, Christopher John Helmer Cox
Application Of Classification In Machine Learning: An Analysis Of Highway-Rail Grade Crossing Systems Safety, Christopher John Helmer Cox
Theses and Dissertations
Highway-rail grade crossing accidents are the second leading cause of fatalities within the railway transportation industry. Highway-rail grade crossing fatality statistics have failed to improve over the last decade, and in some years have increased. Because of these trends, research has found that considerable Federal funding initiatives exist to support and develop contemporary risk reduction methodologies involving machine learning and artificial intelligence. In accord with these initiatives, this thesis investigates the highway-rail grade crossing safety problem using machine learning to implement an ensemble decision tree-based classification application. The resulting classifier has been validated to achieve a less than three percent …