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Quantitative Evaluation of Drone-Based Linear Asset Condition Monitoring.
Record Type:
Language materials, manuscript : Monograph/item
Title/Author:
Quantitative Evaluation of Drone-Based Linear Asset Condition Monitoring./
Author:
Askarzadeh, Taraneh.
Description:
1 online resource (246 pages)
Notes:
Source: Dissertations Abstracts International, Volume: 85-07, Section: B.
Contained By:
Dissertations Abstracts International85-07B.
Subject:
Remote sensing. -
Online resource:
click for full text (PQDT)
ISBN:
9798381426496
Quantitative Evaluation of Drone-Based Linear Asset Condition Monitoring.
Askarzadeh, Taraneh.
Quantitative Evaluation of Drone-Based Linear Asset Condition Monitoring.
- 1 online resource (246 pages)
Source: Dissertations Abstracts International, Volume: 85-07, Section: B.
Thesis (Ph.D.)--North Dakota State University, 2023.
Includes bibliographical references
Linear transportation assets require regular monitoring to ensure their performance. The evolution of remote sensing technologies is now enabling faster and more cost-effective inspection methods. Departments of Transportation are increasingly adopting these technologies for asset inspection. This dissertation develops a framework for quantifying the advantages of employing drones in the expansion of this area. The research proposes a comprehensive framework for evaluating the utility of drones in inspecting and monitoring linear transportation assets, with a focus on bridges. The framework delivers an in-depth analysis of direct and indirect costs and benefits, integrating statistical models including various probability distributions, and Monte Carlo simulation to steer investment decisions towards drone technology. A detailed case study on bridges illustrates the method of quantifying the benefits and costs within the proposed framework. Moreover, the dissertation undertakes a cost-benefit analysis to determine the economic feasibility of drone technology in bridge inspection and performs a sensitivity analysis to assess the generalizability of the cost-benefit analysis to changes in drone costs resulting from technological advancements. The contribution of this dissertation to the field lies in demonstrating how drones can streamline the inspection process, offer detailed infrastructure data, and foster improved maintenance decisions for long-term asset management.
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024
Mode of access: World Wide Web
ISBN: 9798381426496Subjects--Topical Terms:
557272
Remote sensing.
Subjects--Index Terms:
Advanced air mobilityIndex Terms--Genre/Form:
554714
Electronic books.
Quantitative Evaluation of Drone-Based Linear Asset Condition Monitoring.
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Source: Dissertations Abstracts International, Volume: 85-07, Section: B.
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Advisor: Bridgelall, Raj.
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Includes bibliographical references
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Linear transportation assets require regular monitoring to ensure their performance. The evolution of remote sensing technologies is now enabling faster and more cost-effective inspection methods. Departments of Transportation are increasingly adopting these technologies for asset inspection. This dissertation develops a framework for quantifying the advantages of employing drones in the expansion of this area. The research proposes a comprehensive framework for evaluating the utility of drones in inspecting and monitoring linear transportation assets, with a focus on bridges. The framework delivers an in-depth analysis of direct and indirect costs and benefits, integrating statistical models including various probability distributions, and Monte Carlo simulation to steer investment decisions towards drone technology. A detailed case study on bridges illustrates the method of quantifying the benefits and costs within the proposed framework. Moreover, the dissertation undertakes a cost-benefit analysis to determine the economic feasibility of drone technology in bridge inspection and performs a sensitivity analysis to assess the generalizability of the cost-benefit analysis to changes in drone costs resulting from technological advancements. The contribution of this dissertation to the field lies in demonstrating how drones can streamline the inspection process, offer detailed infrastructure data, and foster improved maintenance decisions for long-term asset management.
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Ann Arbor, Mich. :
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Remote sensing.
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click for full text (PQDT)
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