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Now showing items 31-38 of 38
A Systematic Literature Review of Drone Utility in Railway Condition Monitoring
(2023)
Drones have recently become a new tool in railway inspection and monitoring (RIM) worldwide, but there is still a lack of information about the specific benefits and costs. This study conducts a systematic literature review ...
Predicting Advanced Air Mobility Adoption by Machine Learning
(2023)
Advanced air mobility (AAM) is a sustainable aviation initiative to deliver cargo and passengers in urban and regional locations by electrified drones. The widespread expectation is that AAM adoption worldwide will help ...
Identifying Factors Associated with Terrorist Attack Locations by Data Mining and Machine Learning
(2023)
While studies typically investigate the socio-economic factors of perpetrators to comprehend terrorism motivations, there was less emphasis placed on factors related to terrorist attack locations. Addressing this knowledge ...
Reducing Risks by Transporting Dangerous Cargo in Drones
(2022)
The transportation of dangerous goods by truck or railway multiplies the risk of harm to people and the environment when accidents occur. Many manufacturers are developing autonomous drones that can fly heavy cargo and ...
Ranking Risk Factors in Financial Losses From Railroad Incidents: A Machine Learning Approach
(2023)
The reported financial losses from railroad accidents since 2009 have been more than US$4.11 billion dollars. This considerable loss is a major concern for the industry, society, and the government. Therefore, identifying ...
Perspectives on Using Connected Vehicles for Transportation Infrastructure Condition Monitoring
(2022)
The condition of surface transportation infrastructure directly affects the economic health of a nation. However, it is difficult to justify the large sums of money needed to extend current methods to monitor all the ...
Data-Driven Deployment of Cargo Drones: A U.S. Case Study Identifying Key Markets and Routes
(2023)
Electric and autonomous aircraft (EAA) are set to disrupt current cargo-shipping models.
To maximize the benefits of this technology, investors and logistics managers need information on
target commodities, service ...
Unlocking Drone Potential in the Pharma Supply Chain: A Hybrid Machine Learning and GIS Approach
(2023)
In major metropolitan areas, the growing levels of congestion pose a significant risk of supply chain disruptions by hindering surface transportation of commodities. To address this challenge, cargo drones are emerging as ...