Automated and Scalable Footstep Vibration-Based Pedestrian Localization in Built Environments Using Deep Learning

dc.contributor.author	Appelle, Aaron
dc.contributor.author	Salvino, Liming
dc.contributor.author	Lynch, Jerome P.
dc.date.accessioned	2026-08-20T21:26:10Z
dc.date.available	2026-08-20T21:26:10Z
dc.date.copyright	2025/10/16
dc.date.issued	2026
dc.identifier.other	JCCEE5.CPENG-6869.pdf
dc.identifier.uri	http://yetl.yabesh.ir/yetl1/handle/yetl/4314448
dc.description.abstract	AbstractWorks of social infrastructure, such as public parks and markets, play a crucial role in fostering well-being in urban communities. To evaluate their effectiveness, there is a need for nonintrusive, continuous mapping of pedestrian movement ...
dc.publisher	American Society of Civil Engineers
dc.title	Automated and Scalable Footstep Vibration-Based Pedestrian Localization in Built Environments Using Deep Learning
dc.type	Journal Article
dc.journal.volume	40
dc.journal.issue	1
dc.journal.title	Journal of Computing in Civil Engineering
dc.identifier.doi	10.1061/JCCEE5.CPENG-6869
dc.journal.fristpage	04025131-1
dc.journal.lastpage	04025131-16
dc.page	16
dc.tree	Journal of Computing in Civil Engineering:;2026:;Volume ( 040 ):;issue: 001
dc.contenttype	Fulltext