2 citations · 7 across the 7 of their papers we have counts for
7 papers
UAV-Based Infrastructure Inspections: A Literature Review and Proposed Framework for AEC+FM
Amir Farzin Nikkhah, Dong Chen, Bradford Campbell +2
Unmanned Aerial Vehicles (UAVs) are transforming infrastructure inspections in the Architecture, Engineering, Construction, and Facility Management (AEC+FM) domain. By synthesizing…
Real-Time Roadway Obstacle Detection for Electric Scooters Using Deep Learning and Multi-Sensor Fusion
Zeyang Zheng, Arman Hosseini, Dong Chen +2
The increasing adoption of electric scooters (e-scooters) in urban areas has coincided with a rise in traffic accidents and injuries, largely due to their small wheels, lack of sus…
Detecting Plant VOC Traces Using Indoor Air Quality Sensors
Seyed Hamidreza Nabaei, Ryan Lenfant, Viswajith Govinda Rajan +4
In the era of growing interest in healthy buildings and smart homes, the importance of sustainable, health conscious indoor environments is paramount. Smart tools, especially VOC s…
Multimodal Data Integration for Sustainable Indoor Gardening: Tracking Anyplant with Time Series Foundation Model
Seyed Hamidreza Nabaei, Zeyang Zheng, Dong Chen +1
Indoor gardening within sustainable buildings offers a transformative solution to urban food security and environmental sustainability. By 2030, urban farming, including Controlled…
Impact of Road Infrastructure and Traffic Scenarios on E-scooterists' Riding and Gaze Behavior
Dong Chen, Arman Hosseini, Arik Smith +5
The growing adoption of e-scooters has raised significant safety concerns, particularly due to a surge in injuries and fatalities. This study explores the relationship between road…
Performance Evaluation of Real-Time Object Detection for Electric Scooters
Dong Chen, Arman Hosseini, Arik Smith +4
Electric scooters (e-scooters) have rapidly emerged as a popular mode of transportation in urban areas, yet they pose significant safety challenges. In the United States, the rise…
WcDT: World-centric Diffusion Transformer for Traffic Scene Generation
Chen Yang, Yangfan He, Aaron Xuxiang Tian +5
In this paper, we introduce a novel approach for autonomous driving trajectory generation by harnessing the complementary strengths of diffusion probabilistic models (a.k.a., diffu…