Deng Ai

Dr. Deng Ai

orcid

Research Focus & Metrics

Academic Career Length

2Years (2025-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
22 August 2025 in Sustainability
Verified
Journal Article
Open access
PDF file
DADeng Ai
Deng Ai
DKDa Kuang
Da Kuang
Yiqi TaoYiqi Tao
Yiqi Tao
FZFanbo Zeng
Fanbo Zeng
Amid growing demands for heritage conservation and precision urban governance, this study proposes a multimodal framework to analyze tourist perception and behavior in Macau’s Historic Centre. We integrate geotagged social media images and text, ultra-wideband (UWB) pedestrian trajectories, and a LiDAR-derived 3D digital twin to examine the interplay among spatial configuration, movement, and affect. Visual content in tourist photos is classified with You Only Look Once (YOLOv8), and sentiment polarity in Weibo posts is estimated with a fine-tuned Bidirectional Encoder Representations from Transformers (BERT) model. UWB data provide fine-grained trajectories, and all modalities are georeferenced within the digital twin. Results indicate that iconic landmarks concentrate visual attention, pedestrian density, and positive sentiment, whereas peripheral sites show lower footfall yet strong emotional resonance. We further identify three coupling typologies that differentiate tourist experiences across spatial contexts. The study advances multimodal research on historic urban centers by delivering a reproducible framework that aligns image, text, and trajectory data to extract microscale patterns. Theoretically, it elucidates how spatial configuration, movement intensity, and affective expression co-produce experiential quality. Using Macau’s Historic Centre as an empirical testbed, the findings inform heritage revitalization, wayfinding, and crowd-management strategies.

19 February 2025 in Buildings
Verified
Journal Article
Open access
PDF file
FZFanbo Zeng
Fanbo Zeng
HWHaofeng Wang
Haofeng Wang
JLJianhua Lei
Jianhua Lei
XHXujie Huo
Xujie Huo
YSYuan Shi
Yuan Shi
DADeng Ai
Deng Ai
This study introduces an automated method for constructing residential functional modules from the perspective of user behavior. By integrating the design structure matrix (DSM) and Fuzzy C-Means Clustering Algorithm (FCM), this approach systematically explores architectural functional modules. The DSM is employed to statistically analyze the correlations between residential behaviors. These correlations are then processed using FCM to generate various module segmentation schemes. The optimal scheme is selected based on modularity calculations. The results demonstrate improved modularity compared to traditional room-based designs, offering a greater variety of combinations and hierarchical organization. This methodology provides architects with a novel approach to address space integration challenges.