Evidence map›Paper›PMID 40573524›Full record

ArticleSensors (Basel, Switzerland)2025

A BIM-GIS Framework Integrated with CCTV Analytics for Urban Walkability Assessment.

Mingzhu Wang, Peter Kok-Yiu Wong, Jack C P Cheng

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Mingzhu WangDepartment of Architecture and Civil Engineering, City University of Hong Kong, Hong Kong 999077, China.ORCID 0000-0003-2622-1939
Peter Kok-Yiu WongDepartment of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Hong Kong 999077, China.ORCID 0000-0003-1758-675X
Jack C P ChengDepartment of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Hong Kong 999077, China.ORCID 0000-0002-1722-2617

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study proposes a novel framework integrating Building Information Modeling (BIM) and Geographic Information Systems (GIS) with real-time crowd analytics from Closed-Circuit Television (CCTV) for quantitative walkability assessment. The framework extends open data standards (IFC and CityGML) to model infrastructural and pedestrian flow attributes comprehensively. A walkability scoring mechanism quantifies route quality based on accessibility, efficiency, and physical comfort, differentiating among pedestrian groups, such as individuals sensitive to weather conditions or carrying belongings. Implemented at the Hong Kong University of Science and Technology (HKUST), results indicate that the framework effectively captures variations in walkability scores due to directional differences (uphill vs. downhill), crowd conditions, and operational constraints like facility closures. Statistical tests confirm significant differences in walking costs across these scenarios with variations of up to 30%, demonstrating the framework's robustness and practical utility for real-time, human-centric urban infrastructure planning.

Indexed as

BIM-GIS integrationCCTV analyticscomputer visiondata schemareal-time crowd monitoringwalkability assessment

Identifiers

PMID40573524
PMCPMC12196588

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.