1
Return

Toward Explainable Digital Twins for Indoor Environmental Risk Prediction Using Open IoT Sensor Data

delete2026-08-03
delete0
delete
OA
AI
Y
Yaqoob Al Hindasi
M
Marjan Ilbeigi *
M
Mahnaz Rezaei
F
Fatemeh zare mohammadjani
E
Elyas Jahanshahi
A
Afrodit Barjani
L
Leila Yarloo
DOI：10.1016/j.rineng.2026.112313delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
• Proposed an explainable digital twin for indoor risk forecasting. • Combined IoT data fusion, ML, and explainable AI in one framework. • Captured complex environmental dynamics via multimodal features. • Discovered operational risk states through latent-space clustering. • Supported proactive and intelligent indoor environmental management.
Keywords:
Digital twin
Indoor environmental quality
Internet of Things (IoT)
Environmental risk prediction

Journal

Results in Engineering cover
Results in Engineering
IF:
7.9
Papers:
1.1W
Citations:
1.7W

Organization

U
university technology malaysia
Scholars:
15
Papers: 8
Citations: 0
M
Mashhad Branch
Scholars:
2
Papers: 2
Citations: 0
C
chalous branch
Scholars:
2
Papers: 1
Citations: 0
K
Khatam University
Scholars:
16
Papers: 12
Citations: 181
I
islamic azad university
Scholars:
4.0K
Papers: 2.0K
Citations: 0
Cited Papers

Cited Papers

Citing Papers

Citing Papers