Hazard- and Fairness-Aware Evacuation with Grid-Interactive Energy Management: A Digital-Twin Controller for Life Safety and Sustainability

The paper introduces a real-time digital-twin controller that manages evacuation routes while operating GEEM for emergency energy management during building fires. The system consists of three interconnected parts which include (i) a physics-based hazard surrogate for short-term smoke and temperature field prediction from sensor data (ii), a router system that manages path updates for individual users and controls exposure and network congestion (iii), and an energy management system that regulates the exchange between PV power and battery storage and diesel fuel and grid electricity to preserve vital life-safety operations while reducing both power usage and environmental carbon output. The system operates through independent modules that function autonomously to preserve operational stability when sensors face delays or communication failures, and it meets Industry 5.0 requirements through its implementation of auditable policy controls for hazard penalties, fairness weight, and battery reserve floor settings. We evaluate the controller in co-simulation across multiple building layouts and feeder constraints. The proposed method achieves superior performance to existing AI/RL baselines because it reduces near-worst-case egress time (T95 and worst-case exposure) and decreases both event energy Eevent and CO2-equivalent CO2event while upholding all capacity, exposure cap, and grid import limit constraints. A high-VRE, tight-feeder stress test shows how reserve management, flexible-load shedding, and PV curtailment can achieve trade-offs between unserved critical load Uenergy and emissions. The team delivers implementation details together with reporting templates to assist researchers in reaching reproducibility goals. The research shows that emergency energy systems, which integrate evacuation systems, achieve better safety results and environmental advantages that enable smart-city integration through digital thread operations throughout design, commissioning, and operational stages.

Authors

Institutions

Publication Details

Journal
Sustainability
Published
2025-12-22
DOI
https://doi.org/10.3390/su18010133
Citations
1
Primary Topic
Evacuation and Crowd Dynamics
Type
article
Field-Weighted Citation Impact
1.15

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Hazard- and Fairness-Aware Evacuation with Grid-Interactive Energy Management: A Digital-Twin Controller for Life Safety and Sustainability

Ibrahim S. Alkhazi, Saleh Albelwi, Sami Mnasri, Mansoor Alghamdi et al.
1 citations
Sustainability
Evacuation and Crowd Dynamics
1.15
article

Hazard- and Fairness-Aware Evacuation with Grid-Interactive Energy Management: A Digital-Twin Controller for Life Safety and Sustainability

Ibrahim S. Alkhazi, Saleh Albelwi, Sami Mnasri, Mansoor Alghamdi, Sultan A Alghamdi, Ahmad Abadleh, Malek Alrashidi
article en
1 citations

Abstract

The paper introduces a real-time digital-twin controller that manages evacuation routes while operating GEEM for emergency energy management during building fires. The system consists of three interconnected parts which include (i) a physics-based hazard surrogate for short-term smoke and temperature field prediction from sensor data (ii), a router system that manages path updates for individual users and controls exposure and network congestion (iii), and an energy management system that regulates the exchange between PV power and battery storage and diesel fuel and grid electricity to preserve vital life-safety operations while reducing both power usage and environmental carbon output. The system operates through independent modules that function autonomously to preserve operational stability when sensors face delays or communication failures, and it meets Industry 5.0 requirements through its implementation of auditable policy controls for hazard penalties, fairness weight, and battery reserve floor settings. We evaluate the controller in co-simulation across multiple building layouts and feeder constraints. The proposed method achieves superior performance to existing AI/RL baselines because it reduces near-worst-case egress time (T95 and worst-case exposure) and decreases both event energy Eevent and CO2-equivalent CO2event while upholding all capacity, exposure cap, and grid import limit constraints. A high-VRE, tight-feeder stress test shows how reserve management, flexible-load shedding, and PV curtailment can achieve trade-offs between unserved critical load Uenergy and emissions. The team delivers implementation details together with reporting templates to assist researchers in reaching reproducibility goals. The research shows that emergency energy systems, which integrate evacuation systems, achieve better safety results and environmental advantages that enable smart-city integration through digital thread operations throughout design, commissioning, and operational stages.

SustainabilityVol. 18(1)
University of Tabuk (SA)
University of Tabuk
Openalex Percentile: Top 16%
Evacuation and Crowd Dynamics
1.15
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.