From Observations to Infrastructure: A GPS-Based Smart City Mobility Data Framework for Wildfire Evacuation Planning

Abstract

Smart cities increasingly rely on interconnected data infrastructures, yet emergency management systems—particularly for wildfire evacuation—remain disconnected from these capabilities. This paper proposes a four-layer GPS-based smart city mobility data framework that integrates crowd-sourced location data as a permanent component of urban evacuation planning infrastructure. The framework encompasses passive GPS sensing and ingestion, behavioral inference through origin detection and departure timing analysis, dynamic multi-criteria routing with fire-risk awareness, and governance-compliant decision support. Proof-of-concept validation using 181 million GPS records from the 2023 McDougall Creek wildfire in Kelowna, British Columbia, demonstrates that GPS-calibrated behavioral inputs combined with hybrid dynamic routing reduce evacuation clearance time by 39% and fire-risk exposure by 61% compared to conventional approaches. We discuss data integration challenges, accuracy considerations across GPS and cellular sources, transferability conditions, and governance requirements for operational deployment in wildland–urban interface communities.