ZHAO,YU-QING
I-Shou University Student, Department of Information Engineering
E-mail：lorina960411@gmail.com
TAN,AN-CHEN
I-Shou University Student, Department of Information Engineering
E-mail：frcquail@gmail.com
CHEN,PIN-WEI
I-Shou University Student, Department of Information Engineering
E-mail：SSChec123456@gmail.com
JHOU,JIA-HONG
I-Shou University Professor, Department of Electronic Engineering
E-mail：topjkpos@gmail.com
Abstract
This study proposes the “Urban Eye: Smart Rescue Decision & System Response Ecosystem,” aiming to address critical pain points in current emergency rescue operations, such as traffic congestion and cross-agency information silos. The system integrates 5G communication networks, AIoT technologies, and existing urban infrastructure. It utilizes Unity 3D to develop a highly realistic digital twin city model with dynamic feedback, and fully incorporates edge computing and image de-identification to ensure citizens’ privacy and security.
Its core applications include: dynamically controlling traffic lights via the cloud to provide continuous green corridors for rescue vehicles, effectively reducing arrival times by 20% to 40%; pushing navigation warnings to the general public to reduce the probability of secondary accidents; creating a multi-agency synchronized 3D cloud command platform to achieve seamless collaboration; deploying 5G-integrated drones when necessary to establish a comprehensive air-ground collaborative rescue model with no blind spots; and deeply linking with smart buildings to grasp internal information within disaster zones.
This system features non-destructive upgrades and a Zero Trust cybersecurity architecture, aligning with sustainable development indicators. Simulation results indicate that this architecture is expected to effectively enhance cross-agency collaboration efficiency, providing a feasible technical framework for disaster prevention and response in future smart cities.
Keywords：Cross-agency Collaboration, Artificial Intelligence of Things, Dynamic Traffic Signal Control, Smart Rescue