Emergency Management

Emergency Management

The Role of Quality Standards in Optimizing the Efficiency of Artificial Intelligence Systems for Urban Crisis Management

Document Type : Original Article

Authors
Mostafa Tamtaji 1
Alireza Ekrami kivaj 2
1 Assist. Prof., Dept. of Strategic Management, Faculty of Management and Industrial Engineering, Malek Ashtar University of Technology, Tehran, Iran
2 Ph.D., Dept. of Aerospace Engineering, Faculty of Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
Abstract
The integration of artificial intelligence (AI) into urban crisis management holds transformative potential in addressing the challenges posed by natural and man-made disasters. This study aims to examine the role of quality standards in optimizing the efficiency of AI systems for managing urban crises. The research data comprises international quality standards, performance indicators such as response time, data accuracy, system reliability, and simulated urban crisis scenarios. The research methodology is based on multi-agent modeling and numerical simulations, assessing the impact of quality standards on the performance of AI across 12 crisis scenarios (including earthquakes, floods, and cyberattacks). Key findings indicate that AI systems built on quality standards reduce response time by up to 65% and improve data accuracy by 25% compared to traditional methods. Moreover, these standards ensure interoperability across platforms and adherence to ethical principles. The study concludes that quality standards not only enhance the efficiency of AI but also strengthen urban resilience through faster, more accurate, and ethically aligned responses.
Keywords
Quality Standards
Artificial Intelligence
Urban Crisis Management
Multi-Agent Simulation
Resilience
Subjects
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  • Receive Date 01 February 2025
  • Revise Date 15 April 2025
  • Accept Date 01 July 2025