Cloud of Things in Crowd Engineering: A Tile-Map-Based Method for Intelligent Monitoring of Outdoor Crowd Density

Area of Science:

• Computer Science
• Urban Planning
• Public Health

Background:

• Effective citizen and community safety management is crucial for future smart cities.
• Crowd analysis and monitoring are vital during the COVID-19 pandemic to mitigate infection transmission risks.
• Accurate people counting and privacy preservation pose significant challenges in crowd tracking.

Purpose of the Study:

• To propose a novel intelligent method for outdoor crowd density monitoring.
• To integrate cloud of things and data analytics for real-time crowd activity analysis.
• To support the development of smart cities by enhancing public safety and accident reduction.

Main Methods:

• A tile-map-based approach for crowd analysis.
• Integration with cloud of things (CoT) infrastructure.
• Application of data analytics for intelligent monitoring and pattern detection.

Main Results:

• The proposed model demonstrates feasibility in real-time crowd density detection.
• The system effectively analyzes crowd activity patterns for contingency planning.
• Experimental results show acceptable performance in assisting crowd management tasks.

Conclusions:

• The developed intelligent system offers a viable solution for real-time outdoor crowd density monitoring.
• This technology can significantly contribute to accident reduction and public safety in urban environments.
• The method supports smart city initiatives by providing intelligent crowd management capabilities.