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群工程中的物联云:基于瓦片图的户外人群密度智能监控方法

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

机构信息

College of Computer Science and Engineering, University of Jeddah, Jeddah 23890, Saudi Arabia.

出版信息

Sensors (Basel). 2022 Apr 26;22(9):3328. doi: 10.3390/s22093328.

Abstract

Managing citizen and community safety is one of the most essential services that future cities will require. Crowd analysis and monitoring are also a high priority in the current COVID-19 pandemic scenario, especially because large-scale gatherings can significantly increase the risk of infection transmission. However, crowd tracking presents several complex technical challenges, including accurate people counting and privacy preservation. In this study, using a tile-map-based method, a new intelligent method is proposed which is integrated with the cloud of things and data analytics to provide intelligent monitoring of outdoor crowd density. The proposed system can detect and intelligently analyze the pattern of crowd activity to implement contingency plans, reducing accidents, ensuring public safety, and establishing a smart city. The experimental results demonstrate the feasibility of the proposed model in detecting crowd density status in real-time. It can effectively assist with crowd management tasks such as monitoring, guiding, and managing crowds to ensure safety. In addition, the proposed algorithm provides acceptable performance.

摘要

管理公民和社区安全是未来城市最基本的服务之一。人群分析和监测也是当前 COVID-19 大流行情况下的重中之重,尤其是因为大规模聚集会显著增加感染传播的风险。然而,人群跟踪存在一些复杂的技术挑战,包括准确的人数统计和隐私保护。在这项研究中,使用基于瓦片地图的方法,提出了一种新的智能方法,该方法与物联网和数据分析云集成,提供户外人群密度的智能监测。所提出的系统可以检测和智能分析人群活动模式,以实施应急计划,减少事故,确保公共安全,并建立智慧城市。实验结果表明,所提出的模型在实时检测人群密度状态方面具有可行性。它可以有效地协助人群管理任务,如监控、引导和管理人群,以确保安全。此外,所提出的算法提供了可接受的性能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d08e/9101630/2193cb0dcbfe/sensors-22-03328-g001.jpg

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