走向语义智能城市:关于语义上下文推理系统的概念化和实施的研究
1Depatment of Convergence Engineering for Intelligent Drone, Sejong University, Gwangjin-gu, Seoul 05006, Republic of Korea.
Sensors (Basel, Switzerland)
|December 9, 2023
概括
本研究介绍了一个使用语义推理和5W1H原则的智能城市系统,以积极预测和解决疾病和恐怖主义等城市问题,增强城市管理和安全.
科学领域:
- 城市信息学 城市信息学
- 人工智能的人工智能
- 公共安全公众安全.
背景情况:
- 智能城市利用综合城市数据提供服务,但难以自主识别疾病和恐怖主义等新出现的威胁.
- 现有的智能城市框架缺乏主动识别和应对前所未有的城市挑战的能力.
- 无法预见的城市问题带来了巨大的财务和人力风险,需要先进的预测能力.
研究的目的:
- 开发一个能够预测潜在城市问题并支持主动解决问题的系统.
- 加强智能城市环境中新出现的城市挑战的自主识别和缓解.
主要方法:
- 使用语义推理和5W1H (谁,什么,什么时候,在哪里,为什么,如何) 原则作为推理规则.
- 通过使用特定领域的模板集成各种城市数据源 (市政数据,物联网平台) 来构建语义图.
- 实现基于5W1H推理的自主上下文推断和积累,以确定情境模式.
主要成果:
- 该系统通过检测反复出现的服务中断及其相互连接,成功地推断出潜在的城市问题.
- 通过积累的上下文数据,确定了易受城市问题影响的特定时间和地点.
- 展示了系统连接不同事件的能力,揭示了潜在的城市挑战.
结论:
- 提出了一个主动城市问题预测系统的综合概念模型.
- 提供了实施案例和使用案例,突出了实际应用.
- 提高城市管理人员和公民对潜在问题区域的认识,使预防性缓解策略成为可能.
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