智能城市情景编辑器用于一般的"如果"分析
Lorenzo Adreani1, Pierfrancesco Bellini1, Stefano Bilotta1
1DISIT Lab, Department of Information Engineering, University of Florence, 50139 Florence, Italy.
Sensors (Basel, Switzerland)
|April 13, 2024
概括
本研究介绍了Snap4City平台上的一个新的场景模型和编辑器,用于多域城市分析. 它使灵活的假设场景能够应对城市面临的诸如交通拥堵和污染等挑战.
科学领域:
- 城市规划和智慧城市技术
- 数据科学和大数据分析
- 环境科学和可持续的流动性
背景情况:
- 城市化在流动性,能源和环境方面带来了复杂的挑战.
- 现有的城市场景分析解决方案是特定于领域的,不灵活的,并使用专有格式.
- 来自各种来源 (物联网,地理信息系统,遗留系统) 的大数据可以提供对城市状态和潜在变化的见解.
研究的目的:
- 为城市环境提供一种新的,灵活的,多领域的场景模型和编辑器.
- 将这个解决方案集成到开源的Snap4City平台中.
- 为了实现先进的数据处理和智能城市应用程序的假设分析.
主要方法:
- 开发一个新的场景模型和编辑器.
- 集成到Snap4City开源平台中.
- 实施NGSIv2合规的数据模型和一个场景版本方法.
- 通过多领域分析和交通拥堵案例研究进行演示.
主要成果:
- 拟议的解决方案支持多域处理和假设分析.
- 它使用NGSIv2兼容的数据模型与正式的城市背景描述.
- 一个关于交通拥堵的案例研究验证了该模型的有效性和实用性.
结论:
- 新的场景模型和编辑器增强了Snap4City平台的智能城市管理能力.
- 该解决方案提供灵活性,并解决现有的单域工具的局限性.
- 它为分析城市变化和支持可持续移动倡议提供了一个强大的框架.
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