雾计算:用于大数据营销分析的平台
Jacob Hornik1, Matti Rachamim2, Sergei Graguer3
1Coller School of Management, Tel-Aviv University, Tel Aviv, Israel.
Frontiers in artificial intelligence
|October 20, 2023
概括
雾计算解决了从物联网 (IoT) 系统中管理大量,多样化的营销数据的挑战. 这种去中心化的方法使计算更接近用户,使先进的AI和智能营销策略成为可能.
科学领域:
- 营销科学 营销科学
- 计算机科学 计算机科学
- 数据管理数据管理
背景情况:
- 营销科学越来越多地利用各种数据类型和测量工具进行战略决策.
- 来自物联网 (IoT) 传感器的大规模,异质数据的管理给营销经理带来了重大挑战.
- 传统的基于云的物联网系统在高延迟和数据量方面扎,阻碍了有效的营销应用程序.
研究的目的:
- 突出云计算在处理物联网部署中的营销数据方面的局限性.
- 引入雾计算作为营销中去中心化数据处理和分析的新解决方案.
- 探索雾计算在支持人工智能和"智能营销"管理策略方面的潜力.
主要方法:
- 对传统基于云的物联网系统在营销数据管理方面的挑战进行审查.
- 介绍和解释雾计算范式作为一个分散的替代方案.
- 讨论雾计算的分布式和联合模型,以使计算更接近边缘.
主要成果:
- 雾计算有效地解决了基于云的物联网营销数据中固有的规模,异质性和延迟问题.
- 通过雾计算分散应用程序和数据分析,提高了响应能力和效率.
- 雾计算为在智能营销环境中整合人工智能和先进管理策略提供了可行的框架.
结论:
- 雾计算为管理物联网设备生成的复杂营销数据提供了一种变革性的方法.
- 这种分散的计算模型对于实现实时分析和现代营销中的知情决策至关重要.
- 雾计算代表了开发复杂的人工智能驱动的"智能营销"计划的重大进步.
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