基于物联网的边缘计算 (IoTEC) 改善环境监测
Javad Roostaei1, Yongli Z Wager1, Weisong Shi2
1Department of Civil and Environmental Engineering, Wayne State University, 5050 Anthony Wayne Dr., Detroit, MI 48202.
概括
具有边缘计算 (IoTEC) 的物联网传感器网络显著降低了数据延迟和传输,为环境监测降低了高达82%的成本. 这种方法也提高了电源供应的持续时间,证明了其有效性.
科学领域:
- 环境科学 环境科学
- 计算机科学 计算机科学
- 工程 工程师 工程师 工程师
背景情况:
- 传统的传感器网络在数据延迟,能源消耗和环境监测的成本效益方面面临挑战.
- 边缘计算与物联网 (IoT) 的整合为这些局限性提供了潜在的解决方案.
研究的目的:
- 为了评估与边缘计算 (IoTEC) 结合的物联网传感器网络的性能,用于环境监控.
- 在数据延迟,能源消耗和经济成本方面,将IoTEC与传统传感器监控方法进行比较.
- 评估在边缘服务器上部署机器学习的可行性,以进行高级数据分析.
主要方法:
- 设计并实施了两个试点应用程序:蒸汽入侵的环境监测和基于废水的藻类培养系统性能.
- 收集和分析数据数据延迟,能源消耗和经济成本,无论是物联网EC还是传统方法.
- 评估了IoTEC对电力供应持续时间和潜在成本节约的影响.
主要成果:
- 与传统物联网网络相比,IoTEC可将数据延迟降低13%,数据传输降低50%.
- 通过IoTEC方法,电源供应时间增加了130%.
- 监测蒸汽入侵的年度成本降低了55%-82%,更多的房屋节省了更多的成本.
结论:
- 物联网环境监测 (IoTEC) 方法为环境监测的效率和成本效益提供了显著的改进.
- 通过在边缘服务器上部署机器学习,IoTEC展示了先进数据处理和分析的可行性.
- 这项技术有望为更可持续,更经济的环境监测解决方案提供希望.
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