The Internet of Things (IoT) enables the interconnection of new cyber–physical devices that generate significant traffic of distributed, heterogeneous, and dynamic data at the network edge. Since several IoT applications demand for short response times (e.g., industrial applications, emergency management, real-time systems, and healthcare systems) and, at the same time, rely on resource-constrained devices, the adoption of traditional data mining techniques is neither effective nor efficient. Therefore, conventional data mining techniques need to be adjusted for optimizing response times, energy consumption, and data traffic while still providing adequate accuracy as required by the IoT applications.

中文翻译：

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物联网边缘数据挖掘方法和基础设施特刊


物联网 (IoT) 实现了新的网络物理设备的互连，这些设备在网络边缘产生大量分布式、异构和动态数据流量。由于一些物联网应用需要较短的响应时间（例如工业应用、应急管理、实时系统和医疗保健系统），同时又依赖于资源受限的设备，因此采用传统的数据挖掘技术既不可行又不可行。有效或高效。因此，传统的数据挖掘技术需要进行调整，以优化响应时间、能耗和数据流量，同时仍然提供物联网应用所需的足够的准确性。