为低功耗蓝牙(BLE)设备提供云端物联网数据管理

Theodoros Soultanopoulos, Stelios Sotiriadis, E. Petrakis, C. Amza
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引用次数: 4

摘要

可穿戴传感器的使用及其与互联网的连接为存储传感数据提供了巨大的好处,这些数据可以智能地用于多种用途应用,例如医疗保健领域的监测目的。这项工作提出了一种物联网(IoT)网关服务,利用现代移动设备及其与可穿戴蓝牙低功耗(BLE)传感器通信的能力,使数据可以实时地转发到云端。该服务将移动平台(如智能手机)转换为网关,允许根据需要或自动决策从设备转发到云的数据的连续快速通信。其功能包括(a)使用一个内部处理机制BLE传感器信号和定义的数据发送到云,(b)动态服务,因为它有能力轻松地识别新BLE传感器属性调整根据动态模式和数据模型(c)普遍BLE设备功能,自动注册和监控在飞,而它使历史数据,可以集成到有意义的商业智能。基于面向服务的设计原则,该服务充分利用云服务来处理由越来越多的用户和传感器产生的潜在大数据流。这项工作的贡献是物联网数据传输速率,平均计算为128毫秒,在实验部分,我们讨论了这对于实时数据来说是非常低的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Internet of Things data management in the cloud for Bluetooth Low Energy (BLE) devices
The use of wearable sensors and their connectivity to Internet offers significant benefits for storing sensing data that could be utilized intelligently for multiple purpose applications such as for monitoring purposes in healthcare domain. This work presents an Internet of Things (IoT) gateway service taking advantage of modern mobile devices and their capabilities to communicate with wearable Bluetooth low energy (BLE) sensors so data could be forwarded to the cloud on the fly and on real time. The service transforms a mobile platform (such as a smartphone) to a gateway allowing continuous and fast communication of data that is forwarded from the device to the cloud on demand or automatically for an automated decision making. Its features include (a) use of an internal processing mechanism for the BLE sensor signals and defines the way in which data is send to the cloud, (b) dynamic service as it has the ability to recognize new BLE sensors properties by easily adapting the data model according to a dynamic schema and (c) universal BLE devices capability that are registered automatically and are monitored on the fly while it keeps historical data that could be integrated into meaningful business intelligence. Building upon principles of service oriented design, the service takes full advantage of cloud services for processing potential big data streams produced by an ever increasing number of users and sensors. The contribution of this work is on the IoT data transmission rate that is averagely calculated to 128 milliseconds and in the experimental section we discuss that this is significantly low for real time data.
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