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Institutional Repository [SANDBOX]
Technical University of Crete
Technical University of Crete
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| URI: | http://purl.tuc.gr/dl/dias/B4295075-8993-4BA6-8DD7-7B4DC4DC781D | ||
| Year | 2016 | ||
| Type of Item | Conference Full Paper | ||
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| Bibliographic Citation | T. Soultanopoulos, S. Sotiriadis, E. Petrakis and C. Amza, "Internet of Things data management in the cloud for Bluetooth Low Energy (BLE) devices," in 3rd Internatioal Workshop on Adaptive Resource Management and Scheduling for Cloud Computing, 2016, pp. 35-39. doi: 10.1145/2962564.2962568 https://doi.org/10.1145/2962564.2962568 | ||
| Appears in Collections |
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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