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. 2012;12(7):9253-72.
doi: 10.3390/s120709253. Epub 2012 Jul 5.

Using a communication model to collect measurement data through mobile devices

José Bravo  1 , Vladimir Villarreal, Ramón Hervás, Gabriel Urzaiz
Affiliations

Using a communication model to collect measurement data through mobile devices

José Bravo et al. Sensors (Basel). 2012.

Abstract

Wireless systems and services have undergone remarkable development since the first mobile phone system was introduced in the early 1980s. The use of sensors in an Ambient Intelligence approach is a great solution in a medical environment. We define a communication architecture to facilitate the information transfer between all connected devices. This model is based in layers to allow the collection of measurement data to be used in our framework monitoring architecture. An overlay-based solution is built between network elements in order to provide an efficient and highly functional communication platform that allows the connection of a wide variety of devices and technologies, and serves also to perform additional functions such as the possibility to perform some processing in the network that may help to improve overall performance.

Keywords: communication model; data transmission; mobile devices; sensors integration.

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Figures

Figure 1.
Figure 1.
Functionality and elements of the architecture.
Figure 2.
Figure 2.
Distribution of mobile devices that interact with the software architecture.
Figure 3.
Figure 3.
Ontology distribution used for the communication model.
Figure 4.
Figure 4.
The three layers of the model.
Figure 5.
Figure 5.
Elements of the data layer (left) and the flow data that define this layer (right).
Figure 6.
Figure 6.
Elements of the communication layer (left) and basic code to communication process generation (right).
Figure 7.
Figure 7.
Major components of the VQN model related with our layers distribution.
Figure 8.
Figure 8.
Server process requirements in a traditional solution.
Figure 9.
Figure 9.
Alternate solution with PIN functionality.
Figure 10.
Figure 10.
Elements of the application layer (left) and some examples implemented on each level.
Figure 11.
Figure 11.
Generation of the final application based in our framework.
Figure 12.
Figure 12.
Results of the quality aspect evaluated for the final users.
Figure 13.
Figure 13.
Proof of concept test scenario.
See this image and copyright information in PMC

References

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    1. Kientz J.A., Patel S.N., Jones B., Price E., Mynatt E.D., Abowd G.D. The Georgia Tech Aware Home. Proceedings of CHI' 08 Extended Abstracts on Human Factors in Computing Systems; Florence, Italy. 5–10 April 2008; pp. 3675–3680.
    1. Choi M., Jones B.D. Remote Home Health Monitoring Management Using Smartphones; Poster Presented at mHealth Summit 2010; Washington DC, USA. 8– 10 November 2010.
    1. University of Virginia Smart IN-HOME Monitoring System. Available online: http://marc.med.virginia.edu/projectssmarthomemonitor.html (accessed on 5 November 2011)
    1. Intel Corporation HealthCare. Available online: http://www.intel.com/about/companyinfo/healthcare/people/research/approa... (accessed on 10 November 2011)

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