Data visualization: From body sensor network to social networks

Mohamed Abdur Rahman, Abdulmotaleb El Saddik, W. Gueaieb
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引用次数: 15

Abstract

Sensors can capture very sensitive and valuable information without human intervention and send it to remote location. However, capturing sensory data from a Body Sensor Network (BSN) and sending it to social networks is a challenging task. This is because it requires a number of distributed networks to work together seamlessly. The task becomes more challenging when both the BSN and the social networks are mobile. It requires a framework which can handle the mobility of both the BSN and members of social networks and can send the sensory data to the social networks for real-time visualization. In this paper, we propose an open source framework, named SenseFace, which seamlessly incorporates a four-tier network including a BSN, cellular network, Internet and an overlay network consisting of social networks, to pass sensory data from a mobile BSN to the overlay network. The overlay network can intelligently manage one's social network and produce different data visualization formats suitable for email, fax, voicemail, SMS, MMS, APRS network, IM networks such as hotmail, gmail, yahoo, and existing social networks such as Facebook, YouTube, LinkedIn, delicious, Wordpress etc. Finally, we present the framework design and the hardware and software that have been used for the implementation of the framework.
数据可视化:从身体传感器网络到社交网络
传感器可以在没有人为干预的情况下捕获非常敏感和有价值的信息并将其发送到远程位置。然而,从身体传感器网络(BSN)捕获感官数据并将其发送到社交网络是一项具有挑战性的任务。这是因为它需要许多分布式网络无缝地协同工作。当BSN和社交网络都是移动的时候,这项任务变得更具挑战性。它需要一个既能处理BSN和社交网络成员的移动性,又能将感知数据发送到社交网络进行实时可视化的框架。在本文中,我们提出了一个名为SenseFace的开源框架,该框架无缝集成了一个四层网络,包括BSN、蜂窝网络、互联网和由社交网络组成的覆盖网络,将移动BSN的传感数据传递到覆盖网络。覆盖网络可以智能管理一个人的社交网络,并产生不同的数据可视化格式,适用于电子邮件,传真,语音邮件,短信,彩信,APRS网络,即时通讯网络,如hotmail, gmail,雅虎,以及现有的社交网络,如Facebook, YouTube, LinkedIn, delicious, Wordpress等。最后,给出了框架的设计和实现框架所用到的硬件和软件。
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