Data visualization: From body sensor network to social networks

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.

A Survey on the Web of Things

“…Finally, we register a considerable interest in the bridging of Body Sensor Networks (BSNs) into the WoT via SNS platforms. Among others, we cite the pioneering study in [35] and the SenseFace [119] platform. In the first paper, the authors propose to integrate BSNs and SNSs so that only the authorized users can monitor in real-time the data coming from other members of the BSN.…”