I am a Master's student in Computer Science at University of Salerno. I started research on how to exploit crowdsourcing to improve quality of both personal health and life of our urban environment. In particular, I wondered the possibilities of reducing traffic congestion (and consequent air-pollution damages ) through pervasive gaming.
However, my ongoing research switched to another interesting issue in Pervasive Computing: how to detect and enforce proximity. In particular, I am focusing on how to build a solution able to find a proper trade-off between granularity of the detected position, energy consumption and privacy.
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Detecting and Exploiting Proximity in a Pervasive World
- 05.05.2014 - 11.30 am
- Nowadays, smartphones are proxies to the habits and daily patterns of users. As a result, we assisted to a rapid proliferation of applications able to sense and recall social context. Moreover, Proximity-based Social Interactions (PSI) are becoming popular . With PSI, people's virtual interactions become more location-centric and tied to their physical neighborhood. As a consequence, the problem of detecting proximity became a key challenge for both research and industry. Applications for which an efficient proximity detection service is fundamental range from advertisement to mobile gaming, file sharing and so on. However, more effort must be done in order to achieve a proper trade-off between granularity of the detected position, energy consumption and privacy.In this talk, we will first draw a big picture of the context we are focusing on. Then, we will walk through the analysis of some of the proposed solutions facing the detection of proximity and, based on them, we will provide a sketch of our proposal. Finally, a shallow description of the related privacy issues.
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- Kunzli, Nino, et al. ”Public-health impact of outdoor and traffic-related air pollution: a European assessment.” The Lancet 356.9232 (2000):795-801.
- Brunekreef, Bert, and Stephen T. Holgate. ”Air pollution and health.” The lancet 360.9341 (2002): 1233-1242.
- Chieh-Jan Mike Liang, Haozhun Jin, Yang Yang, Li Zhang, and Feng Zhao, Crossroads: A Framework for Developing Proximity-based Social Interactions.