Human Mobility Computing and Privacy: Fad or Reality?


== Abstract ==

The advent of mobile computing and sensing technologies, in conjunction with omni-present and high-speed mobile networks, allow nowadays the capture of human mobility data at an extremely high fidelity. Modern mobile computing services not only have the capacity to store spatio-temporal mobile data, these nowadays also have the capability to process incoming data in near-real time. As a result, we have a better chance to develop effective strategies and build intelligent systems that play critical roles in areas like public health, traffic engineering, urban planning and economic forecasting. On the other hand, detailed movement data often poses a threat to the privacy and security of users and companies, given that mobile devices are associated with real human custodians. One fundamental question is whether human mobility computing and privacy can co-exist under the same roof, given different cultural, religious, legal, technological and socio-economic backgrounds of societies. This panel will explore how the academia and industry are tackling human mobility computing and privacy challenges at a global scale. It will also identify and debate the key challenges and opportunities, in terms of applications, queries, architectures, to which the mobile data management community should contribute. © 2015 IEEE. 2 42 43 <p>Sponsors: Aalborg University et al. IEEE Computer Society IEEE Technical Committee on Data Engineering The National Science Foundation University of Pittsburgh Conference code: 118117


== Original document ==

The different versions of the original document can be found in:

* [http://gnosis.library.ucy.ac.cy/handle/7/54369 http://gnosis.library.ucy.ac.cy/handle/7/54369]