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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Michael, M.G. Michael, Katina Perakslis, Christine |
| Copyright Year | 2014 |
| Description | Author affiliation: Information Systems & Technology University of Wollongong, Australia (Michael, Katina) || Graduate Programs, Johnson & Wales University, Rhode Island, USA (Perakslis, Christine) || Information Systems & Technology, University of Wollongong, Australia (Michael, M.G.) |
| Abstract | Historically telecommunications companies have measured voice and data traffic for reasons related to service dimensioning and engineering management. Today, personalised devices make it possible to understand not only requirements for the capacity needed in a network environment, but household and individual usage patterns. This has changed the way that companies now market their products and services and sell direct to individual or groups of consumers. Beyond marketing is the intimate knowledge gathered of why people do things, inferred by pattern-of-life data and metadata. This is precise knowledge of customer behaviours, traits, habits and characteristics. Of the most pervasive devices is the smart phone which is carried by most consumers, young and old, everywhere they go. Coupled with additional self-disclosed data in social media, corporations now know a great deal more about people than prior to the mobile Internet revolution. Digital chronicles automatically generated using rich onboard sensors on smartphones gather streams of historical user-based data every single day. The end result is that time-based digital chronicles are now being used to proactively profile individuals and households for more than just telecommunications engineering. The Internet of Things promises even greater connectedness as individual items begin to come alive on a global network each with their respective IP address. Big data will soon be able to reveal patterns and trends that were previously incalculable. Humans in actual fact have become akin to mobile network access nodes, as they move around going about their business, quantified with a variety of measures. We will seek even greater levels of scrutiny in the not-too-distant future heralding in an age of uberveillance. We now know much more about consumers than traditional call holding times and the location of an individual user in a mobile network. Through evidence we know what consumers are thinking, how they are feeling, and even what they will do next with a high degree of accuracy. Embedded surveillance devices will likely replace clunky mobile and wearable handsets and headsets which will introduce an ability to transcend physical boundaries. This paper will define uberveillance and discuss the limits of connectedness when convenience overrides efficiency. What are the social implications to consumers when companies can exploit the intimate knowledge they collect for more than just service availability? |
| Starting Page | 1381 |
| Ending Page | 1386 |
| File Size | 921528 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781479966295 |
| DOI | 10.1109/IC3I.2014.7019829 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-11-27 |
| Publisher Place | India |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Embedded systems Uberveillance Surveillance Companies Data collection Cameras Mobile communication Big data Data analytics Sensors Biomedical monitoring |
| Content Type | Text |
| Resource Type | Article |
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