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A survey on life logging data capturing

Zhou, Lijuan Marissa and Gurrin, Cathal (2012) A survey on life logging data capturing. In: SenseCam Symposium 2012, 3-4 Apr 2012, Oxford, UK.

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PDF (An oral presentation at SenseCam 2012 about Survey on Diverse Lifelog Devices and People's Attitude on LifeLogging Devices) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
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With the recent availability of inexpensive wearable sensing technologies, the emergence and of both off-line and on-line digital-storage capacity and an acceptance of personal data gathering and online social sharing (timeline), life logging has become a mainstream research topic and is being embraced by early adaptors. For example, currently we have the ability to gather and store large volumes of personal data (location, photos, motion, orientation, etc.) in a very cheap manner, using an inexpensive smartphone. However, with many available lifelogging tools, the question of which ones to use has not been seriously addressed in literature. In this work, we report on a survey of various approaches to capturing lifelog data, which includes the SenseCam/Vicon Revue, wearable smartphones, wearable video cameras, location loggers using GPS, bluetooth device loggers, human body biological state monitors (temperature/heart rate etc.) and so on. We compare these devices and analyze the advantages and disadvantages of different capture methods, including the consistency and integrity of capture, the ‘life coverage’ of the captured data, as well as people’s attitude and feeling to these data capture devices, which we do through user studies and surveys. To complete this work, we provide our opinion of the most suitable model of data capture for personal life logging in a variety of domains of use.

Item Type:Conference or Workshop Item (Speech)
Event Type:Conference
Uncontrolled Keywords:personal data capture
Subjects:Computer Science > Lifelog
Social Sciences > Social psychology
DCU Faculties and Centres:Research Initiatives and Centres > CLARITY: The Centre for Sensor Web Technologies
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:17533
Deposited On:02 Oct 2012 14:57 by Ms Lijuan Marissa Zhou. Last Modified 13 Mar 2014 11:08

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