LifeLog

LifeLog is interested in three major data categories: physical data, transactional data, and context or media data. “Anywhere/anytime” capture of physical data might be provided by hardware worn by the LifeLog user. Visual, aural, and possibly even haptic sensors capture what the user sees, hears, and feels. GPS, digital compass, and inertial sensors capture the user’s orientation and movements. Biomedical sensors capture the user’s physical state. LifeLog also captures the user’s computer-based interactions and transactions throughout the day from email, calendar, instant messaging, web-based transactions, as well as other common computer applications, and stores the data (or, in some cases, pointers to the data) in appropriate formats. Voice transactions can be captured through recording of telephone calls and voice mail, with the called and calling numbers as metadata. FAX and hardcopy written material (such as postal mail) can be scanned. Finally, LifeLog also captures (or at least captures pointers to) the tremendous amounts of context data the user is exposed to every day from diverse media sources, including broadcast television and radio, hardcopy newspapers, magazines, books and other documents, and softcopy electronic books, web sites, and database access.

LifeLog can be used as a stand-alone system to serve as a powerful automated multimedia diary and scrapbook. By using a search engine interface, the user can easily retrieve a specific thread of past transactions, or recall an experience from a few seconds ago or from many years earlier in as much detail as is desired, including imagery, audio, or video replay of the event. In addition to operating in this stand-alone mode, LifeLog can also serve as a subsystem to support a wide variety of other applications, including personal, medical, financial, and other types of assistants, and various teaching and training tools. As increasing numbers of people acquire LifeLogs, collaborative tasks could be facilitated by the interaction of LifeLogs, and properly anonymized access to LifeLog data might support medical research and the early detection of an emerging epidemic. Application of the LifeLog abstraction structure in a synthesizing mode will eventually allow synthetic game characters and humanoid robots to lead more "realistic" lives. However, the initial LifeLog development is tightly focused on the stand-alone system capabilities, and does not include the broader class of assistive, training, and other applications that may ultimately be supported.

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