  Studying human behaviour through lifelogging has seen an increase in
attention from researchers over the past decade. The opportunities that
lifelogging offers are based on the fact that a lifelog, as a "black box" of
our lives, offers rich contextual information, which has been an Achilles heel
of information discovery. While lifelog data has been put to use in various
contexts, its application to indoor environment scenario remains unexplored. In
this proposal, I plan to design a method that enables us to capture and record
indoor lifelog data of a person's life in order to facilitate healthcare
systems, emergency response, item tracking etc. To this end, we aim to build an
Indoor Information Retrieval system that can be queried with natural language
queries over lifelog data. Judicious use of the lifelog data for the indoor
application may enable us to solve very fundamental but non-avoidable problems
of our daily life. Analysis of lifelog data coupled with Information Retrieval
is not only a promising research topic, but the possibility of its indoor
application especially for healthcare, lost-item tracking would be an
innovative research idea to the best of our knowledge.
