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./20170404-0144-cet-state-of-the-art-23-lifelogging-presentation-personal-big-data-1.pdf

• Above is the attached .pdf of the presentation.
• Here is the link to the presentation, https://www.slideshare.net/cgurrin/personal-big-data.

• The title for this presentation is "Lifelogging A New Big Data Challenge".

• Sample workflow of this project.
• I think mine is similar, but I would like to put sensors between the human and log.

• Extreme Lifelogging.
• This is like creating log (blog, vlog, ...) but done automatically.
• The lifelogging term means to capture real - life activities.
• The principle here is to use fitting wearable sensors.
• The result would be a personal awareness search engine that knows anything about you.
• However, this search engine is not intended to replace your organic memory.

• There is a slide that shows about the result of one year lifelogging.

• There is an assumption made here that the data captured from the lifelogging activities are all useful.
• I think this where machine learning could take in.

• This project is really about big data.
• There should be management mechanism somewhere.
• I think that management mechanism could be machine learning.
• At this point manual human editing is not feasible anymore.
• What is semantics?
  • Semantics is a branch of languages that gives meaning.
  • There are 2 main areas of semantics.
    • Logical semantics, the implicit semantics that inferred from human senses.
    • Lexical semantics, the explicit semantics.

• This is what I meant by context agent.
• Context agent answers all possible wh - based questions from values received from sensors.

• Example of application interface.
• I think the panel in the right shows you some usage of computer vision.
• However, I am not sure if computer vision can be that accurate.
• Perhaps, it is manual input by human.

• There is an example application developed within this "lifelogging" project titled My Visual Diary.
• This application shows images capture from the wide angle lens of the video sensor.

• 1 purpose of this "lifelogging" process is to have quantified self - analysis of one's personal life.

• Aside from personal use of traditional logging activities.
• There are other areas as well that could be benefited by having proper "lifelogging" tools. These are for examples.
  • Depression management, Wittgenstein - esque.
  • Healthcare.
  • Lifestyle.

• The other purpose is to enhancing productivity.
• There should be a point in your life about "I know I have read that notion somewhere, somewhen.".
  • This actually happens a lot to me during this project.

• "Lifelogging" could works both ways.
• It could works by logging 1 user.
• It could works by logging people.
  • For example logging used by coffee robot to automatically determine which coffee each possible users would like.

• Example of personal memory search engine.
• There should be context and the agent to determine the relevancy of quantitative data.

• The concern is as usual, privacy.
• In this example third party face will be blurred.