How 'far' are you quantified?

Good day!

As part of analyst community I have been quantifying various aspects of my life for some time (my last hobbie is the app timing apps (e.g. atimelogger) where you define a set of activities and run a timers against them). Being new to the community I would like to shoot my first question - what is ‘Self’ we try to quantify?

Is it just our body and psy-physiological processes? Or may be Quantified Self is the one who is quantifying his impact on the environment to some degree or environment on him?

What is more important where QSelf ends? E.g. should QS be quantifying the use/reuse of various axillary tools and mechanisms in daily life: whether it will be how much of recyclables we use or whether we are minimizing our footprint for the environment?

Would be glad to hear the feedback from community and my apologies for my initial ignorance. :angel:

Cheers,
Svamin

I don’t think QS is limited to health or fitness data, and would agree with Ian Forrester:

Ejain, agree with you totally. It is just not so much talking happening how increased awareness helps us to reduce carbon emissions. I would assume ‘FitBit-alike’ is not the only tool you use. Could you give an example of how the external environment quanitification helps you to get a change in behaviour.

For instance, being an financial professional I wish to have a more detailed cost breakdown used by various car systems, ideally at TCO (total cost of ownership) level (and not just fuel)… and basically the cost per trip. Equipped this info in real-time, I could learn HOW to drive in cost effective way (economic use of fuel and other power consuming devices).

I’m collecting data with a Netatmo, to help me understand how environmental variables such as temperature and air quality affect my sleep.

Recently started using Automatic, which tells me how much fuel I used on each trip, mpg, and how much I paid for that fuel etc. As with sleep, there are a lot of confounding variables, so the insights haven’t been very forthcoming yet :slight_smile:

Interesting Ejain! It seams like this topic is not so in favour than ‘Wearable body temperature tool?’ with 14.5K of views… Thanks - I found at least a single user of such technologies in your face.

Indeed with home measurement you have so many variables (controllable, e.g. windows shut and uncontrollable like wind), I found it difficult to identify the major factors and tie them to any of my behaviour traits. The situation with cars is more encouraging.

I was looking at the series of such App-OBD devices for a long time, but three questions stopped me from getting into it - hence would be great to get your first-hand opinion:

  1. (assumption 1: real-time feedback is the more effective than post-fact in changing the behaviour). Does Automatic provides the data in real time?
  2. (assumption 2: more granular data gives you more insight on where exactly you should tweak your behaviour). Does it provide just the total cost of the trip or some more granular information/breakdown?
  3. (assumption 3: new quantified technology is expected to be implemented in ecological way with minimal negative impact on other cognitive activities). How easy it is to use Automatic (as APP) together with Navigation, Inphone hands-free calls and normal driving mode (more distractions?)? In the absence of good mobile connection/etc.?

I was looking into these two (http://dash.by/ http://zubie.co/) as well, but would rather hear for the existing QS opinions before considering…

  1. The Automatic plug beeps when you accelerate or break too hard, or go above 70mph (this can be disabled).
  2. Automatic records the exact time and location of these three events, but other data like fuel consumption and speed are reported as per trip averages or totals only.
  3. Automatic won’t record unless your phone is nearby (BLE), but doesn’t require a network connection throughout the trip. The app runs in the background, and does not show any stats while driving.

Looks like Dash now has an API as well, but the the level of detail in the data is similar.