Warning: this article contains Anecdotes and Conjecture. For a related article of containing practical application click here.
My sleep cycle times are measured by an NFC tag next to my bed – this tag has 2 functions, the first is to activate the Webhook which logs the time and automatically inputs this into my spreadsheet. The second is to unlock my phone with smart lock: this may seem trivial but its how to get around the NFC reader only working with an unlocked phone.
Originally the process was, alarm>unlock>swipe>Do button (A IFTTT function)
In total(from alarm deactivation) this took approx 4-5 seconds to wake and log.
The process is now alarm>hold phone to tag
In total (From alarm deactivation) this takes approx 2-3 seconds to wake and log.
Alarm clock apps that need a NFC trigger are also available – but I found mine enraged me and it just wasn’t a good start to the day.
Tracking Calorie Consumption outlines inconsistencies in my input. Whilst accounting for this as a variable its I keenly tracked productivity patterns re: KJ amongst other things.
Calories (as far as metrics go) are easy to track, I have a general distaste for food and subsequently my RDI is fulfilled by a DIY soylent diet (dopamine permitting, I will elaborate on my Soylent experiment in a later post). It’s not for everyone. Frankly, it’s not for most.
My meals themselves are divided into approximately 2150Kj each and whilst I try to keep regular intervals, this is not always the case.
As the soylents measurements can be neatly divided, the point that time, is the only metric to be fulfilled. In addition, my water can be similarly accounted – for except these are measured in .9L bottles.
As a result, I place NFC tags on water bottle/soylent tubs and scan from there. Admittedly, I have had to replace the tags a few times, luckily I’m in a position to find a decent water resistant wet-inlay.
The webhook that the NFC tag calls, automatically inputs the data to a spreadsheet.
Caffeine and Nicotine are (some) of my vices, seems fitting to track these habits. I can get a estimate as each of my cigarettes 12mg. I am basing this on colour indications from years ago. Since we now have plain packaging cigarettes in Australia I can only ‘estimate’ – we are not told the strength of the cigarettes.
We can’t even ask certain questions to the cashier regarding the pricing (because ‘prices are advertising’). No shit.
Curious how Australia can simultaneously nurture a massive concentration of the world’s most deadly animals…and facilitate parabolic nanny-state tactics that prevent us from knowing the tar/nicotine concentrations.
Each cigarette is automatically logged into a spreadsheet by scanning the ferrite-layered tag on my cigarette case.
Caffeine measurement is similar but the metric for the amount of caffeine in each coffee is impossible to average without a spectrometer, subsequently I can only log the ‘amount’ of coffee I have had.
Without predetermined units that are individually divided on things like food and coffee, I imagine this would require some workarounds (multiple tags would do it). This is done with tags on the coffee jars. It can be on the cups themselves, but that is a lot of tags and excessive exposure to such heat may degrade them
Logging bathroom breaks can reveal…interesting patterns. Tracking each visit, I adopted a NFC technique I’ve used previously for alternate reasons. A while ago, I started experimenting with embedding NFC chips into my suits and vest – these had simple functions such as unlocking as it came out of pocket or starting a google search. I had historically sewed industrial tags into my vest and found that one of these sufficed considering heat and moisture during washing. A quick scan on the way in and the spreadsheet is updated.
As a contractor, logging my work hours was vital. I found that a tag at my desk and door assisted with this. A simple on/off logging function that tracks time and day is automatically updated with every webhook sent by the tag.
In retrospect, by my recount I follow this routine with the stoic resolution of a buddhist vulcan. I don’t. My aggregate spreadsheet data looks like swiss cheese.