I now make the distinction between a band being "open" and a band being "open to" some place where people are awake and operating their radios. I link each marker to web info about each place and thus feel much more the world traveler.
Our first thought was to record screenshots from the application we already have running. See Spark Signals
How to record a screen timelapse using QuickTime + iMovie. Etcetera. post ![]()
We wanted to make a time-lapse movie and looked at this work as a way to test ideas.
The mere thought that TLS credentials were require to use the api moved us away from this as a way to satisfy our own curiosities. Maybe bypass the browser in our recording path?
.
Although we were attracted to the idea of having a animated gif as output to post on social media, we now think the shortest and most interesting path is to produce logs of markers appearing and disappearing. We can then "preform" these scripts over live leaflet maps to be explored by the viewer as history replays.
Imagine scripts collected and written to a JSONL file where subsequent lines represents changes by band at a new time. We could instrument our web app or write a server-side version of the data handling part to transform our years of data.
line = {time, [change]} change = {band, [new], [old]} new = "call square" old = "call"
We'll start with something even simpler.
[time | new | old]
With each payload we record the arrival time, list new calls for one band, if any, and then list any old calls on any band due to be removed for inactivity.
1702330799574 N7UJJ KT8O 1702330801034 VA5KEN DO70 KO4VVQ FM16 KD4EBL
We identify records by the time of first event. We'll develop scripts for indexing and playback viewing over interactive leaflet maps. github ![]()
pages/watch-bands-open-and-close
http://ft8.ward.asia.wiki.org/assets/pages/watch-bands-open-and-close/catalog.html
.