Meetup 20190110

Wings and chairs and maps and cables

Hard at work

I decided towards the end of last year that the organising of the meetup was going on in too many disparate places: I advertised it on ZaTech Slack, Facebook, Twitter and we even had a Whatsapp group. I wanted to consolidate all of that. This is the first meetup organised through meetup.com, which is great for introducing the meetup to people in the area.

I reorganised my garage a bit before the meetup, throwing some things away and moving others so that we can easily get to all the tools. By the time the meetup began, things were still pretty chaotic, but much clearer than the previous times.

Steph had built his wing and cut out the tail. We talked about good ways to get the bevels cut on the control surfaces, and I hunted down some gears salvaged from printers etc so that he could build a gearbox. It might be better to first use a stock motor and gearbox to test it all. I might lend him some things.

Chris (a new member) showed up with a bunch of cardboard tubes and sheets, planning on building a chair. We discussed all kinds of ways to get it stable and strong enough. By the end of the evening, he had cut down the tubes and fashioned a seat, well on his way to getting a usable piece of furniture.

Jan had the MaslowCNC motors and encoders all wired up, but the encoders weren’t counting correctly. He disassembled one of the wiring connectors, reassembled it and it started working! After some more debugging, we came to the conclusion that there was a short in the wiring harness. Measuring it directly confirmed that.

Kolijn and JP (new member) brought a LoRaWAN transmitter that was used in Zambia to map signal strength and had a broken antenna. Apparently, having a very flat area densely populated with trees is not good for LoRa range. JP also had a new LoRaWAN dev kit from Microchip. The kit combines a LoRa transceiver with an ARM processor on a single chip at $5 in quantity, so it could be a real game-changer.

JP has a hobby project: TTN Mapper, but it was getting too slow to render the heatmaps. We discussed a lot of ways to slice the data to make it easier to render the heatmaps, including bundling levels of map zooming, caching strategies and using different database structures. I think we made progress?