Free LoRaWAN Books | Hacker News Reader

Free LoRaWAN Books

univ-smb.fr

20 pointsteleforce4 comments

I use a handful of YoLink devices which use LoRa for their connectivity and I have to say it does seem reliable, one single hub covers my entire house whereas 3 Eero Pro 6E mesh APs still don't have that "ease" of coverage (of course, they're capable of a lot more bandwidth) but it seems like LoRa seems like the perfect option for IoT stuff, at minimum. Don't see many things using it though.

The big problem with LoRa today is that in some places, the typical frequencies you can use for LoRa (915MHz in the US) are saturated with traffic. Also LoRa literally is Long Range, and those IoT packets might be heading out >1 mile from your house easily.

It will work when n==1, but not when n==1000 in a square mile, say. Given that, I would certainly be trimming back on the power so it doesn't transmit more than 500 feet out of your house. I've had a heltec Meshtastic receiver broadcast about 2 miles line of sight easily.

And then there's the whole thing about encryption, since your packets can travel miles, and your devices can receive packets from miles away...

As long as you are using the LoRaWAN protocol (not just LoRa modulation), encryption is not optional. It's built into the link layer of LoRaWAN, and a device cannot join a network without a unique key that's shared out of band.

Also, the range is entirely the point of using LoRaWAN for some of us. All other IoT protocols have an abysmally short range, making them impractical for anything other than single building applications. Maybe most don't need a mile of range, but the fact that it can reach across a couple of acres enables a lot of applications.

Just for those unfamiliar with LORAWAN, LORA WAN is a combination of AI's "low rank adaptation" (LORA) approach with phsysionerual networks where by the WAN network grid is mirrored by an identically structured neural network. By performing a LORA on the neural network model of the physical network the network flow and efficiency can abstractly be "fine tuned" to a particularly observed use case, then deployed physically as node executor policy. Using it generally entails (1) system-wide packet-dump A LA NSA to build a training set (not saying whether or not the NSA does this sort of thing) then (2) fine tuning against the LORAWAN model and finally (3) deployment of the AI engine for each note to manage packet forwarding ,routing, and queueing policies.

Reply on news.ycombinator.com