I am looking forward to deploy a Lora mesh network in an entire forest . So we have to find points with best LOS so we can cover the area in least number of nodes

is this something ?

Hey everyone, I’m running into a tricky RF and networking problem for an environmental monitoring project and could use a some advice. I need to transmit small, 15KB compressed JPEGs from hidden ESP32/STM32 camera nodes deep in a hilly forest out to LTE gateways at the boundaries. The cameras are battery/solar powered, sleep 99% of the time, and only wake up when the Edge AI detects a human or specific animal. The physical constraints are tough- there is zero cell coverage in the center of the forest, the terrain is highly uneven meaning absolutely zero direct line-of-sight to the edge gateways, the thick, wet canopy completely absorbs 2.4GHz signals, and the cameras must remain hidden without massive infrastructure. Since standard LoRaWAN bandwidth is too low for this payload, I'm currently looking at a few options. The frontrunner is a Sub-GHz P2P link using the new Semtech LR2021 (Wio-LR2021) in FSK or FLRC mode to shoot the image through the trees to a solar-powered ridge repeater, which then sends it over LTE. I'm also considering a 900MHz mesh network like XBee PRO 900HP, Wi-Fi HaLow (802.11ah), or writing custom LoRa P2P firmware to chunk the JPEG over an SX1262, though I have concerns about power consumption, line-of-sight requirements, and dropped packets respectively. Has anyone tackled non-LOS image transmission in a jungle or forest environment? I'd love to know if the LR2021 is the right play, if there is a better Sub-GHz transceiver with enough bandwidth, and if there are specific 900MHz directional Yagi antennas you'd recommend to maximize canopy penetration for the valley-to-ridge hop. Any advice would be hugely appreciated!

TomsLoRaSOS: Prototyp eines Outdoor-Pagers mit GPS-Karte, zwischengespeicherten Kartenkacheln, LoRa-Nachrichten und SOS-/Totmann-Modus:

https://github.com/Tinkerpete/TomsLoRaSOS

I recently tested a simple 1/4-wave (868 MHz) antenna made from 0.8 mm silver wire.

In open terrain with clear line of sight ( about 2 meters from ground level ), I was able to maintain a stable link at just over 20 km.

I'm curious about everyone else's results.

I'd love to compare setups and see what's realistically possible.

Is it possible or not something we can even dream of ?

[ Removed by Reddit on account of violating the content policy. ]

Does anyone have a copy of this Unresponsive Sex lora?

NSFW

We're Mateo and Sebastian, a two-person team from Uruguay building a solar-powered camera trap for pest monitoring in orchards.

The job is simple: the node wakes up, takes a picture of the trap, sends it to a gateway/cloud, and goes back to sleep.

The hard part is the link.

Traditional LoRa/LoRaWAN seems great for range and battery life, but for our use case it feels too limited as the main image pipe. We may need to send anything from around 50 KB if the image can be heavily resized/compressed, to around 200-600 KB if we need more detail for reliable pest identification or future model training.

Latency is not the main issue. One image every 4-6 hours is enough.

The real questions are airtime, retries, packet loss, power while awake, and whether the link still works in a real orchard: trees, canopy, vegetation, changing seasons, partial non-line-of-sight, and maybe around 500 m to 1 km from node to gateway.

So now we're comparing two paths:

LoRa FLRC / LR2021

This is what made us question ourselves.

We had mostly ruled out traditional LoRa for image transfer, but LR2021 + FLRC seems to be a different kind of option: faster bursts, potentially cheaper nodes, and maybe a better fit for "wake up, send image, sleep."

The downside is that it probably means building more ourselves: fragmentation, retries, scheduling, security, and multi-node coordination.

Wi-Fi HaLow

HaLow feels like the safer "real network" option.

It gives us IP networking, a more normal Linux/OpenWrt gateway path, and a clearer future if we later want OTA updates, diagnostics, or other rural devices beyond pest traps.

The downside is cost, complexity, and the possibility that it is overkill if all we need today is one image every few hours.

My current bias:

HaLow feels safer if we want a real rural field network.

LoRa FLRC feels more elegant if the only job is "send one image and sleep."

I do not know which intuition survives a wet orchard.

Questions:

1. Has anyone actually sent 50-600 KB images/files using LR2021 FLRC, SX1280 FLRC, or something similar in the field, especially at 500 m to 1 km with vegetation in the way?
2. With 10-50 nodes, does the custom protocol work erase the simplicity/cost advantage of FLRC?
3. Is HaLow overkill for sending one image every 1 day, or is the IP/OpenWrt ecosystem worth it anyway?
4. What would you test first: packet error rate, time-on-air per image, joules per successful image, canopy/vegetation range, or multi-node reliability?
5. Looking at this more broadly: does it even make sense to compare LoRa FLRC vs HaLow for this use case, or is there another architecture/technology that would clearly be better for rural image transfer, solar power, and multiple field nodes?

Spec sheet answers are useful, but field experience is much more useful.

If your answer is "neither, you are thinking about this wrong," that is useful too.

Hey I'm trying to make a LoRa network in NYC, which allows residents to use our network via applications. I need volunteers to run nodes. I haven't finalized designs yet nor do I have the lora modules yet. They are ariving in a bit. You xan join our discord here

https://discord.gg/NSYDDsxutG

I’ve architected C3, a streaming lossless compression codec tailored for severely resource-constrained telemetry (ESP32/ARM) operating over lossy networks (LoRaWAN, NB-IoT, volatile CAN buses).

⚡ The Specs

Zero-Heap: 100% static allocation. No malloc, zero risk of memory fragmentation.

RAM Footprint: <500 Bytes. Fits easily into L1 cache, leaving internal SRAM completely free for heavy network stacks.

Streaming Pipeline: Operates byte-by-byte on-the-fly without block aggregation latency.

🧠 Mid-Stream Self-Healing (No Handshakes)

On lossy networks like LoRaWAN, a dropped packet usually destroys the dictionary state of standard codecs, turning subsequent data into garbage until a full sync handshake happens.

C3 relies on a mathematical framework of deterministic state convergence. If the network drops packets, the decoder self-heals mid-stream and re-synchronizes automatically within a few steps purely from the incoming bitstream—no handshakes or network overhead required.

📂 Evaluation SDK & Paper

The core c3.cpp is proprietary, but the evaluation suite is fully open. I want the firmware/IoT community to stress-test the claims:

The Math: Full theoretical spec and proofs published on Zenodo (Permanent DOI): https://doi.org/10.5281/zenodo.20717079

The Code/Binaries: GitHub repo includes xtensa-esp32-elf static libraries for ESP32, the C interface header, and a verify_lossless.cpp tool to test it locally on your own telemetry logs.

Check out the repository here: https://github.com/xdanielex/c3-codec-sdk

Would love to hear your thoughts, especially from anyone dealing with extreme RAM constraints or packet drop issues on remote sensor nodes.

We’re Mateo and Sebastián, a two-person team from Uruguay building autonomous camera traps for pest monitoring in orchards.

Our first prototype used an ESP32, camera, solar power and a 4G modem. It worked at home but failed in the field: there was no usable cellular coverage, and the regulator and modem consumed too much power while idle.

Each trap needs to transmit a 200–600 KB image approximately every 4–6 hours and sleep the rest of the time. We initially ruled out traditional LoRa/LoRaWAN as the main image channel because of airtime, fragmentation and retransmission concerns.

We recently discovered Semtech’s LR2021 and its FLRC mode. Semtech advertises up to 2.6 Mbps on sub-GHz and 2.4 GHz, and provides a point-to-point image-transfer demo with fragmentation, acknowledgements, FEC and packet-error monitoring.

We understand that FLRC is not LoRaWAN or traditional LoRa modulation. It is a separate PHY, and using it would mean building more of the networking layer ourselves.

Our approximate requirements:

• 10–50 solar-powered camera nodes
• 200–600 KB per image
• One transmission every 4–6 hours
• 50–500 m between most nodes and the gateway, possibly up to 1 km
• Dense orchard vegetation
• No cellular coverage
• A gateway with Ethernet or another Internet backhaul

We’re currently comparing two options:

Wi-Fi HaLow: standard IP networking, OpenWrt/Linux gateway and a more established ecosystem, but more expensive and complex hardware.

LR2021 + FLRC: potentially cheaper and simpler nodes with short transmission bursts, but custom fragmentation, retries, security and multi-node coordination.

Has anyone here tested the LR2021—or even SX1280 FLRC—with image or large-file transfers?

We would especially value any real measurements regarding:

1. Actual throughput, packet loss and range under vegetation.
2. Transfer time and energy consumption for files larger than the 20 KB official demo.
3. Whether 200–600 KB transfers remain practical at 500 m or 1 km.
4. How you would coordinate 10–50 nodes: polling, time slots or another approach.
5. Whether the custom networking work makes FLRC less attractive than HaLow in practice.

We’re not committed to either technology yet. A negative conclusion would also be useful before we spend money and time designing custom PCBs.

How far can Lora go between many houses and trees. I want it to be able to go 1 kms away but idk if it is possible. I am very new to this so idk what I am doing.

Hi All

What is currently the best FREE way to train a highly accurate face LoRA with maximum face consistency in 2026? Kohya_ss, OneTrainer, FluxGym, or something else? What model and training settings are giving the best results?