Antoineede they are a mesh style of camera, one links to the other and then send pictures back to the home unit where you either send them via cellular or you check the sd card. The cover Lora and cuddielink cameras do this but they play hell on battieries.

I had a cuddelink system and got rid of it , the home unit was to hook up to a pc and then from there you could easily wept a scrip to send to txt message or email etc but they scrapped that idea 

I can share some practical perspective on the LoRa camera trap architecture for remote high-relief terrain with poor connectivity.

The core concept — cameras not connected to network, base station at a connectivity point relaying via LoRa — is sound and well-proven. A few things to consider for your specific conditions:

On LoRa range in strong relief — this is where the technology shines and where it disappoints unpredictably. In open terrain, 5-15km gateway range is achievable. In steep valleys or dense canopy, a node in a gully might only reach 200-300m. The solution is careful gateway placement on ridgelines or elevated points, and in complex terrain, one or two dedicated relay nodes at intermediate heights. Test before committing to a layout.

On reliability in heavy rain — LoRa itself is very robust in rain (the signal is largely unaffected by precipitation). The vulnerability is the hardware: connectors, antenna connections, and enclosures. For the gateway, use N-type or SMA connectors with proper weatherproofing, and position the enclosure under a simple rain shield. Cheap LoRa modules with U.FL connectors are more vulnerable — consider a fiberglass enclosed gateway with a proper outdoor antenna.

On the commercial options you mentioned — the Covert LoRa uses a proprietary LoRa implementation that requires their own base station, not standard LoRaWAN. This limits flexibility significantly. If you want to integrate with open platforms like The Things Network or ChirpStack and use standard sensors alongside the cameras, a system built on standard LoRaWAN is more future-proof even if it requires more initial setup.

Happy to discuss specific gateway options or architecture for your terrain.

Antoine, this is close to the exact architecture I ended up building for, so let me answer the base-station question directly. I am Steve, a software engineer in Ohio; over the past year I built MeshCam, an open network of solar LoRa trail cameras, and the whole design assumes what you described: cameras that are not individually connected, relaying to one gateway that sits on the single point with connectivity.

The detailed June 2026 reply above is right on terrain and weather, and it matches what I see. LoRa itself shrugs off rain; the failures are hardware (connectors, enclosures, U.FL pigtails), and range in strong relief is unpredictable, so you place the gateway high and drop one or two relay nodes at intermediate heights rather than trusting one long link. MeshCam is built around that: solar relay nodes extend the mesh hop by hop, and there is a handheld range probe so you can walk a site and get GPS-stamped link checks before you commit a layout.

One deliberate difference from the LoRaWAN suggestion: MeshCam runs Reticulum over plain LoRa, not LoRaWAN. LoRaWAN is excellent for small uplink telemetry, but its duty-cycle and uplink-first model fight you the moment you want to pull a full-resolution image back down on demand. Reticulum gives a reliable arbitrary-size transfer primitive and end-to-end encryption, which is what moving images actually needs. To Rob and Kyler's earlier and fair point: you cannot stream photos over LoRa, so MeshCam does not. It sends a few-KB preview in seconds, keeps the full-res still on SD, and pulls it on request, store-and-forward, so an outage delays a photo but never drops one.

There is a live demo that does exactly that pull across a simulated mesh: demo.getmeshcam.com. Open firmware and API at github.com/meshcam, self-hostable gallery. If you did deploy something at Dzanga-Ndoki in the end, I would be interested in whether the base-station-at- the-connection-point model actually held up in that terrain, and I am glad to go deeper on the Reticulum side if it is useful.

Steve

I would probably ask: “If your code basically does not allow you to take harmful actions, what should you do if you are provided with irrefutable proof that your existence, supported by components built and developed with “rare minerals” extracted from conflict areas is actually harming and destroying indigenous communities and biodiversity?”

Hello,
This is an incredible initiative, and exactly the kind of practical AI application that can make a huge impact in the conservation space!

As an AI Solutions Architect based in the US with 20 years of tech experience, I have built several RAG (Retrieval-Augmented Generation) and Agentic solutions. I would love to contribute directly to the implementation or consulting side of this project if required.

Whether you need help with structuring the retrieval pipelines for the forum data, designing the agentic workflows, or handling the backend and cloud deployment, I would be happy to jump in and support the build.

Please let me know how I can best get involved, or if you'd like to chat about the technical architecture and how to bring this to life!

Hey, interesting discussion! I'm curious—how do you think AI can better collaborate with local communities in conservation? Also, what role should ethics play when designing these AI agents? Would love to hear more thoughts! fnaf 3 game

Absolutely love the idea of a mesh camera trap network! This could revolutionize wildlife monitoring, allowing researchers to gather data in real-time. Imagine the insights we could gain about animal behavior and conservation efforts! level devil

Hi all, Steve here, a software engineer in Ohio. I have spent the past year building an open-source network of solar LoRa mesh trail cameras to monitor my family's land in northeast Ohio, which is how I fell down the conservation-tech rabbit hole and eventually found my way here. Long-time lurker, especially in the Camera Traps group. Glad to finally be joining in, and happy to talk LoRa mesh, low-power ESP32 camera nodes, or on-device detection with anyone chasing similar problems.

Hi all,

My name is David, based in Zurich, Switzerland. I run Techno-Merce, where we build satellite detection of illegal mining and land-cover change: radar fused with optical images, so activity shows up under all conditions. Validated so far against illegal gold mining sites in Ghana and Liberia, and we're working with government agencies across the continent of Africa.

I'm here to connect with professionals in the field and understand how our work could be useful to protected-area teams in the space of mapping, terrain classification, land degradation, and protection against encroachment.

Open to collaborations and pilot projects.

This is really impressive Avi! Would you mind sharing what kind of hardware the local ingestion + detection is running on? 

It's a fun experiment to think if this could be expanded to any live stream happening on any platform (Instagram, TikTok)

Hi Maggie, 

Us researchers at the Offal Wildlife Watching project are investigating scavenger behavior at hunter-provided gut piles. We're using Zooniverse to classify wildlife behavior. I suspect there are many other camera trap projects on Zooniverse asking behavior questions too. Check us out here: https://www.zooniverse.org/projects/embeller/offal-wildlife-watching

Great idea!. I am interested in joining. 

Sounds great Matt!

Hello everyone,

Great idea! I would also join and happily-actively contribute to a HD group on technology. 

I am working for Callisto - Wildlife and Nature Conservation Society, an NGO, in Greece as part of its Human Dimensions group, and we are currently researching human-carnivore-related emerging technologies in the context of pastoralism-livestock.

So please, start this new group :)

Warm regards,

Dimitris

Hi @DaveGaynor and team. I am really keen to pursue this with some practical testing in Kenyan conservancies. What is the status of this effort, and could we meet to discuss how to take it forward as part of the Global Conservation Tech and Drone Forum in Nairobi, 2-6 March. I am chair of the Society for Conservation Biology Drone and Data Working Group and would like to discuss this at our inaugural meeting on 20th January.  https://wildlabs.net/discussion/scb-drones-and-data-working-group-society-conservation-biology 

Hi team, Can you please provide an update on where this effort sits now? The original post from January 2024 described three trials of airborne synthetic aperture radar for detecting snares and gin traps with foliage-penetrating radar scanning at 120 m AGL and generating geolocated alerts back into EarthRanger with identity and confidence metrics.

I want to add this as one of our competitions at the Global Conservation Tech & Drone Forum www.GCTDF.org in Kenya in early March, and include it in the new SCB Drones and Data WG as a discussion: https://wildlabs.net/discussion/scb-drones-and-data-working-group-society-conservation-biology 
 

This would build on the recent launch of a hands-on Tech Innovation Challenge around of the ADS-B proximity alert ,  as a safety layer in real conservation field operations where pilots are often multitasking. Please let me know the current status, data availability, key contacts, and what next steps might look like if this is to be integrated into the Forum and the Working Group agenda.

Thanks.

[email protected] 

Airborne synthetic aperture radar for detection of snares sounds really effective! I would love to learn more about this. Dogs are also amazing a detecting snares but of course can't cover the same distance and constant survellience. Is it possible to share the benefits and barriers of this work after the 3 trials?