Over the past year, I’ve found myself returning again and again to one big question: How can we make conservation tech work where the wild really begins , where the signal drops, the power is limited, and every gram of hardware matters?

That curiosity led me to edge AI and edge computing technologies that bring intelligence closer to the source. Instead of sending data to the cloud and waiting for insights, what if we could process it right there, in real time, on-device? Whether it’s a smart camera trap deep in a rainforest, an underwater drone scanning coral reefs, or a weather station powered by solar panels, edge solutions can make conservation tech faster, smarter, and more resilient.

But as I dug deeper, I realized something: the people working at this intersection :technologists, ecologists, engineers, and field researchers are scattered. Many of us are solving similar problems in isolation: How do we optimize models for low-power devices? How do we manage data transmission in real-time from the field? How do we balance autonomy and connectivity in places with little or no internet?

That’s when I thought: What if we had a space on WILDLABS to bring all of us together?

What I’m Proposing

I’m currently preparing to apply for the 2025–2026 WILDLABS Group Leader Programme, and I’d like to propose a new community group focused on Edge AI and Edge Computing in Conservation.

Before I submit my application, I’d love to gauge the community’s interest. Would you find value in a group like this? Would you join?

Who This Group Is For

This group would welcome anyone working at the intersection of conservation and edge tech, including:

• Conservationists deploying camera traps, drones, audio sensors, or underwater monitoring systems
• Engineers building embedded systems that run AI models on-device
• Researchers exploring TinyML and lightweight neural networks for field use
• Practitioners solving the real-world challenge of transmitting data from the field in near real-time using low-bandwidth, intermittent, or mesh-based networks
• Anyone curious about how to process and transmit environmental data closer to the source

Whether you're trying to get models to run on a microcontroller or figure out how to relay real-time data from a rainforest to a base station, this group is for you.

What This Group Could Offer

Here’s what I imagine we could build together:

• A space to share field-tested tools, datasets, models, and hardware setups
• Knowledge exchange on optimizing ML models for energy, latency, and memory constraints
• Discussions about transmission protocols from LoRa to satellite relays for real-time data delivery from remote sites
• A library of open-source code, deployment templates, and troubleshooting guides
• Workshops on model quantization, device selection, and transmission strategies
• A bridge between conservation goals and edge computing capabilities
• Case studies from successful (and failed!) deployments to accelerate learning

Why Host This on WILDLABS?

You can talk edge tech on Slack, GitHub, or Reddit. But WILDLABS is where conservation and technology intersect with intention. The conversations here are grounded in biodiversity, real-world challenges, and a shared desire to make tech serve nature not the other way around.

That’s why I believe this group belongs here: because we’re not just talking about processors and packets we’re talking about turtles, trees, migration patterns, and survival.

Interested? Let’s Build This Together

If this idea resonates with you, I’d love to hear from you. Please leave a comment or react to this post your feedback will help shape the group’s direction and strengthen my application.

I’m also looking for a potential co-lead, so if you’re already working in this space or would like to help shape the group from day one, feel free to reach out.

Thanks so much for reading and I hope we can bring this group to life together. :) 

Youssef BAYOULI