About
OpenCollar is an open-source conservation collaboration that provides the hardware schematics, firmware, and software needed to build and deploy GPS-enabled wildlife tracking collars. Launched by Smart Parks in 2019 with an Elephant tracker, the platform has grown to support field-tested collars for rhinos, lions, cheetahs, wisent, wild dogs, feral cats, raccoons, and more—with active development underway for pangolins, baboons, desert lions, giant anteaters, and pygmy hippos. All hardware designs and source code are freely available on GitHub and documented on community forums like Wildlabs, enabling students, researchers, and conservationists worldwide to build and customize collars for their specific environments and animals. Collars can be configured with GPS, GSM, or LoRa communication modules in various combinations depending on terrain, connectivity, and use case. A key innovation roadmap item is Machine Learning on the Edge—bringing on-device AI inference directly to tracking collars for real-time animal behavior detection without cloud dependency. First showcased in the Hackster.io ElephantEdge campaign, this capability is being integrated across the full OpenCollar Edge device lineup. Users can either self-build from open-source repositories or procure ready-to-deploy collars from Smart Parks. OpenCollar is ideal for conservation organizations, wildlife researchers, universities, and technology enthusiasts who want to generate actionable data and help protect biodiversity through affordable, community-developed tools.
Key Features
- Open-Source Hardware & Firmware: All collar hardware schematics and firmware are freely available on GitHub, enabling anyone to build, modify, and deploy tracking collars at minimal cost.
- Multi-Species Collar Support: Field-tested collar designs for elephants, rhinos, lions, cheetahs, wild dogs, raccoons, and many more, with ongoing development for additional endangered species.
- Modular Communication Options: Supports GPS, GSM, and LoRa modules in configurable combinations to suit diverse terrain types and connectivity conditions worldwide.
- Machine Learning on the Edge: On-device AI inference enables real-time animal behavior detection directly on the collar hardware, reducing reliance on continuous cloud connectivity.
- Community-Driven Development: Active collaboration on GitHub and Wildlabs forums connects conservationists, engineers, and researchers to co-develop and continuously improve the platform.
Use Cases
- Tracking elephant herds across protected reserves to monitor migration corridors and trigger anti-poaching alerts.
- Deploying collars on endangered species like rhinos and cheetahs to gather behavioral data for conservation management.
- University research teams building and testing custom tracking collar prototypes using open-source hardware designs.
- Conservation NGOs generating baseline population and movement data for lesser-studied species such as pangolins and pygmy hippos.
- Implementing edge AI on deployed collars to detect unusual behavior patterns in real time without relying on continuous cellular or satellite connectivity.
Pros
- Fully Free and Open Source: All designs and code are openly licensed, dramatically lowering the barrier and cost of deploying wildlife monitoring systems globally.
- Highly Customizable and Modular: Interchangeable hardware modules let users tailor collars to specific animals, habitats, and project requirements without starting from scratch.
- Expanding Species and AI Coverage: Continuously growing roster of supported species combined with edge AI roadmap makes it one of the most forward-looking open conservation platforms.
- Backed by Proven Field Deployments: Smart Parks has tested and refined collars in real conservation environments, providing a solid, reliable foundation for community contributions.
Cons
- Requires Technical Expertise to Self-Build: Assembling collars from open-source repositories demands hardware and firmware knowledge, creating a steep learning curve for non-technical users.
- Edge AI Features Still Maturing: Machine learning on-device capabilities are still being integrated across the full device lineup and are not yet universally available.
- Limited Turnkey Vendor Options: Smart Parks is currently the primary commercial supplier of ready-made OpenCollar products, limiting off-the-shelf purchasing alternatives.
Frequently Asked Questions
What is OpenCollar?
OpenCollar is an open-source conservation collaboration that provides freely available hardware designs, firmware, and software for building customizable wildlife tracking collars. It was initiated by Smart Parks in 2019 to make wildlife monitoring more accessible and affordable.
Which animal species does OpenCollar support?
OpenCollar currently supports elephants, rhinos, lions, cheetahs, wisent, wild dogs, feral cats, raccoons, and more. Active development is expanding coverage to pangolins, baboons, desert lions, giant anteaters, pygmy hippos, rabbits, and additional species.
How can I get OpenCollar tracking collars?
There are two routes: you can build your own collars using the open-source hardware and software on GitHub, or you can procure field-ready collars directly from Smart Parks, which offers a commercial catalog of proven devices.
What communication technologies are supported?
OpenCollar devices support GPS, GSM, and LoRa communication modules. These can be mixed and matched in different configurations depending on the animal species, terrain, and connectivity requirements of your project.
Does OpenCollar incorporate artificial intelligence?
Yes. OpenCollar is actively developing Machine Learning on the Edge, enabling on-device AI inference for real-time animal behavior detection. First demonstrated in the Hackster.io ElephantEdge campaign, this feature is being integrated across all OpenCollar Edge devices.
