It’s finally time to announce the winners of The Boring Fund 2024! 

From 16 September to 9 October, we received a whopping 227 applications for the first-ever round of The Boring Fund, run in partnership with Arm. The WILDLABS team reviewed the applications and evaluated them based on three criteria: unique fit with The Boring Fund, relevance to the conservation technology sector and community, and application quality and perceived feasibility. 

There were so many high-quality applications for projects that are strengthening the foundations of the sector. The overwhelmingly positive response to this funding opportunity highlights the critical need to support projects that may not be the most glamorous for donors, but are essential for building a sustainable and effective ecosystem of work. 

Today, we are so pleased to officially announce the winners of The Boring Fund 2024! 

We'll be publishing discussion threads for each project over the next few days, which will give WILDLABS members the opportunity to chat with each team about their work. 

Improve MoveApps Usability (@annescharf)

About MoveApps: MoveApps allows users to design and share Workflows composed of analysis modules (Apps) that access and analyse tracking data. On MoveApps, code developers can share open source analysis code with data owners and domain experts interactively. Users browse Apps, build Workflows, customise parameters, execute analyses and access results through an intuitive web-based interface.

The project: Improve core aspects of MoveApps, including the findability of Apps, public Workflows, documentation of features, and instructions to report errors to App developers. 

Why it’s important to fund: These updates will make MoveApps more easily accessible, especially to the broader conservation community that will benefit from its use. 

Modernising the Xeno-Canto Code Base (@rplanque, @WP, Ruud Altenburg)

About Xeno-canto: Xeno-canto started in 2005 and is now a global, successful, open and FAIR, bioacoustics citizen science project where sounds of nature are shared.

The project: Address the technical debt of Xeno-canto, including a deep-dive in the code to root out possible vulnerabilities, and to retroactively fix some existing code.

Why it’s important to fund: Managing technical debt will help Xeno-canto stay its course by reducing the possibility of unforeseen disruptive and costly issues with legacy code.

Workshop on Artificial Intelligence for Ecological Monitoring in Latin America (@ethanwhite  and @benweinstein)

The project: Conduct an AI for ecological monitoring workshop in the Northern Andes that covers machine learning development for camera traps, audio recorders, and airborne data collection. It will involve active instruction by in-country mentors and focus on serving underrepresented groups in Northern Latin America.

Why it’s important to fund: AI promises to reduce the time required to convert audio and imagery into actionable information for biodiversity projects, but there are still significant computational and technical obstacles to unlocking the power of AI for global conservation monitoring. Current models, documentation, and data are highly biased towards US and European sources, limiting their application to high biodiversity tropical ecosystems and perpetuating global inequality. The goal of this project is for participants to act as catalysts for the growth of AI development in their own communities.

Safe and Sound, Exploring a Standard to Exchange Monitoring Acoustic Data (@JuliaWiel , Sanne Govaert, Peter Desmet, @bencretois)

The project: Standardize the exchange of passive acoustic monitoring (PAM) data via workshops that assess if and how Camtrap DP can be applied to PAM and how its development process can be used in the eco-acoustic community. 

Why it’s important to fund: PAM is rapidly growing, but a core bottleneck is the lack of accepted standard for the exchange of PAM data, thereby limited data exchange, large-scale studies, and publication of open and FAIR data to platforms such as the GBIF. 

Sentinel Documentation and Tutorials (Brandon Asheim, @pcbermant, @Henrikcox, @Deadalos)

About Sentinel: The Sentinel is a device that plugs into and upgrades trail cameras with AI image recognition capabilities, enabling near real-time data on invasive species and endangered wildlife. 

The project: Create high-quality, multilingual, clear documentation and online video tutorials that walk users through every step of Sentinel deployment—from unboxing and installation to troubleshooting and data review. They will provide supplementary written guides and diagrams designed to be downloaded and used offline, ensuring that users in the field can refer to the quick and easy materials regardless of internet connectivity. The resources will also include setup protocols tailored to different field conditions (e.g. density of tree cover, reliability of power supply, connectivity).  

Why it’s important to fund: These materials provide critical user support, which is foundational to ensuring effective adoption, long-term success, and scalability in conservation technology. By making Sentinel more user-friendly, they enable broader correct use of the technology, helping conservationists across the globe effectively monitor and protect biodiversity. This project benefits not only the current Sentinel users in ten countries and counting but future users of the technology. Furthermore, by offering these resources as open access, we create a model for other tech providers and conservation organizations to replicate.