Advancements in on-board technologies and AI integration hold great potential to further enhance the existing drone-based crocodilian monitoring method. Improvements in drone hardware, such as hybrid models with extended flight times and enhanced camera resolutions, allow for broader habitat coverage and the capture of more detailed imagery in complex environments. Integrating artificial intelligence (AI) represents a significant opportunity to streamline image analysis by automating crocodile detection and size estimation using allometric models. These AI-driven enhancements could provide near real-time data processing, reducing reliance on time consuming manual analysis.

This improvements are currently under development with my collaborators

This building block on capacity building on local stakeholders including Indigenous including Peoples and Local Communities (IPLCs) to operate drones, enabling them to take active roles in conservation. 

Ease of Use of the method devellopted:

1. Minimal Technical Skills Required:
   Users only need basic training in drone operation and measurement extraction from high-resolution images. The process is straightforward:
   • Fly the drone following the standardized flight protocol.
   • Marke crocodilians on overhead images.
   • Measure the visible head length using accessible image analysis tools (e.g., ImageJ, QGIS).
   • Apply the corresponding allometric equation or lookup from pre-prepared tables (abaques) for total length estimation.
2. Readily Adaptable:
   The framework uses easy-to-read tables (abaques), making it accessible to both specilialists and non-specialists for operators can quickly apply the method without requiring advanced scientific expertise.
3. Accessible Equipment:
   The approach relies on consumer-grade drones and widely available software, ensuring affordability and reducing barriers to adoption.

Why It’s Effective:

The framework’s simplicity, scalability, and reliability make it ideal for diverse contexts, from remote wetlands to urban-adjacent habitats. It empowers a broad range of users to generate scientifically robust data.

The allometric framework is a non-invasive tool designed to estimate the total body length of crocodilians based on the measurement of their head length, captured through high-resolution drone imagery. By leveraging established species-specific head-to-body length ratios, this method eliminates the need for physical capture or handling, reducing risks for both researchers and wildlife. Validated for 17 of the 27 crocodilian species, the framework allow to provides reliable demographic data essential for population monitoring and conservation management.

The framework uses easy-to-read tables (abaques), making it accessible to non-specialists, operators can quickly apply the method without requiring advanced scientific expertise.

Understanding the demographic structure is vital for wildlife research and conservation. For crocodylians, accurately estimating total length and demographic class usually necessitates close observation or capture, often of partially immersed individuals, leading to potential imprecision and risk. Drone technology offers a bias-free, safer alternative for classification. This study evaluated the effectiveness of drone photos combined with head length allometric relationships to estimate total length, and propose a standardized method for drone-based crocodylian demographic classification. 

This building block establishes standardized flight parameters for effective crocodilian monitoring

One of the biggest barriers to large-scale restoration is cost. Our solution eliminates the need for costly nurseries and reduces labor-intensive efforts, enabling efficient large-scale planting. The drones can plant up to 2,000 seeds in under 10 minutes, drastically reducing time and labor costs. This affordability makes restoration feasible for low-income regions and opens up opportunities for scaling in areas previously deemed inaccessible. The process is adaptable to other restoration challenges, such as reforestation or agricultural regeneration, making it versatile across multiple applications.

Restoration is not just about planting—it’s about ensuring long-term impact. Our AI-powered MRV system provides real-time tracking of restoration progress and environmental health. It also addresses critical issues like illegal fishing, poaching, and deforestation, empowering communities to protect their restored ecosystems. This system integrates satellite data, drone imagery, and AI analytics to provide actionable insights, which can be adapted to other restoration or conservation efforts. It also supports transparency and accountability, ensuring stakeholders can measure progress and outcomes effectively.

Our licensing and training platform equips communities to independently build, operate, and maintain drones. This approach is hands-on and collaborative, fostering local expertise and enabling communities to adapt the technology to their unique needs. The platform goes beyond technical skills, creating a foundation for communities to innovate and modify drones for additional applications such as surveillance, mapping, and precision agriculture. Importantly, the platform fosters a feedback loop where communities share their innovations, enriching the broader global network of users.

Our modular drones are designed for accessibility, adaptability, and sustainability. Initially crafted using wooden components with fewer than six screws and zip ties, they are simple to assemble, repair, and replicate using local materials, empowering communities to lead restoration projects independently.

As we’ve advanced, we’ve integrated hydrogen fuel cells and hybrid-electric propulsion systems, enhancing flight endurance, energy efficiency, and environmental sustainability. These innovations enable drones to cover larger areas and operate in remote environments while reducing their carbon footprint.

The modular design ensures flexibility for continuous adaptation, allowing communities to upgrade drones with tools like cameras or sensors for monitoring. This approach combines simplicity and cutting-edge innovation, bridging grassroots empowerment with scalable, impactful environmental restoration.

• Involvement of the local community
• Responding to community needs