The infrared system collects a large number of images daily, including many that are unrelated to elephants. With AI technology, the system has learned to automatically identify and filter out non-elephant images with over 99% accuracy, even detecting partial figures or shadows. Warnings are generated within 13–15 seconds through a fully automated process, reducing the need for manual review and enhancing the efficiency of elephant management.
So far, the system has captured over 3 million images and issued more than 12,000 automated warnings. All data is uploaded in real time to a centralized platform and shared with relevant agencies for research, management, and decision-making. This contributes to GBF Target 20 by promoting knowledge systems, technology, and innovation in biodiversity protection.

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.

Under the application of the trap for intermittent harvest, the best results were achieved with the following combination of variables: maize bran (supplementary feed) x maize bran (trap bait) x O. Shiranus (species) x 2 fish/m2 (stocking density).

The total yields under this combination were 25 percent higher than in the control group with single batch harvest. A higher stocking density (3 fish/ m2) led to a slightly higher total harvest in the control group, but to a lower net profit. The use of pellets reinforced both effects and was the least economical.

Results from the on-farm trials (see Figure 1) have demonstrated the functionality and the excellent catch effect of the traps. Over the three-month on-farm trial period, the trap was used 2 to 3 times a week and a total of 27 times. On average, around 120 small fish – an equivalent of 820 grams – were caught each intermittent harvest. With the use of the trap, all households reported that they now eat fish twice a week. Before that, fish consumption was between one and four times a month.

The benefits:

• Reducing the competition for oxygen and food among the fish in the pond and thus measurable increase in yield.
• Improved household consumption of small, nutritious fish and better cash flow.

Success factors:

• Traps are easy and inexpensive to build (USD 3).
• Traps are easy to use, also for women.
• Directly tangible added value thanks to easy and regular access to fish.

Examples from the field

Overall, the user experience of households engaged in the on-farm trials was very positive:

“As a family we are now able to eat fish twice and sometimes even three times a week as compared to the previous months without the technology when we ate fish only once per month.” (Doud Milambe)

“Catching fish is so simple using the fish trap and even women and children can use it.” (Jacqueline Jarasi)

“It is fast and effective compared with the hook and line method which I used to catch fish for home consumption that could take three to four hours but to catch only three fish and thus not enough for my household size.” (Hassan Jarasi)

• Involvement of the local community
• Responding to community needs 

For many conservationists, including our participants, the knowledge to effectively use conservation technology is not enough without the funding to access the tools. Recognizing this barrier, we provide each participant with USD$500 in seed funding to support the implementation of their conservation solutions. Participants are required to propose and carry out projects, which have ranged from building predator-proof bomas and underwater camera traps to developing AI tools, mobile apps, and community-driven citizen science initiatives. Each participant is required to report on their project’s progress over the following year, fostering accountability and impact tracking.

To ensure long-term sustainability, we also deliver training in grant writing, proposal development, and funder engagement to equip participants with the skills needed to secure sustained future funding. Ongoing mentorship and support also continue beyond the initial training. Our team, along with a growing alumni network, provides guidance on grant applications, reference letters, and professional development opportunities. Many of the projects and collaborations initiated during the program have led to graduate study, published research, and conference presentations, reinforcing participants’ continued growth as conservation leaders. 

Our technical training emphasizes experiential learning by giving participants direct, practical experience with conservation technologies. Whenever possible, students are encouraged to set up and deploy tools themselves in safe, low-pressure environments, creating space to experiment, make mistakes, and learn by doing. For instance, students may choose camera trap locations based on the classroom training module, then evaluate the effectiveness of their decisions by analyzing the resulting data. This process helps bridge theory and practice while building confidence in problem-solving and tool use.

In cases where participants cannot operate the tools directly, trainers and field practitioners from host institutions provide live demonstrations, such as tracking wildlife using GPS or operating drones, ensuring students still gain exposure to how these technologies function in real-world conservation settings.

We select participants who are at the beginning stages of their careers, such as those who have completed their bachelor’s degrees and are entering the NGO or conservation workforce or embarking on higher education.The goal is to identify participants whose careers would benefit the most from the type and amount of training, funding, mentorship, and support we provide. Over the past two years, we’ve recruited at least one participant from a non-academic background who nevertheless possesses extensive on-the-ground experience. These individuals have thrived in the program, highlighting an opportunity to further cater to this audience in future iterations.

Host institutions are selected based on their capacity to support both classroom and field-based instruction, and on their engagement with active conservation challenges where technology plays a meaningful role. For instance, the RISE Grumeti Fund in Tanzania is an ideal training site, offering educational facilities, student accommodations, and running active, tech-enabled initiatives such as anti-poaching and rhino protection programs.

Furthermore, we prioritize institutions that share our commitment to advancing education for women and early-career conservationists, have strong ties to local conservation and research communities, and demonstrate leadership in integrating technology into conservation practice. These partnerships are essential to ensuring our program is both sustainable and deeply embedded in the communities it aims to serve.

Project findings were disseminated through multiple academic and public platforms, including:

• An academic article in Ocean-Land-Atmosphere Research (a Science Partner Journal).
• Featured content on the AAASScience WeChat Public Platform, the official media of the American Association for the Advancement of Science in China.
• A case study contribution to the Yangtze River Delta Pilot Site.
• Integration into major NSFC-supported oceanographic research projects.

GBF Alignment: Aligns with GBF Target 20.
Contribution: Enhances global conservation efforts by sharing scalable methodologies.

Results were disseminated via an academic paper in Ocean-Land-Atmosphere Research (a Science Partten Journal) and shared in AAASScience WeChat Public (Official Media of American Association for the Advancement of Science in China). The findings were also included as a case study in the Yangtze River Delta Pilot Site and included in the support of major research projects on oceanography by the National Natural Science Foundation (NSFC).

By systematically integrating remote sensing data, deep learning, and ecological analysis, the project has significantly advanced wetland conservation methodologies, offering scalable solutions for biodiversity preservation,  biological invasion control,  and ecosystem management globally.