Hack The Planet acknowledge that our partnerships allow us to combine strengths, resources, and expertise, amplifying the impact and fostering innovative solutions. Collaborating creates shared value and builds networks, enabling mutual growth and sustainability.

Scanneredge is a collaboration with Tech for Conservation organisation Smartparks, Management of national parks like Gonarezhou - Zimbabwe, park technicians, rangers(QRU) and the local community. Through this cross-sector partnership, we have demonstrated that ScannerEdge is ready for broader deployment, increasing the number of active national parks and total scanners in use.

Leveraging real-time alerts from ScannerEdge, a response unit can quickly assess and mitigate potential threats, such as poaching or other illegal activities.

ScannerEdge specializes in monitoring RF signals from mobile and satellite phones, as well as other communication devices, to detect human activity in remote areas.

Ensuring that ScannerEdge devices are properly installed and configured in the field, with thorough training for operators to maximize their effectiveness in detecting illegal human activities.

Inclusive and participatory mapping of all stakeholders in the mangrove space in the five counties of Kwale, Mombasa, Kilifi, Tana River and Lamu. A series of meetings for sensitization on the National Mangrove Management Plan, and later facilitated formation of the national and five county committees. The committees were then facilitated in developing their workplans and executing some of the activities. This has since been picked up. 

An Act of Parliament that provide for the development and sustainable management, including conservation and rational utilization of all forest resources for the socio-economic development of the country and for connected purposes

Connecting the public: This mini program aims to promote the mainstream of biodiversity conservation by desensitizing current monitoring data in the industry and designing low threshold interactions for the traditional data labeling process. This allows the public to participate in the training process of biodiversity models in a more accessible and intuitive way through the mini program. On the one hand, the public can enjoy and learn about the most authentic protection monitoring images through the form of "playing games"; On the other hand, the power of the public can be utilized to continuously train a universal model of biodiversity, achieving the goal of citizen science in the process.
Through product design, 'Wild Friends' breaks down the process of annotating and verifying institutional data into tool based tasks, reducing the initial training costs of institutions. With simple guidance, volunteers or the general public can complete basic annotation content.
The first step is to check for the presence of animals (manually identified or judged by AI);
Step two, estimate the number of animals (manually determined);
Step three, select animals (manually or through AI evaluation of selection accuracy);
Step four, identify the name of the animal (manually selected or judged by AI);
Step five, randomly allocate cross validation in the background. Ensure the accuracy and consistency of data.
 

AI species recognition: This product uses AI recognition as the underlying technology, with endangered species as the core recognition object. It trains a large biodiversity recognition model that can support monitoring of mountains, rivers, forests, fields, lakes, grasses, and sands systems. The model is free and open to public welfare organizations dedicated to biodiversity conservation, such as research institutes, conservation organizations, and individuals. The reason why "wild friends" are so powerful is because they have a powerful "engine": YOLO World.
As the underlying universal model of 'wild friends', its primary characteristic is strong learning ability. It has powerful multimodal zero sample recognition and few sample recognition capabilities, which means it can quickly identify animal location regions and species information of multiple species through a small number of samples. For example, to recognize a new species, traditional models require thousands of photos and several days of training; YOLO World only requires a small number of photos and training iterations to achieve rapid adaptation.
Secondly, it has a high degree of tolerance. No longer limited to training and prediction of specific species, it has strong open vocabulary recognition ability and zero sample recognition ability, and can accurately identify and locate untrained species. For example, traditional models can only recognize trained species such as tigers and antelopes; The new model can also recognize snow leopards and foxes simultaneously - even if it has never trained these two animals before.
Another advantage of "wild friends" is that they spend less money. Common AI models heavily rely on high-performance acceleration cards, which result in high costs for both hardware environment and maintenance operations.

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This building block focused on enhancing the oversight capacity of the AA and the Board of Trustees to ensure effective governance of the WMA. Training sessions were conducted on strategic planning, financial oversight, and stakeholder engagement. Peer-to-peer learning opportunities were also organized, allowing AA and Board of Trustees members to learn from other successful WMAs. Regular meetings between the management team and oversight bodies were institutionalized to review progress, discuss challenges, and make strategic decisions. Strengthening oversight has ensured that the management team remains accountable and that community interests are represented in decision-making processes.