A comprehensive artificial breeding program was established over four years, producing 10,000 fish annually for conservation and reintroduction. Challenges included low genetic diversity and habitat-specific requirements.

Sensor alert system will be activated after sensor installation and software platform development phase till the end of data collection phase. A trial-based action response plan for each type of sensor is listed below. For long run, an action response plan will be developed through fine tuning after the completion of review and evaluation of IoT system phase. 

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.

Local involment:
The scanners send real-time alerts to the anti-poaching control room. These alerts can also be shared with local communities or neighboring farms, enabling them to act as third-party partners in anti-poaching efforts. By involving locals directly in the response process, the system fosters collaboration, increases situational awareness, and empowers communities to take an active role in protecting wildlife.

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.