Mobilise resources for training the volunteers. Develop a training program together with relevant authorities (Police, DNPW). Train the community volunteers and local rangers on forestry laws, human rights, and enforcement strategies. Graduate Community Scouts and provide a Certificate. The volunteers sign an official commitment with the Government as Volunteers. 

Support communities to identify and organize volunteers committed to protecting the forest and catchment areas. Close collaboration with local authorities and local governmental structures such as the Department of National Parks and Wildlife or Department of Forestry (DNPW/DF).

Assess how many GVHs are located in the critical areas. Visit the local authorities to listen to their needs, concerns, and ideas for sustainable livelihoods linked to forest conservation.

Identify the mountain’s location, natural and human challenges, and its economic potential (e.g., tourism). Engage existing partners working on the mountain and collaborate to secure funding.

The adoption of FFMA among fishers through awareness and capacity building using multi-pronged strategies like awareness campaigns at the village level, conducting mass campaigns at the harbour level, promoting community level fisher friend ambassadors and master fishers for peer to peer learning, announcing top users for every month and audio and video visuals to spread the importance of FFMA in day to day fishing activities etc. All these positivly reflect on the adoption of FFMA. 

The Protected Area Management System (PAMS) by NOARKTECH is a centralized, intuitive dashboard aggregating data from edge devices. Co-designed with forest officials and community members, it delivers predictive analytics, real-time alerts, and supports evidence-based decision-making.

NOARKTECH’s WildGuard AI uses on-device Edge AI models and LoRaWAN communication to process data locally and transmit alerts even in low-connectivity regions. This low-power, scalable network allows instant wildfire detection, animal tracking, and real-time environmental monitoring.

NOARKTECH’s WildGuard AI integrates bio-acoustic microphones, air quality sensors (CO, VOC), and hyperlocal climate monitors to detect wildlife movement, forest fires, and ecological disturbances. This system enables real-time environmental intelligence for conservation, climate resilience, and human-wildlife conflict prevention.

The creation of a comprehensive, open-access DNA reference library of native plant and animal species was foundational to our solution. Recognizing that global databases lacked coverage for many Eastern Mediterranean species, we built the first Lebanese library encompassing plants, mammals, and now expanding to insects, birds, and fungi. This reference database improves the accuracy of DNA sequence matching and enables precise identification of species present in environmental samples. It also fills a critical regional data gap and facilitates ecological studies, biodiversity monitoring, and conservation planning. By publishing the library openly, we promote transparency, collaboration, and the potential for adaptation in similar biodiversity hotspots.