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 local leadership process began between 1997 and 1998,
when a group of artisanal fishers identified a growing conflict
with industrial fishing that affected their practices and territories.
The most critical point of the conflict occurred between 2002 and
2005, when the industry intensified its presence, generating loss
of equipment and greater pressure on the resources. This
prompted the community to organize to represent their interests
and seek solutions from the government. Leveraged by local
governance schemes, these leaders were able to support each
other in order to advance the process of establishing the ZEPA.

Building local and regional expertise in DNA barcoding and metabarcoding is vital for sustainable biodiversity conservation. Supported by BBI-CBD funding, our training programs target conservation practitioners from Lebanon, Tunisia, Côte d'Ivoire, and Jordan, including those without prior molecular biology experience. These hands-on workshops cover sample collection, laboratory techniques, data analysis, and interpretation, empowering participants to independently apply molecular tools in their contexts. Capacity building democratizes access to innovative technologies, fosters regional collaboration, and ensures continuity beyond the project lifecycle.

Meaningful engagement with Lebanese Ministries of Environment and Agriculture, local NGOs, practitioners, and communities ensured that scientific insights informed policy and restoration practices. By communicating findings clearly and collaboratively, we helped integrate molecular data into the National Biodiversity Action Plan. Awareness campaigns targeted schools, universities, farmers, and land managers, raising understanding of the ecological roles animals play in forest regeneration. This knowledge mobilization builds local ownership, promotes evidence-based decision-making, and bridges science with societal needs for long-term ecosystem resilience.

Partnerships with the Smithsonian Institution, iBOL, and Saint Joseph University have been central to our project’s success. The Smithsonian provided advanced expertise in metabarcoding methodology and quality assurance, enabling rigorous application of DNA analysis. iBOL supports the expansion of barcoding efforts, particularly for insects, linking our regional data to global biodiversity initiatives. Saint Joseph University leads research implementation and capacity building, ensuring regional ownership and continuity. These collaborations combine global knowledge with local ecological and institutional context, enabling innovation and scalability.

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.

DNA barcoding and metabarcoding are cutting-edge molecular techniques that allow precise identification of species from small biological samples such as animal scats. Barcoding targets a single species by sequencing a standard gene region, while metabarcoding amplifies multiple DNA markers simultaneously, enabling comprehensive analysis of complex mixtures. These methods provide detailed insights into animal diets, predator-prey relationships, and seed dispersal patterns without invasive sampling. In our solution, these techniques were adapted to the Lebanese ecological context, enabling high-throughput biodiversity assessment and revealing key interactions between fauna and flora. This approach overcomes limitations of traditional ecological surveys and opens new possibilities for monitoring biodiversity changes, especially in regions with scarce baseline data.

This building block provides hands-on training for researchers and conservationists in Benin and South Africa (offline) and globally (online via Zoom) on using Declas. The sessions cover:

• Software use: Uploading data, interpreting AI-generated results, and integrating findings into conservation strategies.
• Conservation advocacy: Raising awareness on vulture decline and AI’s role in scalable monitoring.

Trainees will learn to deploy Declas in field surveys, reducing reliance on manual counts while improving data accuracy. The hybrid approach ensures broad accessibility, empowering local teams with cost-effective technology.

Goal: To lay the foundation for integrating I&T solutions into traditional wetland management

Objectives: 

 - To introduce three proposed IoT applications to wetland stakeholders and I&T sectors 

 - To consult wetland stakeholders and I&T sectors for their views and comments 

 - To review potential IoT applications beneficial to the management of MPNR 

 - To identify and integrating relevant IoT solutions for gei wai operation and wetland research into MPNR  

Partnership with EMSD allows us to utilize GWIN network as a transmission layer for all sensors installed for this project at Mai Po Nature Reserve (MPNR) with no network recurring cost required.

The technology offers several benefits that make it well-suited for wireless data transmission in IoT applications. Its long-range capabilities allow data to be transmitted over a distance, making it ideal for vast rural areas like MPNR. Furthermore, LoRa’s efficient power consumption extends the battery life of battery-powered devices. LoRa data transmission also ensures the confidentiality and integrity of the data through secure protocols.

In this project, four GWIN LoRa gateways were installed by EMSD within Mai Po Nature Reserve (MPNR). The sensors installed at MPNR are connected to gateways via the low-power and private LoRa network and eventually connected back to the GWIN backend via the 4G network. Besides these four gateways specially installed for this project, other GWIN gateways near MPNR can further secure data transmission reliability. 

In return, these four gateways can also help receiving signal from the sensors installed by various government departments in the surrounding area.