RiKhaNET: Realtime Integrated Knowledge on Habitat & Animals – Network
Deployed
JNWSFL
Nubi Gewog (Bhutan)
RiKhaNET addresses a core operational challenge in Bhutan’s tiger landscapes where field data and incident information are often fragmented across tools and stakeholders, limiting timely prevention. RiKhaNET consolidates these inputs into a single, governed platform by integrating Bhutan’s SMART (Spatial Monitoring and Reporting Tool) data with AI-driven analytics and real-time sensor inputs. Using machine-learning models, the system generates dynamic risk heatmaps, geofencing alerts, and automated notifications to help rangers and communities anticipate conflict hotspots before incidents occur, shifting response from reactive to proactive prevention.
The Stakeholder meetings conducted emphasized that the pilot must be designed to strengthen trust and adoption, not only technology performance. Three design requirements were highlighted:
Data governance and transparency: The current hosting arrangements raise concerns about filtering, access control, and sensitive wildlife-location data; governance must be explicit and communicated clearly.
Community safety communication: The alert systems must be carefully designed so alerts support prevention and coordinated action rather than increasing fear; community focal persons can strengthen trusted communication.
Operational realism for detection: It has been noted that tiger detections can be rare; deployments may run for months yet capture limited tiger events, so the pilot should prioritize focused hotspot monitoring with sufficient duration to produce meaningful training and pattern data.
What We Are Seeking
Clearly defined roles, responsibilities, and governance, through formal agreements and approvals through a legally binding MoA for retaining operational flexibility for adaptive implementation.
Data-sharing and operational coordination with relevant agencies (including wildlife and livestock stakeholders) to ensure the alert system connects to real-world response workflows and prevention actions.
A hosting and architecture decision for the pilot that protects sensitive wildlife-location data to improve transparency and access control, and to remain financially sustainable over time.
How It Works (Current Operational Design)
Detection layer: Autonomous field sensor nodes to capture camera imagery, motion and acoustic signals, time/location, and environmental context, with edge processing and low-power solar/battery design in weatherproof casing.
**Connectivity options:**Architecture to explore both LoRaWAN-based
Why This Matters Now
Human-Tiger conflict in Bhutan is not merely an issue of conservation; it has become an urgent public safety and rural livelihood challenge. In the absence of early warning systems, incidents are more likely to incite fear, spur reactive decision-making, and lead to repeated losses, resulting in broader social disruption in communities that already function on tight economic margins. As noted in the project narrative, the current situation reveals that both communities and rangers face safety risks, responses are often fragmented and reactive, valuable ecological data exists but remains under-utilized, and livestock losses jeopardize rural livelihoods, all of which exacerbate the growing national risk of human-tiger conflict.
Why This Matters and Why RiKhaNET
RiKhaNET signifies a strategic evolution in Bhutan's approach to conservation, integrating technology as a fundamental aspect of the national social infrastructure rather than merely a supplementary tool. The DHI’s 10X Roadmap views economic growth through the lens of public value, harmonizing financial advancement with social, environmental, and intergenerational outcomes in line with the principles of Gross National Happiness. Within this framework, innovation is deemed crucial for addressing future societal challenges and fostering a resilient, knowledge-driven economy.
RiKhaNET is at the forefront of Bhutan's transformative phase, where Research, Development, and Innovation are becoming key drivers of the nation's economic growth. Aligned with the national vision to cultivate a thriving innovation sector grounded in Bhutan's unique conditions and values, RiKhaNET is leveraging cutting-edge technologies like Artificial Intelligence and the Internet of Things. Through these innovations, RiKhaNET is addressing critical national challenges, including biodiversity protection, rural livelihoods, and public safety, playing a central role in Bhutan's evolving landscape.
Project Cost
Funding requested (WWF cash / GTIF): USD 170,000.
Total project value:USD 208,095
Way Forward (National + Beyond Scale)
National Platform (Institutionalization at Scale)
Establish RiKhaNET as Bhutan's national platform for preventing human-wildlife conflict and monitoring wildlife. It should be integrated with SMART and utilized as the standard operating system for rangers and local authorities. This integration allows for consistent reporting nationwide, enhances response coordination, and provides a single source of truth for identifying hotspots, planning patrols, and implementing preventive measures.
Want to collaborate on this project? Write the lead directly, or pitch an adjacent idea through the open queue.
Partnerships primarily with Conservation agencies that support long-term sustainability and incentives
.
Currently exploring WWF’s Tiger Impact Certificates (TIC) as a complementary mechanism where RiKhaNET can strengthen monitoring/verification evidence and TIC can strengthen community incentives and stewardship.
and
GSM-based
deployments depending on terrain and coverage realities.
Real-time tiger detection pipeline: A tiered approach based on edge filtering (TinyML), gateway-level detection and classification (including confidence thresholds for alert vs review), and cloud-level model improvement and heatmap generation, targeting detection-to-alert within 60 seconds, with an offline-capable, edge-first design.
Predictive conflict heatmap: An ensemble risk model combining tiger occurrences (SMART + sensors), conflict history, land cover, terrain, and human activity; it will differentiate habitat suitability from conflict likelihood and apply a temporal update layer, producing a 100m-grid risk output for community and ranger views.
Community alert hub (village layer): Designed to be an inclusive hybrid system that can deliver SMS/mobile alerts, activate beacon lights in low-connectivity areas, and provide dashboards and predictive indicators, with possibility for future extension to other species.
The urgency is highlighted by the inadequacy of current information and monitoring systems for prevention. Data is often dispersed across various tools and institutions, hindering decision-making and limiting the capacity to recognize patterns, anticipate hotspots, and coordinate consistent response efforts. RiKhaNET directly addresses this gap by integrating SMART data, AI analytics, and IoT sensor inputs into a comprehensive real-time decision platform that generates predictive risk maps and early warning alerts, shifting conservation efforts from a reactive stance to a proactive one.
This pivotal moment also represents a unique opportunity for national readiness. Bhutan's conservation agencies already possess extensive field data and monitoring practices; what is essential is an integrated, governed mechanism to convert that information into timely, actionable prevention strategies. Furthermore, discussions around coordination highlight the necessity of proactively addressing data sensitivity and governance, especially considering concerns about externally managed hosting and sensitive wildlife location information. Establishing the right governance and architecture during the pilot phase is, therefore, crucial to avoid barriers to adoption in the future.
In summary, the need for action is pressing. The lack of early warning systems and coordinated decision support, conflicts are more likely to escalate, leading to social, economic, and political repercussions. RiKhaNET is designed as a preventive infrastructure response that aims to reduce preventable losses, enhance frontline safety, and transform underutilized ecological and conflict data into actionable early interventions that can be institutionalized and scaled nationwide.
At the heart of the project lies a significant national concern where communities and rangers encounter safety threats, livestock losses jeopardize rural economies, and valuable ecological data is underutilized, all while conflicts escalate without effective early-warning systems. RiKhaNET fills these gaps by integrating SMART data, AI analytics, and IoT sensors into a cohesive, real-time decision-making platform. This platform produces predictive risk maps and alerts, transforming conservation efforts from reactive responses to proactive prevention.
Beyond technological progress, RiKhaNET promotes social advantages by prioritizing preventive safety over reactive harm. The ongoing human–tiger conflict places recurring economic and psychological burdens on rural families; predictive protection helps mitigate the likelihood and severity of these impacts, while alleviating the operational strain on responders. The initiative is intentionally community-focused, fostering local ownership and ensuring that solutions are both operationally feasible and socially acceptable.
Furthermore, RiKhaNET contributes to national capability development. Its implementation through DHI InnoTech and the Jigme Namgyel Wangchuck Super Fab Lab ensures that expertise in AI, IoT, and data analytics remains within Bhutan, reducing long-term dependence on external vendors and fortifying future-ready institutions. This local development strategy enhances cost efficiency, technology ownership, and long-term sustainability.
Essentially, the project is not designed as a standalone pilot; it is intentionally integrated into Bhutan’s national innovation ecosystem. This structure revolves around drivers, facilitators, and enabling finance, supporting institutional adoption, transparent governance, and scalable deployment beyond initial landscapes. GTIF financing serves as catalytic capital, expediting a pathway already established for national integration and enduring sustainability.
From an investment and policy standpoint, this alignment significantly mitigates risks associated with the initiative. Intellectual property governance, recognized as a cornerstone of Bhutan’s transition to a knowledge-based economy, fosters durable system ownership. It ensures that locally adapted hardware, predictive models, and operational workflows can be sustained and refined within national systems over time.
Ultimately, RiKhaNET embodies a unique convergence of innovation and practical implementation: a solution adept at protecting livelihoods, conserving biodiversity, and enhancing coexistence, all while positioning Bhutan to create a distinctive national identity at the intersection of conservation technology and human–wildlife harmony. By aligning closely with DHI’s public-value agenda and Bhutan’s innovation framework, the project minimizes the risks associated with execution and sustainability, paving a credible pathway toward national-scale impact.
Sustainable Financing (From Pilot to Long-Term Operations)
Shift from relying on grants to a blended financing model that ensures long-term sustainability. This includes government program budgets for core operations, conservation funds for growth and improvements, and mission-aligned impact capital for scaling infrastructure. Such a model establishes a reliable funding pathway that supports maintenance, replacement cycles, training, and national roll-out without the risk of repeated "pilot restarts."
Multi-Species Scale (Expand Impact per Unit Investment)
Broaden the focus from just tigers to other priority conflict species by employing the same sensing, data governance, and analytics framework. This will create a national multi-species risk layer, enhancing the platform's return on investment by improving safety and mitigation outcomes across various conflict scenarios while also bolstering biodiversity monitoring and ecosystem intelligence.
Replication and IP (Productize and Export Bhutan’s Model)
Package RiKhaNET as a modular, deployable core that includes hardware reference designs, software modules, governance templates, and a proven deployment playbook. This approach facilitates regional replication and generates revenue opportunities through implementation services, certified training programs, and governance-grade data products, all while maintaining national ownership and control.
Eco-Tourism Value (Turn Safety and Intelligence into Economic Upside)
Create controlled, non-sensitive outputs such as safety advisories, seasonal hotspot insights, and site-management dashboards tailored for eco-tourism operators and protected area managers. This enhances visitor safety and experience, builds destination credibility, and paves the way for co-investment opportunities where tourism stakeholders contribute to sustaining the monitoring infrastructure.
A mini ‘Fab Lab’ platform that equips Bhutanese schools with digital fabrication tools, teacher training, and ongoing technical support to drive hands-on STEAM learning and student-led innovation.
The proposed geothermal program is a multi-phase initiative led by Druk Holding and Investments (DHI) to unlock Bhutan’s geothermal potential across multiple Dzongkhags such as Gasa, Punakha, and Gelephu:
Electricity Generation – Deploy small-scale electricity generation providing baseload renewable power to the grid.
Druk Holding and Investments (DHI) was established with a mandate to enhance the performance and value of its portfolio companies and safeguard national wealth for all generations of Bhutanese through prudent investments. Over the past decade, DHI has built a diversified group of companies operating across key sectors — energy, telecommunications, finance, manufacturing, technology, and services.
