About the Project

Agricultural disasters affect millions of farmers worldwide, threatening food security and rural livelihoods. Traditional damage assessment methods are slow, labor-intensive, and inadequate for the scale and urgency of modern agricultural challenges.

Before Flood

After Flood

Local communities responding to flood emergency - demonstrating the immediate human impact of agricultural disasters

Rural homes submerged in flood waters, displacing families and destroying livelihoods

Extensive rice fields under water - crops that took months to grow destroyed in days

Critical infrastructure damage affecting agricultural communities and food distribution

Close-up view of flood-damaged rice crops showing the detailed assessment challenge

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Recent studies reveal systematic climate-driven agricultural devastation. Heavy rains in October 2025 alone caused Rs 3.5 billion in crop damages. Systematic reviews spanning 1979–2024 show persistent impacts on food security and yields (Aryal et al., 2025). Yet losses remain fragmented and inconsistently reported.

Our AI-driven system processes high-resolution satellite imagery, drone footage, and ground-based photographs to automatically detect, classify, and quantify agricultural damage across vast landscapes using advanced computer vision models and machine learning algorithms.

Autonomous drone conducting agricultural damage assessment over flood-affected areas

Professional field assessment team operating drone technology for comprehensive damage evaluation

Aerial perspective showing the scale of assessment challenge - comprehensive view only possible through drone technology

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This project represents a comprehensive approach to building agricultural resilience through community engagement, capacity building, and international collaboration. Beyond technology development, we prioritize knowledge transfer and local empowerment to create sustainable impact.

The initiative benefits from multi-level partnerships spanning international organizations (FAO), research institutions (NAAMII), technology providers (NAXA), and implementation support through AI SENSE LLC, which brings over 40 years of technical experience in civil engineering, computer science, database architecture, and AI/ML systems development.

FAO Nepal presenting "Partnering up for food security" at the Science Innovation Forum during World Food Forum, Rome - showcasing the AI-driven agricultural assessment solution to the global community

Enhancing Nepal's Post-Disaster Agricultural Response Through Advanced AI, Drone Technologies, and Capacity Building - November 19-20, 2025, Kathmandu

Celebrating success: Participants and trainers from the comprehensive workshop on AI-driven agricultural damage assessment technologies

Building Nepal's tech-ready workforce: Young professionals, private-sector experts, and community members united in agricultural resilience training

Advancing Skills in UAV Operations and AI Applications: Participants learning about drone types, national policies, pilot certification, and emerging AI tools

Hands-on learning environment: Interactive training sessions combining theoretical knowledge with practical applications in agricultural technology

Recognizing achievement: Certificate presentation to participants who completed the comprehensive training program in agricultural damage assessment

Building a Diverse, Tech-Ready Workforce for Agricultural Recovery: Strengthening Nepal's capacity for faster, more accurate, and inclusive disaster response

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The system has been successfully deployed in Nepal's first integrated disaster response system, demonstrating its effectiveness during the October 2025 Koshi Basin floods. This deployment marked a significant milestone in the application of AI technology for agricultural disaster response in South Asia.

The project gained international recognition when FAO Nepal presented the solution at the Science Innovation Forum during the World Food Forum in Rome, showcasing the collaborative approach to global food security challenges. The project is also supported by NSF SBIR Phase I funding, demonstrating its potential for global application and scaling.

As climate change continues to intensify agricultural challenges globally, the need for rapid, accurate damage assessment becomes increasingly critical. Our AI-driven system represents the beginning of a new era in agricultural resilience technology.

We envision expanding this technology to serve agricultural communities worldwide, integrating with existing early warning systems, and continuously improving through machine learning to better serve farmers, governments, and humanitarian organizations.

The fusion of ancient agricultural wisdom with cutting-edge AI technology – embodying the journey from "vedas to deep learning" – represents our commitment to creating solutions that honor traditional knowledge while embracing innovation for a more resilient agricultural future.