Assessing the Impact of Desert Locust Through AI

Background

Desert locust infestations pose a severe threat to food security across East Africa. Already, 3.1 million people in Kenya’s arid and semi-arid regions face food insecurity. This challenge is compounded by locust breeding, recent flooding, and the COVID-19 pandemic. Regionally, over 25.3 million people in Ethiopia, Kenya, Somalia, South Sudan, Sudan, and Uganda are battling acute food insecurity, with more than 11 million directly affected by locust infestations. This underscores the urgent need for innovative solutions to mitigate the crisis.

Objective

The project aimed to leverage advanced AI technologies, including satellite and drone imagery, to:

• Accurately assess the impact of desert locust infestations.
• Provide actionable insights for food security interventions.
• Support decision-making processes for humanitarian aid and policy-making.

Approach

A team of 50 technology changemakers collaborated with the Kenya Red Cross Society to tackle the crisis using innovative AI solutions. The project utilized:

1. Data Sources: High-resolution satellite and drone imagery to monitor locust breeding areas and affected farmlands.
2. Methods: AI algorithms to analyze large datasets, detect locust swarms, and evaluate their impact on vegetation and agriculture.
3. Tools: Advanced image processing tools, machine learning frameworks, and geospatial analysis software.

These techniques allowed for a detailed and timely assessment of locust infestations across affected regions.

Results and Impact

The project achieved significant outcomes:

• Developed a comprehensive mapping system to monitor desert locust spread.
• Identified critical regions at risk, enabling targeted humanitarian responses.
• Strengthened local and regional food security efforts by providing data-driven insights to mitigate the crisis.

This initiative directly supported millions of people in East Africa, ensuring timely interventions and minimizing food shortages in the hardest-hit areas.

Future Implications

The findings from this project hold substantial potential for future applications:

• Policy Development: Informing government policies on locust control and disaster preparedness.
• Research: Advancing AI-based methodologies for managing agricultural and ecological crises.
• Scalability: Expanding the use of AI for monitoring other climate-related challenges globally.

By integrating technology with humanitarian efforts, this project showcases the transformative power of AI in addressing complex environmental and social challenges.