Challenge background
This project addresses a critical need in Nepal's disaster management efforts, taking into account the country's unique geographical and cultural landscape. By leveraging AI and data from various sources, it aims to significantly improve the efficiency and effectiveness of post-earthquake recovery efforts, potentially saving lives and accelerating the rebuilding process in affected communities.
The problem
Nepal, with its diverse terrain and remote communities, faces significant challenges in coordinating post-earthquake recovery efforts. After major seismic events, there's often a mismatch between available resources and actual needs across different regions. The country's rugged landscape and limited infrastructure further complicate the efficient distribution of aid and deployment of volunteers. There's a critical need for a system that can effectively match resources with needs while considering Nepal's unique geographical and cultural context.
Goal of the project
Develop an AI-powered platform that coordinates post-earthquake recovery efforts in Nepal. The system will use machine learning algorithms to match needs with resources and volunteers, considering factors such as terrain accessibility, cultural sensitivities, and the urgency of different types of aid. The platform will integrate real-time data from various sources to provide a comprehensive view of the recovery landscape and optimize resource allocation.
Project timeline
- 1
Week 1
Data Collection
- 2
Week 2
Data Preprocessing
- 3
Week 3
Model Development
- 4
Week 4
Model Deployment
- 5
Week 5
Research paper/blog
What you'll learn
- Essentials of geological data from collection to preprocessing
- Data analysis
- Feature engineering
- Model development
- Model integration