Predicting Future Infrastructure Needs in Africa for Policy Makers

Background

The African Center for Economic Transformation (ACET) identified a pressing challenge: African governments are heavily investing in infrastructure projects that often address current or past needs rather than future demands. Factors like climate change, migration, and urbanization require forward-looking strategies to optimize limited fiscal resources. Effective planning is essential to ensure infrastructure serves the needs of Africa’s people for the next 50 to 100 years.

Objective

This project  aimed to:

• Build predictive models for future infrastructure needs across selected African countries.
• Analyze aspirations, sentiments, and demographic changes using diverse data sources.
• Provide actionable recommendations for verification approaches and scalable networks to guide infrastructure planning in other regions.

Approach

The project tackled the challenge through a multidisciplinary collaboration involving a global team of AI practitioners. They utilized the following methods and tools:

1. Data Sources: Satellite imagery, socio-economic, climate, topological, demographic data, Google Trends, business listings, social media, and open-source data.
2. Techniques:
   • Modeling current infrastructure and historical population changes.
   • Predicting future demands using machine learning and data analysis.
   • Leveraging natural language processing (NLP), remote sensing, and route planning.
3. Tools:
   • Machine learning algorithms.
   • Streamlit for interactive dashboards to visualize predictions and data insights.

Results and Impact

The Omdena team delivered a comprehensive solution, including:

1. Predictive models for future infrastructure needs tailored to selected African countries.
2. Insights into aspirations and sentiments using social media and demographic analysis.
3. An interactive Streamlit dashboard showcasing:
   • Tweet analysis.
   • Population trends across African countries.
   • Electricity access.
   • Distance to vital amenities.
   • Water stress indices.

This project equips policymakers and stakeholders with data-driven insights to guide sustainable infrastructure development, ensuring optimal resource allocation for long-term impact.

A demo of the StreamLit dashboard:

Future Implications

The project sets the stage for more effective infrastructure planning across Africa, demonstrating how AI-driven tools can forecast future needs. These findings could shape future policies, improve funding efficiency, and inform global strategies for developing infrastructure in resource-constrained regions. Future research could expand the models to additional countries and infrastructure types, creating a scalable framework for other regions facing similar challenges.