But not tied down to the following:

1. Problem Statement

• What to Include: Clearly define the specific problem your project addresses. Explain why it’s important and how it connects to one or more of the United Nations Sustainable Development Goals (SDGs).
• Key Points:
  • Highlight the real-world significance of the issue.
  • Use data or examples (e.g., statistics, anecdotes) to show the problem’s urgency or scale.
• Purpose: Sets the context for your solution and demonstrates its relevance.

2. Solution Overview

• What to Include: Describe your AI-based solution. Explain what it does, how it functions, and how it solves the problem you’ve identified.
• Key Points:
  • Keep it simple and focused on the value it provides.
  • Use visuals (e.g., diagrams, flowcharts) to clarify complex ideas.
• Purpose: Showcases the innovation and practicality of your project.

3. Technical Implementation

• What to Include: Provide details about how you built your solution. Discuss the AI model(s), data sources, algorithms, or techniques you used, and highlight any unique or creative approaches.
• Key Points:
  • Focus on key technical decisions and challenges you overcame.
  • Avoid excessive jargon—make it understandable for a broad audience.
• Purpose: Proves your solution is technically feasible and well-executed.

4. Impact and Scalability

• What to Include: Explain the potential impact of your solution with measurable outcomes. Discuss how it could scale to benefit more people or be applied in other contexts, including any strategies or partnerships for real-world use.
• Key Points:
  • Use specific metrics (e.g., "This could improve healthcare access for 50,000 people").
  • Address feasibility of scaling up.
• Purpose: Demonstrates your project’s potential for widespread, meaningful change.