Challenge Area:
Urban waste management.

Problem Statement:
Inefficient waste sorting in cities leads to increased landfill use and pollution.

Solution Concept:
Design an AI-powered waste sorting system using computer vision to classify recyclables at collection points, integrated with a citizen app for waste disposal guidance.

Expected Impact:
Increase recycling rates by 25% in 3 cities.

Next Steps:
Develop image classification models, prototype sorting hardware, and engage local waste management agencies.

Challenge Area:
Urban Planning

Problem Statement:
Urban traffic congestion increases emissions and commute times due to poor traffic flow management.

Solution Concept:
Develop an AI-based traffic optimization system using real-time GPS data and reinforcement learning to adjust traffic signals. The PoC includes data pipelines for GPS data and scalable cloud infrastructure.

Expected Impact:
Reduces congestion by 25%, cutting emissions by 15% in cities.

Next Steps:
Integrate with smart city platforms, add pedestrian data, and optimize for low-latency processing.