PS-03Healthcare & Well-being
SaansAI
Personal Air-Quality Exposure and Action Guidance
SDG 3SDG 11SDG 13
The challenge
Air-quality alerts are usually issued for large geographic areas, while a person’s actual exposure depends on route, time, local traffic, nearby emission sources and duration outdoors. Children, older adults and people with respiratory sensitivity may need more actionable information than a city-wide AQI value. Create an AI-based exposure-support system that combines local air-quality readings, weather, location and planned activity to estimate short-term exposure and suggest lower-exposure choices. The solution must communicate uncertainty clearly and must not diagnose disease or replace professional medical advice.
What a working submission needs
Develop a mobile/web prototype that ingests public or simulated air-quality data, produces a location/time-specific exposure score, compares two activity or travel options, and gives understandable protective guidance.
Include an explanation of the main risk factors and data freshness.
Stretch goals
short-horizon AQI forecasting, school/worker dashboards, multilingual alerts or low-cost sensor integration.
Optional. A working core counts for more than feature count.Suggested stack
Web/mobile application, AI/ML models, a mapping or dashboard interface, and open APIs as appropriate to the problem.
Scope and responsibility
Healthcare, safety and public-sector challenges are decision-support tools, not autonomous clinical, legal, emergency-command or enforcement systems. Name your prototype’s limitations in the demo. Judging weighs a working core, justified use of AI, technical quality, real-world impact and responsible design above feature count.
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