👉 The archived project was an interdisciplinary initiative that combined data science, environmental monitoring, and community engagement to address urban air quality issues. Initially launched as a pilot program in a major metropolitan area, it aimed to collect and analyze real-time air pollution data using IoT sensors deployed across various neighborhoods. The project integrated this data with satellite imagery and weather patterns to create predictive models, enabling city planners to identify high-risk zones and implement targeted interventions. Community members were involved through mobile apps that provided personalized air quality alerts and suggested actions to reduce exposure, fostering a collaborative approach to environmental health. Over three years, the project not only improved data accuracy and policy effectiveness but also empowered residents with actionable insights, leading to a measurable decrease in pollution-related health issues.
