Abstract:
The Air Pollution Monitoring Forecasting System project aims to develop
a comprehensive system for air quality management through innovative sensor
technology, data analysis, and AI techniques. It combines multi-sensor data
collection, AI-driven forecasting, and public engagement to provide timely insights
into pollution dynamics. The project’s foundation lies in a network of specialized
sensors strategically positioned to monitor various pollutants and pollution sources.
The integration of artificial intelligence constitutes a pivotal advancement in
this project’s methodology. The AI setup introduces a novel early warning system
that transcends retrospective reporting, revolutionizing the ability to mitigate
the adverse effects of air pollution. The user-friendly website provides accessible air
quality information to the general populace, encouraging informed decision-making
and behavior changes that contribute to cleaner air and healthier lifestyles.
However, certain challenges and opportunities for future development emerge,
such as sensor accuracy, data reliability, and continuous refinement of
AI algorithms. potential for collaborative partnerships, sensor technology
enhancements, and the expansion of the system’s geographical coverage
underscores apromising trajectory for continued improvement and impact.
