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Smart Mining of Urban Air: A Data-Driven Solution to Dust Pollution in Rapidly Growing Cities.

Students & Supervisors

Student Authors
Md. Helal Uddin
Bachelor of Science in Computer Science & Engineering, FST
Md. Ridwan Al Mustavy
Bachelor of Science in Computer Science & Engineering, FST
Md. Mubashir Tajuare Partho
Bachelor of Science in Computer Science & Engineering, FST
Marowa Jahan
Bachelor of Science in Computer Science & Engineering, FST
Supervisors
Fatema Tuz Zohra, Ph.d
Associate Professor, Faculty, FST

Abstract

Urban dust pollution is a growing concern, especially in highly populated areas. This study examines factors affecting dust concentration using data mining techniques and statistical analysis. We collected responses from different urban locations in Bangladesh to understand perceptions of dust levels and their sources. Our findings reveal that road dust, vehicle emissions, and construction activities are the main contributors. Additionally, seasonal changes play a significant role, with higher dust levels observed during dry seasons. A chi-square test confirmed no relation between duration of residence and dust perception, while regression analysis showed a strong link between traffic density and dust concentration. The results suggest that improving urban policies, increasing greenery, and controlling emissions can reduce dust pollution. Real-time dust monitoring could also help communities take preventive measures. This research highlights the urgent need for data-driven solutions to enhance urban air quality and create healthier living environments.

Keywords

Keywords— Urban dust pollution seasonal variation statistical analysis chi-square test.

Publication Details

  • Type of Publication:
  • Conference Name: RUEC 1st International Research Conference 2025
  • Date of Conference: 06/09/2025 - 06/09/2025
  • Venue: Rajshahi University
  • Organizer: Rajshahi University Education Club
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