Publication Type

Journal Article

Publication Date (Issue Year)

2025

Journal Name

(IJACSA) International Journal of Advanced Computer Science and Applications

Abstract

Urban air pollution is a growing public-health challenge in African cities, yet traditional monitoring stations are sparse and expensive. The paper presents CleanCity IoT, a deployed, low-cost, vehicle-mounted air-quality platform that combines IoT sensors, GSM connectivity, cloud aggregation, and machine learning to produce near-real-time exposure maps and 2-hour forecasts for multiple pollutants. Each device integrates low-cost sensors for PM2.5, PM10, NO₂, O₃, SO₂, and CO₂, alongside temperature and humidity. Measurements are geotagged and transmitted over mobile networks form vehicles to a cloud backend, where data are validated, stored, and visualized through a user-friendly dashboard that also issues automated alerts and periodic reports. Using a dataset collected in Kigali and secondary cities via routine vehicular routes, the paper introduces the training of a multivariate time-series model to forecast short-horizon pollutant levels, supporting proactive health guidance and regulatory action. The system reports a performance in terms of latency, uptime, coverage, and data quality, and evaluate forecast accuracy using MAE/RMSE/MAPE and event-oriented metrics for spike prediction. Results indicate that CleanCity IoT provides reliable, scalable, and cost-effective urban air-quality intelligence, closing key gaps in spatiotemporal coverage while enabling citizen access, policy support, and social impact. The platform demonstrates a practical blueprint for African cities to operationalize air-quality intelligence using existing mobile infrastructure and locally developed technology.

Keywords

CleanCity IoT, air quality, mobile sensing, multivariate forecasting, spike detection

Grantee Name(s)

Eric Nizeyimana

Project Title

Leveraging IoT Mobile Networks for Urban Air Quality Insights in Rwanda

Type of Grant

JIRA Award

Thematic Area

ICTs Including Big Data and Artificial Intelligence

Funding Statement

The team acknowledges the support of the University of Rwanda, College of Science and Technology, and its African Centre of Excellence in Internet of Things (ACEIoT) for the use of their facilities and laboratory.

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