Development of UAV-Based PM2.5 Monitoring System

Huda Jamal Jumaah,Naonori Ueda,Alfian Abdul Halin,Shattri Mansor,Bahareh Kalantar,Sarah Jamal Jumaah

doi:10.3390/drones5030060

Abstract

This paper proposes a UAV-based PM2.5 air quality and temperature-humidity monitoring system. The system includes an air quality detector comprising four Arduino sensor modules. Specifically, it includes a dust (DSM501A) sensor and a temperature and humidity (DHT11) sensor. The NEO-6M GPS module and DS3231 real-time module are also included for input visualization. A DIY SD card logging shield and memory module is also available for data recording purposes. The Arduino-based board houses multiple sensors and all are programmable using the Arduino integrated development environment (IDE) coding tool. Measurements conducted in a vertical flight path show promise where comparisons with ground truth references data showed good similarity. Overall, the results point to the idea that a light-weight and portable system can be used for accurate and reliable remote sensing data collection (in this case, PM2.5 concentration data and environmental data).

Highlights

Fast economic growth over the latest decade in some Asian regions has resulted in rapid urbanization and industrial development
Measuring particulate matter (PM) pollution in the air is acknowledged as an imperative task to control air pollution [3]
A small, light-weight, and low-cost air quality monitoring system is presented using a mini Unmanned Aerial Vehicles (UAVs) that is combined with air quality and temperate-humidity sensors

Summary

Introduction

Fast economic growth over the latest decade in some Asian regions has resulted in rapid urbanization and industrial development. Green landscapes have been replaced by housing estates and high-rise buildings and, when combined with increased vehicular utilization, have led to acute atmospheric contamination (dust and haze). Concentrations of particulate matter in the air have increased to undesirable levels [1]. It is necessary to identify the main sources of atmospheric aerosols to limit their expanding level, requiring sufficient monitoring [2]. Measuring particulate matter (PM) pollution in the air is acknowledged as an imperative task to control air pollution [3]. Since air pollution is seemingly inescapable in most urban settings, the ability to gauge current air quality is necessary [4]. Classic methods afford daily measurements but are stationary, costly and have a low spatial resolution [5]

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Discussion

Conclusion