Development of Quadcopter Drone and IoT Module Technology in Geospatial-Based Air Emission Monitoring

his research introduces an innovative drone-based air quality monitoring system, equipped with multi-parameter sensors to measure temperature, humidity, CO2 concentration, and PM2.5 in real-time. The system is designed with integration to the Internet of Things (IoT), enabling direct data transmission to smart devices for instant access and quick analysis. This system provides a practical solution for monitoring air quality flexibly, especially in areas that are difficult to reach with conventional monitoring devices. Simulations showed that the drone canoperate for 4.8 to 14.77 minutes with an 80% battery depletion, depending on environmental conditions. Calibration testing of the sensors showed high accuracy, although data variations were significantly affected by temperature changes. The system underwent trial and calibration as an initial step to ensure device reliability and open opportunities for broader application development, including air quality monitoring in urban areas, industrial zones, and natural environments. The main advantage of this system lies in its ability to provide real-time data and flexibility in data collection from various locations. However, the study also identified several challenges, such as battery capacity limitations and communication range, which will be the focus of further development. Potential improvements include optimizing battery capacity, expanding communication range, and developing predictive

Authors

Publication Details

Journal
Journal of Artificial Intelligence and Software Engineering (J-AISE)
Published
2025-03-26
DOI
https://doi.org/10.30811/jaise.v5i1.6300
Primary Topic
Air Quality Monitoring and Forecasting
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Development of Quadcopter Drone and IoT Module Technology in Geospatial-Based Air Emission Monitoring

‪Brainvendra Widi Dionova, Anindya Ananda Hapsari, Devan Junesco Vresdian, Teddy Andreansyah
Journal of Artificial Intelligence and Software Engineering (J-AISE)
Air Quality Monitoring and Forecasting
article

Development of Quadcopter Drone and IoT Module Technology in Geospatial-Based Air Emission Monitoring

‪Brainvendra Widi Dionova, Anindya Ananda Hapsari, Devan Junesco Vresdian, Teddy Andreansyah
article en

Abstract

his research introduces an innovative drone-based air quality monitoring system, equipped with multi-parameter sensors to measure temperature, humidity, CO2 concentration, and PM2.5 in real-time. The system is designed with integration to the Internet of Things (IoT), enabling direct data transmission to smart devices for instant access and quick analysis. This system provides a practical solution for monitoring air quality flexibly, especially in areas that are difficult to reach with conventional monitoring devices. Simulations showed that the drone canoperate for 4.8 to 14.77 minutes with an 80% battery depletion, depending on environmental conditions. Calibration testing of the sensors showed high accuracy, although data variations were significantly affected by temperature changes. The system underwent trial and calibration as an initial step to ensure device reliability and open opportunities for broader application development, including air quality monitoring in urban areas, industrial zones, and natural environments. The main advantage of this system lies in its ability to provide real-time data and flexibility in data collection from various locations. However, the study also identified several challenges, such as battery capacity limitations and communication range, which will be the focus of further development. Potential improvements include optimizing battery capacity, expanding communication range, and developing predictive

Journal of Artificial Intelligence and Software Engineering (J-AISE)Vol. 5(1)
Openalex Percentile: Top 94%
Air Quality Monitoring and Forecasting
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.