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Methodology for automated greenhouse gas data collection and transmission to cloud repository using low-cost drones.

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Title: Methodology for automated greenhouse gas data collection and transmission to cloud repository using low-cost drones.
Authors: Daud Filho, Antonio Carlos1,2,3 (AUTHOR) antonio.daud.filho@usp.br, de Paula Caurin, Glauco Augusto2 (AUTHOR) gcaurin@usp.br, Silva, José Reinaldo1,3 (AUTHOR) reinaldo@usp.br, Vital, Elinilson1,3 (AUTHOR) vital@usp.br, Nelli Silva, Emilio Carlos1,3 (AUTHOR) ecnsilva@usp.br
Source: Environmental Monitoring & Assessment. Jun2026, Vol. 198 Issue 6, p1-17. 17p.
Subject Terms: *Greenhouse gases, *Automatic data collection systems, *Drone aircraft testing, *Environmental monitoring, *Commercial drones, *Mobile satellite communication, *Carbon dioxide detectors, *Data transmission systems
Abstract: Greenhouse gas (GHG) emissions are crucial for monitoring and mitigating climate change and the degradation of sensitive biomes. Such demand motivates the search for automated processes to collect and manage GHG emissions data, with open access to researchers and institutions working with sustainability. This work proposes an automated data collection process using low-cost drones, with direct data transfer to a cloud-based data space. Low-cost drones were equipped with onboard sensors to measure CO 2 and methane emissions. The focus was not on data accuracy but on automating data collection and transmission, drone design specifications, and testing, exploring the balance between data accuracy and low-cost sensors. The first practical proof-of-concept experiments demonstrating the system's capabilities used a drone prototype with simple sensors in an outdoor campus environment, sending data to a cloud-based data space called Digital Amazon (intended to store GHG emissions from the Amazon Forest), via 4G internet communication network. The system's design addressed aspects such as avoiding interference during data collection and trajectory adjustment, data transfer, and finalizing dataset composition in the cloud. The results provide initial evidence supporting the feasibility of the proposed system in an outdoor environment. However, its application to more complex scenarios, such as forests, other biomes, or urban areas, will be explored in subsequent research based on the reference model presented and will require further validation under diverse environmental and operational conditions. Enhancements to accommodate future communication based on Low Earth Orbit (LEO) and Very Low Earth Orbit (VLEO) satellite systems would help reduce transmission latency, but this issue was not assessed in the present study. [ABSTRACT FROM AUTHOR]
Database: Energy & Power Source
Description
Abstract:Greenhouse gas (GHG) emissions are crucial for monitoring and mitigating climate change and the degradation of sensitive biomes. Such demand motivates the search for automated processes to collect and manage GHG emissions data, with open access to researchers and institutions working with sustainability. This work proposes an automated data collection process using low-cost drones, with direct data transfer to a cloud-based data space. Low-cost drones were equipped with onboard sensors to measure CO 2 and methane emissions. The focus was not on data accuracy but on automating data collection and transmission, drone design specifications, and testing, exploring the balance between data accuracy and low-cost sensors. The first practical proof-of-concept experiments demonstrating the system's capabilities used a drone prototype with simple sensors in an outdoor campus environment, sending data to a cloud-based data space called Digital Amazon (intended to store GHG emissions from the Amazon Forest), via 4G internet communication network. The system's design addressed aspects such as avoiding interference during data collection and trajectory adjustment, data transfer, and finalizing dataset composition in the cloud. The results provide initial evidence supporting the feasibility of the proposed system in an outdoor environment. However, its application to more complex scenarios, such as forests, other biomes, or urban areas, will be explored in subsequent research based on the reference model presented and will require further validation under diverse environmental and operational conditions. Enhancements to accommodate future communication based on Low Earth Orbit (LEO) and Very Low Earth Orbit (VLEO) satellite systems would help reduce transmission latency, but this issue was not assessed in the present study. [ABSTRACT FROM AUTHOR]
ISSN:01676369
DOI:10.1007/s10661-026-15478-9