Virtual Sensors: Toward High-Resolution Air Pollution Monitoring using AI and IoT

Zaidan, Martha Arbayani; Motlagh, Naser Hossein; Boor, Brandon E.; Lu, David; Nurmi, Petteri; Petäj̈ä, Tuukka; Ding, Aijun; Kulmala, Markku; Tarkoma, Sasu; Hussein, Tareq

doi:10.1109/iotm.001.2200103

Cited by 6 publications

(2 citation statements)

References 17 publications

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“…Alternatively, it may also be possible to use algorithmic techniques to overcome such variations in sensor availability. One example is the use of data reconstruction techniques, and another possibility is to harness virtual sensing which uses machine learning to predict the values of missing sensors using other variables [179].…”

Section: B Sensing and Data Processingmentioning

confidence: 99%

Unmanned Aerial Vehicles for Air Pollution Monitoring: A Survey

Hossein Motlagh,

Kortoçi,

et al. 2023

IEEE Internet Things J.

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Unmanned AerialVehicles (UAVs) equipped with air quality sensors offer a powerful solution for increasing the spatial and temporal resolution of air quality data, searching and detecting emission sources, and monitoring emissions from fixed and mobile sources. Despite the numerous advantages of using UAVs, their use, however, presents several challenges that limit their broader adoption. For example, UAVs require efficient algorithms and components to minimize power consumption, the overall payload used on UAVs needs to be small to ensure optimal portability which poses limitations on the sensors that can be integrated with UAVs, and there is a need for specialized algorithms, e.g., for identifying and locating air pollution sources. Currently, most solutions for UAV-based air quality monitoring focus on specific challenges or demonstrating the potential of using UAVs, and there is a lack of comprehensive overview of the research field and its open challenges. In this paper, we contribute a systematic review of UAV-based air quality monitoring, highlighting and analyzing technical solutions and challenges, and identifying open challenges with the aim of providing a research roadmap for the path forward.

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Section: B Sensing and Data Processingmentioning

confidence: 99%

Unmanned Aerial Vehicles for Air Pollution Monitoring: A Survey

Hossein Motlagh,

Kortoçi,

et al. 2023

IEEE Internet Things J.

Self Cite

View full text Add to dashboard Cite

show abstract

“…The real-time monitoring and forecasting of air quality is an essential and challenging endeavor to make informed decisions [ 25 , 26 ]. Most studies focus on the deployment and application of air quality sensors and IoT for monitoring air quality in cities [ [27] , [28] , [29] , [30] ]. Besides, air quality sensors, new technologies have also surfaced and proved effective in removing gaseous pollutants from the local environment [ [31] , [32] , [33] ].…”

Section: Introductionmentioning

confidence: 99%