Autonomous multi-species environmental gas sensing using drone-based Fourier-transform infrared spectroscopy

Rutkauskas, Marius; Asenov, Martin; Ramamoorthy, Subramanian; Reid, Derryck T.

doi:10.1364/oe.27.009578

Cited by 30 publications

(9 citation statements)

References 17 publications

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“…In this paper, we presented a new formulation of angleaware coverage control for 3-D map reconstruction and a 2 We have determined the cells in an ad-hoc manner. More careful selection of the cells might enhance the performance but this exceeds the scope of this paper.…”

Section: Discussionmentioning

confidence: 99%

“…In this paper, we mainly consider a 2-D motion of 1 This assumption is motivated by the fact that path planning of a drone for aerial image sampling normally focuses on the 2-D coverage while keeping the flight altitude constant as in Fig. 1 [2]. The present approach is in principle still applicable with a few modifications even in the absence of this assumption, but more detailed investigations on 3-D motion control are left as future work.…”

Section: A Drones Virtual Field and Geometrymentioning

confidence: 99%

“…Drones have increasingly been a key technology in environmental monitoring in several fields, e.g., smart farming [1], airborne gas sensing [2], and wildfire tracking [3]. In particular, drone networks with distributed control are expected to enhance the monitoring efficiency and robustness against failures while ensuring computational scalability.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Angle-Aware Coverage Control for 3-D Map Reconstruction With Drone Networks

Shimizu

Yamashita

Hatanaka

et al. 2022

IEEE Control Syst. Lett.

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In this paper, we address environmental monitoring for 3-D map reconstruction using drone networks. In view of the fact that the 3-D reconstruction requires images from a variety of viewing angles, we first formulate a novel angle-aware coverage control problem, based on a concept of virtual field that combines the position of a monitoring target and the viewing angle. Then, we define an objective function with an importance index, updated according to the history of the past coverage states. In the present scenario, drones are required not only to minimize the objective function but also to take situationadaptive actions, e.g. a drone should quickly escape a region having low importance indices. To this end, we design a QPbased controller that switches actions depending on the current importance index. We finally demonstrate the effectiveness of the presented controller through simulations on Robot Operating System.*This research was partially funded by the project "New technical and operative solutions for the use of drones in Agriculture 4.0" (PRIN 2017, Prot. 2017S559BB) and JSPS KAKENHI Grant Number 21K04104.

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Section: Discussionmentioning

confidence: 99%

Section: A Drones Virtual Field and Geometrymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Angle-Aware Coverage Control for 3-D Map Reconstruction With Drone Networks

Shimizu

Yamashita

Hatanaka

et al. 2022

IEEE Control Syst. Lett.

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“…This allows for accurate measurements of the concentration of pollutants in the air in large areas, including hazardous or hard-to-reach areas. These measurements are useful not only in monitoring the environment but also in the case of the need to assess chemical contamination in industrial areas emitted by production plants in standard operations and during breakdowns [50][51][52].…”

Section: Scatteringmentioning

confidence: 99%

Monitoring of Selected CBRN Threats in the Air in Industrial Areas with the Use of Unmanned Aerial Vehicles

et al. 2020

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Unmanned aerial vehicles (UAVs) play an increasingly important role in various areas of life, including in terms of protection and security. As a result of fires, volcanic eruptions, or other emergencies, huge amounts of toxic gases, dust, and other substances are emitted into the environment, which, together with high temperature, often leads to serious environmental contamination. Based on the available literature and patent databases, an analysis of the available UAVs models was carried out in terms of their applicability in air contaminated conditions in industrial areas, in the event of emergencies, such as fire, chemical contamination. The possibilities of using the devices were analyzed in terms of weather conditions, construction, and used materials in CBRN (chemical, biological, radiological, nuclear) threat situations. It was found that, thanks to the use of appropriate sensors, cameras, and software of UAVs integrated with a given system, it is possible to obtain information on air quality at a given moment, which is very important for the safety of people and the environment. However, several elements, including the possibility of use in acidification conditions, requires refinement to changing crisis conditions.

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“…Phillips et al also used Open Path-Fourier Transform Infrared technology (OP/FTIR) to detect the influence of the inorganic compound ammonia (NH 3 ) emitted by automobiles [19]. Rutkauskas et al deployed OP/FTIR technology onto an unmanned aerial vehicle for environmental monitoring using a spectrometer; this approach was able to provide rotational-vibrational spectroscopy over the entire molecular fingerprint area of 3-11 µm [20].…”

Section: Introductionmentioning

confidence: 99%

Air Pollution: Sensitive Detection of PM2.5 and PM10 Concentration Using Hyperspectral Imaging

et al. 2021

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This paper proposes a method to detect air pollution by applying a hyperspectral imaging algorithm for visible light, near infrared, and far infrared. By assigning hyperspectral information to images from monocular, near infrared, and thermal imaging, principal component analysis is performed on hyperspectral images taken at different times to obtain the solar radiation intensity. The Beer–Lambert law and multivariate regression analysis are used to calculate the PM2.5 and PM10 concentrations during the period, which are compared with the corresponding PM2.5 and PM10 concentrations from the Taiwan Environmental Protection Agency to evaluate the accuracy of this method. This study reveals that the accuracy in the visible light band is higher than the near-infrared and far-infrared bands, and it is also the most convenient band for data acquisition. Therefore, in the future, mobile phone cameras will be able to analyze the PM2.5 and PM10 concentrations at any given time using this algorithm by capturing images to increase the convenience and immediacy of detection.

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Autonomous multi-species environmental gas sensing using drone-based Fourier-transform infrared spectroscopy

Cited by 30 publications

References 17 publications

Angle-Aware Coverage Control for 3-D Map Reconstruction With Drone Networks

Angle-Aware Coverage Control for 3-D Map Reconstruction With Drone Networks

Monitoring of Selected CBRN Threats in the Air in Industrial Areas with the Use of Unmanned Aerial Vehicles

Air Pollution: Sensitive Detection of PM2.5 and PM10 Concentration Using Hyperspectral Imaging

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