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Erschienen in:
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2017 | OriginalPaper | Buchkapitel

Mobile Wireless System for Outdoor Air Quality Monitoring

verfasst von : Anton Koval, Eloy Irigoyen

Erschienen in: International Joint Conference SOCO’16-CISIS’16-ICEUTE’16

Verlag: Springer International Publishing

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Abstract

Outdoor air quality monitoring plays crucial role on preventing environment pollution. The idea of use of unmanned aerial vehicles (UAV) in this area is of great interest cause they provide more flexibility than ground systems. The main focus of this work is to propose alternative, competitive outdoor wireless monitoring system that will allow to collect pollution data, detect and locate leakage places within petrol, gas and refinery stations or in hard to reach places. This system should be lightweight, compact, could be mounted on any UAV, operate in GPS denied environments and should be easily deployed and piloted by operator with minimal risk to his health. This paper presents the system, configured on a commercial UAV AR.Drone, embedding gas sensor to it, where as a ground station stands Robot Operation System. Conducted first stage experiments proved capabilities of our system to operate in real-world conditions and serve as a basis to carry out further research.

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Literatur
1.
Edokpolo, B., Yu, Q.J., Connell, D.: Health risk characterization for exposure to benzene in service stations and petroleum refineries environments using human adverse response data. Toxicol. Rep. 2, 917–927 (2015)CrossRef
2.
Terrés, I.M.M., Miñarro, M.D., Ferradas, E.G., Caracena, A.B., Rico, J.B.: Assessing the impact of petrol stations on their immediate surroundings. J. Environ. Manage. 91(12), 2754–2762 (2010)CrossRef
3.
Correa, S.M., Arbilla, G., Marques, M.R.C., Oliveira, K.M.P.G.: The impact of BTEX emissions from gas stations into the atmosphere. Atmos. Pollut. Res. 3(2), 163–169 (2012)CrossRef
4.
Kountouriotis, A., Aleiferis, P.G., Charalambides, A.G.: Numerical investigation of voc levels in the area of petrol stations. Sci. Total Environ. 470, 1205–1224 (2014)CrossRef
5.
Sairat, T., Homwuttiwong, S., Homwutthiwong, K., Ongwandee, M.: Investigation of gasoline distributions within petrol stations: spatial and seasonal concentrations, sources, mitigation measures, and occupationally exposed symptoms. Environ. Sci. Pollut. Res. 22(18), 13870–13880 (2015)CrossRef
6.
Valavanis, K.P., Vachtsevanos, G.J.: Handbook of Unmanned Aerial Vehicles. Springer Publishing Company, Incorporated, Dordrecht (2014)MATH
7.
Lozano, J., Suárez, J.I., Arroyo, P., Manuel, J.: Wireless sensor network for indoor air quality monitoring. Chem. Eng. 30, 319–324 (2012)
8.
Yu, T.-C., Lin, C.-C., Chen, C.-C., Lee, W.-L., Lee, R.-G., Tseng, C.-H., Liu, S.-P.: Wireless sensor networks for indoor air quality monitoring. Med. Eng. Phys. 35(2), 231–235 (2013)CrossRef
9.
Li, J., Xin, J., Li, M., Lai, B., Ma, Q.: Wireless sensor network for indoor air quality monitoring. Sens. Transducers 172(6), 86–90 (2014)
10.
Bartholmai, M., Neumann, P.: Micro-drone for gas measurement in hazardous scenarios via remote sensing. In: Proceedings of 6th WSEAS International Conference on Remote Sensing (REMOTE 2010) (2010)
11.
Neumann, P., Bartholmai, M., Schiller, J.H., Wiggerich, B., Manolov, M.: Micro-drone for the characterization and self-optimizing search of hazardous gaseous substance sources: a new approach to determine wind speed and direction. In: 2010 IEEE International Workshop on Robotic and Sensors Environments (ROSE), pp. 1–6. IEEE (2010)
12.
Neumann, P.P., Bennetts, V.H., Lilienthal, A.J., Bartholmai, M., Schiller, J.H.: Gas source localization with a micro-drone using bio-inspired and particle filter-based algorithms. Adv. Robot. 27(9), 725–738 (2013)CrossRef
13.
Neumann, P., Asadi, S., Schiller, J.H., Lilienthal, A.J., Bartholmai, M.: An artificial potential field based sampling strategy for a gas-sensitive micro-drone. In: IROS Workshop on Robotics for Environmental Monitoring (WREM), pp. 34–38 (2011)
14.
Rossi, M., Brunelli, D., Adami, A., Lorenzelli, L., Menna, F., Remondino, F.: Gas-drone: portable gas sensing system on uavs for gas leakage localization. In: 2014 IEEE SENSORS, pp. 1431–1434. IEEE (2014)
15.
Croizé, P., Archez, M., Boisson, J., Roger, T., Monsegu, V.: Autonomous measurement drone for remote dangerous source location mapping. Int. J. Environ. Sci. Dev. 6(5), 391 (2015)CrossRef
16.
Klein, G., Murray, D.: Parallel tracking and mapping for small ar workspaces. In: 6th IEEE and ACM International Symposium on Mixed and Augmented Reality, 2007, ISMAR 2007, pp. 225–234. IEEE (2007)
17.
Engel, J., Sturm, J., Cremers, D.: Accurate figure flying with a quadrocopter using onboard visual and inertial sensing. In: IMU, vol. 320, p. 240 (2012)
18.
Liu, Z., Li, Z., Liu, B., Xinwen, F., Ioannis, R., Ren, K.: Rise of mini-drones: applications and issues. In: Proceedings of the 2015 Workshop on Privacy-Aware Mobile Computing, pp. 7–12. ACM (2015)
19.
20.
Krajník, T., Vonásek, V., Fišer, D., Faigl, J.: AR-Drone as a platform for robotic research and education. In: Obdržálek, D., Gottscheber, A. (eds.) EUROBOT 2011. CCIS, vol. 161, pp. 172–186. Springer, Heidelberg (2011). doi:10.​1007/​978-3-642-21975-7_​16CrossRef
21.
Quigley, M., Conley, K., Gerkey, B., Faust, J., Foote, T., Leibs, J., Wheeler, R., Ng, A.Y.: Ros: an open-source robot operating system. In: ICRA Workshop on Open Source Software, vol. 3, p. 5 (2009)
22.
23.
Liu, X., Cheng, S., Liu, H., Hu, S., Zhang, D., Ning, H.: A survey on gas sensing technology. Sensors 12(7), 9635–9665 (2012)CrossRef
24.
Mercado, D.A., Castillo, P., Lozano, R.: Quadrotor’s trajectory tracking control using monocular vision navigation. In: 2015 International Conference on Unmanned Aircraft Systems (ICUAS), pp. 844–850. IEEE (2015)
25.
Nguyen, T., Mann, G.K.I., Gosine, R.G., Vardy, A.: Appearance-based visual-teach-and-repeat navigation technique for micro aerial vehicle. J. Intell. Robot. Syst. pp. 1–24 (2016). doi:10.​1007/​s10846-015-0320-1
26.
Li, P., Garratt, M., Lambert, A., Lin, S.: Metric sensing and control of a quadrotor using a homography-based visual inertial fusion method. Robot. Auton. Syst. 76, 1–14 (2016)CrossRef
27.
Engel, J., Sturm, J., Cremers, D.: Scale-aware navigation of a low-cost quadrocopter with a monocular camera. Robot. Auton. Syst. 62(11), 1646–1656 (2014)CrossRef
28.
Daugaard, M.: Semi-autonom indendørs navigation for luftbåren robot. Ph.D. thesis, Aarhus Universitet, Datalogisk Institut (2012)
29.
Thyregod, T., Daugaard, M.: Navigation for robots with wifi and cv (2012)
30.
31.
Metadaten
Titel
Mobile Wireless System for Outdoor Air Quality Monitoring
verfasst von
Anton Koval
Eloy Irigoyen
Copyright-Jahr
2017
Buch
International Joint Conference SOCO’16-CISIS’16-ICEUTE’16

Print ISBN: 978-3-319-47363-5

Electronic ISBN: 978-3-319-47364-2

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-3-319-47364-2_33

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