Mobile Wireless System for Outdoor Air Quality Monitoring
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.
KeywordsAR.Drone Pollution Gas ROS
This work comes under the framework of the project IT874-13 granted by the Basque Regional Government. The authors would like to thank the Erasmus Mundus Action 2 ACTIVE fellowship program, and the participating colleagues from the SUPREN research group, Environment and Chemical Engineering Department of the University of the Basque Country.
- 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)CrossRefGoogle Scholar
- 7.Lozano, J., Suárez, J.I., Arroyo, P., Manuel, J.: Wireless sensor network for indoor air quality monitoring. Chem. Eng. 30, 319–324 (2012)Google Scholar
- 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)Google Scholar
- 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)Google Scholar
- 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)Google Scholar
- 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)Google Scholar
- 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)Google Scholar
- 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)Google Scholar
- 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)Google Scholar
- 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)Google Scholar
- 19.Parrot.: Ar.drone 1.0 (2010). http://ardrone2.parrot.com/support-ardrone-1/
- 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)Google Scholar
- 22.Monajjemi, M., et al.: Ardrone autonomy: a ROS driver for AR.Drone 1.0 & 2.0 (2015). http://github.com/AutonomyLab/ardrone_autonomy
- 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)Google Scholar
- 28.Daugaard, M.: Semi-autonom indendørs navigation for luftbåren robot. Ph.D. thesis, Aarhus Universitet, Datalogisk Institut (2012)Google Scholar
- 29.Thyregod, T., Daugaard, M.: Navigation for robots with wifi and cv (2012)Google Scholar
- 30.Nosaari. Ardudrone (2011). https://code.google.com/archive/p/ardudrone/
- 31.Gunnarsson, G.: Udp client/server system (2012). https://www.abc.se/m6695/udp.html
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