SwarmCity project: monitoring traffic, pedestrians, climate, and pollution with an aerial robotic swarm Data collection and fusion in a smart city, and its representation using virtual reality
Smart cities have emerged as a strategy to solve problems that current cities face, such as traffic, security, resource management, waste, and pollution. Most of the current approaches are based on deploying large numbers of sensors throughout the city and have some limitations to get relevant and u...
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| Published in | Personal and ubiquitous computing Vol. 26; no. 4; pp. 1151 - 1167 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
London
Springer London
01.08.2022
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1617-4909 1617-4917 |
| DOI | 10.1007/s00779-020-01379-2 |
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| Abstract | Smart cities have emerged as a strategy to solve problems that current cities face, such as traffic, security, resource management, waste, and pollution. Most of the current approaches are based on deploying large numbers of sensors throughout the city and have some limitations to get relevant and updated data. In this paper, as an extension of our previous investigations, we propose a robotic swarm to collect the data of traffic, pedestrians, climate, and pollution. This data is sent to a base station, where it is treated to generate maps and presented in an immersive interface. To validate these developments, we use a virtual city called SwarmCity with models of traffic, pedestrians, climate, and pollution based on real data. The whole system has been tested with several subjects to assess whether the information collected by the drones, processed in the base station, and represented in the virtual reality interface is appropriate. Results show that the complete solution, i.e., fleet control, data fusion, and operator interface, allows monitoring the relevant variables in the simulated city. |
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| AbstractList | Smart cities have emerged as a strategy to solve problems that current cities face, such as traffic, security, resource management, waste, and pollution. Most of the current approaches are based on deploying large numbers of sensors throughout the city and have some limitations to get relevant and updated data. In this paper, as an extension of our previous investigations, we propose a robotic swarm to collect the data of traffic, pedestrians, climate, and pollution. This data is sent to a base station, where it is treated to generate maps and presented in an immersive interface. To validate these developments, we use a virtual city called SwarmCity with models of traffic, pedestrians, climate, and pollution based on real data. The whole system has been tested with several subjects to assess whether the information collected by the drones, processed in the base station, and represented in the virtual reality interface is appropriate. Results show that the complete solution, i.e., fleet control, data fusion, and operator interface, allows monitoring the relevant variables in the simulated city. |
| Author | Mazariegos, Pablo Roldán-Gómez, Juan Jesús Barrientos, Antonio Garcia-Aunon, Pablo |
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| Cites_doi | 10.1016/j.cogsys.2018.10.031 10.1016/S0166-4115(08)62386-9 10.1016/j.proeng.2015.06.106 10.14358/PERS.81.4.281 10.1016/j.ijtst.2016.11.002 10.1007/s13676-014-0045-5 10.1145/1026799.1026821 10.1126/science.1167311 10.1109/ACCESS.2019.2934998 10.3390/s150203334 10.1109/ITNEC.2016.7560507 10.1109/PERCOMW.2019.8730677 10.3390/s16071072 10.1016/j.jocs.2018.10.004 10.1016/S0924-0136(00)00717-2 10.1109/ACCESS.2019.2924938 10.1007/978-3-319-91590-6_2 10.7551/mitpress/9780262029728.001.0001 10.3390/s17081720 10.1016/j.cities.2016.10.005 10.1109/ICUAS.2014.6842265 10.1080/00221341.2015.1070366 10.3390/app8050711 10.1080/19427867.2017.1354433 10.1109/ICAC.2015.64 10.1109/MCE.2019.2892279 10.1109/ICE/ITMC39735.2016.9025965 10.1016/j.scs.2018.01.053 10.1109/JIOT.2016.2546307 10.1109/MCOM.2018.1700444 10.1109/MPOT.2018.2850386 10.1002/ett.2931 10.1016/j.rcim.2019.05.004 10.3390/s18114015 |
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| Keywords | Data fusion Robot swarm Swarm intelligence Immersive interface Smart city Virtual reality |
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| References_xml | – reference: Garcia-AunonPBarrientos CruzAComparison of heuristic algorithms in discrete search and surveillance tasks using aerial swarmsAppl Sci2018852076341710.3390/app8050711 – reference: Li Z, Chen X, Ling L, Wu H, Zhou W, Qi C (2019) Accurate traffic parameter extraction from aerial videos with multi-dimensional camera movements. Tech Rep – reference: Roldán JJ, Peña-Tapia E, Garzón-Ramos D, de León J, Garzón M, del Cerro J, Barrientos A (2019) Multi-robot systems, virtual reality and ROS: developing a new generation of operator interfaces. In: Robot Operating System (ROS). Springer, pp 29–64 – reference: BereitschaftBGods of the city? Reflecting on city building games as an early introduction to urban systemsJ Geogr20161152516010.1080/00221341.2015.1070366 – reference: Hashimoto K, Yamada K, Tabata K, Oda M, Suganuma T, Rahim A, Vlacheas P, Stavroulaki V, Kelaidonis D, Georgakopoulos A (2015) iKaas data modeling: a data model for community services and environment monitoring in smart city. In: 2015 IEEE International Conference on Autonomic Computing. IEEE, pp 301–306 – reference: Alsamhi S, Ma O, Ansari M, Almalki F (2019) Survey on collaborative smart drones and internet of things for improving smartness of smart cities. IEEE Access – reference: Kim H, Mokdad L, Ben-Othman J (2018) Designing UAV surveillance frameworks for smart city and extensive ocean with differential perspectives. IEEE Commun Mag:99 – reference: RoldánJJPeña-TapiaEGarcia-AunonPDel CerroJBarrientosABringing adaptive & immersive interfaces to real-world multi-robot scenarios: application to surveillance and intervention in infrastructuresIEEE Access201972169353610.1109/ACCESS.2019.2924938 – reference: ChowJYDynamic UAV-based traffic monitoring under uncertainty as a stochastic arc-inventory routing policyInt J Transp Sci Technol20165316718510.1016/j.ijtst.2016.11.002 – reference: PasnakIJustification possibility of using drones to study the parameters of traffic2017 – reference: Xiaoyuan Y, Jiwei D, Tianjie Y, Qingfu Q (2016) A method for improving detection of gas concentrations using quadrotor. In: 2016 IEEE Information Technology, Networking, Electronic and Automation Control Conference. IEEE, pp 971–975 – reference: VillaTFGonzalezFMiljievicBRistovskiZDMorawskaLAn overview of small unmanned aerial vehicles for air quality measurements: Present applications and future prospectivesSensors2016167107210.3390/s16071072 – reference: RoldánJJCrespoEMartín-BarrioAPeña-TapiaEBarrientosAA training system for industry 4.0 operators in complex assemblies based on virtual reality and process miningRobot Comput Integr Manuf20195930531610.1016/j.rcim.2019.05.004 – reference: McLaren D, Agyeman J (2015) Sharing cities: a case for truly smart and sustainable cities. MIT Press – reference: UrraOIlarriSSpatial crowdsourcing with mobile agents in vehicular networksVeh Commun2019171034 – reference: PajaresGOverview and current status of remote sensing applications based on unmanned aerial vehicles (UAVs)Photogramm Eng Remote Sens201581428133010.14358/PERS.81.4.281 – reference: DedeCImmersive interfaces for engagement and learningscience20093235910666910.1126/science.1167311 – reference: LagkasTArgyriouVBibiSSarigiannidisPUAV IoT framework views and challenges: towards protecting drones as “things”Sensors20181811401510.3390/s18114015 – reference: Mohammed F, Idries A, Mohamed N, Al-Jaroodi J, Jawhar I (2014) UAVs for smart cities: opportunities and challenges. In: 2014 International Conference on Unmanned Aircraft Systems (ICUAS). IEEE, pp 267–273 – reference: BarmpounakisENVlahogianniEIGoliasJCBabinecAHow accurate are small drones for measuring microscopic traffic parameters?Transp Lett201911633234010.1080/19427867.2017.1354433 – reference: Roldán J, Garcia-Aunon P, Peña-Tapia E, Barrientos A (2019) Swarmcity project: can an aerial swarm monitor traffic in a smart city? In: 2019 IEEE International Conference on Pervasive Computing and Communications. 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| Title | SwarmCity project: monitoring traffic, pedestrians, climate, and pollution with an aerial robotic swarm |
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