SwarmCity project: monitoring traffic, pedestrians, climate, and pollution with an aerial robotic swarmData collection and fusion in a smart city, and its representation using virtual reality

被引:0
作者
Juan Jesús Roldán-Gómez
Pablo Garcia-Aunon
Pablo Mazariegos
Antonio Barrientos
机构
[1] Centre for Automation and Robotics (CAR),Department of Computer Engineering
[2] Universidad Politécnia de Madrid (UPM),undefined
[3] Autonomous University of Madrid,undefined
来源
Personal and Ubiquitous Computing | 2022年 / 26卷
关键词
Smart city; Robot swarm; Swarm intelligence; Data fusion; Immersive interface; Virtual reality;
D O I
暂无
中图分类号
学科分类号
摘要
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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收藏
页码:1151 / 1167
页数:16
相关论文
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  • [1] Anthopoulos L(2017)Smart utopia vs smart reality: learning by experience from 10 smart city cases Cities 63 128-148
  • [2] Petrolo R(2017)Towards a smart city based on cloud of things, a survey on the smart city vision and paradigms Trans Emerg Telecommun Technol 28 e2931-484
  • [3] Loscri V(2015)Smart environment monitoring system by employing wireless sensor networks on vehicles for pollution free smart cities Procedia Eng 107 480-3417
  • [4] Mitton N(2018)Comparison of heuristic algorithms in discrete search and surveillance tasks using aerial swarms Appl Sci 8 2076-118
  • [5] Jamil MS(2018)Control optimization of an aerial robotic swarm in a search task and its adaptation to different scenarios J Comput Sci 29 107-713
  • [6] Jamil MA(2018)Towards sustainable smart cities: a review of trends, architectures, components, and open challenges in smart cities Sustain Cities Soc 38 697-34
  • [7] Mazhar A(2019)Spatial crowdsourcing with mobile agents in vehicular networks Veh Commun 17 10-73
  • [8] Ikram A(2019)Location-aware network of drones for consumer applications: supporting efficient management between multiple drones IEEE Consumer Electron Mag 8 68-185
  • [9] Ahmed A(2018)UAV IoT framework views and challenges: towards protecting drones as “things” Sensors 18 4015-198
  • [10] Munawar U(2016)Dynamic UAV-based traffic monitoring under uncertainty as a stochastic arc-inventory routing policy Int J Transp Sci Technol 5 167-36