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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