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Smart Cities have emerged as a strategy to solve problems that current cities face, such as traffic, resource management, waste, pollution, etc. Most of the Smart City proposals are based on placing sensors in fixed locations of the city or, at the most, in public transportation systems. These strategies can produce blind zones, given that the sensors are fixed or their movement cannot be controlled. The SwarmCity Project proposes the use of an aerial swarm to monitor the city state, including traffic, crowds, climate and pollution. This paper is focused on traffic and tries to answer the question: “Can an aerial swarm monitor the traffic in a Smart City?”. The work presents a data processing algorithm developed and optimized to fuse the data provided by the drones and build maps of traffic in real time. The proposed method is integrated with a surveillance algorithm and tested under different conditions in a city simulator. The results demonstrate the viability of SwarmCity Project and the potential use of aerial swarms as tools to collect data and model traffic in Smart Cities.
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Roldán et al. (2019) studied this question.
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