Poli/COPPE-Universidade Federal do Rio de Janeiro, Av. Athos da Silveira Ramos 149, Rio de Janeiro 21941-972, Brazil.
DETEL/PEL-Universidade do Estado do Rio de Janeiro, Rua São Francisco Xavier 524, Rio de Janeiro 20550-013, Brazil.
Sensors (Basel). 2018 Jun 20;18(6):1976. doi: 10.3390/s18061976.
A cost-effective approach to gather information in a smart city is to embed sensors in vehicles such as buses. To understand the limitations and opportunities of this model, it is fundamental to investigate the spatial coverage of such a network, especially in the case where only a subset of the buses have a sensing device embedded. In this paper, we propose a model to select the right subset of buses that maximizes the coverage of the city. We evaluate the model in a real scenario based on a large-scale dataset of more than 5700 buses in the city of Rio de Janeiro, Brazil. Among other findings, we observe that the fleet of buses covers approximately 5655 km of streets (approximately 47% of the streets) and show that it is possible to cover 94% of the same streets if only 18% of buses have sensing capabilities embedded.
在智慧城市中,一种经济有效的信息收集方法是在公交车等车辆中嵌入传感器。为了了解这种模式的局限性和机会,研究这种网络的空间覆盖范围至关重要,特别是在只有一部分公交车嵌入了传感设备的情况下。在本文中,我们提出了一种选择能够最大化城市覆盖范围的正确公交车子集的模型。我们在基于巴西里约热内卢市超过 5700 辆公交车的大规模数据集的真实场景中评估了该模型。在其他发现中,我们观察到公交车队覆盖了大约 5655 公里的街道(约占街道的 47%),并表明如果只有 18%的公交车具有嵌入的传感功能,那么就有可能覆盖 94%的相同街道。