Journals Proceedings

Abstract

The concept of smart city is widely favored, as it enhances the quality of urban citizens’ life, involving multiple disciplines. Consequent to the complex urban networks, data processing complexity has increased significantly. Thus, it creates a crucial demand to facilitate autonomous decision-making and real-time data processing and analysis of smart cities. Therefore, in this paper we propose a smart city framework based on Big Data analytics. The proposed framework operates in three levels 1) Data generation and acquisition level, 2) Data management and processing level, and 3) Application level. Moreover, we analyzed the water consumption, traffic congestion, and air pollution data of Surrey (Canada) and Aarhus (Denmark) cities to determine the threshold values for data filtering. The analysis shows that the proposed architecture offers useful insights to the community development authorities to improve the existing smart city architecture.