Theconcept of the smart city is widely favored, as it enhances the quality of life of urban citizens, involvingmultiple disciplines, that\nis, smart community, smart transportation, smart healthcare, smart parking, and many more. Continuous growth of the complex\nurban networks is significantly challenged by real-time data processing and intelligent decision-making capabilities. Therefore, in\nthis paper, we propose a smart city framework based on Big Data analytics.The proposed framework operates on three levels: (1)\ndata generation and acquisition level collecting heterogeneous data related to city operations, (2) data management and processing\nlevel filtering, analyzing, and storing data to make decisions and events autonomously, and (3) application level initiating execution\nof the events corresponding to the received decisions. In order to validate the proposed architecture, we analyze a fewmajor types of\ndataset based on the proposed three-level architecture. Further, we tested authentic datasets onHadoop ecosystem to determine the\nthreshold and the analysis shows that the proposed architecture offers useful insights into the community development authorities\nto improve the existing smart city architecture
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