Toward Sustainable Smart City: An Intelligent Transportation Model for Enabling Smart Services

Abstract

with the rapid growth of Information and Communication Technology (ICT) smart city applications has become imperative to ad dress the continually escalating urbanization demands worldwide. These increasing demands pose significant challenges to urban infrastructure, necessitating a sustainable approach for future Smart Cities. The surging service requirements inherent in the smart city paradigm necessitate effective monitoring and management of the constrained infrastructures within smart cities to uphold the Quality of Service (QoS) for essential services of smart cities. To address the exponential growth in ser vice demand and ensure the maintain QoS, it is essential to incorporate context-aware computing in conjunction with fog computing. In this pa per, authors envisioned to improve the QoS of traffic while employing a ML technique at the fog layer to manage the smart traffic services and an intelligent context-aware communication technique, which further improve the QoS of smart city. The aforesaid network simulated CloudSim and image process using python. The performance of the proposed scheme improves prediction efficacy by approximately 11% to 20% when compared to existing context sharing based algorithms.