An Effective Implementation of Intelligent Cost Optimization for Transformed Urban Transportation Network

The digital revolution has profoundly transformed many domains, promoting viable and sustainable solutions. Over the last few decades, a push in digital transformation in promoting the transportation sector has gained the brighter light of attention to enhance the safe and comfort access of entertainments. With the advent of cuttingedge technologies such as Internet-of-Things(IoT), Artificial Intelligence(AI), and Blockchain (BC)helps by by transforming the traditional systems into the secured and intelligent ecosystem However, many challenges, such as security, noninteroperability, and non-précised cost optimization, raise the quest for deploying the complete digital transformation process. To overcome this aforementioned challenge, this research article proposes a novel meta-heuristic framework that utilizes an ensemble of hybrid meta-heuristic techniques to impart the cost optimization for maintaining a sustainable transportation network in the evolving technological revolution. The comprehensive experimentation was conducted using Urban Tranportation datasets. The outcomes have been analysed qualitatively, to prove the efficacy of the suggested digital technologies and the factors that hinder the suggested digital transformation. Furthermore, suggested transformed framework has evaluated quantitatively and qualitatively. The proposed technology facilitates smart transportation (by enhancing 35% in reduced operations and 38% less time consumption), high passenger satisfaction index, and predictive analysis with high security and seamless communication. This paper explores the current landscape, benefits, barriers, and future trends of digital transformation in transportation, emphasizing its pivotal role in shaping the future of global transportation services.