IoT cloud platform for information processing in smart city. (5th August 2020)

• Record Type: Journal Article
• Authors: Chen, Xiangcong; Zhang, Shuqing; Ding, Xiaohui; Kadry, Seifedine Nimer; Hsu, Ching‐Hsien
• Other Names: Srivastava Gautam guestEditor.; Hsu Ching‐Hsien (Robert) guestEditor.; Kumar Priyan Malarvizhi guestEditor.
• Is Part Of: Computational intelligence. Volume 37:Number 3(2021)
• Page Start: 1428
• Page End: 1444
• Publication Date: 2020-08-05
• Subjects: mobility management -- modern carriage systems -- transportation and traffic pattern; Artificial intelligence -- Periodicals; Computational linguistics -- Periodicals; 006.3
• DOI: 10.1111/coin.12387
• Languages: English
• ISSNs: 0824-7935

Abstract

Abstract: The construction of a sustainable transport network for people or goods will gain and harm mobility depending on their nature and implementation, using new technology and business models. The regular mobile handoff and replacement of connections allow the efficient mobility management of asynchronous wireless transfer mode (ATM) networks. Hence, the design of the broad spectrum usability network architecture for public ATM systems has been given considerable attention in the literature. Since it has been done on the critical subject of estimating user mobility and the prediction, which aims to improve communication efficiency and the bandwidth efficiency of the underlying system architecture, this article addresses the problem by developing the impact of hierarchical framework of service on transportation and traffic pattern (HFSTTP). The growth in mobile Internet and the use of mobile devices over the last decade allowed for omnipresent information on traffic. With the growing use of unique mobile apps, the number of routing users has evolved to be sufficiently large to interrupt the traffic flow pattern. Modern carriage systems and urban logistics improve the efficiency of the transport of goods and slow down the use of road infrastructure. Numerical examples of vehicle traffic include proof of ties between the network traffic and the routing decision‐making layer. The partnership between a cooperative control layer and a lower control layer to optimize freight transport is a second example. The congestion price in all over the world shows how to incorporate the social plan layer in future mobility services.