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Scientific Article details

Title IoTcloud platform for information processing in smart city
ID_Doc 39971
Authors Chen, XC; Zhang, SQ; Ding, XH; Kadry, SN; Hsu, CH
Title IoTcloud platform for information processing in smart city
Year 2021
Published Computational Intelligence, 37, 3
DOI 10.1111/coin.12387
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.
Author Keywords mobility management; modern carriage systems; transportation and traffic pattern
Index Keywords Index Keywords
Document Type Other
Open Access Open Access
Source Science Citation Index Expanded (SCI-EXPANDED)
EID WOS:000555525100001
WoS Category Computer Science, Artificial Intelligence
Research Area Computer Science
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