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Object tracking sensor networks in smart cities: Taxonomy, architecture, applications, research challenges and future directions

Adam, MS and Anisi, MH and Ali, I (2017) 'Object tracking sensor networks in smart cities: Taxonomy, architecture, applications, research challenges and future directions.' Future Generation Computer Systems. ISSN 0167-739X

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Abstract

The development of pervasive communication devices and the emergence of the Internet of Things (IoT) have acted as an essential part in the feasibility of smart city initiatives. Wireless sensor network (WSN) as a key enabling technology in IoT offers the potential for cities to get smatter. WSNs gained tremendous attention during the recent years because of their rising number of applications that enables remote monitoring and tracking in smart cities. One of the most exciting applications of WSNs in smart cities is detection, monitoring, and tracking which is referred to as object tracking sensor networks (OTSN). The adaptation of OTSN into urban cities brought new exciting challenges for reaching the goal of future smart cities. Such challenges focus primarily on problems related to active monitoring and tracking in smart cities. In this paper, we present the essential characteristics of OTSN, monitoring and tracking application used with the content of smart city. Moreover, we discussed the taxonomy of OTSN along with analysis and comparison. Furthermore, research challenges are investigated concerning energy reservation, object detection, object speed, accuracy in tracking, sensor node collaboration, data aggregation and object recovery position estimation. This review can serve as a benchmark for researchers for future development of smart cities in the context of OTSN. Lastly, we provide future research direction.

Item Type: Article
Uncontrolled Keywords: Object tracking sensor network, Smart city, Monitoring, Monitoring, Energy
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Elements
Date Deposited: 22 Dec 2017 19:45
Last Modified: 20 Dec 2018 02:00
URI: http://repository.essex.ac.uk/id/eprint/20917

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