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Title Object tracking sensor networks in smart cities: Taxonomy, architecture, applications, research challenges and future directions
ID_Doc 40418
Authors Adam, MS; Anisi, MH; Ali, I
Title Object tracking sensor networks in smart cities: Taxonomy, architecture, applications, research challenges and future directions
Year 2020
Published
DOI 10.1016/j.future.2017.12.011
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 smarter. 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. (c) 2017 Elsevier B.V. All rights reserved.
Author Keywords Object tracking sensor network; Smart city; Monitoring; Object recovery; Energy
Index Keywords Index Keywords
Document Type Other
Open Access Open Access
Source Science Citation Index Expanded (SCI-EXPANDED)
EID WOS:000527331800071
WoS Category Computer Science, Theory & Methods
Research Area Computer Science
PDF http://repository.essex.ac.uk/20917/1/1-s2.0-S0167739X17310385-main.pdf
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