Title
A Synergetic Orchestration Of Objects, Data, And Services To Enable Smart Cities
Abstract
Smart cities (SCs), as a novel solution built on top of large-scale Internet of Things (IoT) systems, experiences a rapid growth worldwide, in which, a synergetic orchestration among objects, data, and services is emphasized for innovative solutions to elevate the intelligence of cities based on the fusion of multisource and multimodal data. To enable such orchestration, this article proposes a smart service orchestration architecture (SSOA) to coordinate ubiquitous objects, create interlinked data, and implement versatile smart services. As a proof of concept of SSOA, an informed design platform (IDP) is presented to demonstrate how a smart service system can be designed and how a synergetic orchestration can be implemented to support an informed place design. Moreover, two dedicated mechanisms, namely, place utilization analysis mechanism (PUAM) and ensemble-based activity detection mechanism (EADM), are implemented in a multisource data processing flow to illustrate how massive geo-referenced data can be analyzed effectively and efficiently by machine learning algorithms to extract key information for a comprehensive data fusion required in using multimodal IoT systems. As evaluated, PUAM running in a distributed environment can dramatically improve the performance of geospatial clustering about 11 times from the baseline 53.6 to 4.7 s, and EADM with an ensemble activity classifier achieves the highest accuracy about 87.7% and also the highest f-score per activity category. Finally, various insights about the project testbed Jurong East, Singapore, are discussed to reveal its place design context.
Year
DOI
Venue
2019
10.1109/JIOT.2019.2939496
IEEE INTERNET OF THINGS JOURNAL
Keywords
Field
DocType
Ensemble learning, geospatial clustering, informed design, multisource data processing, place utilization and activity analysis, smart cities (SCs), social media data analysis, synergetic orchestration
Computer science,Orchestration (computing),Multimedia,Distributed computing
Journal
Volume
Issue
ISSN
6
6
2327-4662
Citations 
PageRank 
References 
0
0.34
0
Authors
5
Name
Order
Citations
PageRank
Linlin You1305.75
Bige Tunçer2182.14
Rui Zhu3167.74
Hexu Xing421.03
Chau Yuen54493263.28