title: A fast density-based clustering algorithm for real-time Internet of Things stream.
abstract: Data streams are continuously generated over time from Internet of Things (IoT) devices. The faster all of this data is analyzed, its hidden trends and patterns discovered, and new strategies created, the faster action can be taken, creating greater value for organizations. Density-based method is a prominent class in clustering data streams. It has the ability to detect arbitrary shape clusters, to handle outlier, and it does not need the number of clusters in advance. Therefore, density-based clustering algorithm is a proper choice for clustering IoT streams. Recently, several density-based algorithms have been proposed for clustering data streams. However, density-based clustering in limited time is still a challenging issue. In this paper, we propose a density-based clustering algorithm for IoT streams. The method has fast processing time to be applicable in real-time application of IoT devices. Experimental results show that the proposed approach obtains high quality results with low computation time on real and synthetic datasets.
authors.affiliation: Department of Information System, Faculty of Computer Science and Information Technology, University of Malaya, 50603 Kuala Lumpur, Malaysia.
authors.forename: Amineh
authors.identifier: 0000-0001-8427-5455
authors.initials: A
authors.lastname: Amini
authors.affiliation: Department of Information System, Faculty of Computer Science and Information Technology, University of Malaya, 50603 Kuala Lumpur, Malaysia.
authors.forename: Hadi
authors.identifier: 0000-0001-5173-0300
authors.initials: H
authors.lastname: Saboohi
authors.affiliation: Department of Information System, Faculty of Computer Science and Information Technology, University of Malaya, 50603 Kuala Lumpur, Malaysia.
authors.forename: Teh Ying
authors.initials: TY
authors.lastname: Wah
authors.affiliation: Department of Information System, Faculty of Computer Science and Information Technology, University of Malaya, 50603 Kuala Lumpur, Malaysia.
authors.forename: Tutut
authors.identifier: 0000-0001-9262-9137
authors.initials: T
authors.lastname: Herawan
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D020407:Internet; D008962:Models, Theoretical