Keyword search (4,163 papers available)

"Sensors (Basel)" Category Publications:

Title Authors PubMed ID
1 On the Impact of Biceps Muscle Fatigue in Human Activity Recognition. Elshafei M, Costa DE, Shihab E 33557239
ENCS
2 Towards Detecting Biceps Muscle Fatigue in Gym Activity Using Wearables. Elshafei M, Shihab E 33498702
ENCS
3 Finite Element Modelling of Bandgap Engineered Graphene FET with the Application in Sensing Methanethiol Biomarker. Singh P, Abedini Sohi P, Kahrizi M 33467459
ENCS
4 A Benchmark of Data Stream Classification for Human Activity Recognition on Connected Objects. Khannouz M; Glatard T; 33202905
ENCS
5 Contactless Capacitive Electrocardiography Using Hybrid Flexible Printed Electrodes. Lessard-Tremblay M, Weeks J, Morelli L, Cowan G, Gagnon G, Zednik RJ 32927651
ENCS
6 Determining the Optimal Restricted Driving Zone Using Genetic Algorithm in a Smart City. Azami P, Jan T, Iranmanesh S, Ameri Sianaki O, Hajiebrahimi S 32316356
ENCS
7 A Quantitative Comparison of Overlapping and Non-Overlapping Sliding Windows for Human Activity Recognition Using Inertial Sensors. Dehghani A, Sarbishei O, Glatard T, Shihab E 31752158
ENCS
8 Characterization and Efficient Management of Big Data in IoT-Driven Smart City Development. Alsaig A, Alagar V, Chammaa Z, Shiri N 31141899
CONCORDIA
9 A Crowdsensing Based Analytical Framework for Perceptional Degradation of OTT Web Browsing. Li K, Wang H, Xu X, Du Y, Liu Y, Ahmad MO 29762493
ENCS
10 Fast Feature-Preserving Approach to Carpal Bone Surface Denoising. Salim I, Hamza AB 30037109
ENCS
11 Big Data-Driven Cellular Information Detection and Coverage Identification. Wang H, Xie S, Li K, Ahmad MO 30813353
ENCS
12 Surface Profiling and Core Evaluation of Aluminum Honeycomb Sandwich Aircraft Panels Using Multi-Frequency Eddy Current Testing. Reyno T, Underhill PR, Krause TW, Marsden C, Wowk D 28906434
PHYSICS

 

Title:Characterization and Efficient Management of Big Data in IoT-Driven Smart City Development.
Authors:Alsaig AAlagar VChammaa ZShiri N
Link:https://www.ncbi.nlm.nih.gov/pubmed/31141899?dopt=Abstract
Publication:
Keywords:
PMID:31141899 Category:Sensors (Basel) Date Added:2019-06-07
Dept Affiliation: CONCORDIA
1 Concordia University, 1455 De Maisonneuve Boul. W, Montreal, QC H3G 1M8, Canada. alaasaig@hotmail.com.
2 Jeddart University, Hamzah Ibn Al Qasim Street, Al Sharafeyah, Jeddah 23218, Saudi Arabia. alaasaig@hotmail.com.
3 Concordia University, 1455 De Maisonneuve Boul. W, Montreal, QC H3G 1M8, Canada. alagar@cs.concordia.ca.
4 Concordia University, 1455 De Maisonneuve Boul. W, Montreal, QC H3G 1M8, Canada. zakichammaa@gmail.com.
5 Concordia University, 1455 De Maisonneuve Boul. W, Montreal, QC H3G 1M8, Canada. shiri@cse.concordia.ca.

Description:

Characterization and Efficient Management of Big Data in IoT-Driven Smart City Development.

Sensors (Basel). 2019 May 28;19(11):

Authors: Alsaig A, Alagar V, Chammaa Z, Shiri N

Abstract

Smart city is an emerging initiative for integrating Information and Communication Technologies (ICT) in effective ways to support development of smart cities with enhanced quality of life for its citizens through safe and secure context-aware services. Major technical challenges to realize smart cities include resource use optimization, service delivery without interruption at all times in all aspects, minimization of costs, and reduction of resource consumption. To address these challenges, new techniques and technologies are required for modeling and processing the big data generated and used through the underlying Internet of Things (IoT). To this end, we propose a data-centric approach to IoT in conceptualizing the "things" from a service-oriented perspective and investigate efficient ways to identify, integrate, and manage big data. The data-centric approach is expected to better support efficient management of data with complexities inherent in IoT-generated big data. Furthermore, it supports efficient and scalable query processing and reasoning techniques required in development of smart city applications. This article redresses the literature and contributes to the foundations of smart cities applications.

PMID: 31141899 [PubMed]





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