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On the Impact of Biceps Muscle Fatigue in Human Activity Recognition.

Author(s): Elshafei M, Costa DE, Shihab E

Nowadays, Human Activity Recognition (HAR) systems, which use wearables and smart systems, are a part of our daily life. Despite the abundance of literature in the area, little is known about the impact of muscle fatigue on these systems' performance. I...

Article GUID: 33557239
Towards Detecting Biceps Muscle Fatigue in Gym Activity Using Wearables.

Author(s): Elshafei M, Shihab E

Fatigue is a naturally occurring phenomenon during human activities, but it poses a bigger risk for injuries during physically demanding activities, such as gym activities and athletics. Several studies show that bicep muscle fatigue can lead to various inj...

Article GUID: 33498702
Finite Element Modelling of Bandgap Engineered Graphene FET with the Application in Sensing Methanethiol Biomarker.

Author(s): Singh P, Abedini Sohi P, Kahrizi M

In this work, we have designed and simulated a graphene field effect transistor (GFET) with the purpose of developing a sensitive biosensor for methanethiol, a biomarker for bacterial infections. The surface of a graphene layer is functionalized by manipula...

Article GUID: 33467459
A Benchmark of Data Stream Classification for Human Activity Recognition on Connected Objects.

Author(s): Khannouz M; Glatard T;

This paper evaluates data stream classifiers from the perspective of connected devices, focusing on the use case of Human Activity Recognition. We measure both the classification performance and resource consumption (runtime, memory, and power) of five usua...

Article GUID: 33202905
Contactless Capacitive Electrocardiography Using Hybrid Flexible Printed Electrodes.

Author(s): Lessard-Tremblay M, Weeks J, Morelli L, Cowan G, Gagnon G, Zednik RJ

Traditional capacitive electrocardiogram (cECG) electrodes suffer from limited patient comfort, difficulty of disinfection and low signal-to-noise ratio in addition to the challenge of integrating them in wearables. A novel hybrid flexible cECG electrode wa...

Article GUID: 32927651
Determining the Optimal Restricted Driving Zone Using Genetic Algorithm in a Smart City.

Author(s): Azami P, Jan T, Iranmanesh S, Ameri Sianaki O, Hajiebrahimi S

Sensors (Basel). 2020 Apr 16;20(8): Authors: Azami P, Jan T, Iranmanesh S, Ameri Sianaki O, Hajiebrahimi S

Article GUID: 32316356
A Quantitative Comparison of Overlapping and Non-Overlapping Sliding Windows for Human Activity Recognition Using Inertial Sensors.

Author(s): Dehghani A, Sarbishei O, Glatard T, Shihab E

Sensors (Basel). 2019 Nov 18;19(22): Authors: Dehghani A, Sarbishei O, Glatard T, Shihab E

Article GUID: 31752158
Characterization and Efficient Management of Big Data in IoT-Driven Smart City Development.

Author(s): Alsaig A, Alagar V, Chammaa Z, Shiri N

Sensors (Basel). 2019 May 28;19(11): Authors: Alsaig A, Alagar V, Chammaa Z, Shiri N

Article GUID: 31141899
A Crowdsensing Based Analytical Framework for Perceptional Degradation of OTT Web Browsing.

Author(s): Li K, Wang H, Xu X, Du Y, Liu Y, Ahmad MO

Sensors (Basel). 2018 May 15;18(5): Authors: Li K, Wang H, Xu X, Du Y, Liu Y, Ahmad MO

Article GUID: 29762493
Fast Feature-Preserving Approach to Carpal Bone Surface Denoising.

Author(s): Salim I, Hamza AB

Sensors (Basel). 2018 Jul 21;18(7): Authors: Salim I, Hamza AB

Article GUID: 30037109
Big Data-Driven Cellular Information Detection and Coverage Identification.

Author(s): Wang H, Xie S, Li K, Ahmad MO

Sensors (Basel). 2019 Feb 22;19(4): Authors: Wang H, Xie S, Li K, Ahmad MO

Article GUID: 30813353
Surface Profiling and Core Evaluation of Aluminum Honeycomb Sandwich Aircraft Panels Using Multi-Frequency Eddy Current Testing.

Author(s): Reyno T, Underhill PR, Krause TW, Marsden C, Wowk D

Sensors (Basel). 2017 Sep 14;17(9): Authors: Reyno T, Underhill PR, Krause TW, Marsden C, Wowk D

Article GUID: 28906434
Title:Characterization and Efficient Management of Big Data in IoT-Driven Smart City Development.
Authors:Alsaig A,  Alagar V,  Chammaa Z,  Shiri N
Link:https://www.ncbi.nlm.nih.gov/pubmed/31141899?dopt=Abstract
Category:Sensors (Basel)
PMID:31141899
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]