Journal ArticleDOI
Data-driven optimizations in IoT: a new frontier of challenges and opportunities
Sharda Tripathi,Swades De +1 more
TLDR
IoT data driven unique communication approaches and optimization techniques to reduce the data handling footprint, leading to communication bandwidth, cloud storage, and energy saving, without compromising the service quality are presented.Abstract:
Internet of Things (IoT) has gained tremendous popularity with the recent fast-paced technological advances in embedded programmable electronic and electro-mechanical systems, miniaturization, and their networking ability. IoT is expected to change the way of human activities by extensively networked monitoring, automation, and control. However, widespread application of IoT is associated with numerous challenges on communication and storage requirements, energy sustainability, and security. Also, IoT data traffic as well as the service quality requirements are application-specific. Through a few practical example cases, this article presents IoT data driven unique communication approaches and optimization techniques to reduce the data handling footprint, leading to communication bandwidth, cloud storage, and energy saving, without compromising the service quality. Subsequently, it discusses newer challenges that are needed to be tackled, to make the IoT applications practically viable for their wide-ranging adoption.read more
Citations
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Journal ArticleDOI
Adaptive Multivariate Data Compression in Smart Metering Internet of Things
TL;DR: Performance studies indicate that compared to the state-of-the-art, the proposed technique is able to achieve impressive bandwidth saving for transmission of data over communication network without compromising faithful reconstruction of data at the receiver.
Journal Article
Multi Label Deep Learning classification approach for False Data Injection Attacks in Smart Grid
TL;DR: In this article, a Deep Learning based Locational Detection technique is proposed to continuously recognize the specific areas of FDIA, which is based on the development area solver gap happiness is a False Data Detector (FDD) that incorporates a Convolutional Neural Network (CNN).
Journal ArticleDOI
Edge Intelligence Framework for Data-Driven Dynamic Priority Sensing and Transmission
TL;DR: A novel edge intelligence-based data-driven priority-aware sensing and transmission framework that saves up to 41% energy and 32% bandwidth with 68% data accuracy compared to the existing competitive frameworks for non-real-time systems.
Journal ArticleDOI
Channel-Adaptive Transmission Protocols for Smart Grid IoT Communication
Sharda Tripathi,Swades De +1 more
TL;DR: Novel channel prediction frameworks using stochastic modeling as well as data-driven learning of channel variability are proposed, which are complemented with an adaptive channel coding scheme to increase the transmission reliability of time-critical grid monitoring data over a wireless channel.
Journal ArticleDOI
A Data-Driven WSN Security Threat Analysis Model Based on Cognitive Computing
TL;DR: A simulation platform based on OMNeT++ to make up for the shortcomings of current WSN simulation platforms, improve the simulation capability of WSN security protocols, and provide a new technical means for designing and verifying security protocols is developed.
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