Abstract
Big data-driven futuristic fabric system (B_FFS) is the most immersive technological solutions that give seamless, real-time integration, and massive data access across the diverse big data sources using artificial intelligence, Internet of Things (IoT), information science, statistics, pattern recognition, collaborative learning, database, security, cognitive technologies, knowledge acquisition, and data visualization technology. Society is endlessly upgrading with a faster way under digital transformation using digital communication and infrastructures. The B_FFS consists of data access, discovery, orchestration, ingestion, processing, management, and intelligence.
The B_FFS is continuously gathering digital social data in high-velocity, high-volume, and high-variety from computer-based communications and social media interactions. The B_FFS datasets having massive user information. The process of B_FFS consists of three stages like data acquisition; data mining; and data validation. An intelligent B_FFS improves the business decision support process by extracting meaningful user information from different sources. The information is coming from the various sources via sensors used to accumulate traffic, health, weather, transportation data, and posts to various social media sites.
This special issue focuses on the recent development of B_FFS for increasing the massive data integration in a single platform smoothly and intelligently. Thus, we here are seeking the most impactful and newest findings on how to process and visualize the B_FFS using emerging Artificial intelligence/computational intelligence in the Internet of Things.
This special issue seeks original unpublished papers focusing on theoretical analysis, emerging applications, novel system architecture construction and design, experimental studies, and social impacts of big social data analytics and visualization services. Topic areas include, but are not limited to, the following
Health, transportation, traffic information processing in B_FFS
Digital Communications and Digital Transportation for IoT-B_FFS
Collaborative learning-assisted B_FFS management
Health, transportation, traffic information processing in B_FFS
AI-enabled B_FFS service management
Decision support systems and ontology for B_FFS
Digital Buildings and Digital Factory for B_FFS Digital Twins, Digital Identity, Digital Culture for B_FFS
Big data leakage resilient methodologies for B_FFS
Data leakage detection from Cloud, edge, fog, IoT, or Mobile applications
Semantic web and Data mining for B_FFS
Multimedia B_FFS analytics
Digital Misinformation and Fake News for B_FFS
Computational intelligence in remote B_FFS analytics
Complex social data analysis for B_FFS
Robust optimization techniques for B_FFS analytics
Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers. Paper submissions for this special issue should follow the submission format and guidelines. Please visit our website at www.liebertpub.com/big for more information.