Emerging technologies for AI-enabled Big Data Analytics in IoT: Their integration and challenges

Scope

The Artificial Intelligence (AI), Internet of Things (IoT), and Big Data analytics are the latest trending technologies making human lives and society comfortable. They are attracting immense research interest and have found their presence in numerous applications such as healthcare, transportation, manufacturing, energy, and automation, among others. AI-enabled IoT (AIoT) with Big Data are paving the path for a wide set of new opportunities, both for novel services/applications and increased efficiency/scalability. These opportunities include locally sharing information, collaborating, generating, consuming a huge amount of data and learning from a massive amount of data in real time to quickly identify innovative, emerging and unforeseen patterns. Indeed, distributed big data analytics, modern machine learning (ML) techniques, real-time data collection and processing, scalability and distributed security solutions such as blockchain, and distributed secure data processing, play a significant role. However, successful decision-making needs to combine the best qualities of both human and digital knowledge. To do so, it is vital to structure any type of relevant and reliable knowledge and incorporate it as part of decision analytics Indeed, there is an increasing recognition of utilizing knowledge whenever available or can be created purposefully. This includes contextual and organizational information that analytics by itself does not provide.

AIoT & BD track is devoted to increase the understanding and impact of emerging technologies for IoT, AI, Big Data Analytics, Data Science, Blockchain, Educational Technologies, Knowledge Management, etc. for individuals, organizations, and society and how these technologies have evolved. This track aims to provide researchers and practitioners with opportunities to discuss, attract, and explore areas related to ideas, concepts, theories, methodologies, and applications of multidisciplinary contributions on emerging technologies and intelligent systems. We hence encourage original paper submissions, which have not been published or submitted for publication elsewhere, from both academia and industry presenting novel research addressing the aforementioned challenges

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Topics

AIoT for emerging applications of smart city

Large-scale sensor networks for AIoT and Big Data Analytics

Fog, edge, and cloud computing paradigms for AIoT and Big Data Analytics

Beyond 5G technologies for edge-assisted AIoT applications

Unmanned Aerial Vehicle (UAV)-assistant AIoT applications

Security and privacy in AIoT

Emerging applications for mining edge and cloud-assisted data in IoT

AIoT-based innovative applications and services

Novel ML/DL techniques for Big Data analytics and IoT

Publication

All registered papers will be submitted for publishing by Springer and made available through SpringerLink Digital Library.

Proceedings will be submitted for inclusion in leading indexing services, such as Web of Science, Compendex, Scopus, DBLP, EU Digital Library, Google Scholar, IO-Port, MathSciNet, Inspec, and Zentralblatt MATH.

Authors of selected best accepted and presented papers will be invited to submit an extended version to:

Wireless Networks (WINET) Journal [IF: 2.602 (2020)]

All accepted authors are eligible to submit an extended version in a fast track of:

EAI Endorsed Transactions on Industrial Networks and Intelligent Systems (Open Access) – recently accepted for inclusion in Scopus
EAI Endorsed Transactions on Internet of Things (Open Access)

Additional publication opportunities:

EAI/Springer Innovations in Communications and Computing Book Series
(titles in this series are indexed in Ei Compendex, Web of Science & Scopus)

Paper submission

Papers should be submitted through EAI ‘Confy+‘ system, and have to comply with the Springer format (see Author’s kit section).

All conference papers undergo a thorough peer review process prior to the final decision and publication. This process is facilitated by experts in the Technical Program Committee during a dedicated conference period. Standard peer review is enhanced by EAI Community Review which allows EAI members to bid to review specific papers. All review assignments are ultimately decided by the responsible Technical Program Committee Members while the Technical Program Committee Chair is responsible for the final acceptance selection. You can learn more about Community Review here.