International Workshop on IoT-enabled Big Data Analytics using Machine Learning for Smart Societies

Aim and Scope

Smart society is a viewpoint in which ICT-assisted skills are communicated with handlers in all aspects. Smart industry-leading scientific novelties offer peace of mind to senior living residents, staff, and families. To sustain novelties, they should permit the three mainstays of sustainability that are social, financial, and environmental sustainability. Smart cities and societies have become apparatuses for the quality of life of the citizens. The competency to produce and accumulate the data of community concern within the city area (for instance, community services, social events, and mobility) has amplified at an extraordinary rate and the data is hastily mounted to Big (society) Data. Big Data is a melting pot of a wide range of complex and inter-dependent issues and challenges of smart societies. The efficient processing of Big Data is a significant challenge among them. Sophisticated protocols are required that could solve these issues by providing intelligence to Big Data. Although numerous works are conducted or currently in progress for intelligent processing of Big Data, a lot of work still needs to be conducted to galvanize these applications around the globe, particularly using Big Data analytics techniques. To this end, state-of-the-art proposals for Big Data analytics need to be designed to guarantee intelligent data processing in smart societies.

The IoT comprises of a network associated with various kinds devices and sensors. The 5G aptitudes a radical addition of the band that is 100 times faster than 4G. The modern smart societies have been boosted due to the reduced latency, the high-speed broadband convergence, and higher aptitude. Social care and sustainable health is a significant component of the society. Smart social care agendas require to be industrialized and reinforced in a way that will mollify the today’s residents and coming generations’ demands. Enormous amounts of data are produced every day from personnel records, IoT devices, social networks, businesses, and the Internet in frequent measures and layouts. This surely postures a key test to the productivity of existing infrastructures and systems. IoT-enabled smart society management assimilates the digital traces generated by things and humans. The key purpose of the smart society to analyze the data and produce valuable insights and hidden patterns to offer services to society and overcome the existing challenges faced by the citizens of the societies. 

This special session aims to discover the promises of big data analytics in IoT-enabled smart cities and societies using machine leaning and come across innovative solutions for useful insights with flourishing results. Besides, the objectives include offering informative investigation and effective techniques that can support an efficient smart city and society architecture using big data analytics.

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Topics and keywords

• IoT-enabled Big Data analytics using Machine Learning
• Big Data analytics using Deep Learning for intelligent decision making
• Scalable edge intelligence using Big Data analytics smart society
• Advanced system modeling using Big Data analytics
• Smart city architectures using Machine Learning-enabled Big Data analytics
• The application of Big Data analytics in a smart society
• The innovative ecological architecture of smart society using Big Data analytics
• Big Data analytics in environmental pollution, in society
• Big Data analytics for community health strategy
• Big Data architectures and frameworks for a smart society
• Big Data analytics in cloud computing for city data management
• Big Data analytics for society economy, business, and finance policy management
• Novel Big Data analytics techniques for IoT-enabled smart cities and societies 
• Advanced scheduling methods for Big Data processing
• Efficient parallel and distributed mechanism for Big Data 
• Emerging architectures for Big Data management of smart city applications
• Security and privacy issues in Big Data of smart city
• Advanced resource allocation in smart cities infrastructures
• IoT-enabled applications for COVID-19 like epidemic
• IoT-enabled mass surveillance in smart health to preclude pandemic spread
• Emergency health management in smart healthcare
• Socio-economic challenges of smart health
• Distributed Computing for Big Data in Smart Healthcare
• Big Data Analytics in Diseases Prediction
• Big Data Collection in Wearable Sensors
• Remote Patient Monitoring using Big Data
• Predictive Modelling for Improving Healthcare using Big Data

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:

• Mobile Networks and Applications (MONET) Journal

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

• EAI Endorsed Transactions on Internet of Things (Open Access)
• EAI Endorsed Transactions on e-Learning (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.

Workshop Chairs

Dr. Muhammad Babar
Allama Iqbal Open University (AIOU), Pakistan

Mian Muhammad Aimal
Virtual University Lahore, Pakistan

Important dates

Full Paper Submission deadline
10 March 2022
Notification deadline
31 March 2022
Camera-ready deadline
28 April 2022
Start of Conference
29 July 2022
End of Conference
31 July 2022