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活动简介

Internet of Things (IoT) is a platform and a phenomenon that allows everything to process information, communicate data, analyze context collaboratively and in the service or individuals, organizations and businesses. In the process of doing so, a large amount of data with different formats and content has to be processed efficiently, quickly and intelligently through advanced algorithms, techniques, models and tools. This new paradigm is enabled by the maturity of several different technologies, including the internet, wireless communication, cloud computing, sensors, big data analytics and machine learning algorithms.

征稿信息

重要日期

2016-11-21
终稿截稿日期

征稿范围

AREA 1: BIG DATA RESEARCH

  • Big Data fundamentals – Services Computing, Techniques, Recommendations and Frameworks

  • Modeling, Experiments, Sharing Technologies & Platforms

  • SQL/NoSQL databases, Data Processing Techniques, Visualization and Modern Technologies

  • Analytics, Intelligence and Knowledge Engineering

  • Data Center Enabled Technologies

  • Sensor, Wireless Technologies, APIs

  • Networking and Social Networks

  • Data Management for Large Data

  • Security, Privacy and Risk

  • Software Frameworks (MapReduce, Spark etc) and Simulations

  • Modern Architecture

  • Volume, Velocity, Variety, Veracity and Value

  • Social Science and Implications for Big Data

 

AREA 2: EMERGING SERVICES AND ANALYTICS

  • Health Informatics as a Service (HIaaS) for any Type of Health Informatics, Computation and Services

  • Big Data as a Service (BDaaS) including Frameworks, Empirical Approaches and Data Processing Techniques

  • Big Data Algorithm, Methodology, Business Models and Challenges

  • Security as a Service including any Algorithms, Methodology and Software Proof-of-concepts

  • Financial Software as a Service (FSaaS) including Risk and Pricing Analysis; Predictive Modeling

  • Education as a Service (EaaS) including e-Learning and Educational Applications

  • Business Process as a Service (BPaaS) including Workflows and Supply Chain in IoT and Big Data

  • Software Engineering Approaches, including Formal Methods, Agile Methods and Theoretical Algorithms for IoT and Big Data

  • Natural Science as a Service (NSaaS) including Weather Forecasting and Weather Data Visualization

  • System Design and Architecture

  • Mobile APIs, Apps, Systems and Prototype

  • Gaming as a Service (GaaS)

  • Framework (conceptual, logical or software)

  • Analytics as a Service (AaaS) for any Types of Analytics

  • Electronic, Logic, Robotic and Electrical Infrastructure, Platforms and Applications

  • Energy-saving and Green IT Systems or Applications

  • Middleware and Agents for IoT and Big Data, Grid and Cluster Computing

  • Integration as a Service (data; service; business; federated IoT and Big Data)

  • Scheduling, Service Duplication, Fairness, Load Balance for SaaS and Analytics

  • Tenant Application Development including Customization, Verification, Simulation, and testing on SaaS and Analytics

  • IaaS, PaaS and SaaS quality of service (QoS), security, reliability, availability, service bus mechanisms

  • Social Networks and Analytics

  • User Evaluations and Case Studies

  • IaaS, PaaS and SaaS, Big Data and Analytics demonstrations and Research Discussions from Computing Scientists, Business IS Academics and Industrial Consultants

  • Wireless Systems and Applications

  • e-Government, e-Commerce, e-Science and Creative Technologies for IoT and Big Data

  • Data as a Service and Decision as a Service

  • IoT Services and Applications

  • New Service Models

  • Software Engineering for Big Data Analytics

  • SOA based approaches to IoT BD

  • Social informatics, challenges and recommendations for IoT

  • Any emerging services

 

AREA 3: BIG DATA FOR MULTI-DISCIPLINE SERVICES

  • Smart City and Transportation

  • Education and Learning

  • Business, Finance and Management

  • Large-scale Information Systems and Applications

  • Energy, Environment and Natural Science Applications

  • Social Networks Analysis, Media and e-Government

  • Proofs-of-concepts and Large-scale Experiments

  • Risk Modeling, Simulation, Legal Challenges

  • Open data: Issues, Services and Solutions

  • Earth Science Simulation and Processing

  • GPUs and Visualization

  • Case Studies of Real Adoption

  • Biomedical Experiments and Simulations

  • Healthcare Services and Health Informatics

  • Cancer and Tumor Studies with Big Data

  • DNA Sequencing, Organ Simulations and Processing

  • Volume, Velocity, Variety and Veracity 

 

AREA 4: INTERNET OF THINGS (IOT) FUNDAMENTALS

  • Network Design and Architecture

  • Software Architecture and Middleware

  • Mobile Services

  • Data and Knowledge Management

  • Context-awareness and Location-awareness

  • Security, Privacy and Trust

  • Performance Evaluation and Modeling

  • Networking and Communication Protocols

  • Machine to Machine Communications

  • Intelligent Systems for IoT and Services Computing

  • Energy Efficiency

  • Social Implications for IoT

  • Future of IoT and Big Data

 

AREA 5: INTERNET OF THINGS (IOT) APPLICATIONS

  • Technological focus for Smart Environments

  • Next Generation Networks

  • Smart City Examples and Case Studies

  • Data Analysis and Visualization for Smart City, Green Systems and Transport Systems

  • Architecture for secure and interactive IoT

  • Intelligent Infrastructure and Guidance Systems

  • Traffic Theory, Modeling and Simulation

  • Sensor Networks, Remote Diagnosis and Development

  • Transportation Management

  • Pattern Recognition and Behavioral Investigations for Vehicles, Green Systems and Smart City

 

AREA 6: ITS TECHNOLOGIES

  • 3D printing

  • Artificial Intelligence

  • Biotechnology

  • Communication

  • Data Processing

  • Electronic Technologies for in-vehicle

  • Internet of Things

  • Mode-to-Mode Systems

  • Nanotechnology

  • Sensors

  • Transport Safety and Mobility

  • Vehicle-to-Infrastructure

  • Vehicle-to-Vehicle

 

AREA 7: SECURITY, PRIVACY AND TRUST

  • Algorithms, software engineering and development

  • System design and implementation

  • Testing (software engineering; penetration; product development)

  • Encryption (all aspects)

  • Firewall, access control, identity management

  • Experiments of using security solutions and proof-of-concepts

  • Large-scale simulations in the Cloud, Big Data and Internet of Things

  • Intrusion and detection techniques

  • Social engineering and ethical hacking: techniques and case studies 

  • Software engineering for security modeling, business process modeling and analytics

  • Trust and privacy

  • Location-based privacy

  • Data security, data recovery, disaster recovery

  • Adoption challenges and recommendation

  • Information systems related issues  

  • Conceptual frameworks and models

  • Emerging issues and recommendations for organizational security

  • E-Commerce and online banking

  • Social network analysis, emerging issues in social networks

  • Education and e-Learning

  • Surveys and their quantitative analysis

  • Architecture (technical or organizational)

  • Case Studies

作者指南

Authors should submit a paper in English, carefully checked for correct grammar and spelling, addressing one or several of the conference areas or topics. Each paper should clearly indicate the nature of its technical/scientific contribution, and the problems, domains or environments to which it is applicable. To facilitate the double-blind paper evaluation method, authors are kindly requested to produce and provide the paper WITHOUT any reference to any of the authors, including the authors’ personal details, the acknowledgments section of the paper and any other reference that may disclose the authors’ identity. 

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重要日期
  • 会议日期

    04月24日

    2017

    04月26日

    2017

  • 11月21日 2016

    终稿截稿日期

  • 04月26日 2017

    注册截止日期

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