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.
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
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.
04月24日
2017
04月26日
2017
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