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

Proceedings will be submitted for inclusion in leading indexing services, Ei Compendex, ISI Web of Science, Scopus, CrossRef, Google Scholar, DBLP, as well as EAI’s own EU Digital Library (EUDL).

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

• Wireless Networks (WINET) Journal (IF: 2.659)

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)
• EAI Endorsed Transactions on Internet of Things (Open Access)
• EAI Endorsed Transactions on Security and Safety (Open Access)

Additional publication opportunities:

• EAI/Springer Innovations in Communications and Computing Book Series

Track topics include, but are not limited to:

Track 1: Computational Intelligence in Intelligent Vehicles and Transportation Systems

• Advanced transportation information, communication and management systems
• Object recognitions such as pedestrian detection, traffic sign detection and recognition
• Multimodal intelligent transport systems and services
• Vehicle communications and connectivity
• Personalized driver and traveller support systems
• Air, road, and rail traffic management
• Simulation and forecasting models
• Driver assistance and automation systems
• Driver state detection and monitoring

Track 2: Computational Intelligence in IoT and Smart Cities

• Novel Architecture and Protocols of AI Integrated with IoT
• Security, Privacy, Access Control, and Trust Frameworks of IoT
• Resource Management Techniques of Using AI for IoT
• Control Schemes in IoT
• Smart Data Storage in IoT
• Software-Defined Networking in IoT
• Applications in Industrial IoT, in Smart Energy Efficiency, in Smart Grids, in Smart City, in Green Networks, in Connected Health, etc.

Track 3: Computational Intelligence in Big Data and Data Mining

• Efficient algorithms on reading, processing and analysis of big data
• Integration of multi-modal, multi-fidelity, and structured and unstructured big data
• Extracting and understanding from distributed, diverse and large-scale data resources
• Visualisation of big data and visual data analytics
• Human-computer interaction and collaboration in big data
• Applications of big data, such as industrial process, business intelligence, healthcare, bioinformatics and security.
• Classification, Clustering, Regression
• Feature learning and feature engineering
• Data mining from nonstationary and drifting environments

Track 4: Computational Intelligence in Control and Automation

• Intelligent Decision Making and Support
• Adaptive and Optimal Control
• Model-Predictive Control
• Fuzzy Systems and Control
• Expert and Decision Support Systems
• System Identification and Learning
• Fault Detection and Diagnosis
• Complex System Modelling
• Fuzzy Evolutionary Systems and Control
• Fuzzy Neural Systems and Control
• Hybrid Intelligent Control

Track 5: Computational Intelligence for Wireless System Communications

• Machine Learning for Networks
• V2X Communications
• Unmanned Aerial Vehicles
• Wireless Sensor Networks
• Low Power Wireless Area Networks
• Network Virtualization
• Quality of Service (QoS)
• Resources Management
• Embedded systems
• Software Defined Networks
• Blockchains
• Waveforms and Radio Access Technologies
• Software Defined Radio
• Visible Light Communication (VLC)
• Edge/Fog computing/networking
• RFID, NFC
• MIMO-based Networks
• Radio Interference Management
• Radio Access Networks

Track 6: Computational Intelligence on Cyber Security

• Intrusion/malware detection, prediction, classification, and response
• Models for survivable, resilient, and self-healing systems
• Sensor network security, web security, wireless and 4G, 5G media security
• Digital forensics, security information visualization
• Self-awareness, auto-defensiveness, self-reconfiguration, and self-healing networking paradigm
• Modelling adversarial behaviour for insider and outsider threat detection
• Cloud and virtualization security
• Block-chain security

Track 7: Computational Intelligence on Image and Pattern Recognition

• Feature ranking and weighting
• Feature selection, extraction, construction, and reduction
• Feature analysis on high-dimensional and large-scale data
• Evolutionary computation for feature analysis
• Neural networks for feature analysis
• Fuzzy logic for feature analysis
• Hybrid evolutionary computation and machine learning, information theory, statistics, mathematical modelling, etc., for feature analysis
• Feature analysis in classification, clustering, regression, image analysis, and other tasks
• Real-world applications of computational intelligence for feature analysis

Track 8: Computational Intelligence for Brain-Computer Interfaces

• Signal processing for Brain-Computer Interface (BCI)
• BCI Feature Extraction
• BCI Pattern Recognition
• BCI multi-view learning
• Multiple modalities for BCI
• Invasive and non-invasive BCIs.
• Online and offline BCI applications.

Computational intelligence is a computer science field by which a computer can learn a specific task from data or experimental observation. It addresses complex real-world problems in which mathematical or traditional modelling are not the preferred solution given that (i) the involved computational process might be too complex for mathematical reasoning; (ii) it might contain some uncertainties during the process, or (iii) by nature, the computational process is a randomly determined one (heuristic). EAI International Conference on Computational Intelligence and Communications (CICom 2020) provides solutions to various problems of this nature.

This event is organized by EAI.

EAI – European Alliance for Innovation is a non-profit organization and a professional community established in cooperation with the European Commission to empower the global research and innovation, and to promote cooperation between European and International ICT communities.

EAI’s vision is to foster excellence in research and innovation on the principles of transparency, objectivity, equality, and openness. Our guiding principle is community cooperation to create better research, provide fair recognition of excellence and transform best ideas into commercial value proposition.

EAI‘s mission is to create an environment that rewards excellence transparently, and builds recognition objectively regardless of age, economic status or country of origin, where no membership fees or closed door committees stand in the way of your research career.

Through these shared values, EAI leads the way toward advancing the world of research and innovation, empowering individuals and institutions for the good of society to fully benefit from the digital revolution.