Call for Papers
page-template-default,page,page-id-16471,bridge-core-1.0.6,ajax_fade,page_not_loaded,,qode-theme-ver-18.2,qode-theme-bridge,disabled_footer_top,disabled_footer_bottom,qode_header_in_grid,wpb-js-composer js-comp-ver-6.0.5,vc_responsive

Call for Papers


The Intelligent Internet of Things (IoT) tsunami is affecting every aspect of our daily lives, ranging from smart cars, smart homes, smart cities, smart factories to smart health, and smart environments. Although IoT vastly expanded the possibilities to fulfill many of our needs, numerous challenges still should to be addressed in order to develop smart, consistent, suitable, safe, flexible and power-efficient systems. To enable this transformation and to better understand the untapped opportunities, the interdisciplinary landscape of IoT demands a large number of significant technological advancements in the hardware and software communities to come together and to synergize their efforts. COINS focuses on novel omni-layer techniques for smart IoT systems, by identifying new perspectives and highlighting impending research issues and challenges. In particular, this conference addresses all important aspects of novel IoT technologies from Connected Devices, to Edge/Fog, Cloud, and application, covering manufacturing, materials, CMOS and beyond-CMOS devices, architecture, embedded systems, reconfigurable hardware, network, cloud, Omni-layer artificial intelligence and machine learning, big data, emerging applications, as well as human-machine interaction. COINS also discusses the associated challenges that need to be overcome for achieving the goal of accuracy, privacy, reliability, and security. The three-day COINS event consists of a conference with plenary keynote speakers, invited papers, regular papers, panels, special hot-topic sessions, and workshops.



Topics of interest include but are not limited to

  • Internet of Things: From Device to Edge, and Cloud
    • 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
    • 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
  • VLSI, EDA, Embedded Systems, and Computer Architecture
    • System-Level Design Methodologies and High-Level Synthesis
    • Formal Methods and Verification Design and Test
    • Architectural and Microarchitectural Design
    • Domain and Application-specific Design
    • Low-power, Energy-efficient and Thermal-aware Design
    • Reconfigurable Systems Logical and Physical Analysis and Design
    • Network on Chip and Communication-Centric Design
    • Real-time and Dependable Systems
    • Circuits and systems for AI
    • Embedded Systems for Deep Learning
    • Hardware accelerators for AI
    • Neuromorphic processors
    • Hardware/software co-design and design automation for AI systems
    • Biological Systems and Electronics, Brain-Inspired Computing, and New Computing Paradigms
    • Embedded Software Architecture, Compilers and Toolchains
    • Cyber-Physical Systems Design
    • Test and Dependability Application Design
    • Robotics and Industry 4.0
    • Emerging devices, circuits, and architectures for IoT, Big Data, machine learning, and approximate computing
    • Application areas, e.g., automotive, avionics, energy, health care, mobile devices, multimedia, and autonomous systems
  • Cloud Computing
    • Cloud computing fundamentals e.g., Application Portability, privacy and security, Interoperability, Standards, QoS, and Resource Management
    • Cloud operations, management Platforms, Reliability, Cloud Automation, Hybrid Clouds and Integration
    • Edge an fog computing
    • Service modeling and analytics e.g., Service Modeling and Specification, Service Simulation, Cost Analysis, Service Performance Analytics
    • Mobile cloud computing
    • Mobile Cloud Architectures and Models
    • Mobile Commerce, Handheld Commerce, and e-markets on Cloud
    • Cloud computing platforms and applications such as Access Control, Design Patterns, Data Centers, Storage, and Networking Technologies, Middleware Frameworks, and Development Methods
    • Cloud computing enabling technologies such as API Management, Virtualization Technologies, Application Containers, Microservices and Lambda Functions, Cloud Optimization and Automation, Cloud Migration, Monitoring of Services, Quality of Service, Service Level Agreements
  • Big Data
    • Big Data fundamentals – Services Computing, Techniques, Recommendations and Framework
    • Modeling, Experiments, Sharing Technologies & Platforms
    • SQL/NoSQL databases, Data Processing Techniques, Visualization and Modern Technologies
    • 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
  • Artificial Intelligence, Machine Learning, Cognitive Computing, and Advanced Analytics
    • Mobile Data analysis, management, and processing for IoT
    • Information fusion for mobile data for IoT
    • Deep learning models, architectures and algorithms for Big Data for IoT
    • Brain-inspired representations learning of Big Data for IoT
    • Edge/for/cloud computing for Big Data and Smart Data for IoT
    • Security, privacy and trust in Big Data and Smart Data for IoT
    • Security, privacy and trust in the Internet of Things
    • Streaming data learning algorithms for IoT
    • Intelligent decision-making systems for Big Data and Smart Data in IoT
    • Prediction methods for Big Data and Smart Data applications in IoT
    • Evolutionary computing in Big Data in IoT
    • Swarm Intelligence and Big data for IoT
    • Handling uncertainty and incompleteness in Big Data and Smart Data for IoT
    • Applications of Fuzzy Set theory, Rough Set theory, and Soft Set theory in Smart Data for IoT
    • Open issues for Smart Data in IoT
    • Swarm Intelligence algorithms for cloud-based Internet of Things
    • Machine learning for cloud-based Internet of Things
    • Multi-agent systems for the cloud-based Internet of Things
    • Natural language processing for cloud-based Internet of Things
    • Cognitive aspects of AI in the cloud-based Internet of Things
    • Intelligent interfaces for cloud-based Internet of Things
    • Fuzzy systems for the cloud-based Internet of Things
    • Neural networks for cloud-based Internet of Things
    • Genetic algorithms for cloud-based Internet of Things
    • Deep learning for cloud-based Internet of Things
    • Heterogeneous memory systems design for AI in the cloud-based Internet of Things
  • Intelligent IoT eHealth
    • Internet of things for medical and healthcare applications
    • Novel devices and circuits, and architectural support for healthcare-aware IoT
    • Nano-CMOS and Post-CMOS based sensors, circuits, and controller
    • Wearable and implantable computing and biosensors
    • Cloud-enabled body sensor networks
    • Secure middleware for eHealth and IoT
    • Energy-efficient PHY/MAC and networking protocols for eHealth applications
    • Reprogrammable and reconfigurable embedded systems for eHealth
    • eHealth traffic characterization
    • eHealth oriented software architectures (Agent, SOA, Middleware, etc.)
    • Big-data analytics, machine learning algorithms, and scalable/parallel/distributed algorithms
    • Theory and practice of engineering semantic e-health systems, especially methods, means and best cases
    • Fog computing/Edge clouds for health care cloud resource allocation and monitoring
    • Privacy-preserving and Security approaches for large scale analytics
    • Fault tolerance, reliability, and scalability
    • Case studies of smart eHealth architectures (telemedicine applications, health management applications, etc.)
    • Autonomic analysis, monitoring and situation alertness
  • Blockchain
    • Recent development in Blockchain research
    • Recent development in IoT research
    • New Blockchain consensus protocols, platforms, and development tools
    • Throughout, latency and performance issues in Blockchain-based IoT systems
    • System design and implementation methods for Blockchain-based IoT systems
    • Blockchain in IoT device identity management and assent tracking
    • Blockchain in IoT supply chain management
    • Blockchain applications in IoT data privacy and security  Blockchain in peer-to-peer and M2M communications
    • IoT assisted Blockchain applications
    • Blockchain applications in banking, real estate, healthcare, and energy system
    • Blockchain in Smart home, smart building, smart city applications
    • Blockchain and IoT courses, curriculum and instructional tools
  • Omni-Layer 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


  • TBA



Doctoral Symposium 

COINS 2020 (Sponsored by IEEE CEDA) Doctoral Symposium provides doctoral students at different stages in their research an opportunity to present their problem statement, goals, methods, and results to receive constructive feedback on their current research and future research directions.

The Ph.D. symposium also provides an opportunity for student participants to interact with established researchers and practitioners in the IoT, AI, ML, Big Data, VLSI, EDA, and Cloud computing community


Finally, the symposium seeks to motivate students in the development of their scientific curiosity and facilitate their networking within the research community.

Ph.D. Symposium attendance is open to all COINS registrants.

The manuscript (2-4 pages) should conform to the IEEE format



  • Deadline for regular paper submission:  January 31, 2020
  • Notification of acceptance of regular papers: April 10, 2020
  • Camera-ready:  April 20, 2020



Authors are invited to submit their original manuscripts written in English via online submission platform of Easychair. Each manuscript should include the complete paper text, all illustrations, and references. The manuscript should conform to IEEE format: single-spaced, double-column, US letter page size, 10-point size Times Roman font, up to 6 pages. In order to conduct a blind review, no indication of the authors’ names should appear in the manuscript, references included.

Every accepted paper MUST have at least one author registered to the Conference by the time the camera-ready paper is submitted; at least one of the authors is also expected to attend the conference and present the paper.



Conference proceedings will be published in IEEE. Accepted papers are allowed six pages in the conference proceedings free of charge. Each additional page beyond six pages is subject to the page charge at 150 Euro per page up to the eight-page limit. IEEE will hold the copyright for COINS proceedings. Authors of accepted papers must sign an IEEE copyright release form for their paper.




All regular papers go through a double-blind peer-review process. Submitted manuscripts s are carefully reviewed by at least two reviewers and rated considering Relevance, Originality, Technical Quality, Significance, and Presentation. Based on the corresponding score/comments given by reviewers, program and track chairs will decide if a paper can be accepted as a full regular paper (with 20 minutes oral presentation) or as a short paper (with poster presentation). It should be noted that only original papers should be submitted. Authors are highly encouraged to carefully study IEEE ethical norms regarding plagiarism and self-plagiarism thoroughly before submitting and must make sure that their submissions do not substantially overlap work which has been published elsewhere or simultaneously submitted to a journal or another conference with proceedings. All the submitted papers will be checked by iThenticate Platform (Plagiarism Detection Software) and those papers that contain any form of plagiarism will be rejected without reviews.