ICICCT

Artificial Intelligence (AI) in Communication Systems, Machine Learning for Communication Networks, Internet of Things (IoT) and Communication Technologies, 5G and Beyond-5G Communication Systems, Cognitive Radio Networks, Software-Defined Networking (SDN) and Network Function Virtualization (NFV), Edge Computing and Communication, Quantum Communication Technologies, Wireless Sensor Networks, Cyber-Physical Systems (CPS) and Communication, Blockchain in Communication Networks, Intelligent Routing and Traffic Engineering, Network Security and Privacy, Context-Aware Communication Systems, Mobile and Ubiquitous Computing, Data Analytics for Communication Systems, Human-Computer Interaction (HCI) in Communication, Social Networks and Communication Technologies, Collaborative and Cooperative Communication, Smart City Communication Infrastructure.

Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), Computer Vision, Expert Systems, Fuzzy Logic, Evolutionary Computation, Swarm Intelligence, Genetic Algorithms, Neural Networks, Reinforcement Learning, Bayesian Networks, Knowledge Representation and Reasoning, Data Mining, Pattern Recognition, Autonomous Agents and Multi-Agent Systems, Decision Support Systems, Cognitive Computing, Human-Computer Interaction (HCI), Edge Computing, Cloud Computing, Fog Computing, Distributed Computing, Virtualization Technologies, Containerization (e.g., Docker, Kubernetes), Serverless Computing, Edge AI (Artificial Intelligence at the Edge), Intelligent Resource Management, Edge-to-Cloud Orchestration, Hybrid Cloud Solutions, Edge Analytics, Data Processing and Storage at the Edge, Edge Security and Privacy, Edge-to-Cloud Connectivity and Communication, Edge-based Machine Learning and Deep Learning, Real-time Data Processing and Decision Making, Edge-based IoT (Internet of Things) Solutions, Edge-based Content Delivery Networks (CDNs), Edge-based Robotics and Autonomous Systems,

• 5G and wireless broadband networks Technologies for 6-100 GHz spectrum
• WLAN, RFID, and NFC Visible light communications
• Heterogeneous networks (HetNets)
• Cognitive radio and white-space networking
• CubeSats/Satellite networking
• Long-range/Low-power wide-area wireless networking
• Connected unmanned aerial/terrestrial/underwater systems

Cryptocurrencies, Smart Contracts, Decentralized Finance (DeFi), Tokenization Consensus Mechanisms, Blockchain Scalability, Privacy and Security, Interoperability, Governance Models, Supply Chain Management, Identity Management, Regulatory Compliance, Energy Efficiency, Blockchain in Healthcare, Education and Awareness, Blockchain in Government, Environmental Impact, Decentralized Autonomous Organizations (DAOs), Cross-Border Payments, Blockchain in IoT.

Threat Intelligence and Analysis, Adaptive Intrusion Detection Systems, Behavior Analysis and Anomaly Detection, Predictive Analytics for Security, Autonomous Response Mechanisms, Self-learning Security Systems, Cognitive Security Models, Intelligent Incident Response, Dynamic Risk Assessment, Context-aware Security Solutions, Machine Learning-based Security Controls, Adaptive Access Control Systems, Real-time Security Monitoring and Adaptation, AI-driven Vulnerability Management, Proactive Security Measures, Intelligent Cyber-Physical Threat Hunting, Automated Security Policy Enforcement, Autonomous Security Patch Management, Adaptive Security Orchestration, Cognitive-driven Cyber-Physical Security Governance.

Neural Networks Deep Learning Natural Language Processing Machine Learning Models AI Ethics Computer Vision Reinforcement Learning AI-powered Automation AI Applications Explainable AI Supervised Learning Unsupervised Learning Classification Regression Clustering Ensemble Learning Feature Engineering Model Evaluation Transfer Learning Anomaly Detection

Artificial Intelligence, Social Security, Healthcare, Ethical Considerations Responsible Deployment, Fraud Detection, Threat Analysis, Disaster Response, Disease Prediction, Personalized Medicine, Public Health Interventions, Interdisciplinary Collaboration, Knowledge Exchange, Societal Well-being

This special session aims to explore the multifaceted applications of Artificial Intelligence (AI) and Machine Learning (ML) in various domains, including Natural Language Processing (NLP), Robotics and Automation, Financial Trading, Agriculture, and Climate Change.

This special session aims to explore the multifaceted applications of Artificial Intelligence (AI) and Machine Learning (ML) in various domains, including Natural Language Processing (NLP), Robotics and Automation, Financial Trading, Agriculture, and Climate Change.

This special session aims to explore the multifaceted applications of Artificial Intelligence (AI) and Machine Learning (ML) in various domains, including Natural Language Processing (NLP), Robotics and Automation, Financial Trading, Agriculture, and Climate Change.

This special session aims to explore the multifaceted applications of Artificial Intelligence (AI) and Machine Learning (ML) in various domains, including Natural Language Processing (NLP), Robotics and Automation, Financial Trading, Agriculture, and Climate Change.

This special session aims to explore the Fog computing as a paradigm that utilizes the advantages of both the cloud and the edge devices providing quality services, reducing latency, providing mobility support, multi- tenancy, and many other functions that support modern computing systems. It is sometimes referred to as fog networking or fogging.

This special session aims to explore the Topics will include but are not limited to, AI-driven automation, ML algorithms for predictive analysis, ethical considerations in AI, leveraging Big Data for actionable insights, and the future landscape of intelligent technologies.

The session will emphasis on disseminating state-of-art technology in the interdisciplinary fields of machine intelligence and real-life applications. This is important because of the ubiquitous nature of intelligent machines and their increasing impact on society.

This special session invites contributions from researchers and practitioners working in diverse fields, including healthcare, finance, cybersecurity, natural language processing, and more. The objectives of this session are to explore fundamental principles and advanced methodologies for enhancing the interpretability of ML/DL models, discuss practical applications in diverse fields and foster collaboration among researchers and practitioners working in the field of intelligent computing.

This session invites researchers, practitioners, and thought leaders to engage in a dynamic discussion on the transformative potential of intelligent computing in addressing global challenges and advancing sustainable development goals. The session seeks to examine the intersection between artificial intelligence (AI) and computer technologies and sustainability objectives. Intelligent computing utilizes advanced algorithms, machine learning, artificial intelligence, and data analytics to optimize resource usage, improve decision-making processes, and encourage innovation in many areas.

This special track certainly aligns closely with the conference theme of "Intelligent Computing and Communication Techniques" as it delves into the synergy between advanced computing paradigms and communication technologies. By focusing on edge computing, it addresses the pressing need for intelligent solutions that not only optimize communication processes but also ensure robust security measures. The objectives of track proposal in Edge Computing for Smart and Secure Communication Technologies strive to address & develop scalable and efficient edge computing architectures tailored specifically for communication networks, ensuring seamless integration and interoperability. Research in contemporary domain of edge computing holds significant promise for advancing the field of intelligent computing. Contributions may include the development of machine learning algorithms for dynamic workload management at the edge, the exploration of AI-driven security mechanisms for threat mitigation, and the design of intelligent edge architectures optimized for specific communication tasks. Moreover, it highlights the role of intelligence in mitigating the challenges associated with edge deployment, thus contributing to the broader discourse on intelligent computing.

• Machine Learning Algorithms and Techniques • Big Data Analytics and Technologies • Data Mining and Knowledge Discovery • Artificial Intelligence Applications • Deep Learning Architectures • Natural Language Processing (NLP) • Predictive Analytics and Forecasting • Healthcare Data Analytics • Financial and Business Analytics • Social Media Analytics • Ethical Issues in Data Science • Human-Computer Interaction in Data Analysis • Text Mining and Sentiment Analysis • Blockchain and its Application Areas • Federated Learning • Meta Learning