Decision Support Systems in Emerging Technologies: Methods and Applications
In today’s rapidly evolving technological landscape, decision support systems (DSS) have become indispensable tools for enhancing decision-making processes across various domains. Emerging technologies such as the Internet of Things (IoT), artificial intelligence (AI), 5G/6G wireless networks, robotics, advanced manufacturing systems, quantum computing are generating vast amounts of data and presenting unprecedented opportunities for innovation. However, these advancements also introduce complexities and uncertainties that demand sophisticated decision-making frameworks.
This special issue focuses on the role of DSS in the emerging technologies to create intelligent, adaptive, and efficient solutions. It aims to showcase novel methodologies, interdisciplinary approaches, and innovative applications that leverage DSS to tackle the unique challenges posed by these technologies. By bridging the gap between theoretical advancements and real-world applications, this issue will explore how DSS can drive technological innovation, improve operational efficiency, and contribute to sustainable development in diverse areas such as smart cities, healthcare, industry, and energy systems. This special issue invites researchers, practitioners, and industry professionals to contribute high-quality articles that explore innovative DSS frameworks and their applications across various domains.
Organizing committee
- Georgia Dede (Assistant Professor, Harokopio University of Athens)
- Thomas Kamalakis (Professor, Harokopio University of Athens)
- Christos Diou (Associate Professor, Harokopio University of Athens)
Expected contributions
Foundational Theories and Frameworks:
- Advanced decision-making methodologies.
- AI- and machine learning-driven DSS frameworks for complex decision environments.
- Integration of big data, cloud computing, and edge computing for enhanced decision-making.
IoT-Enabled Decision Support Systems:
- Real-time and adaptive DSS applications in IoT-based systems.
- IoT-driven decision-making in smart cities, healthcare, agriculture, and industrial automation.
- Privacy, security, and ethical considerations in IoT-integrated DSS.
Applications in Communication and Networking Technologies:
- DSS for planning, management, and optimization of next-generation wireless networks (5G/6G).
- Decision-making frameworks for smart antennas, optical communications, and spectrum allocation.
- AI-enhanced DSS for predictive analytics and fault management in communication networks.
Industry 4.0 and Intelligent Systems:
- DSS for cyber-physical systems, robotics, and digital twin technologies.
- Decision frameworks for predictive maintenance, quality assurance, and operational optimization.
- Applications in advanced manufacturing, logistics, and supply chain management.
Energy and Environmental Decision Support:
- DSS frameworks for renewable energy integration, grid optimization, and energy efficiency.
- Environmental monitoring, impact assessment, and sustainable resource management.
- Applications in climate adaptation, circular economy, and smart environmental systems.
Cross-Disciplinary and Emerging Applications:
- DSS for interdisciplinary challenges, such as smart healthcare, education, and disaster management.
- Collaborative decision-making systems for multi-stakeholder scenarios.
- Ethical, human-centric, and explainable DSS for emerging technologies.
Future Directions and Challenges:
- Scalability, performance, and real-time processing in DSS for large-scale applications.
- Innovative approaches for integrating DSS with blockchain, quantum computing, and edge AI.
- Exploration of societal impacts and opportunities presented by DSS in emerging technologies.