Energy-Efficient IoT (Internet of Things) and Big Data Challenges for Connected Intelligence
A special issue of Big Data and Cognitive Computing (ISSN 2504-2289).
Deadline for manuscript submissions: closed (31 May 2023) | Viewed by 14703
Special Issue Editors
2. Computer Science and Engineering Discipline, Khulna University, Khulna 9208, Bangladesh
Interests: artificial intelligence; machine learning; wireless resource management in 5G; cooperative communication; game theory; health informatics; IIoT; UAV communication
Special Issues, Collections and Topics in MDPI journals
2. Department of Computer Science and Engineering, School of Data and Sciences, BRAC University, Dhaka 1212, Bangladesh
Interests: healthcare-IoT networks; mental-health informatics; ambient intelligence systems; mobile-cloud computing; edge computing; affective computing; UAV image processing
Interests: deep learning; multiaccess edge computing; information-centric networking; in-network caching
Interests: artificial intelligence and stochastic models; Internet of Things; wireless network resource management; sustainable edge computing; intelligent healthcare system; industrial-IoT; resilient smart grid
Special Issue Information
Dear Colleagues,
With the ongoing development of the Internet of Things (IoT), artificial intelligence (AI), and AI as a service, we are rapidly moving towards connected intelligence, where the roles of Big Data become crucial, since individuals and critical cyber-physical systems completely rely on behavior and intuition of data. In future IoT and communication systems, energy-efficient, rational, trustworthy, and data-informed AI models become the key enablers to automatic IoT network and service management. Therefore, to support vertical IoT applications for the modern citizen, AI-supported methods, architectures, and system models are needed, where the system must meet a set of KPIs such as self-sustainable, self-powered, and self-organized qualities. In particular, the mechanisms for analyzing Big Data for critical cyber-physical systems such as Industrial IoT, smart homes, smart grid, intelligent healthcare, connected and autonomous vehicle systems, and smart factories are essential so that system can infer knowledge and be capable to execute in real-time. Further, the modern IoT system must be scalable for adopting 5G and beyond communication systems such as THz sensing and communication, integration of non-terrestrial communication, effective edge, and fog computing. The envision of this special issue is to investigate energy-efficient IoT systems, AI models for analysis and evaluation, use-cases and case studies, as well as the comprehensive review on the roles of Big Data for leaping forward to connected intelligence. We encourage the research community to submit original research articles and comprehensive review articles for receiving high-quality feedback (peer review) from editorial board members. We believe that, together, we can contribute high-quality research to the community by publishing with the journal Big Data and Cognitive Computing (ISSN 2504-2289). Note that papers will be published on an ongoing basis.
The topic of “Energy-Efficient IoT (Internet of Things) and Big Data Challenges for Connected Intelligence” includes, but is not limited to, the following topics:
- Trustworthy artificial intelligence model for energy-efficient IoT network management using Big Data;
- Neurosymbolic artificial intelligence for complex cyber-physical system;
- Role of Big Data for IoT network traffic characterization, measurement, and monitoring;
- Light-weight knowledge graph modeling for IoT services using Big Data;
- Energy-harvesting model for self-powered IoT;
- Role of satellite communication for IoT;
- 6G approaches to serve massive IoT;
- IoT applications and services to convergence with ground, space, and maritime networks;
- Connected intelligence framework designing for smart factory;
- Data-informed intelligent system model for sustainable smart city;
- Cellular IoT with sustainable energy;
- AI methods for quality of experience (QoE) and quality of service (QoS) IoT service delivery;
- Experimental analysis on IoT-based smart energy management;
- Multi-agent intelligent system design for mitigating the tradeoffs between exploration and exploitation;
- AI model performance evaluation of smart grid communications and demand response;
- Tradeoff analysis for solving big data problem with small amount of data for the resilient healthcare system;
- Information-centric networking for connected and autonomous vehicle (CAV) system;
- Testbed and prototype design for target-oriented smart services such as intelligent caching, smart energy, and emergent services for smart citizens;
- Energy-efficient and data-centric AR/VR/MR control design;
- Game theory-based AI model for semantic IoT communication;
- UAV-aided IoT system for energy saving;
- Statistical machine learning algorithm design for performance analysis of IoT network;
- Personalized behavior analysis for infotainment contents delivery to CAV systems;
- Blockchain for target-oriented security, reliability, privacy, and trust enhancement for connected intelligent;
- Public dataset generation for IoT network evaluation;
- Trend analysis for beyond 5G networks of energy-efficient IoT network;
- Performance and energy consumption tradeoffs analysis model using Big Data;
- AI model for priority-based IoT service provisioning;
- Role of Big Data for cellular IoT and Edge computing;
- IoT Use-case analysis for evolvable AI model for multi-access edge computing (MEC) and fog computing infrastructure;
- Trend and performance analysis for sensing and wireless resource management in THz;
- Multi-model AI system design for complex cyber-physical systems;
- AI model for real-time IoT services.
Prof. Dr. Anupam Kumar Bairagi
Dr. Md. Golam Rabiul Alam
Dr. Anselme Ndikumana
Dr. Md. Shirajum Munir
Guest Editors
Manuscript Submission Information
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Keywords
- Internet of Things (IoT)
- connected intelligence
- energy-efficient IoT
- energy harvesting
- self-powered IoT
- artificial intelligence (AI)
- trustworthy AI
- neurosymbolic artificial intelligence
- semantic-based AI
- knowledge Graph
- evolvable AI
- multi-model AI system
- explainable AI model
- machine intelligent
- security, reliability, privacy, and trust for IoT
- connected and autonomous vehicle
- personalized behavior analysis
- cellular IoT
- smart healthcare
- smart city
- complex cyber-physical system
- Big Data fusion
- quality of experience (QoE) and quality of service (QoS) IoT service delivery
- game theory for Big Data
- smart sensing
- THz for IoT
- satellite communication for IoT
- convergence with the ground, space, and maritime networks
- sustainable IoT network
- infotainment for CAV
- self-powered IoT
- real-time IoT services
- dataset of IoT network
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