Exploring Sensor Data Fusion in IoT with Advanced AI Techniques
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".
Deadline for manuscript submissions: 29 August 2025 | Viewed by 61
Special Issue Editors
2. Faculty of Information Technology and Electrical Engineering, University of Oulu, Oulu, Finland
Interests: 5G/6G network; cryptographic; cyber security; edge and cloud computing; intrusion detection systems
Special Issues, Collections and Topics in MDPI journals
Interests: mobile and sensor networks; computer security; digital forensics; 5G security; AI security
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The development of the Internet of Things (IoT) has revolutionized numerous industries by enabling real-time data collection, analysis, and intelligent decision-making. Artificial Intelligence (AI) for the IoT and IoT-driven AI applications are expected to bring transformative changes across various sectors, positioning themselves as the future of technology and innovation.
The increasing reliance on IoT devices in applications such as autonomous vehicles, smart manufacturing, intelligent healthcare systems, and smart cities has intensified the demand for low-latency, high-performance computing solutions. However, unlike centralized cloud environments, MEC and IoT infrastructures often lack robust, specialized security mechanisms tailored to their distributed nature. Parallel processing techniques, essential in distributed computing environments, have become critical for addressing these challenges, particularly in IoT ecosystems that leverage fog, edge, and cloud computing paradigms.
Fog and edge computing techniques complement IoT infrastructures by bringing computational resources closer to the data source, reducing latency and enabling real-time data processing. These distributed computing models are particularly suited for applications involving large-scale sensor networks, real-time analytics, and complex AI-driven tasks. Parallel programming is fundamental to maximizing the potential of fog and edge computing, facilitating efficient resource management, and ensuring scalability in IoT applications.
Addressing data integrity, privacy, and security challenges in IoT environments and sensors requires innovative solutions integrating AI with advanced parallel computing models.
This Special Issue aims to showcase research in AI applications for IoT sensors, focusing on Software-Defined Networking (SDN), fog, and edge computing. We seek contributions focusing on novel architectures, protocols, algorithms, and security frameworks to meet the unique needs of IoT ecosystems.
Topics of interest include, but are not limited to, the following:
- Integration and optimization of sensor networks in AI-powered IoT systems;
- Real-time data processing and analytics in IoT applications using parallel computing techniques;
- AI-enhanced sensor data fusion and interpretation in IoT environments;
- Development of AI algorithms tailored for IoT and sensor environments;
- Design of IoT architectures leveraging AI and software-defined networking;
- Novel parallel programming models for fog, edge, and cloud computing in the IoT;
- Implementation of scientific programming models for interactions among the IoT, sensors, and edge applications;
- Protocols enabling efficient edge-cloud interactions and parallel programming for the IoT;
- IoT resource management with a focus on privacy, trust, and security;
- Multisensor data fusion and multimodal machine learning.
Dr. Amir Javadpour
Dr. Chafika Benzaïd
Guest Editors
Manuscript Submission Information
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Keywords
- sensor data fusion
- Internet of Things (IoT)
- artificial intelligence (AI)
- IoT sensors
- software-defined networking (SDN)
- fog and edge computing
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