Relying on massive sensors on both static and portable devices to perceive the physical world, Internet of things (IoT) has enabled numerous smart things and intelligent systems for the convenience of human beings in daily life. In this paradigm, sensory data plays an important role for efficient and reliable communication and computation. Although the features of scalability, modularity, and openness of IoT make it a multi-disciplinary research area and beneficial for multiple fields, such as healthcare, transportation, and industrial manufacturing, the exponentially increasing number of devices deployed in IoT to satisfy various demands from users raise the big challenges of sensory data fusion, processing, and protection. Thanks to the substantial progress in artificial intelligence, the life cycle of sensory data in IoT can be enhanced with more advanced computing technologies, including various learning frameworks and algorithms. For example, during the fusion stage of sensory data, deep learning can be applied to effectively abstract different levels of information features, which will benefit the next step of accurate data processing and analysis for more intelligent and adaptive decision-making regarding system control; securing sensory data can be achieved in an evolving manner based on reinforcement learning, where the IoT system can gradually establish robust and resilient defense mechanisms via exploring and exploiting in the interactions with malicious attacks.

Although intelligent fusion, processing, and protection of sensory data display a bright perspective for IoT in both academia and industry, they still face great challenges, such as multi-source multi-sensor fusion, spatiotemporal correlated data analysis, and privacy protection. There are also critical challenges about how cutting-edge computation technologies such as big data analytics, federated learning, and blockchain can be seamlessly applied to data processing in IoT, and how to improve efficiency, trustworthy, accountability, robustness, extensibility, adaptivity, self-evolution, and others. Thus, seeking novel designs and methods to advance the usage of sensory data in IoT becomes necessary.

This Special Issue welcomes high-quality original research and review articles that focus on frameworks, models, algorithms, and applications for IoT sensory data fusion, processing, and protection.

Potential topics include but are not limited to the following:

• Attacks and defenses towards IoT sensory big data analysis
• Privacy protection for IoT sensory data
• Blockchain technology for IoT sensory data management
• Cloud/Edge/Fog computing for IoT sensory data
• Learning based resource management for IoT sensory data
• Trustworthy AI for IoT sensory data
• Collaborative learning for IoT sensory data processing
• Distributed learning for IoT sensory data processing
• Intelligent IoT sensory data transmission in 5G/6G networks
• Software defined network for IoT sensory data management
• Modeling, analysis, and evaluation of IoT sensory data processing
• IoT sensory data processing and protection in digital twins
• Quantum computing for IoT sensory data