Context-Aware Sensing in Critical Infrastructure

The rapid development in sensor technologies and analytic tools have enabled new opportunities to collect large quantity of data at the edge for further processing in the cloud. That approach cannot fulfil the strict requirements of many delay-sensitive applications. In many cases, real-time decisions are better taken close to the edge. However, the constrained resources in edge/ fog nodes limits their data ability to process large quantity of data to accurately determine the optimum decision in real time. Hence, accuracy often conflicts with timeliness of decisions.

In critical applications such as smart grid, IoT, healthcare and search & rescue operations, delays can lead to loss of human lives or damage of expensive equipment even if the actions are accurate. Automatic determination and inference of contextual information from a set of observations provided by sensors can improve accuracy of actions in time-critical applications. Thus context aware sensing is a promising technique for optimising the trade-off between accuracy and delay of the decision making at the edge. 

This Special Issue on Context- Aware Sensing in Critical Infrastructure aims to bring together researchers and practitioners interested in the development of new techniques for context-based monitoring for disaster management.    

The broad areas include but not limited to:

• Recent advances in context aware sensing 
• Context awareness in Industry 4.0

• Context data feature engineering using deep learning
• Autonomous context-aware emergency decisions using AI
• Context identification reliability
• Context awareness in crowd sensing
• Trust in context-aware sensing
• Context awareness in IoT
• Context aware sensing framework for smart cities
• Context awareness in energy networks
• Context awareness in smart homes
• Context aware sensing in disaster management
• Context aware sensing in connected & autonomous vehicles
• Context identification reliability
• Context awareness in intelligent transport systems
• Application of context awareness in cyber-security
• Context aware sensing in V2X applications
• Context awareness in communication systems
• Data fusion & context aware sensing  
• Context aware sensing in the Edge 
• Context aware sensing in Fog computing

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