It is generally accepted that sensors that adapt to relevant information in data can greatly enhance the performance of systems under challenging conditions. Over the years, we have studied the philosophy of adaptive sensing from various standpoints such as integrated sensing and processing, computational imaging, task specific sensing, and robustness in complex systems. These are presented in an unified view of adaptive sensing, along with a discussion of how such approaches must be incorporated into real-world systems. We review some of our earlier results, propose a general framework for adaptive sensing and the management of sensor resources, and discuss on-going plans for future work.
Back to Machine Reasoning Workshops III & IV: Mission-Focused Actions/Reactions Based on & System Integration of Information Derived from Complex Real-World Data (by invitation only)