Dynamic Acoustic Networks for Changing Environments (DANCE) Project intends to demonstrate the usefulness and applicability of Dynamic Acoustic Sensor Networks (DASN) by the development of distributed algorithms and systems to audio applications, when there are changes of network topology and objectives, and go forward to the real-time implementation by using emerging computing tools.
Within these audio applications can be included: self-localization of nodes, dynamic RIR and inverse RIR estimation, dynamic characterization and control of acoustic wave fields, adaptation of communication and processing.
DANCE will allow to improve and widen the scope of the fruitful results obtained with static sensor networks using optimized algorithms and systems for non-stationary scenarios. Concretely, the following objectives/developments will be addressed: acoustic characterization of the application scenarios, algorithms to generate self-knowledge in the sensor network, signal processing algorithms for sound equalization and control, as well as source detection and classification, in time-varying scenarios. Furthermore, a very important objective in this project is the development of algorithmic solutions that are conscious of power consumption.