Acoustic Sensor Network

Acoustic sensor networks (ASNs) are distributed systems of microphones used to collect and process sound data, aiming to improve signal quality, enhance source localization, and enable advanced audio applications. Current research emphasizes robust algorithms for signal processing in challenging acoustic environments, including techniques like generalized eigenvalue decomposition (GEVD) for distributed signal estimation, deep learning models (e.g., convolutional neural networks, recurrent neural networks) for noise reduction and source separation, and machine learning for intrusion detection and prevention. These advancements are driving improvements in applications ranging from meeting transcription and environmental monitoring to urban noise management and underwater acoustic communication, impacting fields like speech processing, environmental science, and security.