With the advancement of MEMS technologies, wireless networks consist of tiny sensor devices hold the promise of revolutionizing sensing in a wide range of application domains because of their flexibility, low cost and ease of deployment. However, the constrained computation power, battery power, storage capacity and communication bandwidth of the tiny devices pose challenging problems in the design and deployment of such systems. Target localization using acoustic signal with tiny wireless devices is a particularly difficult task due to the amount of signal processing and computation involved. In this paper, we provide an in-depth study of designing such wireless sensor networks for real-world acoustic tracking applications. We layout a cluster-based architecture to address the limitations of the tiny sensing devices. To achieve effective utilization of the scarce wireless bandwidth, a quality-driven paradigm to suppress redundant information and resolve contention is proposed. One instance of the quality-driven approach is implemented in the acoustic tracking system, where the quality of the tracking reports can be quantified numerically. We demonstrate the effectiveness of our proposed architecture and protocols using a sensor network testbed based on UCBerkeley mica motes. Considering the performance limitations of tiny sensor devices, the achieved acoustic target tracking accuracy is extraordinarily good. Our experimental study also shows that the acoustic target tracking quality can be indeed measured and used to assist resource allocation decisions. This application-driven design and implementation exercises also serve to identify important areas of further work in in-network processing and communications.
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