An Overview of the Use of Remote Embedded Sensors for Audio Acquisition and Processing <s> Communication Environment and Data Reduction <s> Recent advances in miniaturization and low-cost, low-power design have led to active research in large-scale networks of small, wireless, low-power sensors and actuators. Time synchronization is critical in sensor networks for diverse purposes including sensor data fusion, coordinated actuation, and power-efficient duty cycling. Though the clock accuracy and precision requirements are often stricter than in traditional distributed systems, strict energy constraints limit the resources available to meet these goals.We present Reference-Broadcast Synchronization, a scheme in which nodes send reference beacons to their neighbors using physical-layer broadcasts. A reference broadcast does not contain an explicit timestamp; instead, receivers use its arrival time as a point of reference for comparing their clocks. In this paper, we use measurements from two wireless implementations to show that removing the sender's nondeterminism from the critical path in this way produces high-precision clock agreement (1.85 ± 1.28μsec, using off-the-shelf 802.11 wireless Ethernet), while using minimal energy. We also describe a novel algorithm that uses this same broadcast property to federate clocks across broadcast domains with a slow decay in precision (3.68 ± 2.57μsec after 4 hops). RBS can be used without external references, forming a precise relative timescale, or can maintain microsecond-level synchronization to an external timescale such as UTC. We show a significant improvement over the Network Time Protocol (NTP) under similar conditions. <s> BIB001 </s> An Overview of the Use of Remote Embedded Sensors for Audio Acquisition and Processing <s> Communication Environment and Data Reduction <s> This paper evaluates the ability of a wireless mesh architecture to provide high performance Internet access while demanding little deployment planning or operational management. The architecture considered in this paper has unplanned node placement (rather than planned topology), omni-directional antennas (rather than directional links), and multi-hop routing (rather than single-hop base stations). These design decisions contribute to ease of deployment, an important requirement for community wireless networks. However, this architecture carries the risk that lack of planning might render the network's performance unusably low. For example, it might be necessary to place nodes carefully to ensure connectivity; the omni-directional antennas might provide uselessly short radio ranges; or the inefficiency of multi-hop forwarding might leave some users effectively disconnected.The paper evaluates this unplanned mesh architecture with a case study of the Roofnet 802.11b mesh network. Roofnet consists of 37 nodes spread over four square kilometers of an urban area. The network provides users with usable performance despite lack of planning: the average inter-node throughput is 627 kbits/second, even though the average route has three hops.The paper evaluates multiple aspects of the architecture: the effect of node density on connectivity and throughput; the characteristics of the links that the routing protocol elects to use; the usefulness of the highly connected mesh afforded by omni-directional antennas for robustness and throughput; and the potential performance of a single-hop network using the same nodes as Roofnet. <s> BIB002 </s> An Overview of the Use of Remote Embedded Sensors for Audio Acquisition and Processing <s> Communication Environment and Data Reduction <s> A new feature extraction model, generalized perceptual linear prediction (gPLP), is developed to calculate a set of perceptually relevant features for digital signal analysis of animal vocalizations. The gPLP model is a generalized adaptation of the perceptual linear prediction model, popular in human speech processing, which incorporates perceptual information such as frequency warping and equal loudness normalization into the feature extraction process. Since such perceptual information is available for a number of animal species, this new approach integrates that information into a generalized model to extract perceptually relevant features for a particular species. To illustrate, qualitative and quantitative comparisons are made between the species-specific model, generalized perceptual linear prediction (gPLP), and the original PLP model using a set of vocalizations collected from captive African elephants (Loxodonta africana) and wild beluga whales (Delphinapterus leucas). The models that incorporate perceptional information outperform the original human-based models in both visualization and classification tasks. <s> BIB003
Networking remote embedded sensors varies greatly across different deployments, from cases where there is very limited or no connectivity to cases where direct Internet access is possible. Given a data rate and local data reduction policy, the capabilities of the network, combined with local storage capacity, determine the duration of the experiment. There are several networking technologies to consider: No Connectivity. Deployments on the sea floor, in caves, and other locations that have no RF connectivity may simply rely on mass storage to collect data, perhaps with an alarm mechanism or very low bandwidth link for control and status monitoring. Such sites may also be served by "data mules" that physically visit and download data. Satellite Internet. Satellite Internet can provide high speed access to remote locations, although uplink speeds are generally limited to 56 Kbps. However, with limited sample rates and data compression, it may be possible to stream back complete data. Satellite phones are also a possibility, although they are costly and provide only 2.4 Kbps data rates. Long-range Wireless. Long-range wireless links may be useful for reaching nearby infrastructure, although installation of such links requires both time and monetary in-vestment. Off-the-shelf 802.11 radios can be coupled with amplifiers and directional antennas to provide a low-cost long-range link. Work at CENS on the MASE seismic array has deployed a multi-hop 802.11 network with links as long as 10 Km. BIB003 Multi-hop wireless networks are difficult to implement; for this deployment a significant investment in custom routing software was required. High speed connections are also feasible. HPWREN 5 deploys a number of embedded sensors (including audio) on a wireless regional network which spans large portions of the county of San Diego, California with a 45 Mbps wireless backbone. When audio is deployed on a large network, quality of service issues become relevant for some applications. Short-range Wireless. Compared with long-range multihop networks, short range networks are relatively easy to implement; many routing solutions exist off-the-shelf, e.g., BIB002 . Using a short-range network, a single point can act as a local server or a gateway to the Internet for a collection of rapidly deployable nodes. For remote deployments, the server can be a single node with enhanced storage, processing, and user interface capabilities. Short-range networks can also provide time synchronization services. Systems that implement cooperative signal processing often rely on the Global Positioning System (GPS) to provide tight time synchronization, but GPS is not available in all locations, e.g., inside buildings or under dense canopies of foliage. Short-range networks can be used to propagate GPS time references to nodes in GPS-denied areas, enabling them to participate in cooperative signal processing algorithms BIB001 [17]. In consideration of these different technologies, there are clearly limits to the amount of acoustic data that can be carried. A single channel at 16 bit / 24 KHz amounts to 384 Kbps, already larger than the low-end Digital Subscriber Line (DSL) uplink speed, and significantly more than what can be achieved with satellite hardware. For many applications, higher sample rates and sensor arrays are desirable; these requirements multiply the raw data rates. Local data reduction can address these issues. Lossless compression using the Free Lossless Audio Codec BIB001 or WavPack 7 can often achieve lossless reduction of 50% or more. Selecting the minimum sample rate required, or applying a decimation filter in software also cuts down the data rate. In cases where the phenomenon is well-understood, lossy reduction algorithms can be used, such as wavelet compression or event detection and segmentation. Lossy techniques can be used to reserve the limited network bandwidth only for events of interest, while locally storing all data, or can be used to extend the lifetime of the experiment by locally storing only a subset of the raw data. In the latter case, a tiered data retention policy should be formed in which complete raw data are stored for portions of the experiment, and the remaining space is used to store reduced data covering a longer time period.