Habitat Sensor/Server System (HSSS). We have developed a habitat sensor/server system to enable the placement of sensors in remote locations. This led to the development of a habitat sensor platform (HSP) and a local habitat server (HSS) to receive observations made by sensors on-board the habitat sensor platform and to transmit the observations from multiple HSPs to remote servers for analysis and interpretation.

Habitat Sensor Platform. The acoustic habitat sensor platform was designed and developed based on the Crossbow Stargate processor. This processor operates using Linux and requires relatively low power to operate (~3w). The hardware components of the sensor platform comprises a processor, a power supply to convert 12v input (from 12v battery) to 5v output, an acoustic sensor (microphone), a web camera, a USB hub for additional sensors, a 2 GB flash card for local storage, a wireless communication card (802.11b), and a waterproof case. Power is supplied via a 12v deep cycle battery charged using a 18w solar panel.

The figure below illustrates the hardware configuration of the habitat sensor platform (HSP).

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Habitat Sensor Platform Management. A web service module has been developed to manage the on-board sensors and operation of the habitat sensor platform. This enables management of sensor functions including: time of day, time when the sensors record, sensor parameters settings, adding new sensors, setting location on server for data capture; access to a log file for debugging the habitat sensor platform processes and restarting the sensor platform. Each HSP is identified via its IP address and an identification code and a time/date stamp is attached to the sensor files transmitted from the HSP. The configuration of the HSP and operational system is documented in a detailed reference manual (Gage et al 2005).

Habitat Sensor Server (HSS). The habitat sensor server is the communication hub for the set of HSPs in the field. The HSS consists of a laptop with a Linux (Fedora) operating system. Once the web services module is downloaded to each HSP, the HSS is used to receive sensor observations from all sensor platforms within wireless range. The HSS is also able to communicate long distance to remote servers via a second wireless network, wired Ethernet or satellite communication. One server can handle acoustic transmission from twelve habitat sensor servers. The figure below (left) shows the HSP and HSS in the field. To facilitate communication between HSPs in complex large habitats, an intermediate wireless bridge is utilized and operates on battery power supported by solar energy for charging. The diagram below (right) shows the configuration of the communication system between the HSPs and the HSS using a wireless bridge.

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Remote Access to Habitat Sensor/Server System. Access to sensor platforms in the field is a critical component of the HSSS. To achieve this, a habitat sensor web access service was developed to enable management and manipulation of all HSPs and the operation of the HSS at each field site. We used the Google Maps utility to visualize the location and provide the ability to access and manage the operation and function of the HSS and the HSPs in the field. For example the web service will allow interrogation of server activities such as disk capacity, communication activity with HSPs, management of time of transmission, volume of files to upload, etc. Also, each HSP can be accessed and sensor parameters can be managed and/or manipulated to suit changing system or investigator needs. Since one thrust is to operate acoustic and image sensors, the web system has the ability to access, by date and time, the output of sensors from each HSP. This provides a major advantage from the perspective of knowing the status of the network of HSSSs within multiple habitats and enables scaling to regional sensors. One of our sites (KBS) is 70 miles south of MSU and we have been able to easily determine the status of the sensors and communication and to plan scheduled maintenance based on our observations of sensor activity.

To enable better testing and evaluation of our sensor system in the field, we established a research site at the MSU Inland Lakes Research Facility in south campus. This enabled us to test our system without having to travel to the KBS Site. To accomplish this we worked with Peter Chen in the Computer Laboratory to purchase a wireless link to the Campus wireless internet. The establishment of the wireless internet network infrastructure enabled testing a variety of network configurations and solar power types to ensure a sensor platform that would endure in the field under different meteorological conditions. For example, we determined that the optimal power system for the HSP is a combination of two 14v 18w solar panels and one 12v battery.

The figure below shows the sensor platform locations at the MSU Inland Lakes Research Facility. Here we show the web page for 6 habitat sensor platforms handled by one habitat server. Data are transmitted via MSU wireless network to the Manly Miles Building into the regional server in the Computational Ecology and Visualization Laboratory.

We were also able to test our ability to increase wireless communication distance from the Habitat Sensor Platform (HSP) to Habitat Sensor Sever (HSS) using an intermediate wireless bridge in the field so that a sensor platform can send data via the bridge to the server form a long distance away (1 km). We also developed software and hardware technology to increase of wireless network stability within the Habitat Sensor System.

Sensor Information Access System. A sensor information access system has been designed and developed to facilitate access to sensor networks, sensor observations and sensor analysis. This web based system (http://sonic.cevl.msu.edu) provides an overview of the sensor systems developed and utilized to collect observations and the projects underway to characterize the “Sounds of the Biosphere”. Each project includes an overview of the project, geographic location of sensors used in the research, database of sensor observations, analytical and visualization of sensor observations and reports and publications associated with the research. An image of the opening page providing access to the sensor information system is shown below.

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An analytical system has been developed to enable interpretation of observations from the habitat sensors. A focus on the measurement of the soundscape has enabled the habitat sensor-server system to sense multiple environmental variables (images, temperature, light, humidity, etc.). Acoustics has been the focus or our sensing activity. The acoustic signals that stream into the digital library from the habitat sensor servers represent a huge challenge to large scale movement of data over wireless networks to local servers and then to remote regional servers. To approach the analysis of acoustics, both a general and a specific analysis is considered.

General Analytical Approach. The general approach addresses using acoustic signals to assess habitat quality. The general approach partitions an acoustic signal into 1 KHz intervals and computes the power in each of the intervals. An algorithm developed in MATLAB is used to compute the amount of power in each 1 KHz frequency of a sound sample. The analytical process was automated analyze and visualize potentially thousands of acoustic clips sampled at regular intervals over long time periods. An examination of acoustic time series reveals important patterns which characterize a place. Research identified that technophony generally occurs between 1-2 KHz and Biophony generally occurs between 2-7 KHz.

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The figure above is a visualization of acoustic signals showing an ocillogram, a spectrogram, a power spectral density plot and a bar chart of power in 1 KHz frequency bins.

A ratio of biophony to technophony is calculated to create a normalized index (-1 to +1) of habitat quality based on the nature of the soundscape.

The figure below is based on an annual half-hourly sample of the soundscape. This daily pattern is recorded from a rural soundscape in Okemos, MI based on 48 observations per day. The acoustic habitat quality index (AHQI) at this site has a generally strong average biological signal (> 1.0) that dips as people commence commuting around 0730 Hrs, increases until 1100 Hrs, decreases steadily until 2000 Hrs and then biophony increases as human activity lessens in the evening. This figure was derived by automatically processing 17,520 acoustic files to yield this annual pattern.

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Species Specific Analytical Approach. Analysis of species specific acoustics is more complex and thus more problematic. However significant advances in identification of species using signature matching have been accomplished. To identify a species we listen to the sound and identify a signature in the image and extract the signature from the spectrogram image of a sound sample. A signature extraction system using MATLAB has been developed to automate the process of signature development. The signatures of species are then matched to sounds sampled from soundscapes sampled using the habitat sensor platforms.

The process for determining the time of day when the spring peeper signals most often during May is described below. The spring peeper signaling is shown in the spectrogram below (left image). The signature of the spring peeper (right image) is extracted from the spectrogram. It is this signature that is searched for in the acoustic samples.

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A result of the signature match for the spring peeper is shown below. The signature is matched against acoustic samples recorded 48 times per day during May 2006 from a pond site near Okemos, MI. The figure below shows the mean (se) match for each half hourly period. The line at 0.38 is a threshold of match based on listening for spring peeper signals in the sound samples. In this example, spring peepers signal after 2100 and cease signaling after 0600 hrs.

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Many organisms have the ability to communicate by emitting sounds and subsequently can hear and interpret those sounds. This ability is one of the basic senses as this sense enables communication within and between species. In the environment sound plays an important role as an indicator of ecological activity as well as a determinant of ecological stress, especially when ecological systems are disturbed by natural occurrences like fire or human induced activities such as wetland draining. Sounds result from these physical or human induced actions and thus sound is thus a valuable ecological attribute.

Listening to sounds of bats, birds, amphibians, insects and other vocalizing organisms is a method used to document their presence and abundance. The presence or absence of these and other vocalizing organisms is recognized as important because their presence or absence can be indicative of quality of the environment. Rachel Carson recognized this fact long ago and wrote a book titled ‘Silent Spring’ which was a harbinger of the environmental movement in the United States. The listening organ, or ear in the case of humans, is an amazing sensor that can discern and interpret a myriad of acoustic signals. This auditory sensor can be substituted with the microphone, coupled to a recorder can capture and preserve a record of auditory signals. These simple tools can be used to hear species specific occurrence and abundance of vocal organisms and other sounds and is therefore one of the few sensors that can be used to document the occurrence of specific organisms based on their unique signals. From this information we can develop quantitative measures of acoustic diversity and potentially develop indices of biological diversity based on sounds of organisms. This can potentially provide a framework to forecasting ecological change. Measuring, interpreting and modeling ecological change over time using acoustics presents a set of compelling scientific challenges.

My research on acoustics is based on the vision that measuring, recording and analyzing acoustic signals that emanate from the environment can lead to new ecological insights about the interaction between organisms and their environment. The information garnered from such research can have an important message as it may provide humans with a better understanding of the importance of maintaining the integrity of the environment so that it can sustain the life support system for the organisms that live in it.