How do animals use their habitat? Where do they go and what do they do? These basic questions are key not only to understanding a species’ ecology and evolution, but also for addressing many of the environmental challenges we currently face, including problems posed by invasive species, the spread of zoonotic diseases and declines in wildlife populations due to anthropogenic climate and land-use changes. Monitoring the movements and activities of wild animals can be difficult, especially when the species in question are small, cryptic or move over large areas. In this paper, we describe an Automated Radio-Telemetry System (ARTS) that we designed and built on Barro Colorado Island (BCI), Panama to overcome these challenges. We describe the hardware and software we used to implement the ARTS, and discuss the scientific successes we have had using the system, as well as the logistical challenges we faced in maintaining the system in real-world, rainforest conditions. The ARTS uses automated radio-telemetry receivers mounted on 40-m towers topped with arrays of directional antennas to track the activity and location of radio-collared study animals, 24 h a day, 7 days a week. These receiving units are connected by a wireless network to a server housed in the laboratory on BCI, making these data available in real time to researchers via a web-accessible database. As long as study animals are within the range of the towers, the ARTS system collects data more frequently than typical animal-borne global positioning system collars (∼12 locations/h) with lower accuracy (approximately 50 m) but at much reduced cost per tag (∼10X less expensive). The geographic range of ARTS, like all VHF telemetry, is affected by the size of the radio-tag as well as its position in the forest (e.g. tags in the canopy transmit farther than those on the forest floor). We present a model of signal propagation based on landscape conditions, which quantifies these effects and identifies sources of interference, including weather events and human activity. ARTS has been used to track 374 individual animals from 38 species, including 17 mammal species, 12 birds, 7 reptiles or amphibians, as well as two species of plant seeds. These data elucidate the spatio-temporal dynamics of animal activity and movement at the site and have produced numerous peer-reviewed publications, student theses, magazine articles, educational programs and film documentaries. These data are also relevant to long-term population monitoring and conservation plans. Both the successes and the failures of the ARTS system are applicable to broader sensor network applications and are valuable for advancing sensor network research.

Studying animal movement and distribution is of critical importance to addressing environmental challenges including invasive species, infectious diseases, climate and land-use change. Motion sensitive camera traps offer a visual sensor to record the presence of a species at a location, recording their movement in the Eulerian sense. Modern digital camera traps that record video present new analytical opportunities, but also new data management challenges. This paper describes our experience with a year-long terrestrial animal monitoring system at Barro Colorado Island, Panama. The data gathered from our camera network shows the spatio-temporal dynamics of terrestrial bird and mammal activity at the site-data relevant to immediate science questions, and long-term conservation issues. We believe that the experience gained and lessons learned during our year long deployment and testing of the camera traps are applicable to broader sensor network applications and are valuable for the advancement of the sensor network research. We suggest that the continued development of these hardware, software, and analytical tools, in concert, offer an exciting sensor-network solution to monitoring of animal populations which could realistically scale over larger areas and time spans.

The environmental science and engineering communities are actively engaged in planning and developing the next generation of large-scale sensor-based observing systems. These systems face two significant challenges: heterogeneity of instrumentation and complexity of data stream processing. Environmental observing systems incorporate instruments across the spectrum of complexity, from temperature sensors to acoustic Doppler current profilers, to streaming video cameras. Managing these instruments and their data streams is a serious challenge. Critical infrastructure requirements common to all of these sensor-based observing systems are reliable data transport, the promotion of sensors and sensor streams to first-class objects, a framework for the integration of heterogeneous instruments, and a comprehensive suite of services for data management, routing, synchronization, monitoring, and visualization. In this paper we present the RBNB DataTurbine, an open-source streaming data middleware system, and discuss how the RBNB DataTurbine satisfies the critical cyberinfrastructure requirements core to these sensor-based observing systems. The discussion includes the results from real-world deployments.

Large-scale observing systems are poised to become the dominant means of study for a variety of natural phenomena. These systems are comprised of hundreds to thousands of instruments that must be queried, managed, and shared in a scalable fashion. Services-oriented architectures (SOAs) are widely recognized as the preferred framework for building scalable and extensible cyber infrastructure. By applying SOA concepts, we created a framework for organizing observing system resources. Guided by this framework, we developed Web services, custom workflow applications, and an integrated user interface of monitors and controls for managing instruments in large-scale sensor network observing systems. In this paper we present our approach and discuss its application to the NSF EarthScope USArray large-scale seismic observing system

When two sponsoring organizations, working towards separate goals, can employ wireless sensor networks for a finite period of time, it can be efficiency-enhancing for the sponsors to program their sensors to cooperate. But if each sensor privately knows whether it can provide a favor in any particular period, and the sponsors cannot contract on ex post payments, then no favors are performed in any Nash equilibrium. Allowing the sponsors to contract on ex post payments, we construct equilibria based on the exchange of "tokens" that yield significant cooperation and increase expected sponsor payoffs. Increasing the sponsors' liability is beneficial because it enables them to use more tokens.

We describe an application of data mining and decision analysis to the problem of die-level functional test in integrated circuit manufacturing.Integrated circuits are fabricated on large wafers that can hold hundreds of individual chips ("die").In current practice, large and expensive machines test each of these die to check that they are functioning properly (die-level functional test; DLFT), and then the wafers are cut up, and the good die are assembled into packages and connected to the package pins.Finally, the resulting packages are tested to ensure that the final product is functioning correctly.The purpose of die-level functional test is to avoid the expense of packaging bad die and to provide rapid feedback to the fabrication process by detecting die failures.The challenge for a decision-theoretic approach is to reduce the amount of DLFT (and the associated costs) while still providing process feedback.We describe a decision-theoretic approach to DLFT in which historical test data is mined to create a probabilistic model of patterns of die failure.This model is combined with greedy value-of-information computations to decide in real time which die to test next and when to stop testing.We report the results of several experiments that demonstrate the ability of this procedure to make good testing decisions, good stopping decisions, and to detect anomalous die.Based on experiments with historical test data from Hewlett Packard Company, the resulting system has the potential to improve profits on mature IC products.