Eric Yuen

Sensing uncertainty reduction using low complexity actuation

The performance of a sensor network may be best judged by the quality of application specific information return. The actual sensing performance of a deployed sensor network depends on several factors which cannot be accounted at design time, such as environmental obstacles to sensing. We propose the use of mobility to overcome the effect of unpredictable environmental influence and to adapt to run time dynamics. Now, mobility with its dependencies such as precise localization and navigation is expensive in terms of hardware resources and energy constraints, and may not be feasible in compact, densely deployed and widespread sensor nodes. We present a method based on low complexity and low energy actuation primitives which are feasible for implementation in sensor networks. We prove how these primitives improve the detection capabilities with theoretical analysis, extensive simulations and real world experiments. The significant coverage advantage recurrent in our investigation justifies our own and other parallel ongoing work in the implementation and refinement of self-actuated systems.

Fine-Scale Patterns of Soil and Plant Surface Temperatures in an Alpine Fellfield Habitat, White Mountains, California

Abstract Within alpine environments the interactions of air temperature, solar irradiance, wind, surface albedo, microtopography, and biotic traits all influence patterns of soil and plant canopy temperatures. The resulting mosaic of surface temperatures has a profound impact on ecosystem processes, plant survival, and ecophysiological performance. Previous studies have documented large and persistent variations in microhabitat temperatures over mesoscale alpine terrains. We have used a novel mobile system to examine changes in soil and plant canopy surface temperatures at spatial scales of centimeters and temporal scales of minutes in an alpine fellfield habitat in the White Mountains of California. In the middle of a summer day, the mean surface temperature differences between points 2, 5, and 10 cm apart were 2.9, 5.4, and 9.0 °C, respectively, and extreme differences of 18 °C or more were found over distances of a few centimeters. These thermal patterns are due not only to substrate material but also to biotic conditions of plant canopy architecture and ecophysiological traits of individual species. The magnitude of temperature variation at these fine scales is greater than the range of warming scenarios in Intergovernmental Panel on Climate Change (IPCC) projections, suggesting that these habitats offer the capacity of significant thermal heterogeneity for plant survival.

PHASER: Physiological Health Assessment System for emergency responders

Despite significant advances in Personal Protective Equipment (PPE) and enhanced tactics, line of duty deaths (LODD) and injuries due to cardiovascular events in the emergency responder community, specifically fire service, remain at an unacceptably high level each year. To address the tragic loss of life and often debilitating injuries that are too prevalent in the fire service, the Department of Homeland Security, Science and Technology Directorate, has created a Physiological Health Assessment System for Emergency Responders (PHASER) program. PHASER is charged to develop and deploy innovative technology solutions based on the fundamental medical understanding of risk factors to enhance health and safety of emergency responders. One of the outcomes of the program is a low-cost secure networked system — PHASER-Net — capable of remote physiological monitoring, risk profiling, risk mitigation and guidance of the individual emergency responders. The PHASER-Net system has been deployed at multiple fire departments across the country, as well as academic research laboratories for validation, testing and enhancement. From the days of initial deployments, the system proved vital by identifying individuals with high risk of cardiovascular events and providing targeted training guidance for risk mitigation and prevention.

EcoIP: An open source image analysis toolkit to identify different stages of plant phenology for multiple species with pan-tilt-zoom cameras

Because of the increased number of cameras employed in environmental sensing and the tremendous image output they produce, we have created a flexible, open-source software solution called EcoIP to help automatically determine different phenophases for different species from digital image sequences. Onset and ending dates are calculated through an iterative process: (1) training images are chosen and areas of interest identified, (2) separation of foreground and background is accomplished based on a naive Bayesian method, (3) a signal is created based on the separation model and (4) it is then fit to a sigmoid that contains the dates of interest. Results using different phenological events of different species indicate that estimated dates fall within a few days of the observed dates for most cases. Our experiments indicate that color separability and scene illumination are contributing factors to this error. EcoIP is implemented as an open platform that encourages anyone to execute, copy, distribute, study, change, and/or improve the application.

Utilizing public Internet-connected cameras for a cross- continental plant phenology monitoring system

Development of inexpensive, automated ground methods is necessary to advance precision plant phenology monitoring across large spatial extents. We propose the use of free, publicly available, Internet-connected cameras, often associated with nonscientific monitoring, to monitor plant phenology at continental scales. We provide a methodology to detect changes in vegetation greenness and determine timing of spring and fall events from over 1100 public cameras across North America from February 2008 – 2009. Manual image segmentation facilitated spring detection for both deciduous and understory vegetation occurring within a single camera view. Deciduous spring green-up was highly correlated with visual ground truths, despite signal noise introduced by varying image exposure and automatic color correction. Compared to co-occurring satellite remote sensing products, public cameras had an equivalent or higher ability to detect spring with fewer days lost to cloud cover.