Recent cens items

AndWellness: An Open Mobile System for Activity and Experience Sampling

Fri, 4 Nov 2011 00:00:00 +0000

Advances in technology and infrastructure have positioned mobile phones as a convenient platform for real-time assessment of an individuals health and behavior, while offering unprecedented accessibility and affordability to both the producers and the consumers of the data. In this paper we address several of the key challenges that arise in leveraging smartphones for health: designing the complex set of building blocks required for an end-to-end system, motivating participants to sustain engagement in long-lived data collection, and interpreting both the data and the quality of the data collected.

We present AndWellness, a mobile to web platform that records, analyzes, and visualizes data from both prompted experience samples entered by the user, as well as continuous streams of data passively collected from sensors onboard the mobile device. In order to address the system design and participation motivation challenges, we have incorporated feedback from hundreds of...

Participatory Sensing for Community Data Campaigns: A case study

Thu, 28 Jul 2011 00:00:00 +0000

Participatory Sensing is a process whereby individuals and communities use mobile phones and web services to observe, analyze, and present personal and environmental artifacts, events and experiences. In this technical report we describe a community data campaign that made use of smartphone based participatory sensing for environmental needs assessment. Community organizers defined the content of the participatory sensing campaign. 68 individuals participated over the course of 6 weeks, uploading over 450 mini-surveys, including over 700 images.

The Atom LEAP Platform For Energy-Efficient Embedded Computing

Wed, 26 May 2010 00:00:00 +0000

This Technical Report provides a review of a new embedded computing platform enabling research, education and training, and product development based on the Intel Atom processor architecture. This introduces a dramatic advance in the capability for direct characterization of energy and power dissipation in embedded computing platforms and the associated capabilities for optimization of performance and energy. This report includes development, usage, and example operation and results with platform applications in mobile computing, distributed sensing, network routing, and wireless access point implementation. In each case, Atom LEAP is intended to provide both a reference design and a high throughput, easily implemented solution with an unprecedented advance in the capability for characterizing energy usage at a level of computing task and operating system detail substantially superior to prior methods.

Forest understory soil temperatures and heat flux calculated using a Fourier model and scaled using a digital camera

Tue, 20 Apr 2010 00:00:00 +0000

The characterization of the solar radiation environment under a forest canopy is important for both understanding temperature-dependent biological processes and validating energy balance models. A modified sinusoidal model of soil heat conductivity was used to estimate subsurface temperature and heat flux from the uneven but periodic solar heating of the soil surface due to sun flecks from a forest canopy. Using a mobile sensor platform with an infrared thermometer along an 11 m transect, a sunfleck model of soil surface temperature was tested using soil surface temperature maxima, air temperatures, and photodiodes placed on the soil surface to measure sunflecks. A pan-tilt-zoom digital camera on a 10 m tower above the site was then used to capture a time series of panoramic images of sunflecks reflected from the soil surface and to scale the sunfleck temperature model to a wide area. Finally, this image-based model of surface temperatures was combined with the modified sinusoidal...

Budburst and leaf area expansion measured with a ground-based, mobile camera system and simple color thresholding

Tue, 2 Feb 2010 00:00:00 +0000

Plant phenology relates strongly to primary productivity and the energy that enters into ecological food webs, and thus is vital in understanding ecosystem function and the effects of climate and climate change. The manual collection of phenological data is labor-intensive and not easily scalable, thus the ability to quantify leaf flush and other parameters at many locations requires innovative new methodologies such as the use of visible light digital cameras. Improved imaging performancewas obtained by using a cabled, mobile camera system that allowed a repeated image census of branches of Rhododendron occidentale in the understory along a 30m transect during leaf flush. Automatic division of acquired images into areas of interest (leaves) and background for calculating leaf area was accomplished by thresholding images in different color spaces. Transformation of the color space into the hue, saturation, and luminance (HSL) color space before thresholding resulted in a mean...

Tansley Review: Environmental sensor networks in ecological research

Tue, 2 Feb 2010 00:00:00 +0000

Environmental sensor networks offer a powerful combination of distributed sensing capacity, real-time data visualization and analysis, and integration with adjacent networks and remote sensing data streams. These advances have become a reality as a combined result of the continuing miniaturization of electronics, the availability of large data storage and computational capacity, and the pervasive connectivity of the Internet. Environmental sensor networks have been established and large new networks are planned for monitoring multiple habitats at many different scales. Projects range in spatial scale from continental systems designed to measure global change and environmental stability to those involved with the monitoring of only a few meters of forest edge in fragmented landscapes. Temporal measurements have ranged from the evaluation of sunfleck dynamics at scales of seconds, to daily CO2 fluxes, to decadal shifts in temperatures. Above-ground sensor systems are partnered...

Four Billion Little Brothers? Privacy, mobile phones, and ubiquitous data collection

Tue, 8 Sep 2009 00:00:00 +0000

Participatory sensing technologies could improve our lives and our communities, but at what cost to our privacy?

Designing the Personal Data Stream: Enabling Participatory Privacy in Mobile Personal Sensing

Fri, 28 Aug 2009 00:00:00 +0000

For decades, the Codes of Fair Information Practice have served as a model for data privacy, protecting personal information collected by governments and corporations. But professional data management standards such as the Codes of Fair Information Practice do not take into account a world of distributed data collection, nor the realities of data mining and easy, almost uncontrolled, dissemination. Emerging models of information gathering create an environment where recording devices, deployed by individuals rather than organizations, disrupt expected flows of information in both public and private spaces. We suggest expanding the Codes of Fair Information Practice to protect privacy in this new data reality. An adapted understanding of the Codes of Fair Information Practice can promote individuals’ engagement with their own data, and apply not only to governments and corporations, but software developers creating the data collection programs of the 21st century. To support...

Smart Screen Management on Mobile Phones

Wed, 24 Jun 2009 00:00:00 +0000

Large and bright screens on today's mobile phones account for significant energy demand on phones' batteries. In this paper we propose an algorithm that, given the energy profile of the screen, finds the optimal schedule to minimize screen energy dissipation when the phone is idle. We profile the screen energy consumption of two popular smartphones, Nokia N95 and E71, through carefully designed micro-benchmarks. Our energy measurement results suggest that the default screen schedules on these phones are far from optimal - on average our algorithm performs 50% better than default. We also find that on the E71 not using the dim state of the screen and directly turning it off is more energy-efficient. We improve the performance of our screen scheduling algorithm by considering the history of each user's interaction with his/her phone. We study the interaction patterns of six volunteers with their smartphones. The results suggest that the distribution of the length of idle times...

Ambulation: a tool for monitoring mobility patterns over time using mobile phones

Thu, 28 May 2009 00:00:00 +0000

An important tool for evaluating the health of patients who suffer from mobility-affecting chronic diseases such as MS, Parkinson’s, and Muscular Dystrophy is assessment of how much they walk. Ambulation is a mobility monitoring system that uses Android and Nokia N95 mobile phones to automatically detect the user’s mobility mode. The user’s only required interaction with the phone is turning it on and keeping it with him/her throughout the day, with the intention that it could be used as his/her everyday mobile phone for voice, data, and other applications, while Ambulation runs in the background. The phone uploads the collected mobility and location information to a server and a secure, intuitive web-based visualization of the data is available to the user and any family, friends or caregivers whom they authorize, allowing them to identify trends in their mobility and measure progress over time and in response to varying treatments.

An Overview of CENS Contaminant Transport Observation and Management Research

Tue, 12 May 2009 00:00:00 +0000

The contaminant assessment and management (or “Contam”) research area focuses on developing and implementing embedded networked sensing (ENS) technology to support this new observational strategy in the context of mass and energy distributions and fluxes across a range of temporal and synoptic scales. The specific areas of interest for Contam include soils, groundwater, and riparian systems. The Contam application domain is unique relative to the other three CENS applications in that it is often concerned with enabling adaptive management of environmental problems through engineered responses triggered by ENS observations. Example applications include improving our understanding of river metabolism in relation to adjacent and upstream land management practices, creating closed-loop feedback-control systems for conserving irrigation water and avoiding excessive nitrogen application in agricultural systems, delineating nutrient fluxes between groundwater and surface water, and...

Education Overview

Tue, 12 May 2009 00:00:00 +0000

Education Overview

Deriving State Machines from TinyOS programs using Symbolic Execution

Tue, 12 May 2009 00:00:00 +0000

The most common programming languages and platforms for sensor networks foster a low-level programming style. This design provides fine-grained control over the underlying sensor devices, which is critical given their severe resource constraints. However, this design also makes programs difficult to understand, maintain, and debug. In this work, we describe an approach to automatically recover the high-level system logic from such low-level programs, along with an instantiation of the approach for nesC programs running on top of the TinyOS operating system. We adapt the technique of symbolic execution from the program analysis community to handle the event-driven nature of TinyOS, providing a generic component for approximating the behavior of a sensor network application or system component. We then employ a form of predicate abstraction on the resulting information to automatically produce a finite state machine representation of the component. We have used our tool, called...

Tools for Dynamic Deployment and Data Management

Tue, 12 May 2009 00:00:00 +0000

CENS researchers are developing flexible wireless sensing technologies that can be used in a variety of scientific and social applications. These technologies produce data that often have value to both the immediate research questions and to longer-term studies of longitudinal phenomena. CENS sensing systems are being deployed in many different real-world settings. Managing sensor deployments and the resulting data can be difficult. This poster outlines our work in developing tools to help CENS researchers conduct deployments and manage the resulting data, specifically the CENS Deployment Center, Sensorbase, and the deployment webpages created for the Seismic Deployment in Peru. The CENS Deployment Center (CENSDC) is a web-based repository for CENS deployment information. The CENSDC provides a central location for researchers to document deployment activities through the creation of pre-deployment plans and post-deployment feedback/notes. By allowing users to describe their...

Using Imagers for Scaling Ecological Observations

Tue, 12 May 2009 00:00:00 +0000

Stationary and mobile ground-based cameras can be used to scale ecological observations, relating pixel information in images to in situ measurements. Currently there are four CENS projects that involve using cameras for scaling ecological observations: 1. Scaling from one individual to the landscape. Pan-Tilt-Zoom cameras can be zoomed in on a tight focus on individual plants and parts of individuals and then zoomed out to get a landscape view, composed of the same and similar species. 2. Estimating photosynthesis over large areas with HDR. High Dynamic Range imaging is a technique to capture an absolute amount of reflected light in an image. For a meadow composed of similarly reflecting species, we can estimate light received by leaves and thus photosynthesis over a wide area. 3. Scaling soil surface temperature measurements. Soil surface temperatures and soil energy balance are related to solar radiation and air temperature. Sunflecks captured with a camera taking...

Toward Resource Efficient Homes: From Measurements to Sustainable Choices

Tue, 12 May 2009 00:00:00 +0000

The average person is currently unaware of the real-time energy consumption for the different household appliances that he uses. At best, he can observe the monthly or bi-monthly bill indicating the total power consumption of all the appliances combined. This makes it difficult to improve the consumption efficiency, since there is no visibility in the data that he can access. We believe that real-time appliance level monitoring is necessary to allow residents to manage their energy consumption efficiently. However, monitoring end-point level power consumption is difficult to impossible with current technologies because expensive sensors, or professionally installation is necessary. In addition, device aesthetic and the inherent intrusiveness of direct in-line sensors to measure the energy usage at every end-point complicate such a system installation. Since appliances emit measurable signals when they are consuming resources, we argue that less-invasive sensors can be used...

Micro- and Mini-nitrate Sensors for Monitoring of Soils, Groundwater and Aquatic Systems

Tue, 12 May 2009 00:00:00 +0000

Inorganic nitrogen (nitrate, NO3-) is a major source of pollution in groundwater, surface water and the air. Application of nitrate-containing fertilizers can create distributed or non-point source pollution problems. Scalable nitrate sensors (sensors which are small and inexpensive) would enable us to better assess non-point source pollution processes in agronomic soils, groundwater and rivers. Sensor research groups in the CENS have been working toward high-performance scalable nitrate sensors using (1) potentiometric, (2) amperometric method, and the recent addition is (3) spectrochemical sensor. 1. Potentiometric Nitrate Sensor. This work describes the fabrication and testing of inexpensive PVC-membrane-based ion selective electrodes (ISEs) for monitoring nitrate levels in soil water environments. Over the past year, we emphasized testing of the in situ behavior of fabricated sensors in soils subject to irrigation with dairy manure water. Observed temporal responses...

Developments on the CENS Structural Health Monitoring Front

Tue, 12 May 2009 00:00:00 +0000

CENS research related to developing and implementing structural health monitoring (SHM) systems is advancing on two distinct but related fronts: ShakeNet, a portable wireless sensor network for rapid, post-event deployments and SHMnet, a novel SHM system for permanent monitoring of tall buildings and special structures in Los Angeles. The primary objective of the SHMnet research is the development of a robust SHM system along with the associated hardware and software, using tall and special structures (e.g., bridges, port structures, dams) in Los Angeles as a testbed. More specifically, the development of a wireless Data Acquisition (DAQ) toolbox suitable for rapid urban deployments, a suite of state-of-the-art sensors for monitoring key structural responses including innovative methods for directly measuring interstory displacements, and probabilistic post-event assessment algorithms based on experimental motion-damage relationships. Progress on these fronts is highlighted....

Urban Sensing or Personal and Participatory Sensing

Tue, 12 May 2009 00:00:00 +0000

overview poster so no abstract.

Personal Data Vault: A Privacy Architecture for Mobile Personal Sensing

Tue, 12 May 2009 00:00:00 +0000

Participatory sensing tasks deployed mobile devices to form interactive, participatory sensor networks that enable public and professional users to gather, analyze and share local knowledge. Mobile Personal Sensing (MPS) is a platform for participatory sensing with which users use mobile phones to record and transmit sound, images, location, motion data, and web services to aggregate and interpret the assembled information. The data gathered through MPS is personal, as well as being potentially valuable in many aspects; it quantifies habits, routines, associations, and is easy to mine. However, for these reasons, protecting individual privacy, documenting ownership, and providing visibility of processing are important. We propose Personal Data Vault (PDV), the architecture to support these new design criteria by “auditing” all activities on the data (TraceAudit) and dynamically “re-sampling” data feeds to service providers (Adaptive Filter). The TraceAudit allows the user...

Subduction Zone Seismic Experiment in Peru: Results From a Wireless Seismic Network

Tue, 12 May 2009 00:00:00 +0000

This work describes preliminary results from a 50 station broadband seismic network recently installed from the coast to the high Andes in Peru. UCLA's Center for Embedded Network Sensing (CENS) and Caltech's Tectonic Observatory are collaborating with the IRD (French L'Institut de Recherche pour le Developpement) and the Institute of Geophysics, in Lima Peru in a broadband seismic experiment that will study the transition from steep to shallow slab subduction. The currently installed line has stations located above the steep subduction zone at a spacing of about 6 km. In 2009 we plan to install a line of 50 stations north from this line along the crest of the Andes, crossing the transition from steep to shallow subduction. A further line from the end of that line back to the coast, completing a U shaped array, is in the planning phase. The network is wirelessly linked using multi-hop network software designed by computer scientists in CENS in which data is transmitted from...

Imagers as Biological Sensors

Tue, 12 May 2009 00:00:00 +0000

There exist many biological sensing applications where direct measurement is either impossible, extremely invasive, or extremely time consuming. For example, measuring the presence/absence of birds at a feeder station currently requires a human to watch a camera pointed at the feeder, identifying when birds arrive and leave. Similarly, measuring CO2 flux from a plant requires placing the plant inside a growth chamber, destructively modifying the environment. We propose using imagers as biological sensors by constructing a procedure that uses images to obtain approximate measurements of these phenomena. This procedure, composed of state-of-the-art computer vision, image processing, and statistical learning algorithms, will be evaluated in the context of a specific application and shown to be general through multiple instantiations. Through application, it has been found that many of these algorithms make unacceptable assumptions about their input. Providing accurate data...

Ecological Sensing in a Southern California Forest: Integrating Environmental Abiotic and Biotic Measurements to Understand Ecosystem Function.

Tue, 12 May 2009 00:00:00 +0000

Understanding the interactions between belowground and aboveground process and how they respond to annual climatic variability remains a challenging task. In this study, we combined molecular techniques with high frequency images from automated minirhizotrons to determine the identity and temporal variability of fine roots and mycorrhizal fungi in a mixed-conifer forest in Southern California. We also examined how changes in fine roots and mycorrhizal fungi are related to leaf phenology and water dynamics over the course of the growing season. Throughout the study, there was considerable variation in ectomycorrhizal roots, with greater ectomycorrhizal roots during the dry summer months compared to early spring. Although the total number of ectomycorrhizal fungi did not change, there was a significant change in the ectomycorrhizal fungal community over the course of the growing season. Arbuscular mycorrhizal roots, on the other hand, showed little variation during the growing...

Improving Personal and Environmental Health Decision Making with Mobile Personal Sensing

Tue, 12 May 2009 00:00:00 +0000

CENS is focusing on three types of health applications. Personalized medicine (AndWellness, AndAmbulation), epidemiological data collection (Project Surya), and personal decision making and awareness (PEIR). Each of these applications uses a similar systems architecture: time, location (GPS), and motion (accelerometer) trace collection on the mobile phone with a user interface, scientific model-based analytics used to draw inferences from the data, and graphical map or calendar based feedback to users. The specifics of each component depend on the type of data collected, the target populations, and the goals of the project. The UI for AndWellness includes an ecological momentary assessment, which is a set of questions a user completes regarding their feelings at that moment; and control over the time, location, and frequency of reminders, which are included to remind users to complete the assessments. The AndWellness UI aims to make the assessment easy to understand and quick...

Overview of Terrestrial Ecology Observation Systems

Tue, 12 May 2009 00:00:00 +0000

A review of TEOS projects by CENS faculty and staff.

Field Operational Sensor and Lab-on-a-Chip System for Marine Environmental Monitoring and Analysis

Tue, 12 May 2009 00:00:00 +0000

This is a project that aims to expedite research in marine biology using chip-based and state-of-the-art detection technology. The project is a joint effort that will incorporate the expertise of three different groups, Dr. Chih-Ming Ho at UCLA, Dr. David Caron at USC and Dr. Yu-Chong Tai at Caltech. One main focus of the project is to develop Lab-on-a-chip devices that reduce total sample volume and detection time. Also, the chips can be fabricated in large quantities with minimal cost so many experiments can be run in parallel. Here at Caltech, a chip will be developed to culture a small number of algae and screen for factors inducing toxin production. Algal bloom and toxins produced by different algae have always caused problems to the environment and marine ecology. Pseudo-nitzschia is one type of algae that produces a neural toxin called Domoic Acid, which when transferred through the food chain causes sickness and mortality in marine mammals and seabirds. However,...

Two Major Themes in the Design of Sensor Networks: Data Integrity and Sampling.

Tue, 12 May 2009 00:00:00 +0000

In this poster, we consider two major themes in the design of sensor networks: data integrity, and sampling strategies. For the data integrity problem, we propose a signature-based fault detection system for identifying both intermittent faults and persistent faults. Data-dependent features using temporal, spatial, and spatio-temporal information that are useful for detecting faults are identified. These features are combined into signatures that characterize each of the different fault types. We also discuss the problem of simultaneous parameter estimation and fault detection. In this case, parameters must be estimated from a distribution that is truncated in various ways as a result of the fault detection algorithm, which can lead to biased estimates. We propose several methods to account for the bias in parameter estimates. For the sampling problem, we describe two on-going projects. The first one deals with situations where sampling as you move (using sampling paths)...

Seismic Deployments and Experiments: PeruNet, GeoNet, and SeismoPhone.

Tue, 12 May 2009 00:00:00 +0000

In conjunction with Caltech and the Geophysical Institute of Peru, we installed our network of 49 seismic sites across steep and shallow subduction regions in Peru. Flat slab subduction is thought to have formed much of the major geology of the western United States some 100 million years ago. By examining such processes presently active in Central and South America we can piece together the history. The data from the Peruvian sites is delivered to UCLA every night and we have collected almost 1 year so far. In the GeoNet experiment, the science objective is to use a rapidly installable wirelessly linked seismic network to make near-real time unaliased observations in aftershock or volcanic zones. The immediate technical objective is to collaborate with Reftek to construct a new generation digital acquisition system (DAS) based on the CENS-developed LEAP (low-power energy aware processing) system and a newly developed low-power A/D converter from Texas Instruments. We also...

Closing the Loop on Groundwater-Surface Water Interactions, River Hydrodynamics, and Metabolism on the San Joaquin River Basin

Tue, 12 May 2009 00:00:00 +0000

This poster summarizes the body of CENS work in the San Joaquin River (SJR) basin that is aimed at creating a prototypical observation-modeling-management (feedback-control) system. The objective of the proposed system is to clarify the linkages between land use and chemical transport and fate along the soil zone-groundwater-surface water flow path. Work to date is presented on the following sub-projects: (1) The application of high resolution river multi-scale observations to define a 2-D hydrodynamic model at the SJR-Merced River confluence, (2) The use of embedded sensor systems known as temperature javelins to estimate local groundwater fluxes into the Merced River upstream of the confluence, and (3) The installation of long-term sensor systems aimed at continuously observing the flow path between agricultural systems and the Merced River.

Overview of CENS Statistics and Data Practices Research

Tue, 12 May 2009 00:00:00 +0000

Data, statistical models and inferential procedures permeate CENS deployments, from the four founding scientific application areas to the more recent urban sensing campaigns. This cross-center research breaks down into three classes of research: 1) General statistical models for embedded sensing, with specific applications to data quality and continuous sampling, 2) Significant CENS-designed and supported databases and repositories, and 3) Studies into the data lifecycle for embedded sensing systems.

Visualizing microbial pollution in Santa Monica Bay with Geographic Information Systems (GIS) and through field-testing a rapid, robust, field-portable water detection sensing system

Tue, 12 May 2009 00:00:00 +0000

Geographic Information Systems (GIS) is a powerful mapping tool that can be used to reveal spatial and temporal relationships of a criteria of interest. We have used GIS to visualize the seasonal and spatial distribution of microbial pollution obtained from the Heal the Bay beach water quality report (2007). These maps can be used to inform sampling decisions; more specifically, we can use it to identify areas of chronic pollution and can be used as a testbed for a rapid sensing system for bacteria. This rapid detection system can be used to provide higher resolution and understanding of water pollution as well as assist in understanding/characterizing environmental water quality in specific areas. We propose the subsequent use of an covalently-linked immumomagnetic separation/ATP quantification assay that is rapid, robust, and field-portable as an instrument to conduct monitoring of E. coli and Enterococcus in marine and freshwater systems.

Networked Aquatic Microbial Observing Systems: An Overview

Tue, 12 May 2009 00:00:00 +0000

The overarching theme of the Center’s Aquatic application area continues to be the creation and application of a new genre of wireless sensing systems that will provide real-time monitoring capabilities of chemical, physical and biological parameters in freshwater and coastal marine ecosystems. High-resolution temporal and spatial measurements are essential for understanding the highly dynamic nature of aquatic ecosystems and the rapid response of microbial communities to environmental driving forces. Our unique approach to aquatic sensing and sampling, Networked Aquatic Microbial Observing Systems (NAMOS), employs coordinated measurements between stationary sensing nodes (buoys and pier-based sensors) and robotic vehicles (surface robotic boats and autonomous underwater vehicles) to provide in-situ, real-time presence for observing plankton dynamics (e.g. phytoplankton abundance, dissolved oxygen), and linking them to pertinent environmental variables (e.g. temperature,...

Pan-American Sensors for Environmental Observations (PASEO): An Interdisciplinary Pan-American Advanced Studies Institute (PASI)

Tue, 12 May 2009 00:00:00 +0000

PASEO was an NSF-funded PASI, which is a two-week training program for U.S. and Latin American early-career scientists and engineers. It took place in February 2009 in Bahia Blanca and Buenos Aires, Argentina. The host institutions were Instituto Argentino de Oceanografia (CONICET-funded), and Instituto Nacional de Tecnologia Industrial (INTI). Collaborating U.S. groups included GLEON, WATERS Network, and Codar Inc. The topic of PASEO was developing and deploying current sensor technologies to obtain a fuller understanding of environmental and ecological systems. PASEO was intended to be a multi-cultural and multi-disciplinary active learning experience. Applicants participated in active learning sessions related to the fabrication, deployment, and analysis of data streaming from environmental sensors. Scientific topics included lake metabolism, eco-hydrology in a saltwater marsh, soil moisture and energy balances, and plant phenology. Opportunities for hands-on training...

Trajectory Design and Implementation for Multiple Autonomous Underwater Vehicles Based on Ocean Model Predictions

Tue, 12 May 2009 00:00:00 +0000

Trajectory design for Autonomous Underwater Vehicles (AUVs) is of great importance to the oceanographic research community. Intelligent planning is required to maneuver one or many vehicles to high-valued locations to collect data with scientific merit. We consider the use of ocean model predictions to determine the locations to be visited by a team of AUVs, which then provides near-real time, in situ measurements back to the model to increase model skill and the accuracy of future predictions. Iterative application of this procedure determines relevant points of interest that allow the AUV fleet to monitor and track a chosen oceanographic feature. For this study, we select the ocean feature to be a freshwater plume, as their colder, nutrient-rich water promotes productivity, and may result in the formation of a Harmful Algal Bloom (HAB). Monitoring and predicting the formation and evolution of HABs is an area of active research for southern California coastal communities...

Networked Robotic Sensor Platform Deployments for use in Coastal Environmental Assessment in Southern California

Tue, 12 May 2009 00:00:00 +0000

Mobile sensor platforms such as Autonomous Underwater Vehicles (AUVs) and robotic surface vessels, combined with static moored sensors compose a diverse sensor network that is able to provide macroscopic environmental analysis tool for ocean researchers. Working as a cohesive networked unit, the static buoys are always online, and provide insight as to the time and locations where a federated, mobile robot team should be deployed to effectively perform large scale spatio-temporal sampling on demand. Such a system can provide pertinent in situ measurements to marine biologists whom can then advise policy makers on critical environmental issues. This poster presents recent field deployment activity of AUVs demonstrating the effectiveness of our embedded communication network infrastructure throughout southern California coastal waters. We also report on progress towards real-time, web-streaming data from the multiple sampling locations and mobile sensor platforms. Static monitoring...

New Wireless Miniature Sensor Technologies for CENS

Tue, 12 May 2009 00:00:00 +0000

Although many sensors (e.g., temperature, light level, acceleration, etc.) that are compatible with sensor networks (i.e., sensitive, small, low power, etc.) are now commercially available, two important classes of sensors are not as technologically mature and remain an area of active research: chemical sensors and biological sensors. The sensor-technology-development efforts in the CENS center are focused on these very challenging classes of sensors. Successful development of chemical and biological sensors will enable wireless-sensor-network technology to span the full range of possible classes of measurements. In addition to better performance, the technological emphases are miniaturization and automation of the developed sensors. Specific sensor-technology-development efforts include: (1) amperometric and potentiometric electrochemical sensors for monitoring nitrate-ion detection in ground water; (2) lab-on-a-chip aquatic microorganism analysis system; and (3) ultra sensitive...

Summer@CENS: a research internship program

Tue, 12 May 2009 00:00:00 +0000

The Summer@CENS Research Scholars Program continues to be one of the key Education initiatives at CENS. The program is the core of our educational pipeline and is an excellent example of aligned Center research and education activities. The Summer@CENS Research Scholars Program serves as an umbrella for our undergraduate and high school summer research opportunities. It brings together talented undergraduates from around the country and local high school students to engage in Center research for 8-10 weeks over the summer. This poster highlights the structure of the program from planning to implementation as well as some of the outcomes resulting from the program. Also highlighted is the CENS Intel Scholars Program which allows us to extend the summer experience through the academic year for undergraduates at UCLA. This year, the CENS High School Scholars program has also been extended through the academic year to support continuation high school students in Central High...

Recruitment Services for Participatory Sensing Applications

Tue, 12 May 2009 00:00:00 +0000

In traditional sensor systems, one of the fundamental problems concerns the placement of sensors. The analogous problem in participatory sensing is choosing users to perform a particular data collection task. This work details a recruitment framework that is designed to help with this process. Specifically, the framework considers the capabilities in terms of sensors available by a particular user, the availability of the user to participate in terms of spatial and temporal contexts, the reputation of the user as a data collector, and the incentive cost associated with the user participating as elements involved in the process of choosing data collectors. The utility of the recruitment service is shown through a series of campaigns related to ecological and sustainability monitoring.

Physical, chemical, and biological factors shaping phytoplankton community structure in King Harbor, Redondo Beach, California

Tue, 12 May 2009 00:00:00 +0000

Through the NAMOS project, our team of biologists and engineers are assisting municipalities in understanding the underlying causes and effects of harmful microalgal blooms. Since early 2007, we have been studying system-level dynamics of the chemical, physical, and biological processes in King Harbor, a shallow, semi-enclosed urban harbor in Redondo Beach, California. For the last two years a network of dock-based water quality sensors in the harbor has continuously provided data on the environmental parameters relevant to bloom formation. Additionally, intensive human-mediated studies of the phytoplankton community distribution and structure are testing several hypotheses on the biological and physical factors affecting algal growth in this system. Recent field experiments have sought to explain the roles of tidal forcing and phytoplankton behavior and physiology in the structuring and distribution of bloom-forming algal communities.

Engaging women in computer science and engineering: Insights from a national study of undergraduate research experiences

Thu, 7 May 2009 00:00:00 +0000

At UCLA, the Center for Embedded Network Sensing (CENS) in the School of Engineering received NSF funding for a unique project titled: Women @ CENS, created to explore issues of gender equity in engineering and computer science (ECS) undergraduate research internship programs. The Women @ CENS project includes two studies: 1) an evaluation of our own CENS REU program and 2) a national study of REUs in ECS. The goals of these studies were to learn about promising practices in addressing gender equity in the REU setting from our own summer internship program, and to learn about what other REUs were doing in regards to promoting gender equity such that more women will choose to pursue advanced degrees and faculty careers in ECS. Study One utilizes the evaluation of the CENS REU over four program years to understand what has and has not worked for our female students in particular. For Study Two, we surveyed program directors of NSF funded Computer Science and Engineering REUs...

A Receding Horizon Control Algorithm for Adaptive Management of Soil Moisture and Chemical Levels during Irrigation

Wed, 6 May 2009 00:00:00 +0000

The capacity to adaptively manage irrigation and associated contaminant transport is desirable from the perspectives of water conservation, groundwater quality protection, and other concerns. This paper introduces the application of a feedback-control strategy known as Receding Horizon Control (RHC) to the problem of irrigation management. The RHC method incorporates sensor measurements, predictive models, and optimization algorithms to maintain soil moisture at certain levels or prevent contaminant propagation beyond desirable thresholds. Theoretical test cases are first presented to examine the RHC scheme performance for the control of soil moisture and nitrate levels in a soil irrigation problem. Then, soil moisture control is successfully demonstrated for a center-pivot system in Palmdale, CA where reclaimed water is used for agricultural irrigation. Real-time soil moisture, temperature, and meteorological data are streamed wirelessly to a field computer to enable autonomous...

Real-Time Adaptive Management of Soil Salinity Using a Receding Horizon Control Algorithm: A Pilot-Scale Demonstration

Wed, 6 May 2009 00:00:00 +0000

This work demonstrates the application of real-time adaptive management principles to the problem of controlling the salinity levels in, and/or protecting groundwater quality beneath, soils undergoing irrigation with relatively saline water (e.g., reclaimed wastewater) under arid/semi- arid conditions. Here, optimal feedback-control scheme known as Receding Horizon Control (RHC) previously applied offline to control soil moisture levels during irrigation (Park et al., 2009) is applied inline during a pilot-scale field test aimed at balancing reclaimed water reuse and soil/groundwater quality in real-time. RHC is supported by sensor measurements, physically-based state prediction models, and optimization algorithms to drive field conditions to a desired environmental state. A simulation model including a one-dimensional (vertical) form of the Richards equation coupled to energy and solute transport equations is employed as a state estimator to provide predicted soil moisture,...

Nonmyopic Adaptive Informative Path Planning for Multiple Robots

Thu, 9 Apr 2009 00:00:00 +0000

Many robotic path planning applications, such as search and rescue, involve uncertain environments with complex dynamics that can be only partially observed. When selecting the best subset of observation locations subject to constrained resources (such as limited time or battery capacity) it is an important problem to trade off exploration (gathering information about the environment) and exploitation (using the current knowledge about the environment most effectively) for efficiently observing these environments. Even the nonadaptive setting, where paths are planned before observations are made, is NP-hard, and has been subject to much research.

In this paper, we present a novel approach to adaptive informative path planning that addresses this exploration-exploitation tradeoff. Our approach is nonmyopic, i.e. it plans ahead for possible observations that can be made in the future. We quantify the benefit of exploration through the ``adaptivity gap'' between an adaptive...

Sensor Network Data Fault Detection using Hierarchical Bayesian Space-Time Modeling

Tue, 20 Jan 2009 00:00:00 +0000

We present a new application of hierarchical Bayesian space-time (HBST) modeling: data fault detection in sensor networks primarily used in environmental monitoring situations. To show the effectiveness of HBST modeling, we develop a rudimentary tagging system to mark data that does not fit with given models. Using this, we compare HBST modeling against first order linear autoregressive (AR) modeling, which is a commonly used alternative due to its simplicity. We show that while HBST is more complex, it is much more accurate than linear AR modeling as evidenced in greatly reduced false detection rates while maintaining similar, if not better detection rates. HBST modeling reduces false detection rates 41.5% to 96.5% when paired with our simple fault detection method. We also see that HBST modeling is more robust to model mismatches and unmodeled dynamics than linear AR modeling.

Sensor Network Data Fault Detection Using Bayesian Maximum a Posterior Sensor Selection and Hierarchical Bayesian Space-Time Models

Tue, 20 Jan 2009 00:00:00 +0000

Data faults in sensor networks must be marked to ensure accurate inferences. We introduce a two phase semi-realtime end-to-end Bayesian fault detection system for sensor networks. The first phase selects a subset of agreeing sensors from which a model of expected behavior is derived. The second phase uses this subset to derive and tag questionable sensor data. To accurately model the data, we use a hierarchical Bayesian space-time (HBST) model, as compared to the linear autoregressive modeling used in previous works. Applying this system to simulated and real world data, results are excellent when the phenomenon is well modeled by the HBST model. It achieves high detection rates and almost zero false detection rates. Results also indicate that in cases of critically low spatial sampling density a more accurate model is required.

Accurate Energy Attribution and Accounting for Multi-core Systems

Tue, 13 Jan 2009 00:00:00 +0000

This paper presents a novel energy attribution and accounting architecture for multi-core systems that can provide accurate, per-process energy information of individual hardware components. We introduce a hardwareassisted direct energy measurement system that integrates seamlessly with the host platform and provides detailed energy information of multiple hardware elements at millisecond-scale time resolution. We also introduce a performance counter based behavioral model that provides indirect information on the proportional energy consumption of concurrently executing processes in the system. We fuse the direct and indirect measurement information into a low-overhead kernel-based energy apportion and accounting software system that provides unprecedented visibility of per-process CPU and RAM energy consumption information on multi-core systems. Through experimentation we show that our energy apportioning system achieves an accuracy of at least 96% while impacting CPU performance...

Fixing Faults in Wireless Sensing Systems with Confidence

Thu, 25 Dec 2008 00:00:00 +0000

This paper presents Confidence, a tool for identifying and addressing faults in wireless sensing systems. Confidence pinpoints potential sensor and network faults in real time, allowing users to validate unexpected data and address any failures in the field. By introducing a well defined, low-dimension feature space, and functions to map sensor data into this space, we are able to achieve fault detection and diagnosis with relatively simple mechanisms such as outlier detection. Users can directly modify system outcomes by altering a classification label in instances when Confidence's automated algorithm draws the wrong inference. This label is applied to all similar points in the feature space, enabling Confidence to learn from user interaction in the field. This abstraction for incorporating user knowledge provides a lightweight and easy- to-understand interface for the user, while limiting user bur- den and reducing the required a priori environmental knowledge. Confidence...

Forced Vibration Testing of a Four-Story Reinforced Concrete Building Utilizing the nees@UCLA Mobile Field Laboratory

Fri, 19 Dec 2008 00:00:00 +0000

The nees@UCLA mobile ﬁeld laboratory was utilized to collect forced and ambient vibration data from a four-story reinforced concrete (RC) building damaged in the 1994 Northridge earthquake. Both low amplitude broadband and moderate amplitude harmonic excitation were applied using a linear shaker and two eccentric mass shakers, respectively. Floor accelerations, interstory displacements, and column and slab curvature distributions were monitored during the tests using accelerometers, linear variable differential transformers (LVDTs) and concrete strain gauges. The use of dense instrumentation enabled veriﬁcation of common modeling assumptions related to rigid diaphragms and soil-structure-interaction. The ﬁrst six or seven natural frequencies, mode shapes, and damping ratios were identiﬁed. Signiﬁcant decreases in frequency cor responded to increases in shaking amplitude, most notably in the N-S direction of the building, most likely due to preexisting diagonal joint cracks...

Optimal Spectrum Management in Multiuser Interference Channels

Fri, 21 Nov 2008 00:00:00 +0000

In this paper, we investigate the optimal spectrum management problem in multiuser frequency selective interference channels. First, a simple pairwise condition for FDMA to be optimal is discovered: for any two among all the users, as long as the normalized cross couplings between them two are both larger than or equal to 1/2, orthogonalization between these two users is optimal for every existing user. Therefore, this single condition applies to achieving all Pareto optimal points of the rate region. Furthermore, not only is this condition sufficient, but in symmetric channels, it is also necessary for FDMA to be always optimal. When the normalized cross couplings are less than 1/2, the optimal spectrum management strategy can be a mixture of frequency sharing and FDMA, depending on users’ power constraints. We first explicitly solve the sum-rate maximization problem in two user symmetric flat channels by solving a closed form equation, providing the optimal spectrum management...

Fixing Faults with Confidence

Fri, 17 Oct 2008 00:00:00 +0000

This paper presents Confidence, a tool for identifying and addressing faults in wireless sensing systems. Confidence pinpoints potential sensor and network faults in real time, allowing users to validate unexpected data and address any failures in the field. By introducing a well defined, low-dimension feature space, and functions to map sensor data into this space, we are able to achieve fault detection and diagnosis with relatively simple mechanisms such as outlier detection. Users can directly modify system outcomes by altering a classification label in instances when Confidence's automated algorithm draws the wrong inference. This label is applied to all similar points in the feature space, enabling Confidence to learn from user interaction in the field. This abstraction for incorporating user knowledge provides a lightweight and easy-to-understand interface for the user, while limiting user burden and reducing the required a priori environmental knowledge. Confidence has...

NIMSAQ: A novel system for autonomous sensing of aquatic environments

Mon, 14 Jul 2008 00:00:00 +0000

NIMSAQ: A novel system for autonomous sensing of aquatic environments

The Marginal Utility of Cooperation in Sensor Networks

Mon, 14 Jul 2008 00:00:00 +0000

The Marginal Utility of Cooperation in Sensor Networks

On the relationship between the structural and socioacademic communities of an interdisciplinary coauthorship network

Mon, 14 Jul 2008 00:00:00 +0000

This article presents a study that compares detected structural communities in a coauthorship network to the socioacademic characteristics of the scholars that compose the network. The coauthorship network was created from the bibliographic record of an overt interdisciplinary research group focused on sensor networks and wireless communication. The popular leading eigenvector community detection algorithm was employed to assign a structural community to each scholar in the network. Socioacademic characteristics were gathered from the scholars and include such information as their academic department, academic affiliation, country of origin, and academic position. A Pearson's \$\chi^2\$ test, with a simulated Monte Carlo, revealed that structural communities best represent groupings of individuals working in the same academic department and at the same institution. A generalization of this result indicates that, contrary to the common conception of a multi-institutional interdisciplinary...

Seeing Our Signals: Combining location traces and web-based models for personal discovery

Mon, 14 Jul 2008 00:00:00 +0000

Seeing Our Signals: Combining location traces and web-based models for personal discovery

Adaptive Sampling With Multiple Mobile Robots

Mon, 14 Jul 2008 00:00:00 +0000

Adaptive Sampling With Multiple Mobile Robots

Environmental controls and the influence of vegetation type, fine roots and rhizomorphs on diel and seasonal variation in soil respiration

Sat, 12 Jul 2008 00:00:00 +0000

• Characterization of spatial and temporal variation of soil respiration coupled with fine root and rhizomorph dynamics is necessary to understand the mechanisms that regulate soil respiration.

• A dense wireless network array of soil CO2 sensors in combination with minirhizotron tubes was used to continuously measure soil respiration over 1 yr in a mixed conifer forest in California, USA, in two adjacent areas with different vegetation types: an area with woody vegetation (Wv) and an area with scattered herbaceous vegetation (Hv).

• Annual soil respiration rates and the lengths of fine roots and rhizomorphs were greater at Wv than at Hv. Soil respiration was positively correlated with fine roots and rhizomorphs at Wv but only with fine roots at Hv. Diel and seasonal soil respiration patterns were decoupled with soil temperature at Wv but not at Hv. When decoupled, higher soil respiration rates were observed at increasing temperatures, demonstrating a hysteresis...

Achieving Participatory Privacy Regulation: Guidelines for CENS Urban Sensing

Wed, 25 Jun 2008 00:00:00 +0000

Achieving Participatory Privacy Regulation: Guidelines for CENS Urban Sensing

Participatory Design of Sensing Networks: Strengths and Challenges

Mon, 16 Jun 2008 00:00:00 +0000

Participatory design (PD) involves users in all phases of design to build systems that fit user needs while simultaneously helping users understand complex systems. We argue that traditional PD techniques can benefit participatory sensing: community-based participatory research (CBPR) projects in which complex technologies, such as sensing networks using mobile phones, are the research instruments. Based on our pilot work on CycleSense, a community-based data gathering system for bicycle commuters, we discuss the benefits and challenges of PD in participatory sensing settings, and outline a method to integrate PD into the research process.

Participatory Privacy in Urban Sensing

Mon, 21 Apr 2008 00:00:00 +0000

Urban sensing systems that use mobile phones enable individuals and communities to collect and share data with unprecedented speed, accuracy and granularity. But employing mobile handsets as sensor nodes poses new challenges for privacy, data security, and ethics. To address these challenges, CENS is developing design principles based upon understanding privacy regulation as a participatory process. This paper briefly reviews related literature and introduces the concept of participatory privacy regulation. PPR reframes negotiations of social context as an important part of participation in sensing-supported research. It engages participants in ethical decision-making and the meaningful negotiation of personal boundaries and identities. We use PPR to establish a set of design principles based on our application drivers.

Data Transport Control in Wireless Sensor Networks

Wed, 2 Apr 2008 00:00:00 +0000

Dynamics of wireless communication, resource constraints, and application diversity pose significant challenges to data transport control in wireless sensor networks. In this chapter, we examine the issue of data transport control in the context of two typical communication patterns in wireless sensor networks: convergecast and broadcast. We study the similarity and differences of data transport control in convergecast and broadcast, we discuss existing convergecast and broadcast protocols, and we present open issues for data transport control in wireless sensor networks.

Dynamic Node and Fault Tolerance in WSN

Fri, 1 Feb 2008 00:00:00 +0000

Wireless sensor networks are new type of emerging networks with bunch of applications in all fields due to their low cost and low power scheme. As these networks follow open wireless communication, they undergo dynamic node problems and fault node detection due to malicious node activities. In this paper we overcome these problems with the help of algorithms that will provide uninterrupted communication and also save node’s energy and time.function. It is therefore critical for the base station to find out the reason for the node failure. To distinguish these cases, the base station needs to trace all dead nodes.

Reflections on Wireless Sensing Systems: From Ecosystems to Human Systems

Thu, 6 Dec 2007 00:00:00 +0000

This paper presents different applications of wireless sensing systems in environmental sensing and sensing in everyday life.

The Energy Endoscope: Real-time Detailed Energy Accounting for Wireless Sensor Nodes

Fri, 16 Nov 2007 00:00:00 +0000

This paper describes a new embedded networked sensor platform architecture that combines hardware and software tools providing detailed, fine-grained real-time energy usage information. We introduce the LEAP2 platform, a qualitative step forward over the previously developed LEAP and other similar platforms. LEAP2 is based on a new low power ASIC system and generally applicable supporting architecture that provides unprecedented capabilities for directly observing energy usage of multiple subsystems in real-time. Real-time observation with microsecond-scale time resolution now enables direct accounting of energy dissipation for each computing task as well as for each hardware subsystem. This new hardware architecture is exploited with our new software tools, etop and endoscope. A series of experimental investigations provide high-resolution power information in networking, storage, memory and processing for primary embedded networked sensing applications. Using these results...

Heartbeat of a Nest: Using Imagers as Biological Sensors

Wed, 7 Nov 2007 00:00:00 +0000

We present a scalable end-to-end system for vision-based monitoring of a biological phenomenon. Our system enables automated analysis of thousands of images, where manual processing would be infeasible. We automate the analysis of raw imaging data using statistics that are tailored to the task of interest, the study of avian behavior during nesting cycles. The system uses simple image statistics (features) as the low-level representation to be fed to generic classifiers and final inferences exploit the temporal and spatial consistencies. Our testbed achieves bird detection accuracy of 82%, and egg counting accuracy of 84%, allowing inference of avian nesting stage with accuracy within a day. Our results demonstrate the challenges and potential of using imagers as biological sensors. An exploration of system performance under varying image resolution and frame rate suggest that an in situ adaptive vision system is technically feasible.

Sympathy for the Sensor Network Debugger

Tue, 30 Oct 2007 00:00:00 +0000

Sympathy for the Sensor Network Debugger

CENSDC: Adding Context to Content

Mon, 29 Oct 2007 00:00:00 +0000

Scientists and engineers working with embedded networked sensing systems in the environmental sciences are acquiring data at unprecedented rates. Scientific data do not emerge from a vacuum. There is considerable contextual information that surrounds the process of data acquisition that is critical to interpret and analyze data. Current techniques for data sharing involve considerable manual effort to prepare, describe, and transfer this contextual information along with the data itself. This paper reports on a study of the UCLA-based Center for Embedded Networked Sensing (CENS), an interdisciplinary NSF research center that supports collaborations to develop and implement innovative wireless sensor networks. We report here on the development of the CENS Deployment Center, a database for CENS deployment information. The goals of the CENSDC are to facilitate better deployment organization, and to provide a central location for key information that describes the context of data...

Integration and Use of Embedded Sensor Networks

Mon, 29 Oct 2007 00:00:00 +0000

Integration and Use of Embedded Sensor Networks

Campaignr: A Framework for Participatory Data Collection on Mobile Phones

Fri, 26 Oct 2007 00:00:00 +0000

Participatory sensing takes advantage of the pervasive nature of mobile phones to collect data about the urban environment using the available sensors. Campaignr makes collecting this data as simple as a few button pushes. It provides access to the sensors in a robust and flexible way that hides the complexities of the mobile embedded phone environment. This paper describes the design choices and provides some numerical evaluation of Campaignr. Campaignr has been and is being actively used as the data collection method for many research pro jects, both internally and externally.

Metropolitan Wi-Fi Research Network