Title

A Study of Vocalization and Social Behavior of the Acorn Woodpecker (Melanerpes Formicivorus) Based on the Remote Sensor Network

Authors

Yuan Yao, Ying Lin, Hanbiao Wang, Edward Stabler, Kung Yao, & Charles Taylor

Adaptive Language Group

Abstract

The acorn woodpecker (melanerpes formicivorus) is a highly social species with co-breeding behavior. The vocalization of the acorn woodpecker is thought to be complex due to the complexity of its social system. This research aims to study the vocalization and relevant social behaviors of the acorn woodpecker through various aspects such as the vocal features, the functions of different call types, general patterns of vocal communication, intraspecific /interspecific responses to vocal signals. In the study the distributed wireless sensor network will be applied to collect and monitor the vocal signals of acorn woodpeckers. Furthermore, this system could identify and localize individuals from their calls. After the sensor network is built, the information collected by the network will be used in bioacoustic and behavioral analysis.

CENS Area

Habitat

Title

Impact of Climate Change on the Spatial Distribution of Alpine Vegetation in the White Mountains, California

Authors

B. R. Zutta & P. W. Rundel

Abstract

No abstract provided.

CENS Area

Habitat

Title

Web Tasking Interface of the Extensible Sensing System

Authors

Poonam Jolly, Ben Huang, Andrew Wu, & Deborah Estrin

Abstract

Current developments in sensing technology will allow sensor networks to be embedded in diverse environments to allow for the collection, manipulation, and transmission of experimental data.    One such application of this technology is the Extensible Sensing System, which is designed to be the testbed for sensors and user interfaces to be used in environment sensing.  The ultimate goals of the ESS are to provide a means of data flow out of a sensor network, remote sensor tasking, and
network monitoring. Within this extensive project is the design and implementation of a webtasking interface to allow the end-user to interact with the network of sensors. The Web Tasking Interface is expected to provide an external user with the ability to monitor and access data being collected by the sensor network from a remote location by means of a webserver. Various webpages are created to allow the user to modify the nodes in the network with regard to the type of data collected, the number of nodes deployed, the data itself, etc.  With this type of system design, this external user is capable of requesting changes to the network itself, thus making the management of such a network a much simpler task.  In this system, the user makes a data request which travels over a “Publish-Subscribe” bus to the intended target where the message is received by an agent.  The ESS Agent is expected to receive serialized messages that are sent over the publish-subscribe bus, unpack the necessary data they carry, and provide for the appropriate execution of the tasks specified within the message.  Through this implementation, the agent is equipped to provide a means of effective tasking and communication between a remote user and the sensor network. Through the various components of the ESS, sensor networks will have immense capabilities that will revolutionize the face of technology and expose the scientific community to vast amounts of data that was previously unattainable.  This project seeks to allow greater access to scientific data and bridge the gap between the virtual and physical implementations of sensor technology.

CENS Area

Habitat

Title

The Extensible Sensing System**

Authors

Eric Osterweil, Mohan Mysore, Mohamad Rahimi, & Andrew Wu

Abstract

The ESS is designed as a suite of components that enable and facilitate sensor networks, their deployment, management, and usage. In meeting its charter, the ESS spans a comprehensive set of platforms and operates in a diverse set of environments. It is, therefore, based on a tiered architecture comprised of; motes (mica2, tos, chipcon, sensor interface board), microservers (strongarm/xscale, linux, motenic, 802.11), commodity platforms (x86, linux, 802.11) platforms, and enterprise platforms (such as solaris and oracle).  Within the ESS, the motes are responsible for:

·         Sensor data acquisition, conversion, and aggregation

Each mote is equipped (or able to be equipped) with a sensor interface board. These boards are designed with an array of channels ranging from analog to digital I/O to onboard sensors. Data from sensor board channels is converted from raw data values into standard units.

·         Simple temporal filtering and triggering

The motes are programmed with logic that allows them to sample channels at application specific intervals. The motes are also able to react to channels that fire at irregular intervals in response to stimuli. These abilities are currently being augmented to include simple temporal pattern matching.

·         Online tasking

Tasking is supported by sending messages to the mote network that specify the desired sampling and filtering behavior of motes.

·         Duty cycling (S-MAC and CPU idle)

Node-lifetime is a primary concern in long-lived deployments. By duty-cycling the CPU and the radio (via S-MAC), nodes are able to save power and extend their own lifetime in a manner that supports bursty traffic.

Microservers offload processing and work from the motes. Their role includes:

·         Data aggregation/caching

The more capable microservers transport data traffic out of the mote-network and into the rest of the system. To do this, they aggregate data from motes and buffer it before sending bursts to the rest of the ESS.

·         Tasking and communication bridge

While residing on the mote network and the internet, the microservers are able to forward data to the motes (as well as aggregate from them). Data such as configuration and tasking requests are relayed to motes through microservers. When dealing with facilities above the sensor network and microserver layer, typical server environments such as commodity platforms and enterprise systems (x86 running linux or sun solaris, equipped with 802.11 or wired ethernet) facilitate more resource intensive operations.

·         Subject servers

Data are multicast from arbitrary ESS components across a publish and subscribe middleware bus platform called subject servers.

·         Subject clients

ESS components receive data from the subject server bus by registering as subject clients.

·         Analysis tools (matlab, labview)

Data that exist in the ESS are processed and viewed through standard data acquisition tools by connecting to the subject server bus as subject clients.

·         Visualization (Web GUI, Labview)

Data are also visualized, and the system is managed through Web GUIs that also act as subject clients.

·         Database (Oracle)

Sensor data and configuration data is archived in and analyzed from an oracle database that runs on a sparc solaris server.

We will demonstrate the ESS in support of a microclimate monitoring system for use in ecosystems research. The following two architectural features will be demonstrated:

·         Mote DAQ system based on sensor interface board that supports a wide array of sensors and sensor types.

·         A pub/sub bus which supports robustness and flexibility over local and wide areas and is for intermittent connectivity. The bus supports flexible registration and presence, robust management using interrogation and re-tasking remote devices, and heartbeats for system health.

CENS Area

Systems

Title

Triggering on Area: A Systems Approach**

Authors

Benjamin Greenstein, Deborah Estrin, Eddie Kohler, & David Culler

Abstract

We study and devise methods for detecting spatially distributed features, and in particular, for detecting significant regions of homogeneity. We propose and develop a flexible architecture and macro-programming environment for distributed detection and triggering in sensor networks.

CENS Area

Systems

Title

Packet Delivery Performance in Dense Wireless Sensor Networks

Authors

Jerry Zhao & Ramesh Govindan

Abstract

Wireless sensor networks promise fine-grain monitoring in a wide variety of environments. Many of these environments (indoor environments or habitats) can be harsh for wireless communication. From a networking perspective, the most basic aspect of wireless communication is the packet delivery performance: the spatio-temporal characteristics of packet loss, and its environmental dependence. These factors will deeply impact the performance of data acquisition from these networks. In this presentation, we report on a systematic medium-scale (up to sixty nodes) measurement of packet delivery in three different environments: an indoor office building, a habitat with moderate foliage, and an open parking lot. Our findings have interesting implications for the design and evaluation of routing and medium-access protocols for sensor networks.

CENS Area

Systems

Title

Multi-hop Code Distribution for Sensor Networks

Authors

Thanos Stathopoulos, John Heidemann, & Deborah Estrin

Abstract

The multicast reliability problem has been studied extensively in the wired internet domain, and, more recently, in wireless and ad-hoc networks as well. In the context of wireless sensor networks, comprised of small, low power and resource-constrained nodes that interact with the physical environment, it remains an active research area. A special case of multicast reliability that is of particular interest in the sensor network domain is code distribution. The ability to add new functionality or perform software maintenance without having to physically reach each individual node is an important piece of a sensor network infrastructure. It becomes critical as sensor networks mature and move toward larger deployment sizes. We present eemoap, an energy-efficient multihop over the air programming mechanism. We discuss the design goals, choices and optimizations for building an efficient code distribution scheme on mica2 motes. The mechanism is evaluated in simulation as well as in an actual mote implementation.

CENS Area

Systems

Title

Environmental Energy Management in Sensor Networks**

Authors

Aman Kansal, Dunny Potter, & Mani Srivastava

Abstract

Energy is a major constraint in the design of embedded sensor networks. The energy supplied by batteries with acceptable form factor may not be sufficient for several applications. Extracting energy from the environment is a feasible alternative in many practical scenarios. We present methods to make the most of the available energy in a distributed system and to operate reliably from highly variable energy sources. We also demonstrate the first version of our hardware which is compatible with several existing sensor nodes for enabling energy harvesting.

CENS Area

Systems

Title

“Do Not Disturb”: An Application Leveraging Heterogeneous Sensor Network**

Authors

Omprakash Gnawali & Mark Yarvis

Abstract

A modern corporate workspace, consisting of matrix of cubicles on a large floor, does not provide isolation from noise from other employees. Noise becomes a distraction when loud sound reaches a person who is working in a cubicle. "Do not disturb" (DND) is a sensor networking application designed to address distracting noise in a corporate workspace. The system alerts people who are talking loud and may be causing distraction to co-workers in neighboring cubicles. DND is an example application for which we designed and built technologies to leverage processing heterogeneity in a sensor network.

CENS Area

Systems

Title

Em View: The Em* Visualizer**

Authors

Lewis Girod, Alberto Cerpa, & Henri Dubois-Ferriere

Abstract

Em View is an extensible visualization system that integrates to emstar-based systems, simulators, and emulators. It can also be connected via gateways and other means to other systems. Em View grew out of a need to develop a unified visualization system to replace a host of individually developed single-application visualizers. Thus, Em View is designed specifically to visualize a wide range of applications from a single reusable framework. A highly customizable interface enables multiple visualization schemes to coexist in a single display, while a simple API significantly reduces the coding required to develop new application specific visualization modules.

CENS Area

Systems

Title

Hierarchical In-Network Processing

Authors

Ram Kumar, Vlasios Tsiatsis, & Mani Srivastava

Abstract

There is a rich diversity of sensor platforms that are currently available. The platforms cover a large range of MIPS, which is a metric that measures the rate of instruction execution in processors. Also, some of them have specialized architectures (for e.g. DSP, custom H/W on FPGA) which make them efficient for a certain class of applications. However, a single platform alone is not scalable to the large dynamic range of the computational complexity of the sensor network applications. This is mainly because, the processors with high MIPS have higher power consumption which make them inefficient for performing computations that are not very demanding. Conversely, the processors with low MIPS are not suitable for demanding applications. In order to make the entire networked system of sensors to be scalable to the computation load, we advocate a hierarchical organization of the heterogeneous nodes. In such a network, any application is broken down into sub-tasks which are mapped onto the nodes (at different levels of hierarchy) that are most efficient for executing it. In order to provide more fine grained input to the system, we deploy the resource constrained nodes (called micro-node from now on) densely throughout the network. The larger nodes with more computation capability (called macro-node) are deployed sparsely to assist the micro-nodes in performing their computation.

CENS Area

Systems

Title

Integrating Wireless Sensor Networks

Authors

Chih-Chieh Han, Roy Shea, Athanassios Boulis, & Mani Srivastava

Abstract

None provided.

CENS Area

Systems

Title

SensorWare in Use

Authors

Chih-Chieh Han, Athanassios Boulis, Roy Shea, & Mani Srivastava

Abstract

None provided.

CENS Area

Systems

Title

Scalable Multi-Resolution Storage and Search in Sensor Networks

Authors

Deepak Ganesan, Ben Greenstein, Denis Perelyubskiy, Deborah Estrin, & John Heidemann

Abstract

Wireless sensor networks enable dense sensing of the environment, offering unprecedented opportunities for observing the physical world. Centralized data collection and analysis adversely impact sensor node lifetime. Previous sensor network research has, therefore, focused on in network aggregation and query processing, but has done so for applications where the features of interest are known a priori. When features are not known a priori, as is the case with many scientific applications in dense sensor arrays, efficient support for multi-resolution storage and iterative, drill-down queries is essential. Our system demonstrates the use of in-network wavelet-based summarization and progressive aging of summaries in support of long-term querying in storage and communication-constrained networks. We evaluate the performance of our linux implementation and show that:

a)       wavelet-based hierarchical summarization provides accurate responses to a broad spectrum of spatio-temporal queries with low communication overhead; and

b)       in a storage-constrained environment, graceful query degradation over time is achieved by networked aging of summaries, such that more useful summaries are retained longer. To our knowledge, no one has examined data aging in the context of highly distributed sensor systems.

CENS Area

Systems

Title

Matching Data Dissemination Algorithms to Application Requirements

Authors

Fabio Silva, John Heidemann, & Deborah Estrin

Abstract

None provided.

CENS Area

Systems

Title

Density, Accuracy, Delay and Lifetime Tradeoffs in Wireless Sensor Networks: A Multidimensional Design Perspective

Authors

Sachin Adlakha, Saurabh Ganeriwal, Curt Schurgers, & Mani Srivastava

Abstract

With the growing interest in wireless sensor networks, techniques for their systematic analysis design and optimization are essential. Despite numerous research efforts in optimizing hardware, algorithms and protocols for these networks, it remains largely unexplored how these innovations can be all tied together to design a sensor network for a specific practical application. We propose a methodology that starts from four independent quality of service (QOS) parameters and allows the user to completely and unambiguously describe the desired performance, without having to deal with the details of individual devices or protocols. By making appropriate choices in terms of device capabilities and run-time techniques, a design can be positioned in this four-dimensional QOS space. Furthermore, we describe a technique to explore the associated tradeoffs at design time, using both analytical expressions and simulations. To illustrate the benefits of our approach, a design example is worked out, which shows a five fold improvement in network operational lifetime by adapting the event reporting delay.

CENS Area

Systems

Title

The Impact of Spatial Correlation on Routing with Compression in Wireless Sensor Networks

Authors

Sundeep Pattem, Bhaskar Krishnamachari, & Ramesh Govindan

Abstract

While several data aggregation techniques have been proposed for sensor networks, an understanding of the performance of various data aggregation schemes across the range of spatial correlations is lacking. We analyze the performance of routing with compression in sensor networks using an application-independent measure of data compression (an empirically obtained approximation for the joint entropy of sources as a function of the distance between them) to quantify the size of compressed information, and a bit-hop metric to quantify the total cost of joint routing with compression. Analytical modeling and simulations reveal that while the nature of optimal routing with compression does depend on the correlation level, surprisingly, there exists a static clustering scheme which can provide near-optimal performance for a wide range of spatial correlations. The implication, that there exist relatively simple energy-efficient aggregation schemes for correlated sources has much practical importance.

CENS Area

Systems

Title

The Acquire Mechanism for Efficient Querying in Sensor Networks

Authors

Narayanan Sadagopan, Bhaskar Krishnamachari, & Helmy

Abstract

We propose a novel and efficient mechanism for obtaining information in sensor networks which we refer to as acquire. In acquire an active query is forwarded through the network, and intermediate nodes use cached local information (within a look-ahead of d hops) in order to partially resolve the query. When the query is fully resolved, a completed response is sent directly back to the querying node. We take a mathematical modeling approach to calculate the energy costs associated with acquire. The models permit us to characterize analytically the impact of critical parameters, and compare the performance of acquire with respect to alternatives such as flooding-based querying (FBQ) and expanding ring search (ERS). We show that with optimal parameter settings, depending on the update frequency, acquire obtains order of magnitude reduction over FBQ and a potential reduction of 60% over ERS in consumed energy.

CENS Area

Systems

Title

Distributed Index for Multi-dimensional Data in Sensor Networks**

Authors

Xin Li, Young Jin Kim, Ramesh Govindan, & Wei Hong

Abstract

In many sensor network applications, data or events are named by attributes. Many of these attributes have scalar values, so one natural way to query events of interest is to use a multi-dimensional range query. An example of such a range query is: “list all events whose temperature lies between 50 degree and 60 degree, and whose light levels lie between 10 and 15.” Such queries are useful for correlating events occurring within the network represented by different attribute values. In this demo, we will demonstrate an implementation of a distributed index that scalably supports multi-dimensional range queries. Our distributed index for multi-dimensional data} (or dim) uses a novel geographic embedding of a classical index data structure, and is built upon the GPSR geographic routing algorithm.

CENS Area

Systems

Title

SCALE: A Tool for Connectivity Assessment in Lossy Environments

Authors

Alberto Cerpa, Naim Busek, & Deborah Estrin

Abstract

Wireless sensor networks will allow fine-grained monitoring in a wide range of environment (indoor and outdoor). Many of these environments, present very harsh conditions for wireless communication using low-power radios, including multipath/fading effects, reflections from obstacles, and attenuation from foliage. In this work, we introduce scale, a network wireless measurement tool that uses packet delivery as the basic application-level metric. Scale facilitates the gathering of packet delivery statistics using the same hardware platform and in the same environment targeted for deployment. Using up to 55 nodes, we were able to measure and study the connectivity conditions of two hardware platforms, mica 1 and 2 motes, in three different environments: an outdoor habitat reserve, an urban outdoor environment in a university campus, and an office building, under systematically varied conditions. Among other things, we found that there is no clear correlation between packet delivery and distance in an area of more than 50% of the communication range, temporal variations of packet delivery are correlated with mean reception rate of each link, and the percentage of asymmetric links varies from 5% to 30%. Data collected using scale have interesting implications in the design, evaluation, and parameter tuning of sensor network protocols and algorithms.

CENS Area

Systems

Title

Voronoi Scoping in Sensor Networks**

Authors

Henri Dubois-Ferriere, Lewis Girod, & Deborah Estrin

Abstract

A common scenario for sensor networks is data-gathering: nodes gather data (periodically, or triggered by certain conditions) and send it back to a sink (or basestation). Data is sent over multiple hops, using a tree topology. Such a system with a single sink presents scaling difficulties as the network grows: the average distance to the sink increases, and nodes near the top of the tree must relay a disproportionate amount of traffic. Placing multiple sinks (basestations) can alleviate this, but on the other hand introduces additional overhead if all sinks flood the entire network. Voronoi scoping is a simple distributed technique to limit floods so that each flood reaches only the subset of nodes in the originating sinks's region; that is the nodes who have the originator as closest sink. We have implemented the algorithm in one-phase pull; this demo uses emview to visualize in real-time the clusters formed in the LECS lab ceiling array of motes.

CENS Area

Systems

Title

Schedule and Latency Control in S-MAC**

Authors

Yuan Li, Wei Ye, & John Heidemann

Abstract

None provided.

CENS Area

Systems

Title

Monitoring with a Mix of IR Sensors and Cameras**

Authors

Abhishek Rajgarhia, Fred Stann, & John Heidemann

Abstract

None provided.

CENS Area

Systems

Title

Evaluation of GPSR in the Diffusion Filter Framework

Authors

Xi Wang, Fabio Silva, & John Heidemann

Abstract

Directed diffusion is a data-centric communication mechanism for sensor networks. It is supported by a flexible diffusion filter framework. GPSR (greedy perimeter stateless routing) is a routing mechanism commonly used in sensor networks. This project is an effort to connect GPSR with directed diffusion. Compared with existing routing mechanisms in the diffusion platform, including push, pull and gear, GPSR has quite different qualities in performance. It is an importation addition to the diffusion platform. As a widely known protocol, GPSR is also a good benchmark for ongoing and future research works. In this project, GPSR is implemented as a filter in the diffusion platform, and we performed simulations to compare the performance of different routing mechanisms. There are two findings from simulations results: a) overall GPSR is a rather efficient routing protocol. B) the behavior of GPSR is quite sensitive to node density. The performance will degrade significantly for sparse (barely connected) wireless networks. The poster will show simulation results with analysis. It will also show the internal structure and interfaces of the GPSR filter, as the implementation of the GPSR filter is good example of integrating new routing filters to the diffusion platform.

CENS Area

Systems

Title

Wireless Seismic Data Collection

Authors

Paul Davis, Jeremy Elson, Deborah Estrin, Allen Husker, & Igor Stubailo

Abstract

None provided.

CENS Area

Seismic

Title

A Wireless Seismic Sensing Array**

Authors

Ning Xu & Ramesh Govindan

Abstract

We will demonstrate the collection of accelerometer reading by motes in a multi-hop manner, we have implemented data compression to reduce dataset and a NACK based protocol to achieve reliability.

CENS Area

Seismic

Title

Seismic Network Deployment Preparations

Authors

Allen Husker, Igor Stubailo, Monica Kohler, & Paul Davis

Abstract

Technological and scientific preparations are occurring for the development of a multi-hop radio-linked seismic array (MHRLSA) of 50 broadband stations (GURALP 3ts) and its first few deployments. A ruggedized data relay device (DRD) is being fabricated using Intel’s new low power, small form factor stargate motherboard. A DRD will be placed at each node of the array and configured as a local area network (LAN) with station spacing up to 10 km. The objective is to use protocols that have been developed for the world wide web to optimize the acquisition of real time seismic array data. The array DRD’s will self configure to optimize RF transmission from the nodes to a data concentrator using dynamic routing, from where it will be transmitted real time over a long link back to the laboratory. The MHRLSA will have the ability to generate and communicate network time, and compare local GPS time with network time, allowing the opportunity to switch to network time if GPS time has failed or no GPS is available. In this way robust real time will be maintained avoiding needs for timing corrections after recording. Scientific preparation is being done on two fronts: factor data analysis and a Los Angeles basin seismic study. Twenty four single component seismometers are continuously recording data within the UCLA factor building. A model of seismic amplitudes is developed using simple scattering and attenuation theory and fit to data from the 1997 Los Angeles basin passive seismic experiment (LABPSE) using a non-linear least squares inversion. LABPSE ran roughly north to south through the San Gabriel and Los Angeles basins about 60 km with an average station spacing of less than 5 km. The model takes into account site amplification due to soil type, geometrical spreading, earthquake magnitude, and attenuation. The results indicate that for most stations the model is a good first order approximation of the amplitude variation. However events from a restricted range of azimuths for stations near the basin edge have amplitudes that are several times larger than the model predicts. One interpretation of these results is that the Whittier fault at the edge of the Los Angeles basin creates a zone of increased amplification for earthquakes along the path of the fault. This effect has subsequently been included in the model. The model will be applied to and updated with data from the UCLA campus deployment which is located at a basin edge. The dense (~100m) spacing will allow for waveform correlation leading to more exact deep structure determination and hazard analysis.

CENS Area

Seismic

Title

Vision Based Navigation**

Authors

Jason Meltzer & Stefano Soatto

Abstract

We present a method for inferring the location of a robot relative to a three-dimensional map of its environment. The map, created off-line, consists of image patches, their locations in space, and their associated normal vectors. Observational data consist of one or many images taken from the robot’s current viewpoint (a point and orientation in space). We develop a framework for matching images of a scene (observations) to a map and show how this can be applied to the task of robot localization. Localization is posed as an optimization problem, where the observed data and the map are aligned to produce an estimate of the current pose of the robot. We provide a formalization of our model and demonstrate experimental results in unstructured environments.

CENS Area

Signal Processing

Title

Ad-Hoc Localization Infrastructure**

Authors

Yen-Cheng Kuan, Andres Savvides, & Mani Srivastava

Abstract

None provided.

CENS Area

Signal Processing

Title

Collaborative Data Compression in Sensor Networks

Authors

Ameesh Pandya, Aman Kansal, Greg Pottie, & Mani Srivastava

Abstract

We consider the network information theoretic problem of finding the rate distortion bound for separate coding of multiple correlated sources. First, we find the outer region for separate coding with distortion when only one of the sources is to be reproduced and the other sources are used as helpers. We then find the outer region for separate coding when all the sources are to be reproduced with specified distortions. The rate distortion bounds have previously been calculated for two correlated sources. We find an inductive approach to consider several sources one after the other to derive the general result. We also show the practical implications of our work for several implementations. Our results can be directly utilized by designers to choose not only how many of the available sources should actually be coded but also which sources have the highest potential to reduce the distortion.

CENS Area

Signal Processing

Title

Low-Level Vision Algorithms for Localization, Classification, and Tracking

Authors

Kevin N. Gabayan

Abstract

Camera networks can provide images of detected objects that vary in perspective and level of obstruction. To improve the understanding of visual events, vision algorithms are implemented in a wireless sensor network. Methods were developed to fuse data from multiple cameras to improve object identification and location in the presence of obstructions. Training sets of images allow classification of objects into familiar categories. Feature-based object correspondence is used to track multiple objects throughout a sequence of images.

CENS Area

Signal Processing

Title

Entropy-Based Sensor Selection for Localization

Authors

Hanbiao Wang, Kung Yao, Greg Pottie, & Deborah Estrin

Abstract

Entropy-based sensor selection heuristics is proposed for localization applications. Given 1) the prior target location distribution, and 2) the location and sensing uncertainty of a set of sensors, the heuristics selects a sub-optimal sensor whose measurement would yield nearly the greatest uncertainty reduction of the target location probability distribution. The heuristics defines the potential of a sensor to reduce target location distribution uncertainty. The potential is positively proportional to the entropy of the sensor's view of the target location distribution. The potential is negatively proportional to the sensor's sensing uncertainty. All candidate sensors' potential are evaluated without retrieving actual sensor measurements. The heuristics is illustrated with a localization case study in which bearing sensors, range sensor and time difference sensors are used.

CENS Area

Signal Processing

Title

Augmenting Film/Video Footage with Sensor Data**

Authors

Norman Makoto Su, Heemin Park, Eric Bostrom, Jeff Burke, Mani B. Srivastava, & Deborah Estrin

Abstract

With the advent of tiny networked devices, mark weiser's vision of a world embedded with invisible computers is coming to age. Due to their small size and relative ease of deployment, sensor networks have been utilized by zoologists, seismologists and military personnel. In this paper, we investigate the novel application of sensor networks to the film industry. In particular, we are interested in augmenting film and video footage with sensor data. Unobtrusive sensors are deployed on a film set or in a television studio and on performers. During a filming of a scene, sensor data such as light intensity, color temperature and location are collected and synchronized with each film or video frame. Later, editors, graphics artists and programmers can view this data in synchronization with film and video playback. For example, such data can help define a new level of seamless integration between computer graphics and real world photography. A real-time version of our system would allow sensor data trigger camera movement and cue special effects. In this paper, we discuss the design and implementation of the first part of our embedded film set environment, the augmented recording system. Augmented recording is a foundational component for the ucla hypermedia studio's research into the use of sensor networks in film and video production. In addition, we have evaluated our system in a television studio.

CENS Area

Signal Processing

Title

Real Time Implementation of Acoustical Beamforming**

Authors

P. Bergamo, H. Wang, D. Maniezzo, K. Yao, & D. Estrin

Abstract

A real-time system for audio localization is proposed. The required devices are COTS PDAs. The system is based on beamforming an DOA estimation. With COTS PDAs, an audio localization system can be realized. The PDAs are grouped into a subarray in order to perform the beamforming and to estimate the angle of arrival of the waveform.

CENS Area

Signal Processing

Title

Students’ Beliefs about Professional and School Science

Authors

Kelli A. Millwood, William A. Sandoval, Jeffery Bockert, Kathy Griffis, Sara Terheggen, Joe Wise, & Christine Borgman

Abstract

This study examined how urban high school students’ beliefs about the nature of professional science relate to their beliefs about school science, with particular focus on ideas about the purpose of experimentation and factors influencing knowledge change. A published questionnaire (VNOS, Lederman et al., 2002) was used to assess students’ beliefs about professional science, and groups of students were interviewed about an artifact they created from a modeling activity. The interview asked about their perceptions of the purpose of the activity, its relation to experimentation to knowledge change, and to professional scientists work. Analytic themes were developed to characterize students’ responses to interview questions and VNOS items. There are both differences and similarities between students’ responses in both contexts. Students seemed to recognize their activity as like what scientists would do, and understood it as a modeling task. Yet, students seemed to have few resources to draw upon to consider the nature of experimentation in either their own school work or in professional scientific work. As an exploratory attempt to directly link students’ perceptions of school science and professional science, we consider issues in our approach and implications for theories of epistemological beliefs.

CENS Area

Education

Title

Making CENS Data Useful And Usable

Authors

Stasa Milojevic, Kalpana Shankar, & Christine Borgman

Abstract

CENS is producing a vast and rich array of scientific and technical data. Ensuring accessibility and maintaining the integrity of those data is essential for the research and educational efforts of CENS participants and future users of CENS data. The nature of CENS data and the heterogeneity of its users present a number of information and data management challenges. We need to understand better how to collect, organize, access, and preserve scientific data so that they are useful for multiple users having different level of subject expertise and with multiple purposes for use. To do so will require studying current practices and information needs of CENS users, developing user scenarios, and investigating standards, tools, and policies for scientific data, metadata, and information management. Here we present our current research and plans for the future. Our goal is for CENS to become a leader in the implementation of standards and technologies for multidisciplinary data and sensor network portals.

CENS Area

Education

Title

Learning Plant Adaptation in Middle School

Authors

Jeffrey Bockert, Kathy Griffis, Joe Wise, Kelli Millwood, Terheggen, William A. Sandoval, Borgman

Abstract

This poster reports findings from a pilot study of a preliminary version of a CENS middle school inquiry module. The purpose of the pilot was to elicit students’ conceptions of plant evolution, especially leaf structure-function relationships in different environments. Pre-tests of students’ knowledge about plants and plant evolution confirmed our expectations that they lacked knowledge about leaf structure and function and about plant evolution. Post-tests, following approximately 13 hours of instruction, showed significant learning about leaf structure and function, but not plant evolution. Also, students performed better on short-answer questions on a post-test than on an essay that demanded they use conceptual knowledge to explain plant adaptation across environments. These results imply that a major design effort for CENS educational materials must be to help students integrate factual knowledge into coherent conceptual frameworks.

CENS Area

Education

Title

Going Beyond Nodal Aggregates : Spatial Average of a Continuous Physical Process in Sensor Networks

Authors

Saurabh Ganeriwal, Chih-Chieh Han, & Mani B. Srivastava

Abstract

Wireless ad-hoc sensor networks have caught the fancy of many researchers through the world in a very small span of time. Although notable progress has been made in several key areas, several researchers falter in the way they look at sensor networks i.e. just another kind of wireless ad hoc networks, albeit one composed of energy constrained nodes. A key aspect that makes sensor networks different from traditional networks is their strong link to the physical world. We develop this perspective by studying an interesting class of sensor network applications called aggregation applications. We argue that when a user queries for a specific aggregates like maximum, average etc., he is interested in knowing the statistics of the underlying physical process. We introduce a distinction between aggregates calculated over a region and aggregates calculated over a discrete set of nodes and classify them as spatial and nodal aggregates respectively. Till now, researchers have followed the approach of blindly doing nodal aggregation in response to every user query in sensor networks. For a continuous physical process and a random deployment of sensor nodes, which are a norm for sensor networks, the conventional approach of doing nodal aggregation produces inaccurate results. We profound our claim by studying a specific aggregation function namely the average over a region in detail. We use a voronoi-based approach to propose an algorithm for calculating spatial average in sensor networks. The algorithm can work in two modes: centralized and distributed. The energy and accuracy tradeoff associated with each of the two versions is analyzed in detail. The efficacy of the proposed algorithm is tested over a wide variety of physical processes including real precipitation data of South America acquired over a span of past 50 years. We will show that our algorithm gives a 2-8 times performance gain as compared to the conventional approach of doing nodal aggregation. We further explore the robustness of our algorithm to link failures and channel impairments. Although not 100% accurate, our approach is a simple, efficient and a practical solution for calculating the spatial average. We have implemented our algorithm on Berkeley motes. Our first prototype implementation occupies less than 12k flash ROM and consumes less than 1.6k run-time memory. Our algorithm can be easily integrated with available frameworks for doing aggregation in sensor networks.

CENS Area

Actuation

Title

Bacteria-Inspired Motion Strategies for Robotic Sensor Networks

Authors

Amit Dhariwal, Gaurav Sukhatme, Ari Requicha, & David Caron

Abstract

The poster presents a very simple approach for source and boundary detection using biased random walks (inspired from bacterial motion) which could be a novel strategy for robotic sensor network problems.

CENS Area

Actuation

Title

Mobile Robots and Sensor Network: Working Together

Authors

Maxim A. Batalin & Gaurav S. Sukhatme

Abstract

Our research is focused around idea of using sensor network and mobile robots cooperatively for solving various tasks. Moreover, sensor networks and mobile robots both benefit from such collaboration. One of the examples of such 'symbiotic' approach is solution to the mobile robot navigation problem. The task is to detect the area requiring robot's presence in the environment and then to guide the robot into that area. We propose solution to such problem and present results from real-world experiments conducted at Intel research facilities in Hillsboro, Oregon.

CENS Area

Actuation

Title

Boundary Detection Using Actuated Sensor Networks

Authors

Karthik Dantu & Gaurav Sukhatme

Abstract

We present an algorithm that detects and traces a contour of a scalar field. A set of static sensor nodes are deployed in a given area. The algorithm causes a mobile sensor node to approach a given contour. The algorithm uses local communication between the mobile node and its immediate neighbors only. Also, the path generated by the mobile node is near optimal when the static nodes are deployed at reasonable densities (avg. degree of about six).

CENS Area

Actuation

Title

Robomote: Sensor Actuator Platform

Authors

Mohammad Rahimi, Hardik Shah, Sandeep Babel, Guarav Sukhatme, John Heidemann, & Deborah Estrin

Abstract

Robomote is a next generation sensor actuator platform to enable mobility in sensor networks. Mobility assisted sensor networks would be able to do things like network repair, balance energy distribution and boundary detection.

CENS Area

Actuation

Title

Networked Infomechanical Systems (NIMS)**

Authors

Undergraduates: Ahmadi, Burke, Chan, Fong, Goudar, Kao, A. Liu, Lucas, Park, Porter, Ribaya, Sche, Scollans, Sharghi, Shirachi, Waugh, Wangrungvichaisri, & Yuen

Graduate Students: Gruzdas, Kansal, S. Liu, Pon, Rahimi, Ramanathan, Tseng, Verma, & Wu

Faculty: Ambrose, Estrin, Hamilton, Harmon, Jay, Kaiser, Pottie, Srivastava, Sukhatme, & Villasenor

Abstract

Sensor networks have emerged from research on low power, networked, and embedded systems and are now being applied to important scientific and societal issues. However, current sensor network architectures are unable to determine their most fundamental attribute, the quality of their data return, or sensing uncertainty. This poster will introduce networked infomechanical systems (NIMS), a new distributed embedded computing architecture that exploits a smart infrastructure and sensor diversity, is self-aware of its sensing uncertainty, and is able to adaptively reconfigure itself to maximize sensing fidelity. This will also include a description of the first NIMS prototypes and deployments in environmental science, public health, and physical security.

CENS Area

Actuation

Title

Solar Energy Collection and Management for Networked Infomechanical Systems (NIMS)

Authors

Rachel Scollans, Lisa Shirachi, Kris Porter, Richard Pon, Ashutosh Verma, Winston Wu, & William Kaiser

Abstract

Background: the NIMS project places sensors in remote locations. These remote locations are in areas where sensors cannot connect to power grids. Therefore, the project focuses on solar energy as the alternate energy source. This study's main purpose is to establish the amount of energy two solar modules can harvest in one day, and the subsequent energy budget for the project. In addition, this study is to analyze and determine the character of the solar panels, the how to of charging a lead acid battery, and the required battery bank size.

Method: the experimentation tested various properties under different conditions to characterize the solar cells. Results: established the amount of power the solar array could harvest in a day. Some effects of shading and complete coverage on the solar panel were factored and evaluated. The effects of weather on the solar system were found and analyzed.

Conclusions: the battery bank needs a minimum of three days of storage (for short-term deployment) more is optimal. The solar panels should be connected in array to receive more power. To collect more energy from the sun, the array should have an angle of includination of latitude+15 degrees. There is room for additional study on the PV system, particularly the stress on the solar cells due to obstructions. A possible finding upon further study might implement a circuit that cuts off the load if the voltage drops below 11v. Upon testing the solar panels in the field, mounted horizontally, it was found that enough energy was provided to power the node for a 24-hour period.

CENS Area

Actuation

Title

Autonomous Intelligent Mobile Micro Server**

Authors

Davud Jea, Arun Agrahara Somasundara, & Mani Srivastava

Abstract

None provided.

CENS Area

Actuation

Title

Networked Sensing of Nitrate in Support of Groundwater Quality Protection

Authors

Jose Saez, T. Bendikov, T. Schoellhammer, Yeonjeong Park, Juyoul Kim, Miodrag Potkonjak, Deborah Estrin, & Thomas C. Harmon

Abstract

None provided.

CENS Area

Contaminant

Title

On-Chip Chromatography-Based Chemical Sensing

Authors

Qing He, Changlin Pang, Yu-Chong Tai, Weixing Lu, & Chih-Ming Ho

Abstract

We are developing a highly sensitive and selective on-chip chromatography-based chemical sensing system, which has the capability to detect most common ions, such as nitrite, nitrate, fluoride, chloride, phosphate and sulphate, in drinking and underground water, with the sensitivity of PPM to PPB level, and within a few minutes or even fractions of a second. The proposed system consists of two major parts: on-chip chromatography system and chemical sensing system. The integrated chromatography system is built with parylene microfluidic technology. Two sensing techniques, one based on conductivity, the other on surface plasmon resonance (SPR), are being explored for their exceptional sensitivity and miniaturization capability.

CENS Area

Sensors

Title

Development And Environmental Applications of a Nitrate Microsensor Based on Doped Polypyrrole Films

Authors

Tatyana A. Bendikov, Juyoul Kim, & Thomas C. Harmon

Abstract

Many studies over the last two decades have employed the pyrrole polymerization processes, including several utilizing polypyrrole (PPY) doping with various ions and the application of these doped polypyrrole films as ion selective electrodes (ISE). This work extends these studies in two directions: 1) miniaturization of an ise for nitrate anions, based on nitrate-doped PPY films on a substrate of 7 um carbon fibers, and 2) application of these PPY(no3-) electrodes to nitrate transport experiments in an intermediate scale physical aquifer model, which is a prototype of environmental (in situ) measurements of nitrate in soils. Successful completion of this project will lead to the deployment of distributed nitrate sensor networks in complex environments, including soils, ground and surface waters.

CENS Area

Sensors

Title

Obstacle Identification and Localization

Authors

Jessica Feng & Miodrag Potkonjak

Abstract

Location discovery is a task of fundamental importance in wireless ad-hoc networks. The standard localization problem is difficult due to presence of errors in distance measurements and also the need to minimize communication cost. In addition, in real-life situations, there is also a need to consider the existence of obstacles when solving localization problem and interpreting measurements. Obstacles are defined as objects in the instrumented field that significantly alter (prolong) distance measurements. This problem has not yet been properly addressed so far due to its computational intractability and difficulty. Our goal is to introduce conceptual approaches, develop algorithms and software, and also validation techniques to identify and localize obstacles during simultaneous location discovery. The starting point is formulating location discovery as a nonlinear function minimization problem. Then the problem instance is solved using the polak-ribiera conjugate gradient minimization procedure. Furthermore, we have developed a generic approach that enables identification of obstacles by conducting a simple function augmentation. Also, using computational geometry-based technique we transformed the problem of obstacle localization to a graph theoretical problem that can be efficiently solved. In addition to the centralized version, we have developed localized obstacle identification and localization techniques that minimize the communication cost under packet size limitations. Finally, using non-parametric statistical techniques we establish intervals of confidence for all results. We demonstrate these techniques on a comprehensive set of simulation instances and use novel bipartite matching-based comparison of two solutions to evaluate the quality of solutions.

CENS Area

Sensors

Title

Model-based Localized Calibration for Interacting Actuators And Sensors

Authors

Jessica Feng & Miodrag Potkonjak

Abstract

Sensor-based measurements are intrinsically prone to errors. One can distinguish two types of errors: systematic and random noise errors. Calibration is the process of validating and/or adjusting the accuracy of a measuring instrument so that the systematic error is calculated and the bias is corrected. Distributed localized in-field calibration of sensor devices in an ad-hoc wireless network is of crucial importance since manual calibration is not feasible and cost-effective. In order to address calibration for an arbitrary system of sensors and actuators and an arbitrary model of systematic errors, we formulate calibration as nonlinear function minimization problem. We start by identifying the necessary and sufficient conditions to solve a specific instance of calibration in a given network. We solve the minimization problem using combination of polak-ribiere conjugate gradient method and singular value decomposition (SVD) algorithms in conjunction with binary search procedure. In addition, we have developed four-phase localized calibration procedure that minimizes the amount of required multi-hop limited-size packet communication and storage. Furthermore, we obtain the confidence intervals by applying resubstitution-based percentile nonparametric statistical methods. We demonstrate the effectiveness of the calibration process in terms of two canonical problems in sensor networks: location discovery and navigation.

CENS Area

Sensors

Title

Micromachined Amperometric Nitrate Sensor

Authors

Dohyun Kim, Jack W. Judy, & Ira B. Goldberg

Abstract

We have conducted feasibility studies based on chronocoulometry of nitrate for the purpose of fabricating a miniaturized sensor. Detection and monitoring of nitrate ion in surface water are important because of environmental and ecological influence of nitrate. For this application, sensors should be small, stand-alone, and have a low detection limit (<10 œm). Conventional nitrate sensing methods (spectroscopy, chromatography, electrophoresis, etc.) Do not meet aforementioned requirements because of the cumbersome sample preparation and complex implementation. Electrochemical detection is simple and a sensor can be easily miniaturized when using this method. The proposed electrochemical cell (silver working electrode, platinum counter electrode, ag/agcl reference electrode, and sodium hydroxide supporting electrolyte) shows high sensitivity for the nitrate ion detection. Oxygen dissolved in aqueous electrolyte interferes with the nitrate detection, but was successfully removed by a simple differential approach.

CENS Area

Sensors

Title

Smart Object Architecture for Energy-Efficient Wireless Sensors

Authors

Ashutosh Verma, Winston Wu, Sridhar Vemuri, Gregory Pottie, & William Kaiser

Abstract

Advances in distributed embedded computing and wireless networking have enabled the first generation of wireless sensor networks for applications including national security, healthcare, and environmental monitoring. Many applications require nodes with continuous vigilance and unattended operations for periods of months to years with only compact energy sources. In this research we are developing the new Smart Object architecture that is based on modular, reconfigurable, hardware components with intelligent interfaces for local power and performance scheduling and for rapid composabilty. It is focused on the development of architectures and modules along with the corresponding standard object oriented software library interfaces, and the implementation of complete open source wireless sensor solutions.

CENS Area

Sensors

Title

Adaptive Sampling for Marine Microorganism Monitoring

Authors

Bin Zhang, David Caron, Oberg, Ari Requicha, Beth Stauffer, & Gaurav Sukhatme

Abstract

The goal of Adaptive Sampling is to achieve relatively high spatial resolution with relatively few sensors/robots. With the abilities of moving and sensing, the sensors/robots are able to estimate where the important areas are, and then accumulate there. In this way, the environment can be sensed with different resolutions in different places but with emphasis on the interesting place.

CENS Area

Marine

Title

Detection Of Marine Microorganisms using Immuno-Based Methods

Authors

Beth Stauffer, Technical Staff, USC

Abstract

None provided.

CENS Area

Marine