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Open Access Publications from the University of California

CENS, a NSF Science & Technology Center, is developing Embedded Networked Sensing Systems and applying this revolutionary technology to critical scientific and social applications. Like the Internet, these large-scale, distributed, systems, composed of smart sensors and actuators embedded in the physical world, will eventually infuse the entire world, but at a physical level instead of virtual. An interdisciplinary and multi-institutional venture, CENS involves hundreds of faculty, engineers, graduate student researchers, and undergraduate students from multiple disciplines at the partner institutions of University of California at Los Angeles (UCLA), University of Southern California (USC), University of California Riverside (UCR), California Institute of Technology (Caltech), University of California at Merced (UCM), and California State University at Los Angeles (CSULA).

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

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

(2009)

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.

Cover page of Toward Resource Efficient Homes: From Measurements to Sustainable Choices

Toward Resource Efficient Homes: From Measurements to Sustainable Choices

(2009)

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 for inferring real-time resource consumption. However, indirect sensors cannot be calibrated during manufacturing because of varying ambient conditions. Thus, the main challenge becomes to provide a method that autonomously calibrates the sensors. We seek to develop an easy and self-configurable monitoring system for very fine grained resource monitoring in residential spaces.

Cover page of 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

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

(2009)

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.

Cover page of New Wireless Miniature Sensor Technologies for CENS

New Wireless Miniature Sensor Technologies for CENS

(2009)

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 field operational sensor for marine environmental monitoring.

Cover page of Networked Aquatic Microbial Observing Systems: An Overview

Networked Aquatic Microbial Observing Systems: An Overview

(2009)

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, light, nutrients, etc.). Specific projects undertaken in this application area involve the development and deployment of sensor networks to examine harmful algal blooms within King Harbor, City of Redondo Beach, and the construction of mobile sensor networks in open coastal waters off southern California. The latter research involves deployments of autonomous surface and underwater vehicles, and the development of hardware and software for coordinated activities of these robotic vehicles.

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

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

(2009)

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 sites included in this presentation detail the network nodes positioned at Redondo Beach and Marina Del Ray. One of the deployed mobile sensors highlighted here are autonomous Slocum gliders. These nodes operate in the open ocean for periods as long as one month. The gliders are connected to the network via a Freewave radio modem network composed of multiple coastal base-stations. This increases the efficiency of deployment missions by reducing operational expenses via reduced reliability on satellite phones for communication, as well as increasing the rate and amount of data that can be transferred. Another mobile sensor platform presented in this study are the autonomous robotic boats. These platforms are utilized for harbor and littoral zone studies, and are capable of performing multi-robot coordination while observing known communication constraints. All of these pieces fit together to present an overview of ongoing collaborative work to develop an autonomous, region-wide, coastal environmental observation and monitoring sensor network.

Cover page of Personal Data Vault: A Privacy Architecture for Mobile Personal Sensing

Personal Data Vault: A Privacy Architecture for Mobile Personal Sensing

(2009)

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 to track how the data is processed as well as who is using the data in order to provide transparency of data processing and foster a market of “certified” service providers. The adaptive filters govern how the data is sent from PDV to service providers in order to provide a better quality of services with minimal data using two methods: error-tolerant data sampling and anomaly detection.

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

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

(2009)

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 station to station, and collected at Internet drops, from where it is transmitted over the Internet to CENS each night. The instrument installation in Peru is almost finished and we have been receiving data daily from 47 stations (out of total 49) since Jan 2009. Two remain without any network connectivity. The software system provides dynamic link quality based routing, reliable data delivery, and a disruption tolerant shell interface for managing the system from UCLA without the need to travel to Peru. The near real-time data delivery also allows immediate detection of any problems at the sites. We are building a seismic data and GPS quality control toolset that would greatly minimize the station's downtime by alerting the users of any possible problems.