Center for Embedded Network Sensing

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 model for heat conduction to estimate soil subsurface temperatures and heat flux over a wide area due to sunflecks from a forest canopy.

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

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 nationwide about espoused program goals, practices, participant demographics, and in particular, specific efforts designed to address gender inequity in these fields.

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 with subsurface soil measurement networks for physical and biological activity, together with aquatic and riparian sensor networks to measure groundwater fluxes and nutrient dynamics. More recently, complex sensors, such as networked digital cameras and microphones, as well as newly emerging sensors, are being integrated into sensor networks for hierarchical methods of sensing that promise a further understanding of our ecological systems by revealing previously unobservable phenomena.

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 user participation in regulating sharing and disclosure, we discuss three foundational design principles: primacy of participants, data legibility, and engagement of participants throughout the data life cycle. We also discuss social changes that will need to accompany these design principles, including engagement of groups and appeal to the public sphere, increasing transparency of services through voluntary or regulated labeling, and securing a legal privilege for raw location data.

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 that formed during the Northridge earthquake. DOI: 10.1193/1.2991300

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 performed well on real-world deployments, including one deployment of 130 sensors, replayed datasets, and network simulations. Confidence accurately detects and diagnoses at least 90% of all data, and user interaction improves it's performance.

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.

• 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 effect. The diel hysteresis at Wv was explained by including the temperature-dependent component of soil respiration and the variation dependent on photosynthetically active radiation.

• The results show that vegetation type and fine root and rhizomorph dynamics influence soil respiration in addition to changes in light, temperature and moisture

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.