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In Situ Soil Nitrate Sensor

The invention is used for determining in-situ nitrate concentrations in soil solution using either ISE (Ion Selective Electrode) or fiber optic spectroscopy when the liquid in the porous cup of the in-situ probe is equilibrated with surrounding soil solution through the diffusion process.

Ultra-Sensitive Polybrominated Diphenyl Ether (PBDE) Detector

Polybrominated diphenyl ethers (PBDEs) are a common brominated flame retardant, which are commonly found in consumer products. Because they are not chemically bound to polymers, PBDEs are blended in during formation and have the ability to migrate from products into the environment.  Studies suggest that PBDEs pose potential health risks such as hormone disruptors, adverse neurobehavioral toxins and reproductive or developmental effects.  For this reason it is important to have the capability to sense the presence of PBDEs even in low concentrations.

An On-Bed Monitoring System For Rehabilitative Exercises

UCLA researchers have developed a novel method for monitoring rehabilitative exercises using a bed sheet with high-density pressure sensors.

Metal Triazolites

UCLA researchers in the Department of Chemistry and Biochemistry have developed a novel metal-organic framework (MOF) using triazole ligands that allows for facile modification with a variety of metals, which has unique gas separation and adsorption properties.

Multi-Tone Continuous Wave LIDAR

Object detection and ranging is a fundamental task for several applications such as autonomous vehicles, atmospheric observations, 3D imaging, topography and mapping. UCI researchers have developed a light detection and ranging (LIDAR) system which makes use of frequency modulated continuous waves (FMCW) with several simultaneous radiofrequency tones for improved speed of measurement while maintaining robust spatial information. 

Spectro-Temporal Lidar

UCLA researchers in the Department of Electrical and Computer Engineering have developed a LIDAR sensor that collects high frame-rate 3D measurements for autonomous vehicle and robotics applications.

Automated Immersion Mode Ice Spectroscopy

Ice nucleating particles (INPs) suspended in the Earth’s atmosphere influence cloud properties and can affect the overall precipitation efficiency and predictability of cloud systems worldwide. INPs induce freezing of cloud droplets at temperatures above their normal freezing-point (~-38 C), and at a relative humidity (RH) below the normal freezing RH of aqueous solution droplets at lower temperatures. These INP induced variabilities influence cloud lifetime, phase, as well as cloud optical and microphysical properties. Developing a relational model of INPs in global climate models has proven challenging as existing instrumentation systems either require too much air volume (in real-time flow instruments) or exhibit too much temperature variability (in off-line frozen assay based instruments).  Thus, there is a real urgency to address this unmet need.

Linear/Angular Position Stabilization & Control Of An Underwater Robotic System

There are several emerging applications for Autonomous Underwater Vehicles (AUVs) where the agility and accurate control of location and/or orientation is critical. In the presence of random ocean currents and waves, conventional AUV systems need to use a combination of their thrusters to generate an appropriate force/torque and cancel the external disturbance to maintain the desired attitude or position. This is a relatively slow response since it requires accelerating and pushing water around the vehicle body. Thus, existing AUVs have disadvantages: (i) accurate and agile orientation and position control/stabilization is challenging; (ii) since thrusters are operational during reorientation maneuvers, a substantial amount of power is consumed to pump the bulk fluid, wasting the precious power storage of the vehicle and thus reducing its operational time; and (iii) drag forces and torques exerted on the thrusters significantly affect the efficiency of reorientation maneuvers.   UC Berkeley researchers have designed a new device for fast stabilization and control of an underwater robotic vehicle. In this architecture, the attitude maneuvers are performed using reaction torques that the body of the vehicle gains from a central inertial system.   

Device-Free Gesture Recognition System

The popularity of Internet of Things (IoT) devices (without tradition human-computer interfaces) has made gesture recognition an advantageous form of human-computer interaction - especially in smart home applications. However, conventional gesture recognition approaches have issues that limit their pervasive use. For example, wearable devices (e.g. watches and wristbands) with inertial sensors can be inconvenient to always wear; radio frequency systems are cost prohibitive for large-scale deployment; and vision-based systems require favorable lighting and introduce privacy concerns. Recently, WiFi infrastructure, and associated WiFi-enabled mobile and IoT devices have become ubiquitous, and correspondingly, have enabled many context-aware and location-based services. To address the opportunities for gesture recognition and take advantage of the popularity of WiFi, researchers at UC Berkeley developed a gesture recognition system based on analyzing signals from existing WiFi-enabled devices. This novel WiFi-enabled, device-free gesture recognition system can identify human gestures with consistent high accuracy and has robust environmental dynamics.

Device-Free Human Identification System

In our electronically connected society, human identification systems are critical to secure authentication, and also enabling for tailored services to individuals. Conventional human identification systems, such as biometric-based or vision-based approaches, require either the deployment of dedicated infrastructure, or the active cooperation of users to carry devices. Consequently, pervasive implementation of conventional human identification systems is expensive, inconvenient, or intrusive to privacy. Recently, WiFi infrastructure, and associated WiFi-enabled mobile and IoT devices have become ubiquitous, and correspondingly, have enabled many context-aware and location-based services. To address the challenges of human identification systems and take advantage of the popularity of WiFi, researchers at UC Berkeley developed a human identification system based on analyzing signals from existing WiFi-enabled devices. This novel device-free approach uses WiFi signal analysis to reveal the unique, fine-grained gait patterns of individuals as the "fingerprint" for human identification.

Air Quality Monitoring Using Mobile Microscopy And Machine Learning

UCLA researchers have developed a novel method to monitor air quality using mobile microscopy and machine learning.

A New and Cost-Effective Technology to Produce Hybrid-Glass/Optical Bubble Probes

The ability to accurately quantify gas volumes in liquid flows has important applications in environmental science and industry. For example, environmental processes that significantly contribute to changes in earth’s climate, such as methane seeps from the sea floor and the exchange of gases between the ocean and atmosphere at the sea surface, demand precise sensors that are small and sensitive enough to measure the ratio of liquids and gases in these bubbly mixtures. These measurements also play a critical role in the operational efficiency of a wide variety of different engineering processes. Applications include, the monitoring the optimal amount of bubbled oxygen in the treatment of waste water and sewage, and the oil and gas industry, especially in undersea oil pipelines in the Gulf of Mexico alone, have spent billions of dollars annually on added refinement techniques to remove seawater that could be preventable if sensors were able to measure the ratio of crude oil, seawater and gas as the mixture is pumped through pipelines. These challenges exist in both research and industry because the current manufacturing process for making the needed gas/liquid probes have significant cost constraints. Clearly, there is a need for a new and cost-effective technology to produce these probes.

Hydrogen Gas Sensors Based On Patterned Carbon Nanotube Ropes

This is a fabrication method for hydrogen gas sensors; these sensors have more rapid response times and are more sensitive than current detection techniques.

GPS-Based Miniature Oceanographic Wave Measuring Buoy System

Oceanic monitoring helps coastal communities, economies, and ecosystems thrive. The coastlines and open oceans prove to be very important to maritime countries for recreation, mineral and energy exploitation, shipping, weather forecasting and national security. As solar power, GPS, and telecomm improvements have been made, directional wave buoys have emerged and set the standard in wave monitoring. Non-directional and directional wave measurements are of high interest to users because of the importance of wave monitoring for successful marine operations. Wave data and climatological information derived from the data are also used for a variety of engineering and scientific applications.

Combined Greywater-Storm Water System With Forecast Integration

Water is a scarce resource in some part of the United States, and recent droughts in the Midwest and the South have elevated the issue of water scarcity to a national level. Existing water sources will face increasing strain due to population growth and climate change, and financial and regulatory barriers will prevent the development of new sources. One method to alleviate water scarcity is storm water capture. Storm water can be used for non-potable applications such as irrigation, laundry, and toilet flushing to significantly reduce domestic municipal water consumption. However, in arid regions of the US, rain comes in short, intense storms only a few months out of the year, and the duration and intensity of these storms require large storage tank volumes for storm water capture to be financially feasible.    One solution is to integrate storm water capture with greywater capture. Greywater is a reliable source of water for domestic reuse, and includes water from washbasins, laundry, and showers (kitchen sinks and water for toilet flushing are considered blackwater). Combining greywater-storm water in the same collection system allows for a much smaller storage tank. A UC Berkeley researcher, along with other researchers, have developed aforecast-integrated automated control system for combined greywater-storm water storage and reuse. A simple and reliable approach for managing greywater and storm water collection at a household or community level is provided, allowing for the near-continuous monitoring and adjustment of water quantity and quality in a combined greywater-storm water storage tank based on monitored feedback/output from individual, tank-specific sensors and/or sensors located elsewhere in the water collection system.   

Novel Sensor to Transduce and Digitalize Temperature Utilizing Near-Zero-Power Levels

Temperature sensors are routinely found in devices used to monitor the environment, the human body, industrial equipment, and beyond. In many such applications, the energy available from batteries or the power available from energy harvesters is extremely limited, thus the power consumption of sensing should be minimized in order to maximize operational lifetime.

The Flying Wing Autonomous Underwater Glider Technology

The underwater glider can be categorized as an autonomous underwater vehicle (AUV) that does not rely on an electrically driven propeller, but relies on small changes in its buoyancy and wings to move up and down. The pitch and roll is controlled by using an adjustable ballast. The AUV has been quite useful for collecting oceanographic data due to its unique propulsion system that uses very little energy and its ability to be on a sampling mission for weeks to months.

Highly Stretchable & Flexible Electronic Sensors

A new approach to creating highly stretchable electronic devices using twisted conductive microtubules.

Quantification Of Plant Chlorophyll Content Using Google Glass

UCLA researchers in the Department of Electrical Engineering have invented a novel device that can quantify chlorophyll concentration in plants using a custom-designed Google Glass app.

Enhanced Cell/Bead Encapsulation Via Acoustic Focusing

The invention consists of a multi-channel, droplet-generating microfluidic device with a strategically placed feature. The feature vibrates in order to counteract particle-trapping micro-vortices formed in the device. Counteracting these vortices allows for single particle encapsulation in the droplets formed by the device and makes this technology a good candidate for use in single cell diagnostics and drug delivery systems.

Sensitive Detection Of Chemical Species Using A Bacterial Display Sandwich Assay

96 Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Calibri; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin;} Endocrine disrupting compounds are found in increasing amounts in our environment, originating from pesticides, plasticizers, and pharmaceuticals, among other sources. These compounds have been implicated in diseases such as obesity, diabetes, and cancer. The list of chemicals that disrupt normal hormone function is growing at an alarming rate, making it crucially important to find sources of contamination and identify new compounds that display this ability. However, there is currently no broad-spectrum, rapid test for these compounds, as they are difficult to monitor because of their high potency and chemical dissimilarity.   To address this, UC Berkeley researchers have developed a new detection system and method for the sensitive detection of trace compounds using electrochemical methods.  This platform is both fast and portable, and it requires no specialized skills to perform. This system enables both the detection of many detrimental compounds and signal amplification from impedance measurements due to the binding of bacteria to a modified electrode. The researchers were able to test the system finding sub-ppb levels of estradiol and ppm levels of bisphenol A in complex solutions. This approach should be broadly applicable to the detection of chemically diverse classes of compounds that bind to a single receptor.  

Advanced Chemical Sensing Method and Apparatus

Conventional chemical sensors or chemical resistors detect the molecule concentration by monitoring the resistance change caused by the reaction near the sensing material surface. One of the problems with these systems is with drift, when over time the analyte molecules poison the device’s sensing surface, causing weaker performance on selectivity and sensitivity. This often requires rigorous and timely calibrations to the sensor, which involves human intervention, and often times complete sensor replacement. To address this problem, researchers at the University of California, Berkeley, have developed a vertical platform that dramatically improves the sensor’s ability to manage and recover from the poison environments. By examining and manipulating the sensing plane vis-à-vis the near field surface, researchers have demonstrated an effective and robust chemical sensing platform for a range of gas sensing applications.

Improved Energy Harvesting for Current-Carrying Conductors

There are an estimated 130 million wooden poles that support overhead power lines in the US.  Extreme weather, aging, storms or sabotage can all lead to potential damage of these poles and power lines, which can leave large areas without basic necessities.  Due to this risk, it’s anticipated that power utility companies will deploy sensors and corresponding energy harvesters to better respond to potential damage of this critical electricity grid infrastructure. To address this anticipated mass deployment of sensors and harvesters, researchers at UC Berkeley have developed technology improvements to harvesting of electrical energy from energized conductors carrying alternating currents, such as those on overhead and underground power lines (as well as power-supplying conductors in offices and dwellings).  These enhanced harvesters would improve the economics of deploying sensors across a national power grid.  The Berkeley harvesters can readily provide enough power to supply wireless communication devices, energy storage batteries and capacitors, as well as sensors such as accelerometers, particulate matter measuring devices, and atmospheric sensors.

Distributed Dynamic Strain Fiber Optics Measurement For Use In Sensors

96 Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Calibri; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin;} Structural health monitoring (SHM) is becoming critical in structural engineering and geotechnical engineering applications in recent years. The use of fiber optic distributed sensors for SHM has the advantage of long sensing distance, distributed sensing information and small size.  Distributed fiber optic sensors can be used to monitor distributed temperature and strain information but also has application for used in detection of seismic activity, security sensing, and traffic/railway/bridge monitoring.   UC Berkeley researchers have developed methods and sensors for distributed dynamic strain measurement using optical fiber that results in a larger sensing signal, better signal-to-noise ratio and longer sensing distance up to a few km lengths. The system can take strain readings at every 4m along an 1km length optical fiber at 2.5 kHz sampling speed with a strain resolution of 30 microstrain.  

RF-Powered Micromechanical Clock Generator

Realizing the potential of massive sensor networks requires overcoming cost and power challenges. When sleep/wake strategies can adequately limit a network node's sensor and wireless power consumption, then the power limitation comes down to the real-time clock (RTC) that synchronizes sleep/wake cycles. With typical RTC battery consumption on the order of 1µW, a low-cost printed battery with perhaps 1J of energy would last about 11 days. However, if a clock could bleed only 10nW from this battery, then it would last 3 years. To attain such a clock, researchers at UC Berkeley developed a mechanical circuit that harnesses squegging to convert received RF energy (at -58dBm) into a local clock while consuming less than 17.5nW of local battery power. The Berkeley design dispenses with the conventional closed-loop positive feedback approach to realize an RCT (along with its associated power consumption) and removes the need for a sustaining amplifier altogether. 

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