A revolutionary approach to sensor data processing that leverages bio-inspired computing for intelligent sensing.

Brief description not available

Brief description not available

      Goniophotometers measure the luminance distribution of light emitted or reflected from a point in space or a material sample. Increasingly there is a need for such measurements in real-time, and in real-world situations, for example, for daylight monitoring or harvesting in commercial and residential buildings, design and optimization of greenhouses, and testing laser and display components for AR/VR and autonomous vehicles, to name a few. However, current goniophotometers are ill-suited for real-time measurements; mechanical scanning goniophotometers have a large form factor and slow acquisition times. Parallel goniophotometers take faster measurements but suffer from complexity, expense, and limited angular view ranges (dioptric angular mapping systems) or strict form factor and sample positioning requirements (catadioptric angular mapping systems). Overall, current goniophotometers are therefore limited to in-lab environments.      To overcome these challenges, UC Berkeley researchers have invented an optical sensor  for parallel goniophotometry that is compact, cost-effective, and capable of real-time daylight monitoring. The novel optical design addresses key size and flexibility constraints of current state-of-the-art catadioptric angular mapping systems, while maximizing the view angle measurement at 90°. This camera-like, angular mapping device could be deployed at many points within a building to measure reflected light from fenestrations, in agricultural greenhouses or solar farms for real-time monitoring, and in any industry benefitting from real-time daylight data.

Determining the properties that control fluid flow and pressure migration through rocks is essential for understanding groundwater, energy reservoirs and fault zones. Hydraulic diffusivity is the key parameter that controls pressure migration in reservoirs. There is a need to determine it in situ for energy, groundwater and earthquake applications. Direct measurements of these properties underground generally require expensive and invasive processes such as pumping large volumes of water in or out of the ground. Most current methods rely on either active pumping between wells or proxies such as seismic velocity or the migration time of microseismicity. These conventional methods may change the structure that they are trying to measure and do not resolve variations in space without complex, multiple experiments. Moreover, active pumping is expensive, invasive and sensitive to a limited set of scales, while proxies are difficult to calibrate.

 The dynamic patterning of 3D optical point clouds has emerged as a key enabling technology in volumetric processing across a number of applications. In the context of biological microscopy, 3D point cloud patterning is employed for non-invasive all-optical interfacing with cell ensembles. In augmented and virtual reality (AR/VR), near-eye display systems can incorporate virtual 3D point cloud-based objects into real-world scenes, and in the realm of material processing, point cloud patterning can be mobilized for 3D nanofabrication via multiphoton or ultraviolet lithography. Volumetric point cloud patterning with spatial light modulators (SLMs) is therefore widely employed across these and other fields. However, existing hologram computation methods, such as iterative, look-up table-based and deep learning approaches, remain exceedingly slow and/or burdensome. Many require hardware-intensive resources and sacrifices to volume quality.To address this problem, UC Berkeley researchers have developed a new, non-iterative point cloud holography algorithm that employs fast deterministic calculations. Compared against existing iterative approaches, the algorithm’s relative speed advantage increases with SLM format, reaching >100,000´ for formats as low as 512x512, and optimally mobilizes time multiplexing to increase targeting throughput. 

Researchers at the University of California, Davis have developed a system consisting of cameras and multi-wavelength lasers that is capable of precisely locating and inspecting items.

Researchers at the University of California, Irvine have developed a novel algorithm that is designed to be integrated with current multi-tone continuous wave (MTCW) lidar technology in order to enhance the capability of lidar to acquire range (distance) of fast-moving targets as well as simultaneous velocimetry measurements. This technology revolutionizes remote sensing by providing high precision, single-shot simultaneous ranging and velocimetry measurements without the need for sweeping.  

Researchers at the University of California, Davis have developed a phased-locked loop coupled array system capable of generating phase shifts in phased array antenna systems - while minimizing signal losses.

UCLA researchers in the Department of Electrical and Computer Engineering have developed a wirelessly powered, flexible sensor that detects pipe leaks over long distances.

UCLA researchers in the Department of Electrical and Computer Engineering have developed a diffractive neural network that can process an all-optical, 3D printed neural network for deep learning applications.

This materials platform enables flexible engineering of infrared (IR) emissivity and development of thermal radiation devices beyond the Stefan-Boltzmann law. The materials structure is based on thin films of vanadium oxide (VO2) with judiciously designed graded W doping across a thickness less than the skin depth of electromagnetic screening (~100 nm). The infrared emissivity can be engineered to decrease in an arbitrary manner from ~ 0.75 to ~ 0.35 over a temperature range up to 50 C near room temperature. The large range of emissivity tuning and flexible adjustability is beyond the capability of regular materials or structures. This invention provides a new platform for unprecedented manipulation of thermal radiation and IR signals with a wide variety of applications, such as:  The emissivity can be programmed to precisely counteract the T^4 dependence in the Stefan-Boltzmann law and achieve a temperature dependent thermal radiation. Such a design enables a mechanically flexible and power-free infrared camouflage, which is inherently robust and immune to drastic temporal fluctuation and spatial variation of temperature. By tailoring structure and composition, the materials platform can create a surface with robust and arbitrary IR temperature image, regardless of the actual temperature distribution on the targets. This design of infrared "decoy" not only passively conceals the real thermal activity of the object, but also intentionally fools the camera with a counterfeited image. The materials platform can achieve strong temperature dependence of reflectivity over a broad wavelength from near-IR to far-IR, which is promising for high-sensitivity remote temperature sensing by thermoreflectance imaging, or active reflectance modulation of IR signals. 

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. 

UCLA researchers in the Department of Mechanical & Aerospace Engineering and the Department of Pathology & Lab Medicine have proposed a new platform technology to actuate and sense force propagation in real-time for large sheets of cells.

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. 

The technology is a method for multiple users to interact simultaneously with multiple tiled displays.Under this technology, multiple users are allowed to interact with a tiled display with a distributed registration technique.It features easy scalability across different applications, modalities and users and user interactions involve hand gestures or are laser-based.

A composite material system with embedded Erbium-Arsenic (ErAs) nanostructures for 1030nm operation with higher dark resistance and ultrafast carrier lifetime. 

Novel quantum dot field-effect transistors without bias-stress effect that also have high mobility and are environmentally stable.

Modification of scanning probe microscope for direct measurement of both, amplitude and phase of vibration of a single molecule.

Pressure ulcers are formed when constant pressure or rubbing results in breakdown of the skin. Hospitals and nursing homes spend billions of dollars each year to prevent formation of pressure ulcers in their patients, as many current solutions (pressure-distributing beds, re-positioning patients every few hours, etc.) are very expensive and labor-intensive. Additionally, chronic cutaneous wounds affect millions of people each year, costing billions of dollars to treat. These ailments represent critical, unmet needs in clinical medical practice, and result in increased morbidity and mortality at a high human and financial cost.In response to this challenge, investigators and University of California, Berkeley have developed a flexible wound healing monitor. As an objective measurement, wound progression is monitored remotely. Otherwise undetectable features are identified visually. The flexible wound healing monitor uses impedance spectroscopy to measure and characterize tissue health, allowing physicians to identify high-risk areas of skin to prevent formation of pressure ulcers or to objectively monitor progression of wound healing. Uniquely, the flexible wound healing monitor takes measurements across nearest neighbor electrodes in an array to create a visually intuitive map of electrical impedance. Data visualization is through a map resembling the electrode array. Spaces between every two electrodes are filled with a color corresponding to the impedance magnitude or phase as determined by an intuitive color scale. The flexible wound healing monitor can be integrated into the Wound VAC, a current standard-of-care wound treatment. In addition, impedance measurements taken at high-risk sites can allow for early detection of impending pressure ulcer formation. First prototypes of the flexible wound healing monitor were fabricated on rigid FR4 printed circuit boards. The investigators are transferring this technology onto a flexible substrate using inkjet printing of conductive metal ink. 

UCLA researchers in the Department of Bioengineering have created a novel imaging system that measures corneal hydration levels by utilizing terahertz (THz) frequency (100 GHz - 1 THz) sources and detectors.

In 2013, more than 33,000 wildfires have burned in the Western United States, covering over 5,000 square miles, and destroying almost 1000 homes and commercial buildings. In 2012, Federal agencies spent almost $2 billion on national firefighting resources. Fire detection today is much like it was 200 years ago, relying primarily on spotters in fire towers or on the ground and on reports from members of the public. The information can be augmented by expensive aerial reconnaissance and lightning detectors that alert firefighters to ground strikes, which can be a source of wildfires. New technologies that could improve situational awareness though proactive information collection and platform data sharing could advance wildfire decision-making and help protect human health and property worldwide. To help solve these challenges, researchers at Berkeley have successfully developed proprietary computer techniques which, when used with modern imaging detectors, could detect heat from early fires with minute-scale detection times and orders magnitude aerial sensitivity improvement. Berkeley's Fire Urgency Estimator in Geosynchronous Orbit (FUEGO) shows promise in rapid and accurate detection of hot spots on a massive scale, with the capability to identify patterns and detect important content from large volumes of information. By knowing when and where small fires are active, suppression resources can be more efficiently deployed to reduce vulnerability and risk to human safety, health, and property protection.

Ringer distinguishes flexible regions from rigid regions of biomolecules such as drug receptors. To assess the generality and significance of the weak secondary peaks of uniquely modeled residues, we ran Ringer on 402 high-resolution (<=1.5 Å) crystal structures from the Protein Data Bank. Omit electron-density maps were analyzed to reduce the effects of model bias. When applied after refinement is considered complete, Ringer discovers polymorphism at over 3.5 times the frequency that is currently modeled in the PDB. Multiple conformers are found for >18% of unbranched residues in a test set of 402 high-resolution structures, in addition to the 5.1% that are already modeled. More than a method for enhancing crystallographic refinement, however, Ringer is best used as a tool for systematically detecting low-occupancy structural features. The hidden conformational substates identified using Ringer provide clues to the functional roles of protein structural polymorphism and to assess the response of protein side chain distributions to perturbations including ligand binding, temperature changes and mutations. In calmodulin, for example, Ringer identifies side chains that undergo conformational population inversions and side-chain rigidification upon peptide binding, linking the structure to dynamic properties. Similarly, in human proline isomerase, Ringer was used to define the nature of a coupled conformational switch in the free-enzyme that defines motions that occur during turnover. In both cases, the alternate conformations identified by Ringer provided structural insights not available from any other experimental technique. Link to overview of Ringer software