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Thousand-Color Sensor Reveals Contaminants in Earth and Sea by Prof. Eyal Ben-Dor and Tel Aviv University Department of Geography and the Human Environment

TAU technology spots environmental hazards from inches to light-years away

The world may seem painted with endless color, but physiologically the human eye sees only three bands of light — red, green, and blue. Now a Tel Aviv University – developed technology is using colors invisible to the naked eye to analyze the world we live in. With the ability to detect more than 1,000 colors, the “hyperspectral” (HSR) camera, like Mr. Spock’s sci-fi “Tricorder,” is being used to “diagnose” contaminants and other environmental hazards in real time.

Prof. Eyal Ben-Dor of TAU’s Department of Geography and the Human Environment says that reading this extensive spectrum of color allows the sensor to analyze 300 times more information than the human brain can process. Small and easy to use, the sensor can provide immediate, cost-effective, and accurate monitoring of forests, urban areas, agricultural lands, harbors, or marinas — areas which are often endangered by contaminants and phenomena such as soil erosion or sediment dust. Using the hyperspectral camera will ultimately lead to better protection and treatment of the environment.

The HSR sensor, detailed in the journal Remote Sensing of Environment, has both commercial and scientific applications, says Prof. Ben-Dor, who has consulted for local and foreign space agencies in their use of the technology. These applications can include anything from helping companies adhere to regulations on environmental contamination to measuring the extent of environmental damage caused by forest fires.

From far and wide

The sensor interprets reflected sunlight radiation that bounces off an object, material, or environment. Each reflected color represents a different chemical reaction between two compounds. “A combination of absorption or reflection of energy creates the color that the HSR sensor sees,” explains Prof. Ben-Dor. The sensor’s extensive range — reading information from as close as 0.4 inches and as far as 500 miles away — means it can be placed anywhere from the ground itself to unmanned aircraft, satellites or weather balloons. The camera can also be pointed towards the stars to help astronomers gain insight into the make-up of a planet’s atmosphere.

Most recently, Prof. Ben-Dor has used the technology to survey different environments, including soil and sea, seeking to identify problem areas. The area around gas pipelines is one site of environmental contamination, he says. Leaks can be particularly damaging to the surrounding earth, so the sensors can be used to test along a pipeline for water content, organic matter, and toxins alike. In agricultural areas, the sensor can be used to determine levels of salt in the soil to save crops before they are destroyed.

The technique is also effective in marinas, which are highly contaminated by gasoline and sealants from the undersides of sea vessels. “This toxic material sinks, and becomes concentrated on the sediment of the marina, which also contaminates nearby beaches,” Prof. Ben-Dor explains.

The color of possibility

Before the HSR technology was developed, samples of potentially contaminated or endangered soil, sediment or water would have to be taken to the lab for lengthy analysis. With the use of a hyperspectral sensor, real-time analysis allows immediate action to better environmental conditions. The sensor can also be used to determine levels of indoor pollution caused by dust, analyze the strength of concrete being used for buildings in earthquake zones, or scan the environment around an open mine to look at the impact on human health.

According to Prof. Ben-Dor, this technology’s potential is endless and can be used in disciplines such as medicine, pharmacology, textile industry, and civil engineering. Without so much as a touch, the sensor can provide in-depth analysis on environmental composition. It’s a method that can map and monitor the earth from “microscope to telescope,” he says.

OV8850 ||| Color CMOS 8 Megapixel (3280 x 2464) Image Sensor with OmniBSI-2™ Technology by OmniVision

The 1/4-inch OV8850 leads the CMOS sensor pixel design race in the smartphone market by enabling autofocus modules that are 20 percent slimmer than today’s 1/3.2-inch 8-megapixel modules. Besides a small footprint, the 1.1-micron OmniBSI-2 pixel offers significant improvements in power efficiency and comparable image quality to the previous generation 1.4-micron OmniBSI™ pixel, making it an attractive solution for next-generation smartphones and tablets.

An integrated scaler allows the camera to maintain full field of view in 1080p/30 high-definition (HD) video and preview modes and provides extra adjustable resolution for electronic image stabilization (EIS). Additionally, the sensor’s 2 x 2 binning functionality provides EIS for 720p/60 HD video recording. Other advanced features of the OV8850 include an on-chip temperature sensor, two PLLs, context switching, 4 Kbits of one-time programmable memory, lens shading correction, defective pixel cancelling, black sun elimination, and alternate row exposure for high dynamic range (HDR) video and still image capture.

The OV8850 supports 8 and 10-bit RAW image output with all standard image quality control functions supported through the SCCB interface. The sensor fits in an 8.5 x 8.5 mm autofocus camera module with a build height of 4.7 mm and features a 4-lane MIPI/LVDS that facilitates the required high data transfer rate.

Features

Product Specifications

Part Number	OV8850-G04A
Package Size	5550 x 5400 µm
Analog/ Digital	Digital
Chroma	Color
Array Size	3280 x 2464 µm
Resolution	8 MP
Package	RW
Optical Format	1/4″
Pixel Size	1.1 µm
Frame Rate	30 @ EIS1080p 24 @ Full 60 @ EIS720p
Power Consumption	TBD
Temperature	Stable: 0° – 65°C Operating: -30° – 70°C
Output Format	RAW
Product Brief	Product Brief

Apple’s Face Recognition Plans For iOS5 To Make Smartphones Even Smarter by Kit Eaton

Way back in 2010, Apple spent some of its fast-amassing cash pile to buy Polar Rose, a face recognition firm from Sweden. Now it seems it’s been busy ever since incorporating Polar Rose’s face identificationand tracking algorithms into iOS5–its upcoming revision of the operating system that powers iPhones and iPads. So deep is the integration–it’s far beyond a simple app–that there’re API handles.

This is huge news, for all the reasons that Google’s use of face recognition in its online offerings could change much about the web. By adding controls into iOS’ API, Apple’s allowing third-party apps to access the core face recognition tech. Code like “hasLeftEyePosition,” “mouthPosition” and the image-processing for identification means that apps can track faces and also recognize users.

This means games can track face positions for an unusual mode of input, apps like Instagram could automatically tag people’s faces they can identify, smart video apps could use facial cues to do digital image stabilization and so on. In more interactive modes, we can even imagine iOS face IDs on an iPhone being used as an automatic log-in on a paired Mac. And it’s even plausible that Apple may be using facial recognition as part of its secure user authentication for future wireless wave-and-pay systems, which we know it’s been working on.

But wait, there’s more. Another relatively recent Apple purchase, Siri, is also showing up in the latest developer builds of iOS5, alongside evidence that Apple’s including code it acquired as part of its deal with voice recognition experts Nuance. Siri was a highly promising smart personal assistant app, and until now it’s entirely disappeared, so the fact it’s showing up in iOS5 is interesting. And it could be transformational. Because what Apple seems to be doing is enable smart voice control in iOS5 along the lines of “set up a meeting with mark on wednesday at 11 a.m.,” where Mark is a user contact. There’re also text-to-speech powers, which could be really important for using your phone while driving–we can imagine an iPhone reading out incoming SMSs, and also a smarter integrated navigation app (which we know Apple’s also working on).

In this sense, Apple’s moving the iPhone and iPad toward the famous Knowledge Navigator concept it created back in the 1980s. And we are thus tempted to think it’ll only work in full on newer devices–possibly just the iPad 3, the upcoming iPhone 5 (and maybe the current generation too): Apple prefers to make its enhanced user experiences “all or nothing,” implying that the degraded performance older devices offer for new high-tech software is too disappointing to users.

And it’s also a powerful new weapon in the war against Android tablets and phones. When the Android Nexus One first emerged, we called its integration of voice control an important secret feature. But it’s never been properly realized, much less spun into the tightly integrated smart “digital PA” which Apple seems to be working toward. By adding in all this tech, Apple’s enabling all sorts of clever marketing angles, and is even appealing to business users a little more–something it seems keen on at a corporate level.

Resistive switches based on piezoelectric nanowires allow electrical signals to be produced from mechanical actions by John Toon

The piezoelectrically modulated resistive memory (PRM) devices take advantage of the fact that the resistance of piezoelectric semiconducting materials such as zinc oxide (ZnO) can be controlled through the application of strain from a mechanical action. The change in resistance can be detected electronically, providing a simple way to obtain an electronic signal from a mechanical action.

“We can provide the interface between biology and electronics,” said Zhong Lin Wang, Regents professor in the School of Materials Science and Engineering at the Georgia Institute of Technology. “This technology, which is based on zinc oxide nanowires, allows communication between a mechanical action in the biological world and conventional devices in the electronic world.”

The research was reported online June 22 in the journal Nano Letters. The work was sponsored by the Defense Advanced Research Projects Agency (DARPA), the National Science Foundation (NSF), the U.S. Air Force and the U.S. Department of Energy.

In conventional transistors, the flow of current between a source and a drain is controlled by a gate voltage applied to the device. That gate voltage determines whether the device is on or off.
The piezotronic memory devices developed by Wang and graduate student Wenzhuo Wu take advantage of the fact that piezoelectric materials like zinc oxide produce a charge potential when they are mechanically deformed or otherwise put under strain. These PRM devices use the piezoelectric charge created by the deformation to control the current flowing through the zinc oxide nanowires that are at the heart of the devices – the basic principle of piezotronics. The charge creates polarity in the nanowires – and increases the electrical resistance much like gate voltage in a conventional transistor.

“We are replacing the application of an external voltage with the production of an internal voltage,” Wang explained. “Because zinc oxide is both piezoelectric and semiconducting, when you strain the material with a mechanical action, you create a piezopotential. This piezopotential tunes the charge transport across the interface – instead of controlling channel width as in conventional field effect transistors.”

Enlarge

An array of piezoelectrically modulated resistive memory (PRM) cells is shown being studied in an optical microscope. Credit: Gary Meek

The mechanical strain could come from mechanical activities as diverse as signing a name with a pen, the motion of an actuator on a nanorobot, or biological activities of the human body such as a heart beating.

“We control the charge flow across the interface using strain,” Wang explained. “If you have no strain, the charge flows normally. But if you apply a strain, the resulting voltage builds a barrier that controls the flow.”

The piezotronic switching affects current flowing in just one direction, depending whether the strain is tensile or compressive. That means the memory stored in the piezotronic devices has both a sign and a magnitude. The information in this memory can be read, processed and stored through conventional electronic means.

Taking advantage of large-scale fabrication techniques for zinc oxide nanowire arrays, the Georgia Tech researchers have built non-volatile resistive switching memories for use as a storage medium. They have shown that these piezotronic devices can be written, that information can be read from them, and that they can be erased for re-use. About 20 of the arrays have been built so far for testing.

The zinc oxide nanowires, which are about 500 nanometers in diameter and about 50 microns long, are produced with a physical vapor deposition process that uses a high-temperature furnace. The resulting structures are then treated with oxygen plasma to reduce the number of crystalline defects – which helps to control their conductivity. The arrays are then transferred to a flexible substrate.

“The switching voltage is tunable, depending on the number of oxygen vacancies in the structure,” Wang said. “The more defects you quench away with the oxygen plasma, the larger the voltage that will be required to drive current flow.”

The piezotronic memory cells operate at low frequencies, which are appropriate for the kind of biologically-generated signals they will record, Wang said.

Enlarge

Image shows an array of piezoelectrically modulated resistive memory (PRM) cells on which metal electrodes have been patterned using lithography. Credit: Gary Meek

These piezotronic memory elements provide another component needed for fabricating complete self-powered nanoelectromechanical systems (NEMS) on a single chip. Wang’s research team has already demonstrated other key elements such as nanogenerators, sensors and wireless transmitters.

“We are taking another step toward the goal of self-powered complete systems,” Wang said. “The challenges now are to make them small enough to be integrated onto a single chip. We believe these systems will solve important problems in people’s lives.”

Wang believes this new memory will become increasingly important as devices become more closely connected to individual human activities. The ability to build these devices on flexible substrates means they can be used in the body – and with other electronic devices now being built on materials that are not traditional silicon.

“As computers and other electronic devices become more personalized and human-like, we will need to develop new types of signals, interfacing mechanical actions to electronics,” he said. “Piezoelectric materials provide the most sensitive way to translate these gentle mechanical actions into electronic signals that can be used by electronic devices.”

ARM backs massive computer brain and $7m cleantech venture round by Ben Fountain

Low power chip designer, ARM is putting up to a million of its processors into a new breed of computer that aims to replicate the way the brain works and several million of its dollars into a new Cambridge cleantech venture.

Prof Steve Furber, who co-designed the ARM processor with Sophie Wilson while at Acorn Computers in Cambridge is leading the SpiNNaker (Spiking Neural Network architecture) project – a massively-parallel chip multiprocessor system that mimics how nerve cells in the brain interact.

Meanwhile, ARM has co-led a $7m Series A investment into Amantys, a one year startup developing power control technology that reduces the amount of energy lost in the power conversion process. The startup says it can “address power losses all the way from wind and solar photovoltaic modules, transmission grids and transformers through to electric motors and electric vehicles.”

Amantys, which  is staffed by a team of former ARM execs and Dr Patrick Palmer of Cambridge University’s department of engineering, says it is aiming to release its first products by Q4 of this year. The funding round was co-led by Moonray Investors, part of Fidelity International.

Amantys says it is looking to recruit ‘analogue design gurus’, embedded software and power electronics engineers

ARM has quietly assembled an investment portfolio worth $40m and containing 15 companies.

Principal designer of the BBC Microcomputer as well as the ARM 32-bit RISC microprocessor, Prof Furber is now ICL Professor Of Computer Engineering at University of Manchester. He is working with scientists from the universities of Cambridge, Southampton and Sheffield as well as industrial partners – foremost among them, ARM – to develop a massive computer, nicknamed, the ‘brain box.’

By emulating the networks of billions of neurons in the brain using ARM processors, the hope is that scientists will gain a greater understanding of how processing in the brain works – including how damage to the brain interferes with it – but also that these biological models will lead to more efficient and fault-tolerant computers.

Professor Furber said: “Developing and understanding the information processing in the brain is the key. We are actively engaging with neuroscientists and psychologists, both here at the University and elsewhere.

“This could ultimately be of great help for patients, for example, who have presented with reading problems caused by strokes or similar brain injuries. Psychologists have already developed neural networks on which they can reproduce the clinical pathologies. At present they are limited in the fidelity they can achieve with these networks by the available computer power, but we hope that SpiNNaker will raise that bar a lot higher.”

The project has received funding of £5m from EPSRC.

The chips that will power the system – designed in Manchester and manufactured in Taiwan – were delivered from the foundry last month and with 18 ARM processors on board every chip, they will dramatically increase the number of brain cell interactions that can be modeled compared to earlier test systems.

Although there will eventually be up to one million Arm processors in SpiNNaker, making it capable of modelling a billion neurons in real time, this is still only around 1per cent of the human brain.

In the brain, neurons emit spikes which are relayed as tiny electrical signals. Each impulse is modelled in SpiNNaker as a ‘packet’ of data, which is sent to all connected neurons. Neurons are represented by simple equations which are solved in real-time by software running on the Arm processors.

Acorn Computers co-founder, Hermann Hauser, who describes Prof Furber as one of the smartest people he has met, told New Electronics in December 2010 that he was “keeping an entrepreneurial eye” on his latest work. He told the publication: “There is potential in the way the demonstrator works that one can build a computer that can do certain things others cannot. The sort of the things humans are very good at and computers are not.”

Arm was approached in May 2005 to participate in the SpiNNaker project. A subsequent agreement paved the way to make ARM processor IP available to the project, along with ARM cell library IP to aid design and manufacturing.

Mike Muller, CTO at ARM said: “SpiNNaker seeks to create a working model of the ultimate smart system, the human brain. Steve is part of the Arm family, so this project was a perfect way to partner with him and Manchester University, and for ARM to encourage leading research in the UK.”

Solar Cells that See Red: metamaterials that convert lower-energy photons to usable wavelengths could offer solar cells an efficiency boost by Katherine Bourzac

Researchers at Stanford University have demonstrated a set of materials that could enable solar cells to use a band of the solar spectrum that otherwise goes to waste. The materials layered on the back of solar cells would convert red and near-infrared light—unusable by today’s solar cells—into shorter-wavelength light that the cells can turn into energy. The university researchers will collaborate with the Bosch Research and Technology Center in Palo Alto, California, to demonstrate a system in working solar cells in the next four years.

Even the best of today’s silicon solar cells can’t use about 30 percent of the light from the sun: that’s because the active materials in solar cells can’t interact with photons whose energy is too low. But though each of these individual photons is low energy, as a whole they represent a large amount of untapped solar energy that could make solar cells more cost-competitive.

The process, called “upconversion,” relies on pairs of dyes that absorb photons of a given wavelength and re-emit them as fewer, shorter-wavelength photons. In this case, the Bosch and Stanford researchers will work on systems that convert near-infrared wavelengths (most of which are unusable by today’s solar cells). The leader of the Stanford group, assistant professor Jennifer Dionne, believes the group can improve the sunlight-to-electricity conversion efficiency of amorphous-silicon solar cells from 11 percent to 15 percent.

The concept of upconversion isn’t new, but it’s never been demonstrated in a working solar cell, says Inna Kozinsky, a senior engineer at Bosch. Upconversion typically requires two types of molecules to absorb relatively high-wavelength photons, combine their energy, and re-emit it as higher-energy, lower-wavelength photons. However, the chances of the molecules encountering each other at the right time when they’re in the right energetic states are low. Dionne is developing nanoparticles to add to these systems in order to increase those chances. To make better upconversion systems, Dionne is designing metal nanoparticles that act like tiny optical antennas, directing light in these dye systems in such a way that the dyes are exposed to more light at the right time, which creates more upconverted light, and then directing more of that upconverted light out of the system in the end.

The ultimate vision, says Dionne, is to create a solid. Sheets of such a material could be laid down on the bottom of the cell, separated from the cell itself by an electrically insulating layer. Low-wavelength photons that pass through the active layer would be absorbed by the upconverter layer, then re-emitted back into the active layer as usable, higher-wavelength light.

Kozinsky says Bosch’s goal is to demonstrate upconversion of red light in working solar cells in three years, and upconversion of infrared light in four years. Factoring in the time needed to scale up to manufacturing, she says, the technology could be in Bosch’s commercial solar cells in seven to 10 years.