Lifeboat Foundation

As any driver knows, accidents can happen in the blink of an eye—so when it comes to the camera system in autonomous vehicles, processing time is critical. The time that it takes for the system to snap an image and deliver the data to the microprocessor for image processing could mean the difference between avoiding an obstacle or getting into a major accident.

In-sensor image processing, in which important features are extracted from raw data by the image sensor itself instead of the separate microprocessor, can speed up the visual processing. To date, demonstrations of in-sensor processing have been limited to emerging research materials which are, at least for now, difficult to incorporate into commercial systems.

Now, researchers from the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) have developed the first in-sensor processor that could be integrated into commercial silicon imaging sensor chips–known as complementary metal-oxide-semiconductor (CMOS) image sensors–that are used in nearly all commercial devices that need capture visual information, including smartphones.

Someone taps your shoulder. The organized touch receptors in your skin send a message to your brain, which processes the information and directs you to look left, in the direction of the tap. Now, Penn State and U.S. Air Force researchers have harnessed this processing of mechanical information and integrated it into engineered materials that “think”.

The work, published today in Nature, hinges on a novel, reconfigurable alternative to integrated circuits. Integrated circuits are typically composed of multiple electronic components housed on a single semiconductor material, usually silicon, and they run all types of modern electronics, including phones, cars and robots. Integrated circuits are scientists’ realization of information processing similar to the brain’s role in the human body. According to principal investigator Ryan Harne, James F. Will Career Development Associate Professor of Mechanical Engineering at Penn State, integrated circuits are the core constituent needed for scalable computing of signals and information but have never before been realized by scientists in any composition other than silicon semiconductors.

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It’s official: Apple has just sent out invites for its next hardware event. As expected, the company will share what it’s been working on for the past year on September 7th, with a live broadcast from Apple Park starting at 1PM ET. The invite features the words “Far out.” Make of that what you will.

The company is widely expected to announce four new iPhone models at the event. Leading up to today’s announcement, most reports have suggested the 2022 iPhone lineup will consist of a 6.1-inch iPhone 14, a 6.7-inch iPhone 14 Max, a 6.1-inch iPhone 14 Pro and a 6.7-inch iPhone 14 Pro Max. Apple reportedly won’t offer a new “mini” model this year due to lackluster sales of the iPhone 12 mini and iPhone 13 mini.

Enhancements on the standard iPhone 14 models reportedly include the addition of more RAM, longer-lasting batteries and a better selfie camera with autofocus. Meanwhile, the Pro models are expected to feature a new design that trades away Apple’s signature display notch for a Samsung-style hole-punch front camera cutout. Additionally, the Pro variants will reportedly feature a new 48-megapixel main camera and thinner display bezels. They’re also expected to be the only models to ship with Apple’s next-generation A16 chip.

Wearable sensors are ubiquitous thanks to wireless technology that enables a person’s glucose concentrations, blood pressure, heart rate, and activity levels to be transmitted seamlessly from sensor to smartphone for further analysis.

Most wireless sensors today communicate via embedded Bluetooth chips that are themselves powered by small batteries. But these conventional chips and power sources will likely be too bulky for next-generation sensors, which are taking on smaller, thinner, more flexible forms.

Now MIT engineers have devised a new kind of wearable sensor that communicates wirelessly without requiring onboard chips or batteries. Their design, detailed in the journal Science, opens a path toward chip-free wireless sensors.

A Tesla driver can now unlock his car without using his smartphone. Thanks to a chip implanted in his hand, he will never lose his keys again.

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Continue reading “China’s Cyberattack on America Starts With Your Phone” »

Smartphones, tablets, computer screens — all digital media has detrimental effects on your brain. That is a position that Professor Manfred Spitzer, a neuroscientist and author of several books, defends. You might like what you’ll hear, you might not, but don’t say that you haven’t been warned. Especially if you have kids running around with smartphones all day long.

Created by Rimantas Vančys.
Video footage and graphics: Envato Elements.
Additional material: NASA.
Music: Envato Elements.

Continue reading “Negative digital media effects” »

Over the past decade, digital cameras have been widely adopted in various aspects of our society, and are being massively used in mobile phones, security surveillance, autonomous vehicles, and facial recognition. Through these cameras, enormous amounts of image data are being generated, which raises growing concerns about privacy protection.

Some existing methods address these concerns by applying algorithms to conceal sensitive information from the acquired images, such as image blurring or encryption. However, such methods still risk exposure of sensitive data because the raw images are already captured before they undergo digital processing to hide or encrypt the sensitive information. Also, the computation of these algorithms requires additional power consumption. Other efforts were also made to seek solutions to this problem by using customized cameras to downgrade the image quality so that identifiable information can be concealed. However, these approaches sacrifice the overall image quality for all the objects of interest, which is undesired, and they are still vulnerable to adversarial attacks to retrieve the sensitive information that is recorded.

A new research paper published in eLight demonstrated a new paradigm to achieve privacy-preserving imaging by building a fundamentally new type of imager designed by AI. In their paper, UCLA researchers, led by Professor Aydogan Ozcan, presented a smart camera design that images only certain types of desired objects, while instantaneously erasing other types of objects from its images without requiring any digital processing.