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#437216 New Report: Tech Could Fuel an Age of ...

With rapid technological progress running headlong into dramatic climate change and widening inequality, most experts agree the coming decade will be tumultuous. But a new report predicts it could actually make or break civilization as we know it.

The idea that humanity is facing a major shake-up this century is not new. The Fourth Industrial Revolution being brought about by technologies like AI, gene editing, robotics, and 3D printing is predicted to cause dramatic social, political, and economic upheaval in the coming decades.

But according to think tank RethinkX, thinking about the coming transition as just another industrial revolution is too simplistic. In a report released last week called Rethinking Humanity, the authors argue that we are about to see a reordering of our relationship with the world as fundamental as when hunter-gatherers came together to build the first civilizations.

At the core of their argument is the fact that since the first large human settlements appeared 10,000 years ago, civilization has been built on the back of our ability to extract resources from nature, be they food, energy, or materials. This led to a competitive landscape where the governing logic is grow or die, which has driven all civilizations to date.

That could be about to change thanks to emerging technologies that will fundamentally disrupt the five foundational sectors underpinning society: information, energy, food, transportation, and materials. They predict that across all five, costs will fall by 10 times or more, while production processes will become 10 times more efficient and will use 90 percent fewer natural resources with 10 to 100 times less waste.

They say that this transformation has already happened in information, where the internet has dramatically reduced barriers to communication and knowledge. They predict the combination of cheap solar and grid storage will soon see energy costs drop as low as one cent per kilowatt hour, and they envisage widespread adoption of autonomous electric vehicles and the replacement of car ownership with ride-sharing.

The authors laid out their vision for the future of food in another report last year, where they predicted that traditional agriculture would soon be replaced by industrial-scale brewing of single-celled organisms genetically modified to produce all the nutrients we need. In a similar vein, they believe the same processes combined with additive manufacturing and “nanotechnologies” will allow us to build all the materials required for the modern world from the molecule up rather than extracting scarce natural resources.

They believe this could allow us to shift from a system of production based on extraction to one built on creation, as limitless renewable energy makes it possible to build everything we need from scratch and barriers to movement and information disappear. As a result, a lifestyle worthy of the “American Dream” could be available to anyone for as little as $250/month by 2030.

This will require a fundamental reimagining of our societies, though. All great civilizations have eventually hit fundamental limits on their growth and we are no different, as demonstrated by our growing impact on the environment and the increasing concentration of wealth. Historically this stage of development has lead to a doubling down on old tactics in search of short-term gains, but this invariably leads to the collapse of the civilization.

The authors argue that we’re in a unique position. Because of the technological disruption detailed above, we have the ability to break through the limits on our growth. But only if we change what the authors call our “Organizing System.” They describe this as “the prevailing models of thought, belief systems, myths, values, abstractions, and conceptual frameworks that help explain how the world works and our relationship to it.”

They say that the current hierarchical, centralized system based on nation-states is unfit for the new system of production that is emerging. The cracks are already starting to appear, with problems like disinformation campaigns, fake news, and growing polarization demonstrating how ill-suited our institutions are for dealing with the distributed nature of today’s information systems. And as this same disruption comes to the other foundational sectors the shockwaves could lead to the collapse of civilization as we know it.

Their solution is a conscious shift towards a new way of organizing the world. As emerging technology allows communities to become self-sufficient, flows of physical resources will be replaced by flows of information, and we will require a decentralized but highly networked Organizing System.

The report includes detailed recommendations on how to usher this in. Examples include giving individuals control and ownership of data rights; developing new models for community ownership of energy, information, and transportation networks; and allowing states and cities far greater autonomy on policies like immigration, taxation, education, and public expenditure.

How easy it will be to get people on board with such a shift is another matter. The authors say it may require us to re-examine the foundations of our society, like representative democracy, capitalism, and nation-states. While they acknowledge that these ideas are deeply entrenched, they appear to believe we can reason our way around them.

That seems optimistic. Cultural and societal change can be glacial, and efforts to impose it top-down through reason and logic are rarely successful. The report seems to brush over many of the messy realities of humanity, such as the huge sway that tradition and religion hold over the vast majority of people.

It also doesn’t deal with the uneven distribution of the technology that is supposed to catapult us into this new age. And while the predicted revolutions in transportation, energy, and information do seem inevitable, the idea that in the next decade or two we’ll be able to produce any material we desire using cheap and abundant stock materials seems like a stretch.

Despite the techno-utopianism though, many of the ideas in the report hold promise for building societies that are better adapted for the disruptive new age we are about to enter.

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#437145 3 Major Materials Science ...

Few recognize the vast implications of materials science.

To build today’s smartphone in the 1980s, it would cost about $110 million, require nearly 200 kilowatts of energy (compared to 2kW per year today), and the device would be 14 meters tall, according to Applied Materials CTO Omkaram Nalamasu.

That’s the power of materials advances. Materials science has democratized smartphones, bringing the technology to the pockets of over 3.5 billion people. But far beyond devices and circuitry, materials science stands at the center of innumerable breakthroughs across energy, future cities, transit, and medicine. And at the forefront of Covid-19, materials scientists are forging ahead with biomaterials, nanotechnology, and other materials research to accelerate a solution.

As the name suggests, materials science is the branch devoted to the discovery and development of new materials. It’s an outgrowth of both physics and chemistry, using the periodic table as its grocery store and the laws of physics as its cookbook.

And today, we are in the middle of a materials science revolution. In this article, we’ll unpack the most important materials advancements happening now.

Let’s dive in.

The Materials Genome Initiative
In June 2011 at Carnegie Mellon University, President Obama announced the Materials Genome Initiative, a nationwide effort to use open source methods and AI to double the pace of innovation in materials science. Obama felt this acceleration was critical to the US’s global competitiveness, and held the key to solving significant challenges in clean energy, national security, and human welfare. And it worked.

By using AI to map the hundreds of millions of different possible combinations of elements—hydrogen, boron, lithium, carbon, etc.—the initiative created an enormous database that allows scientists to play a kind of improv jazz with the periodic table.

This new map of the physical world lets scientists combine elements faster than ever before and is helping them create all sorts of novel elements. And an array of new fabrication tools are further amplifying this process, allowing us to work at altogether new scales and sizes, including the atomic scale, where we’re now building materials one atom at a time.

Biggest Materials Science Breakthroughs
These tools have helped create the metamaterials used in carbon fiber composites for lighter-weight vehicles, advanced alloys for more durable jet engines, and biomaterials to replace human joints. We’re also seeing breakthroughs in energy storage and quantum computing. In robotics, new materials are helping us create the artificial muscles needed for humanoid, soft robots—think Westworld in your world.

Let’s unpack some of the leading materials science breakthroughs of the past decade.

(1) Lithium-ion batteries

The lithium-ion battery, which today powers everything from our smartphones to our autonomous cars, was first proposed in the 1970s. It couldn’t make it to market until the 1990s, and didn’t begin to reach maturity until the past few years.

An exponential technology, these batteries have been dropping in price for three decades, plummeting 90 percent between 1990 and 2010, and 80 percent since. Concurrently, they’ve seen an eleven-fold increase in capacity.

But producing enough of them to meet demand has been an ongoing problem. Tesla has stepped up to the challenge: one of the company’s Gigafactories in Nevada churns out 20 gigawatts of energy storage per year, marking the first time we’ve seen lithium-ion batteries produced at scale.

Musk predicts 100 Gigafactories could store the energy needs of the entire globe. Other companies are moving quickly to integrate this technology as well: Renault is building a home energy storage based on their Zoe batteries, BMW’s 500 i3 battery packs are being integrated into the UK’s national energy grid, and Toyota, Nissan, and Audi have all announced pilot projects.

Lithium-ion batteries will continue to play a major role in renewable energy storage, helping bring down solar and wind energy prices to compete with those of coal and gasoline.

(2) Graphene

Derived from the same graphite found in everyday pencils, graphene is a sheet of carbon just one atom thick. It is nearly weightless, but 200 times stronger than steel. Conducting electricity and dissipating heat faster than any other known substance, this super-material has transformative applications.

Graphene enables sensors, high-performance transistors, and even gel that helps neurons communicate in the spinal cord. Many flexible device screens, drug delivery systems, 3D printers, solar panels, and protective fabric use graphene.

As manufacturing costs decrease, this material has the power to accelerate advancements of all kinds.

(3) Perovskite

Right now, the “conversion efficiency” of the average solar panel—a measure of how much captured sunlight can be turned into electricity—hovers around 16 percent, at a cost of roughly $3 per watt.

Perovskite, a light-sensitive crystal and one of our newer new materials, has the potential to get that up to 66 percent, which would double what silicon panels can muster.

Perovskite’s ingredients are widely available and inexpensive to combine. What do all these factors add up to? Affordable solar energy for everyone.

Materials of the Nano-World
Nanotechnology is the outer edge of materials science, the point where matter manipulation gets nano-small—that’s a million times smaller than an ant, 8,000 times smaller than a red blood cell, and 2.5 times smaller than a strand of DNA.

Nanobots are machines that can be directed to produce more of themselves, or more of whatever else you’d like. And because this takes place at an atomic scale, these nanobots can pull apart any kind of material—soil, water, air—atom by atom, and use these now raw materials to construct just about anything.

Progress has been surprisingly swift in the nano-world, with a bevy of nano-products now on the market. Never want to fold clothes again? Nanoscale additives to fabrics help them resist wrinkling and staining. Don’t do windows? Not a problem! Nano-films make windows self-cleaning, anti-reflective, and capable of conducting electricity. Want to add solar to your house? We’ve got nano-coatings that capture the sun’s energy.

Nanomaterials make lighter automobiles, airplanes, baseball bats, helmets, bicycles, luggage, power tools—the list goes on. Researchers at Harvard built a nanoscale 3D printer capable of producing miniature batteries less than one millimeter wide. And if you don’t like those bulky VR goggles, researchers are now using nanotech to create smart contact lenses with a resolution six times greater than that of today’s smartphones.

And even more is coming. Right now, in medicine, drug delivery nanobots are proving especially useful in fighting cancer. Computing is a stranger story, as a bioengineer at Harvard recently stored 700 terabytes of data in a single gram of DNA.

On the environmental front, scientists can take carbon dioxide from the atmosphere and convert it into super-strong carbon nanofibers for use in manufacturing. If we can do this at scale—powered by solar—a system one-tenth the size of the Sahara Desert could reduce CO2 in the atmosphere to pre-industrial levels in about a decade.

The applications are endless. And coming fast. Over the next decade, the impact of the very, very small is about to get very, very large.

Final Thoughts
With the help of artificial intelligence and quantum computing over the next decade, the discovery of new materials will accelerate exponentially.

And with these new discoveries, customized materials will grow commonplace. Future knee implants will be personalized to meet the exact needs of each body, both in terms of structure and composition.

Though invisible to the naked eye, nanoscale materials will integrate into our everyday lives, seamlessly improving medicine, energy, smartphones, and more.

Ultimately, the path to demonetization and democratization of advanced technologies starts with re-designing materials— the invisible enabler and catalyst. Our future depends on the materials we create.

(Note: This article is an excerpt from The Future Is Faster Than You Think—my new book, just released on January 28th! To get your own copy, click here!)

Join Me
(1) A360 Executive Mastermind: If you’re an exponentially and abundance-minded entrepreneur who would like coaching directly from me, consider joining my Abundance 360 Mastermind, a highly selective community of 360 CEOs and entrepreneurs who I coach for 3 days every January in Beverly Hills, Ca. Through A360, I provide my members with context and clarity about how converging exponential technologies will transform every industry. I’m committed to running A360 for the course of an ongoing 25-year journey as a “countdown to the Singularity.”

If you’d like to learn more and consider joining our 2021 membership, apply here.

(2) Abundance-Digital Online Community: I’ve also created a Digital/Online community of bold, abundance-minded entrepreneurs called Abundance-Digital. Abundance-Digital is Singularity University’s ‘onramp’ for exponential entrepreneurs—those who want to get involved and play at a higher level. Click here to learn more.

(Both A360 and Abundance-Digital are part of Singularity University—your participation opens you to a global community.)

This article originally appeared on diamandis.com. Read the original article here.

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#436944 Is Digital Learning Still Second Best?

As Covid-19 continues to spread, the world has gone digital on an unprecedented scale. Tens of thousands of employees are working from home, and huge conferences, like the Google I/O and Apple WWDC software extravaganzas, plan to experiment with digital events.

Universities too are sending students home. This might have meant an extended break from school not too long ago. But no more. As lecture halls go empty, an experiment into digital learning at scale is ramping up. In the US alone, over 100 universities, from Harvard to Duke, are offering online classes to students to keep the semester going.

While digital learning has been improving for some time, Covid-19 may not only tip us further into a more digitally connected reality, but also help us better appreciate its benefits. This is important because historically, digital learning has been viewed as inferior to traditional learning. But that may be changing.

The Inversion
We often think about digital technologies as ways to reach people without access to traditional services—online learning for children who don’t have schools nearby or telemedicine for patients with no access to doctors. And while these solutions have helped millions of people, they’re often viewed as “second best” and “better than nothing.” Even in more resource-rich environments, there’s an assumption one should pay more to attend an event in person—a concert, a football game, an exercise class—while digital equivalents are extremely cheap or free. Why is this? And is the situation about to change?

Take the case of Dr. Sanjeev Arora, a professor of medicine at the University of New Mexico. Arora started Project Echo because he was frustrated by how many late-stage cases of hepatitis C he encountered in rural New Mexico. He realized that if he had reached patients sooner, he could have prevented needless deaths. The solution? Digital learning for local health workers.

Project Echo connects rural healthcare practitioners to specialists at top health centers by video. The approach is collaborative: Specialists share best practices and work through cases with participants to apply them in the real world and learn from edge cases. Added to expert presentations, there are lots of opportunities to ask questions and interact with specialists.

The method forms a digital loop of learning, practice, assessment, and adjustment.

Since 2003, Project Echo has scaled to 800 locations in 39 countries and trained over 90,000 healthcare providers. Most notably, a study in The New England Journal of Medicine found that the outcomes of hepatitis C treatment given by Project Echo trained healthcare workers in rural and underserved areas were similar to outcomes at university medical centers. That is, digital learning in this context was equivalent to high quality in-person learning.

If that is possible today, with simple tools, will they surpass traditional medical centers and schools in the future? Can digital learning more generally follow suit and have the same success? Perhaps. Going digital brings its own special toolset to the table too.

The Benefits of Digital
If you’re training people online, you can record the session to better understand their engagement levels—or even add artificial intelligence to analyze it in real time. Ahura AI, for example, founded by Bryan Talebi, aims to upskill workers through online training. Early study of their method suggests they can significantly speed up learning by analyzing users’ real-time emotions—like frustration or distraction—and adjusting the lesson plan or difficulty on the fly.

Other benefits of digital learning include the near-instantaneous download of course materials—rather than printing and shipping books—and being able to more easily report grades and other results, a requirement for many schools and social services organizations. And of course, as other digitized industries show, digital learning can grow and scale further at much lower costs.

To that last point, 360ed, a digital learning startup founded in 2016 by Hla Hla Win, now serves millions of children in Myanmar with augmented reality lesson plans. And Global Startup Ecosystem, founded by Christine Souffrant Ntim and Einstein Kofi Ntim in 2015, is the world’s first and largest digital accelerator program. Their entirely online programs support over 1,000 companies in 90 countries. It’s astonishing how fast both of these organizations have grown.

Notably, both examples include offline experiences too. Many of the 360ed lesson plans come with paper flashcards children use with their smartphones because the online-offline interaction improves learning. The Global Startup Ecosystem also hosts about 10 additional in-person tech summits around the world on various topics through a related initiative.

Looking further ahead, probably the most important benefit of online learning will be its potential to integrate with other digital systems in the workplace.

Imagine a medical center that has perfect information about every patient and treatment in real time and that this information is (anonymously and privately) centralized, analyzed, and shared with medical centers, research labs, pharmaceutical companies, clinical trials, policy makers, and medical students around the world. Just as self-driving cars can learn to drive better by having access to the experiences of other self-driving cars, so too can any group working to solve complex, time-sensitive challenges learn from and build on each other’s experiences.

Why This Matters
While in the long term the world will likely end up combining the best aspects of traditional and digital learning, it’s important in the near term to be more aware of the assumptions we make about digital technologies. Some of the most pioneering work in education, healthcare, and other industries may not be highly visible right now because it is in a virtual setting. Most people are unaware, for example, that the busiest emergency room in rural America is already virtual.

Once they start converging with other digital technologies, these innovations will likely become the mainstream system for all of us. Which raises more questions: What is the best business model for these virtual services? If they start delivering better healthcare and educational outcomes than traditional institutions, should they charge more? Hopefully, we will see an even bigger shift occurring, in which technology allows us to provide high quality education, healthcare, and other services to everyone at more affordable prices than today.

These are some of the topics we can consider as Covid-19 forces us into uncharted territory.

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#436911 Scientists Linked Artificial and ...

Scientists have linked up two silicon-based artificial neurons with a biological one across multiple countries into a fully-functional network. Using standard internet protocols, they established a chain of communication whereby an artificial neuron controls a living, biological one, and passes on the info to another artificial one.

Whoa.

We’ve talked plenty about brain-computer interfaces and novel computer chips that resemble the brain. We’ve covered how those “neuromorphic” chips could link up into tremendously powerful computing entities, using engineered communication nodes called artificial synapses.

As Moore’s law is dying, we even said that neuromorphic computing is one path towards the future of extremely powerful, low energy consumption artificial neural network-based computing—in hardware—that could in theory better link up with the brain. Because the chips “speak” the brain’s language, in theory they could become neuroprosthesis hubs far more advanced and “natural” than anything currently possible.

This month, an international team put all of those ingredients together, turning theory into reality.

The three labs, scattered across Padova, Italy, Zurich, Switzerland, and Southampton, England, collaborated to create a fully self-controlled, hybrid artificial-biological neural network that communicated using biological principles, but over the internet.

The three-neuron network, linked through artificial synapses that emulate the real thing, was able to reproduce a classic neuroscience experiment that’s considered the basis of learning and memory in the brain. In other words, artificial neuron and synapse “chips” have progressed to the point where they can actually use a biological neuron intermediary to form a circuit that, at least partially, behaves like the real thing.

That’s not to say cyborg brains are coming soon. The simulation only recreated a small network that supports excitatory transmission in the hippocampus—a critical region that supports memory—and most brain functions require enormous cross-talk between numerous neurons and circuits. Nevertheless, the study is a jaw-dropping demonstration of how far we’ve come in recreating biological neurons and synapses in artificial hardware.

And perhaps one day, the currently “experimental” neuromorphic hardware will be integrated into broken biological neural circuits as bridges to restore movement, memory, personality, and even a sense of self.

The Artificial Brain Boom
One important thing: this study relies heavily on a decade of research into neuromorphic computing, or the implementation of brain functions inside computer chips.

The best-known example is perhaps IBM’s TrueNorth, which leveraged the brain’s computational principles to build a completely different computer than what we have today. Today’s computers run on a von Neumann architecture, in which memory and processing modules are physically separate. In contrast, the brain’s computing and memory are simultaneously achieved at synapses, small “hubs” on individual neurons that talk to adjacent ones.

Because memory and processing occur on the same site, biological neurons don’t have to shuttle data back and forth between processing and storage compartments, massively reducing processing time and energy use. What’s more, a neuron’s history will also influence how it behaves in the future, increasing flexibility and adaptability compared to computers. With the rise of deep learning, which loosely mimics neural processing as the prima donna of AI, the need to reduce power while boosting speed and flexible learning is becoming ever more tantamount in the AI community.

Neuromorphic computing was partially born out of this need. Most chips utilize special ingredients that change their resistance (or other physical characteristics) to mimic how a neuron might adapt to stimulation. Some chips emulate a whole neuron, that is, how it responds to a history of stimulation—does it get easier or harder to fire? Others imitate synapses themselves, that is, how easily they will pass on the information to another neuron.

Although single neuromorphic chips have proven to be far more efficient and powerful than current computer chips running machine learning algorithms in toy problems, so far few people have tried putting the artificial components together with biological ones in the ultimate test.

That’s what this study did.

A Hybrid Network
Still with me? Let’s talk network.

It’s gonna sound complicated, but remember: learning is the formation of neural networks, and neurons that fire together wire together. To rephrase: when learning, neurons will spontaneously organize into networks so that future instances will re-trigger the entire network. To “wire” together, downstream neurons will become more responsive to their upstream neural partners, so that even a whisper will cause them to activate. In contrast, some types of stimulation will cause the downstream neuron to “chill out” so that only an upstream “shout” will trigger downstream activation.

Both these properties—easier or harder to activate downstream neurons—are essentially how the brain forms connections. The “amping up,” in neuroscience jargon, is long-term potentiation (LTP), whereas the down-tuning is LTD (long-term depression). These two phenomena were first discovered in the rodent hippocampus more than half a century ago, and ever since have been considered as the biological basis of how the brain learns and remembers, and implicated in neurological problems such as addition (seriously, you can’t pass Neuro 101 without learning about LTP and LTD!).

So it’s perhaps especially salient that one of the first artificial-brain hybrid networks recapitulated this classic result.

To visualize: the three-neuron network began in Switzerland, with an artificial neuron with the badass name of “silicon spiking neuron.” That neuron is linked to an artificial synapse, a “memristor” located in the UK, which is then linked to a biological rat neuron cultured in Italy. The rat neuron has a “smart” microelectrode, controlled by the artificial synapse, to stimulate it. This is the artificial-to-biological pathway.

Meanwhile, the rat neuron in Italy also has electrodes that listen in on its electrical signaling. This signaling is passed back to another artificial synapse in the UK, which is then used to control a second artificial neuron back in Switzerland. This is the biological-to-artificial pathway back. As a testimony in how far we’ve come in digitizing neural signaling, all of the biological neural responses are digitized and sent over the internet to control its far-out artificial partner.

Here’s the crux: to demonstrate a functional neural network, just having the biological neuron passively “pass on” electrical stimulation isn’t enough. It has to show the capacity to learn, that is, to be able to mimic the amping up and down-tuning that are LTP and LTD, respectively.

You’ve probably guessed the results: certain stimulation patterns to the first artificial neuron in Switzerland changed how the artificial synapse in the UK operated. This, in turn, changed the stimulation to the biological neuron, so that it either amped up or toned down depending on the input.

Similarly, the response of the biological neuron altered the second artificial synapse, which then controlled the output of the second artificial neuron. Altogether, the biological and artificial components seamlessly linked up, over thousands of miles, into a functional neural circuit.

Cyborg Mind-Meld
So…I’m still picking my jaw up off the floor.

It’s utterly insane seeing a classic neuroscience learning experiment repeated with an integrated network with artificial components. That said, a three-neuron network is far from the thousands of synapses (if not more) needed to truly re-establish a broken neural circuit in the hippocampus, which DARPA has been aiming to do. And LTP/LTD has come under fire recently as the de facto brain mechanism for learning, though so far they remain cemented as neuroscience dogma.

However, this is one of the few studies where you see fields coming together. As Richard Feynman famously said, “What I cannot recreate, I cannot understand.” Even though neuromorphic chips were built on a high-level rather than molecular-level understanding of how neurons work, the study shows that artificial versions can still synapse with their biological counterparts. We’re not just on the right path towards understanding the brain, we’re recreating it, in hardware—if just a little.

While the study doesn’t have immediate use cases, practically it does boost both the neuromorphic computing and neuroprosthetic fields.

“We are very excited with this new development,” said study author Dr. Themis Prodromakis at the University of Southampton. “On one side it sets the basis for a novel scenario that was never encountered during natural evolution, where biological and artificial neurons are linked together and communicate across global networks; laying the foundations for the Internet of Neuro-electronics. On the other hand, it brings new prospects to neuroprosthetic technologies, paving the way towards research into replacing dysfunctional parts of the brain with AI chips.”

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#436530 How Smart Roads Will Make Driving ...

Roads criss-cross the landscape, but while they provide vital transport links, in many ways they represent a huge amount of wasted space. Advances in “smart road” technology could change that, creating roads that can harvest energy from cars, detect speeding, automatically weigh vehicles, and even communicate with smart cars.

“Smart city” projects are popping up in countries across the world thanks to advances in wireless communication, cloud computing, data analytics, remote sensing, and artificial intelligence. Transportation is a crucial element of most of these plans, but while much of the focus is on public transport solutions, smart roads are increasingly being seen as a crucial feature of these programs.

New technology is making it possible to tackle a host of issues including traffic congestion, accidents, and pollution, say the authors of a paper in the journal Proceedings of the Royal Society A. And they’ve outlined ten of the most promising advances under development or in planning stages that could feature on tomorrow’s roads.

Energy harvesting

A variety of energy harvesting technologies integrated into roads have been proposed as ways to power street lights and traffic signals or provide a boost to the grid. Photovoltaic panels could be built into the road surface to capture sunlight, or piezoelectric materials installed beneath the asphalt could generate current when deformed by vehicles passing overhead.

Musical roads

Countries like Japan, Denmark, the Netherlands, Taiwan, and South Korea have built roads that play music as cars pass by. By varying the spacing of rumble strips, it’s possible to produce a series of different notes as vehicles drive over them. The aim is generally to warn of hazards or help drivers keep to the speed limit.

Automatic weighing

Weight-in-motion technology that measures vehicles’ loads as they drive slowly through a designated lane has been around since the 1970s, but more recently high speed weight-in-motion tech has made it possible to measure vehicles as they travel at regular highway speeds. The latest advance has been integration with automatic licence plate reading and wireless communication to allow continuous remote monitoring both to enforce weight restrictions and monitor wear on roads.

Vehicle charging

The growing popularity of electric vehicles has spurred the development of technology to charge cars and buses as they drive. The most promising of these approaches is magnetic induction, which involves burying cables beneath the road to generate electromagnetic fields that a receiver device in the car then transforms into electrical power to charge batteries.

Smart traffic signs

Traffic signs aren’t always as visible as they should be, and it can often be hard to remember what all of them mean. So there are now proposals for “smart signs” that wirelessly beam a sign’s content to oncoming cars fitted with receivers, which can then alert the driver verbally or on the car’s display. The approach isn’t affected by poor weather and lighting, can be reprogrammed easily, and could do away with the need for complex sign recognition technology in future self-driving cars.

Traffic violation detection and notification

Sensors and cameras can be combined with these same smart signs to detect and automatically notify drivers of traffic violations. The automatic transmission of traffic signals means drivers won’t be able to deny they’ve seen the warnings or been notified of any fines, as a record will be stored on their car’s black box.

Talking cars

Car-to-car communication technology and V2X, which lets cars share information with any other connected device, are becoming increasingly common. Inter-car communication can be used to propagate accidents or traffic jam alerts to prevent congestion, while letting vehicles communicate with infrastructure can help signals dynamically manage timers to keep traffic flowing or automatically collect tolls.

Smart intersections

Combing sensors and cameras with object recognition systems that can detect vehicles and other road users can help increase safety and efficiency at intersections. It can be used to extend green lights for slower road users like pedestrians and cyclists, sense jaywalkers, give priority to emergency vehicles, and dynamically adjust light timers to optimize traffic flow. Information can even be broadcast to oncoming vehicles to highlight blind spots and potential hazards.

Automatic crash detection

There’s a “golden hour” after an accident in which the chance of saving lives is greatly increased. Vehicle communication technology can ensure that notification of a crash reaches the emergency services rapidly, and can also provide vital information about the number and type of vehicles involved, which can help emergency response planning. It can also be used to alert other drivers to slow down or stop to prevent further accidents.

Smart street lights

Street lights are increasingly being embedded with sensors, wireless connectivity, and micro-controllers to enable a variety of smart functions. These include motion activation to save energy, providing wireless access points, air quality monitoring, or parking and litter monitoring. This can also be used to send automatic maintenance requests if a light is faulty, and can even allow neighboring lights to be automatically brightened to compensate.

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