In fact, the same circumstances that have led to the explosion in smart consumer gadgets, such as universal wireless connectivity, cloud computing, cheap sensors, and better artificial intelligence, are also being used in conjunction with big data to power the next generation of industry, as well.
This new technological layer, called the Industrial Internet of Things (IIoT), is transforming massive industries like manufacturing, energy, mining, and transportation – and it’ll have a multi-trillion dollar impact on the economy as a whole.
The Birth of the Industrial Internet
Today’s infographic comes to us from Kepware, and it shows how these technological forces have emerged over time to make the IIoT possible.
The road to the creation of the IIoT started in 1968, when engineer Dick Morley made one of the most important breakthroughs in manufacturing history.
That year, Morley and a group of geek friends invented the programmable logic controller (PLC), which would eventually become irreplaceable in automating assembly lines and industrial robots in factories.
Other Major Innovations
Here are some other major innovations that were instrumental in making the IIoT possible:
1983: Ethernet is standardized
1989: Tim Berners-Lee creates Hypertext Transfer Protocol (HTTP)
1992: TCP/IP allows PLCs to have connectivity
2002: Amazon Web Services launches, and cloud computing starts to take hold
2006: OPC Unified Architecture (UA) enables secure communications between devices, data sources, and applications.
2006: Devices start getting smaller, and batteries and solar energy are becoming powerful and more economical.
2010: Sensors drop in price, enabling them to be put into pretty much everything
And today, the IIoT is a big deal: it’s transforming the backbone of major industries by adding a new layer of technology that helps companies optimize operations, track and analyze equipment, implement predictive maintenance, make sense of massive amounts of data, and make real-time decisions that were never before possible.
And by 2030, the IIoT is estimated by Accenture to have a $14.2 trillion on the global economy – making it one of the most important forces shaping the future business world today.
How Self-Driving Cars “See” the World
This video breaks down the complex technology allowing a new generation of self-driving cars to view the world around them.
How Self-Driving Cars “See” the World
Modern cars bear little resemblance to their early ancestors, but the basic action of steering a vehicle has always remained the same. Whether you’re behind the wheel of a Tesla or a vintage Model T, turning the wheel dictates the direction of movement. This simple premise, which places humans at the center of control, may be ripe for disruption as tech giants and car companies race toward a future that would render human-controlled vehicles obsolete.
How does this next generation of self-driving cars “see” the road? Today’s video from TED-Ed explains one of the mind-bending innovations making autonomous vehicles a reality.
Eye of the Laser
Safely getting a vehicle and its passengers from point A to B is no simple matter.
First, weather and time of day can create a wide variety of challenging situations, affecting things like visibility, braking distances, or speed. Next, other vehicles, bikes, and pedestrians are constantly moving through the transportation network, sometimes in unpredictable ways. To further complicate matters, the road network is rarely in optimum form. Road lines fade and construction can throw ambiguous detours into the mix.
Sensing and analyzing the world at a granular level is crucial in making self-driving cars a viable transportation option. To solve this problem, new generations of autonomous vehicles are using photonic integrated circuits, as well as light detection and ranging (LiDAR) to generate an extremely nuanced picture of the road ahead.
How self-driving cars see the world. (Source: Hesai)
LiDAR – which is related to RADAR – uses short laser pulses to sense the depth and shape of objects. Essentially, scattered bursts reflect off objects around the vehicle, painting a detailed 3D picture of its surroundings. LiDAR’s depth resolution is so accurate that it could eventually see details at the millimeter scale.
A Dissenting Opinion
While most companies in the autonomous vehicle space have fully embraced LiDAR, Tesla has a divergent point of view. The company employs a combination of GPS, cameras, and other sensors to help its cars visualize the world.
LiDAR is a fool’s errand. Anyone relying on LiDAR is doomed.
– Elon Musk
Society and Self-Driving Cars
While companies like Uber and Waymo determine the functional mechanics of self-driving cars, the rest of society is left to ponder how this new technology will affect employment, privacy, and personal autonomy.
In the U.S., more than 70% of goods are moved by truck, and over 80% of commuters take a private vehicle to work on any given day. Even partial automation of the nation’s transportation network will have wide-sweeping impacts on the economy.
As AI-powered cars and trucks hit the streets at scale, how cars see the road will be a detail most of us will overlook. The bigger question will be whether we are ready for a society where we’re no longer in the driver’s seat.
Ranked: The Autonomous Vehicle Readiness of 20 Countries
This interactive visual shows the countries best prepared for the shift to autonomous vehicles, as well as the associated societal and economic impacts.
For the past decade, manufacturers and governments all over the world have been preparing for the adoption of self-driving cars—with the promise of transformative economic development.
As autonomous vehicles become more of a looming certainty, what will be the wider impacts of this monumental transition?
Which Countries are Ready?
Today’s interactive visual from Aquinov Mathappan ranks countries on their preparedness to adopt self-driving cars, while also exploring the range of challenges they will face in achieving complete automation.
The Five Levels of Automation
The graphic above uses the Autonomous Vehicles Readiness Index, which details the five levels of automation. Level 0 vehicles place the responsibility for all menial tasks with the driver, including steering, braking, and acceleration. In contrast, level 5 vehicles demand nothing of the driver and can operate entirely without their presence.
Today, most cars sit between levels 1 and 3, typically with few or limited automated functions. There are some exceptions to the rule, such as certain Tesla models and Google’s Waymo. Both feature a full range of self-driving capabilities—enabling the car to steer, accelerate and brake on behalf of the driver.
The Journey to Personal Driving Freedom
There are three main challenges that come with achieving a fully-automated level 5 status:
- Data Storage
Effectively storing data and translating it into actionable insights is difficult when 4TB of raw data is generated every day—the equivalent of the data generated by 3,000 internet users in 24 hours.
- Data Transportation
Autonomous vehicles need to communicate with each other and transport data with the use of consistently high-speed internet, highlighting the need for large-scale adoption of 5G.
- Verifying Deep Neural Networks
The safety of these vehicles will be dictated by their ability to distinguish between a vehicle and a person, but they currently rely on algorithms which are not yet fully understood.
Which Countries are Leading the Charge?
The 20 countries were selected for the report based on economic size, and their automation progress was ranked using four key metrics: technology and innovation, infrastructure, policy and legislation, and consumer acceptance.
The United States leads the way on technology and innovation, with 163 company headquarters, and more than 50% of cities currently preparing their streets for self-driving vehicles. The Netherlands and Singapore rank in the top three for infrastructure, legislation, and consumer acceptance. Singapore is currently testing a fleet of autonomous buses created by Volvo, which will join the existing public transit fleet in 2022.
India, Mexico, and Russia lag behind on all fronts—despite enthusiasm for self-driving cars, these countries require legislative changes and improvements in the existing quality of roads. Mexico also lacks industrial activity and clear regulations around autonomous vehicles, but close proximity to the U.S. has already garnered interest from companies like Intel for manufacturing autonomous vehicles south of the border.
How Autonomous Vehicles Impact the Economy
Once successfully adopted, autonomous vehicles will save the U.S. economy $1.3 trillion per year, which will come from a variety of sources including:
- $563 billion: Reduction in accidents
- $422 billion: Productivity gains
- $158 billion: Decline in fuel costs
- $138 billion: Fuel savings from congestion avoidance
- $11 billion: Improved traffic flow and reduction of energy use
Transportation will be safer, potentially reducing the number of accidents over time. Insurance companies are already rolling out usage-based insurance policies (UBIs), which charge customers based on how many miles they drive and how safe their driving habits are.
Long distance traveling in autonomous vehicles provides a painless alternative to train and air travel. The vehicles are designed for comfort, making it possible to sleep overnight easily—which could also impact the hotel industry significantly.
- Real Estate
An increase in effortless travel could lead to increased urban sprawl, as people prioritize the convenience of proximity to city centers less and less.
With the adoption of autonomous vehicles projected to reduce private car ownership in the U.S. to 43% by 2030, it’s disrupting many other industries in the process.
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