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Timeline: The History of the Industrial Internet of Things

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The Internet of Things (IoT) isn’t only for connecting the latest gadgets, like a voice-activated speaker or a smart thermostat, to your increasingly connected home.

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.

Timeline of the Industrial Internet of Things

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.

IIoT Market

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.

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Automation

The Future of Supply Chain Automation

As COVID-19 disrupts global supply chains, we take a look at how industries are investing in automation—and what this is tells us about the future.

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The Future of Supply Chain Automation

As Amazon continues to set the bar for efficiency by integrating an astounding spectrum of automation technology, it’s becoming increasingly apparent that traditional supply chain models are ripe for disruption.

For this reason, companies around the world are now rethinking their warehouse and distribution systems, with automation taking center stage.

Today’s infographic from Raconteur highlights the state of automation across global supply chains, while also providing an outlook for future investment.

Long Time Coming

Let’s start by taking a look at what supply chain technologies are priorities for global industry investment in the first place:

RankTechnology% of Companies* Investing in Tech
#1Warehouse automation55%
#2Predictive analytics47%
#3Internet of things 41%
#4Cloud logistics40%
#5Artificial intelligence28%
#6Blockchain22%
#7Autonomous vehicles16%
#8Machine-learning16%
#9Fulfillment robots11%
#103D printing10%
#11Augmented reality7%
#12Drones7%
#13Crowd-sourced delivery6%
#14Virtual reality and digital twins6%
#15Delivery robots4%

*Based on survey of supply chain professionals in retail, manufacturing, and logistics fields

As seen above, warehouse automation has already received more investment (55%) than any other supply chain technology on the list, as companies aim to cut delivery times and improve overall margins.

Interestingly, other areas receiving significant investment—such as predictive analytics, internet of things, or artificial intelligence—are technologies that could integrate well into the optimization of supply chain automation as well.

Smoothing the Transition

While fully automated supply chains in most industries may still be a few years away, here is how companies are investing in an automated future today:

Timeline For Acquiring New Automation Tech% of Warehouse Managers Surveyed
Already have23%
Have, looking to upgrade8%
Within 12 months10%
One to three years21%
Three to five years8%
Over five years3%
Not looking26%

According to the above data, over 70% have already integrated automation technology, or are planning to within the next five years. On the flip side, over a quarter of warehouse managers are not currently looking to integrate any new automation tech into their operations at all.

Adoption Rates and Growth

As supply chain automation gains momentum and industry acceptance, individual processes will have varying adoption rates.

Take order fulfillment, for instance. Here, only 4% of current operations are highly automated according to a recent survey from Peerless Research Group:

Order Fulfillment Operations (Picking and Packaging)Percentage of Respondents
Highly automated4%
A mix of automated and manual processes42%
Mostly or all manual49%
Not applicable5%

Meanwhile, 49% of operations were primarily manual, illustrating potential for growth in this particular area.

It’s worth noting that other individual supply chain components, such as conveyor belts, storage, automated guided vehicles, and shuttle systems, will all have differing trajectories for automation and growth.

Post-COVID Supply Chains

The COVID-19 pandemic has shown us that complex supply chains can become fragile under the right circumstances.

As supply chains see increased rates of automation and data collection becomes more integrated into these processes, it’s possible that future risks embedded in these systems could be mitigated.

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Automation

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.

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self driving car technology

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.

self driving car lidar technology

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.

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