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Hyperloop: Engineering the future of transportation

Cognizant

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Photo by Joey Kyber on Unsplash
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By: Manoj Mathew

Next year will mark 150 years since the last spike was driven into the final railroad tie connecting the first transcontinental railroad in the U.S.

On May 10, 1869, supervisors and crew members from three railroad companies gathered a mile above sea level at Promontory Summit in Utah to watch Leland Stanford, the president of Central Pacific Railroad, drive the ceremonial 17.6 karat “Golden Spike.”

Private enterprise spurred the railroad’s development. The government supported it. And as travel time dropped from East to West and back again, the intended increase in commerce followed. As raw materials and finished goods could be transported much more quickly, industrialization of the West picked up speed.

What’s Good for Transportation Is Good for Commerce

Commerce constantly strives to access new markets faster, moving more goods and more people, more cheaply. That drives investment in improved transportation – safer, faster and more economical. Technological advancements in AI, robotics and faster machine-to-machine connectivity allow asset-intensive environments to optimize their performance, take decisive action more quickly, collaborate among themselves and collectively learn.

Take the automotive industry. Carmakers are already reimagining the concept of transportation using perceptual computing (machines that interact with their surroundings using five senses) and pervasive computing (embedded micro controllers to make machines ”smart”) to speed travel, promote safety, improve fuel economy and achieve sustainability.

Related: Connecting Physical and Digital Worlds to Power the Industrial IoT

As the world’s population grows, however, and more people can afford to buy automobiles and other forms of transport, infrastructure and the global environment are coming under intense pressure. Clearly, our planet would struggle if every inhabitant owned an automobile.

Redefining Transportation

Today, digital innovation has purpose beyond commerce: to tie people together without more gridlock; to reduce energy emissions (since even electricity generation burns fossil fuels); to get people from place to place faster, more safely and economically; and to develop innovative products that improve the customer experience — and their lives.

To meet these dictates for transportation systems, no development looks as revolutionary as Hyperloop, a low-pressure tube in which passenger pods travel at a rate near the speed of sound. The transportation system is designed to be underground or supported on pillars above the ground to lessen accidents and natural disaster risks. And Hyperloop proposes to cut rail and automobile travel times between cities such as New York and Washington, D.C., by five or six times.

Certainly, Hyperloop faces engineering challenges. Not the least of these is the effect on the human body of rapid acceleration and deceleration while having to negotiate curves, peaks and troughs. Other practical challenges include energy, efficiency and sustainability. But these are technical challenges that engineers are addressing, including alternative fuel sources such as solar panels, lighter materials, and combining magnetic levitation (maglev) with propulsion systems that convert higher air pressure at the front of the pod into a propellant that supercharges pod performance.

Download: Connecting Physical and Digital Worlds to Power the Industrial IoT

Early Hyperloop experimentation is arousing interest from California to the Netherlands, and from China to Mumbai. As for the practicality of transporting people safely, a development team at the Delft University of Technology recently revealed its ATLAS 01 Hyperloop pod, a half-size prototype of its design for a vehicle to carry passengers inside the Hyperloop tube. TU Delft’s graduate-level engineering team began development of its current entry in September 2017, after the first Hyperloop pod design competition was completed earlier that year. In that earlier Hyperloop competition, which evaluated the best pod design, the TU Delft Hyperloop team won first place overall.

Meeting the Hyperloop Challenge

The recent public reveal of TU Delft’s Hyperloop pod, ATLAS 2.0, comes in advance of a SpaceX Hyperloop competition that will take place July 22, inside a half-size test Hyperloop built by Elon Musk’s SpaceX at its headquarters in Hawthorne, Calif. The team whose model achieves the highest speed wins the competition. This is a tough challenge, as the pod must accelerate, achieve top speed, brake and then come to a full stop in a single kilometer, the total length of the test loop.

Cognizant Digital Business is supporting the TU Delft team as a Prime Partner in the development of its prototype. Its Hyperloop pod’s control system depends on an enormous array of sensors and sophisticated algorithms. Our Connected Products team is helping the team refine and test model-based simulations of the interplay of sensors, the environment and the vehicle. These models of the physical environment — so-called digital twins — allow scenario-testing of the pod itself, with the goal of making it “fail-safe.” (Watch this video to see how.)

Download: Connecting Physical and Digital Worlds to Power the Industrial IoT

This parallels Cognizant’s work in the similarly promising realm of connected cars, rail, airlines, even bicycles. We are providing the TU Delft team with advice and technical support to help ensure the reliability and safety of its designs. The team writes specifications for ways to reduce risk; then they write the software. We test it for them, against our own hardware and software. As with all our work, we’re seeking to bridge the digital and the physical worlds to create real-world solutions.

A New Legacy

The legacy of “the Golden Spike” was easier movement across the country, greater market access and larger profits. Now, technological innovation is leading us forward again, to a future of transportation enabled by digital thinking and technologies built around sensorization, AI, hardware and software design, and human-centered product innovation and engineering.

Humans will continue their quest to realize cheaper, faster, more sustainable modes of transportation. Other mega-programs, like Big Falcon’s effort to provide point-to-point space travel (New York to Shanghai in 30 minutes), are already underway. For now, Hyperloop offers the promise of a Golden Spike in innovation in the 21st century – one that drives connections and commerce that benefit us all. We’re thrilled to be participating in the SpaceX competition. The world will be watching.

Raj Ravindranathan, Head of EMEA Cognizant Connected Products, contributed to this blog.

This article originally appeared on the Digitally Cognizant Blog

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Technology

Lenovo develops new AR headset called ThinkReality

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Chinese technology firm Lenovo is making a serious pitch for a big slice of the augmented reality headset market through the launch of its ThinkReality A6 glasses.

The new headset, the latest under the company’s ThinkReality brand, has been called “small but mighty” by Lenovo, with the headset weighing around 380g (0.83lbs). The weight has been reduced by having the battery worn separately to the main unit.

The headset comes with a 40-degree diagonal field of view with 1080p resolution per eye in a 16:9 aspect ratio. The visuals are powered by an onboard Qualcomm Snapdragon 845 SOC. The device has two fisheye cameras on the front, as well as depth sensors and a 13-megapixel RGB sensor, plus an in-built microphone. One of the important features is that the headset can detect where the user is gazing to optimize resolution or navigation. The headset works over Wi-Fi but not 4G or 5G.

The device has an ecosystem that is capable of integrating with existing enterprise systems. Lenovo have said the ThinkReality A6 is compatible with existing augmented reality content, and it offers highly functional device management software. In terms of the operating system, this is Snapdragon 845 CPU running an Android-based platform, plus an Intel Movidius chipset with wave guide optics from Lumus.

Part of Lenovo’s strategy is to capture the growing business interest in augmented reality. This includes providing services for remote working. Lenovo’s strategy, according to Computer Business Review, includes developing hardware, software and services aimed at the 2.7 billion deskless workers globally,

The cost of the new headset has yet to be confirmed, although aim is for the price to be competitive and to be able to compete with rival products, like Microsoft’s HoloLens 2, which retails around $3,500.

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Financial Services

Unskilled staff threaten banks’ ability to digitally transform

Business Insider

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Only four percent of bank business and IT executives believe that the impact of technology on the pace of banking change has stayed the same over the past three years, while 96 percent said it has either significantly accelerated or accelerated, according to a new report from Accenture.

This technological disruption has a large effect on how banks operate, and it seems unlikely that the pace of change will decelerate anytime soon.

Here’s what it means: Some technologies will have a bigger impact than others, but it will require substantial work from banks to stay on top of them.

AI is the most promising technology to transform the banking space. Forty-seven percent of respondents said AI will have the biggest impact, followed by just 19 percent saying the same for quantum computing and 17 percent for distributed ledgers and blockchain. The disappointing outcome for blockchain appears to be in line with recent announcements from banks: Citi has abandoned its plans to launch a crypto and Bank of America’s tech and operations chief has expressed skepticism on the benefits of blockchain.

Banks’ workforces appear to be at different stages in terms of tech savviness.Seventy-four percent of banking respondents either agree or strongly agree that their employees are more digitally mature than their organization, resulting in a workforce waiting for their organization to catch up. However, 17 percent of respondents said that over 80 percent of their workforce will have to move into new roles requiring substantial reskilling in the next three years, compared with only 5 percent saying the same for the last three years.

Additionally, banks don’t know as much about third-party partners as they perhaps should. Over one in 10 banking respondents believe that their partners’ security posture is extremely or very important, as well as that their consumers trust their ecosystem partners. However, only 31 percent of respondents say they know that their ecosystem partners work as diligently as they do, while 57 percent of them simply trust their partners and 10 percent hope that they are diligent.

The bigger picture: Banks need to prepare for a future that will require them to put in a lot of resources, and some might struggle.

To make the most of AI opportunities in banking, incumbents need to upskill their workforces. While AI is the most promising technology to transform the banking space, this promise can only be realized if banks have the necessary talent in-house to adopt new AI solutions. As such, they should make it a priority to upskill their staff to make AI transformation a success — which may be difficult for those players that have to upskill a majority of their workforce.

And banks need to up their security efforts since open banking is becoming a global trend.Open banking makes working with third parties more frequent. This will force banks to double down on their security efforts, as a security breach with their partners could affect customer trust in a bank’s overall services. If employees aren’t up to date with new technologies — including application programming interfaces used for open banking, and AI — they can’t keep a bank’s network secure.

This article was originally published on Business Insider. Copyright 2019.

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Healthcare

Artificial intelligence assesses PSTD by analysing voice patterns

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Artificial intelligence can be used to assess whether a person is suffering from post-traumatic stress disorder through an analysis of the subject’s voice patterns, noting and processing any variations to predict the medical diagnosis.

The research is not only useful at close quarters, it also offers a potential telemedical approach to use applied to the assessment of patients located in remote areas and away from specialist medical facilities.

The study comes from the NYU Langone Health and NYU School of Medicine, where the researchers used a specially designed computer program to assess the stress levels of veterans by analyzing their voices. The key findings have been presented to the conference of the International Speech Communication Association.

Conventionally post-traumatic stress disorder by clinical interviews or self-assessment. This can prove to be a lengthy and variable process, which was partly the reason for training artificial intelligence as well as the remote medical reasons.

To develop the technology, the scientists used a statistical and machine learning tool termed ‘random forest’. This form of artificial intelligence has the ability to “learn” how to classify individuals based in learnt examples and using decision-making rules together with mathematical models.

The first step with the development of the technology involved recording standard long-term diagnostic interviews (which are classed as PTSD Scales under Clinician’s Checks) with 53 U.S. veterans from campaigns in Iraq and Afghanistan, who has been assessed as suffering from different forms of post-traumatic stress disorder. These were compared with interviews with 78 non-ill veterans.

Each of the recordings was added into the voice software and this produced a total of 40,526 short speech voices. These were used to train the artificial intelligence. Once trained, the technology was then tested with a new set of subjects, who were known to the researchers and some of who had been assessed as having post-traumatic stress disorder. The next aim is to introduce the artificial intelligence into the clinical setting.

Commenting on the study, lead scientist Dr. Charles R. Marmar notes: “Our findings suggest that speech characteristics can be used to diagnose this disease, and with further training and confirmation, they can be used in the clinic in the near future.”

The output from the study has been published in the journal Depression and Anxiety, with the research study titled “Speech‐based markers for posttraumatic stress disorder in US veterans.”

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