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How Will Car Maintenance Evolve In the Autonomous Vehicles Era?

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Imagine the day when your car not only diagnoses its own maintenance needs, but schedules its own appointment and then drives itself to the shop, leaving you with plenty of free time to do as you please.

This scenario is a distinct possibility in the autonomous vehicles (AV) era. Artificial intelligence (AI) will be used to create AVs, and also to enable them to self-diagnose.

In addition to the regular maintenance required in a traditional vehicle, there’s an abundance of equipment involved in building and operating AVs, which will also require upkeep. Waymo, the Google self-driving car, features radar that enables cruise control, ultrasound used for assisted parking, cameras for lane-keeping and back-up assistance, GPS systems to determine a car’s position, and sensors that help with navigation when satellite signals are blocked. And then there’s Waymo’s Light Detection and Ranging (LIDAR) technology, which gives the driver a 360 degree view. The sensors and chips for this car are outrageously expensive, and repairs will cost you.

Tesla, another contender in the race to create fully self-driving cars, is considering bundling the cost of maintenance and insurance with its AV sales, so you won’t necessarily feel it up front, and you won’t have to suddenly come up with the cash at the time maintenance is required.

That’s if you’re even in the market for your own AV.

How AV Rides Will Save

Don’t give up on AVs just yet. Although unexpected car repairs are the most frequent financial upset to family budgets, the future of transportation lies in shared, electric AVs, which will save riders the hassle and cost of vehicle maintenance. According to a May 2017 RethinkX report, the use of fleet-operated autonomous vehicles will help the average family save $5,600 per year on transportation.

[Editor Note: There’s a graphic available at Sightline.org showing that major car repairs were the biggest shock to families in 2015.]  

In urban areas at least, car ownership will lie with fleet operators rather than individuals. You’ll call for an AV – likely via a smartphone app – it will arrive at your location, you’ll get in and enter your destination, and you’ll head for the highway, simple as that. Not only will riders never have to think about maintenance, but they’ll never have to worry about refueling, paying parking tickets or parking fees, cleaning, or buying car insurance.

Additionally, riders won’t need to worry about the cost of a car accident, should one occur. AV manufacturers like Volvo, Google and Mercedes Benz have already pledged to accept responsibility if their product causes an accident.

AI Beyond AV

Transportation is just one industry being impacted by AI technology. Read more about how this technology will permeate various industries in the very near future, providing improved efficiencies and costs.

Prepare your company now by ordering Artificial Intelligence and Ethics in Design, IEEE’s exclusive 5-course training program, and learn how aligning technology with ethical values can help advance innovation, for AVs and more.

Resources

Amblard, Marc. (25 Jan 2018). Autonomous Cars Will Need “Autonomous Maintenance” Solutions. ReadWrite.

Kucharczyk, Sasha. (18 Apr 2017). How will maintenance change with the autonomous vehicle? Readwrite

Malarkey, Daniel. (16 Jan 2018). Part1: Your Car of the Future Is No Car At All. Sightline Institute.

Rosenberg, David J. and Pasciullo, Nicholas A. (29 Aug 2017). Autonomous Vehicles Predicted to Change Car Ownerships, Insurance Industry. The Legal Intelligencer.

Technology and Costs. Google’s Autonomous Vehicle.

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Assessing the Safety of Utility-Owned Smart Grid Equipment

smart grid safety online courses learn NESC smart grid

One of the biggest frontiers in electrical engineering today is the development and implementation of smart grid technology. Fueled by the global demand for greener technologies and alternative fuels, environmentally-friendly smart grid technology has the ability to stimulate stagnated economies and change the way power is delivered to electricity consumers around the world.

Smart grid technology combines existing electrical infrastructure with digital technologies and advanced application to provide much more efficient, reliable and cost-effective energy distribution. It’s a merger of power systems, information technology, telecommunications, switchgear and local power generation, along with other fields. As these separate technologies become merged, new safety considerations must be taken into account.

Ever since the days of Thomas Edison, people have been concerned with the safety of electrical devices. As innovative technologies and new opportunities and safety issues arise, the National Electrical Safety Code® (NESC®) evolves to address any and all concerns.

As Technology Advances, So Does the NESC

As plug-in hybrid electric vehicles (PHEVs) and full electric vehicles (EVs) replace gasoline-only burning vehicles, public parking lots will need to be equipped with outdoor charging stations, including pay-for-use charging stations. These stations will integrate technologies such as electrical metering, switching, information technology, telecommunications and currency handling technology.

Safety comes into play in making the charging station terminals safe for unskilled drivers to use, guarding against intentional access to hazardous voltages, as well as in protecting communication circuits. This may mean putting telecommunication protectors at each end of a campus-run communication conductor where an exposure to lightning or to accidental contact with electric power conductors exists.

Vehicle charging stations are just one example of how advances in technology lead to NESC updates.

Stay on Top of the NESC

smart grid safety national electrical safety code 2017 ieee standardsThe safety of utility-owned smart grid equipment within power generation or transmission circuits, up to and including the service conductors to customer buildings, will to continue to be evaluated for safety in accordance with basic utility safety standards or codes, including NESC.

To help your company prepare to comply with the latest safety guidelines, IEEE offers a complete seven-course NESC program online through IEEE Xplore :

Order the complete program today and stay on top of the critical tech issues affecting the industry.

Resources

Gies, Don. (1 Mar 2014). Safety Considerations for Smart Grid Technology Equipment. In Compliance.

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String of Setbacks Halts Several Autonomous Vehicle Tests

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While many believe the autonomous vehicle (AV) is a form of artificial intelligence (AI) that could ultimately help reduce the number of people killed and injured on the roads each year, it seems that fatalities are inevitable.

Last week, 49-year-old Elaine Hertzberg was struck and killed by an Uber self-driving vehicle in Tempe, Arizona. Although police are still investigating and haven’t determined whether the car was at fault, a video from the vehicle’s dashboard camera shows that the human safety driver present in the Uber vehicle was not watching the road and did not have his hands hovering above the steering wheel, as instructed in case there’s a need for intervention. This is the first death caused by a self-driving car.

Uber’s Struggling Self-Driving Cars

The crash was a major setback for Uber, although even months ago its self-driving car project was falling short of expectations. Among other issues, Uber’s autonomous vehicles were having trouble driving through construction zones and alongside tall vehicles, and its human safety drivers had to intervene far more frequently than the drivers of competing autonomous car projects.

As of March, Uber was struggling to meet its target of 13 miles per intervention in Arizona. Meanwhile, in tests on California roads last year, Waymo reports its cars went an average of nearly 5,600 miles before the driver had to take control. Waymo is now testing in Chandler, Arizona, with no safety drivers.

Testing Comes to a Screeching Halt

Sure that the market for self-driving cars could be worth trillions of dollars, tech companies like Uber and Waymo, as well as automakers like Toyota, Ford and General Motors, have spent billions in development.

In fact, just weeks before Hertzberg’s death, The Economic Times reported that Uber and Toyota had been collaborating on self-driving systems, negotiating a possible deal for Toyota to use Uber’s automated driving technology in one of their minivan models. A Toyota spokeswoman said the company had been regularly exchanging information about automated driving with Uber for some time.

However, since the incident, Uber’s autonomous vehicle trials across North America have been halted and Toyota has decided to pause their Chauffeur mode testing on public roads.

Ford has made no changes to testing operations and GM still plans to roll out its commercial service in 2019.

Resources

Kokalitcheva, Kia, and Fried, Ina. (20 March 2018). Some self-driving car companies hit brakes on tests after fatality. Axios.

Symons, Xavier. (25 Mar 2018). A self-driving car killed a pedestrian. What now? BioEdge.

Wakabayashi, Daisuke. (24 Mar 2018). Uber’s self-driving cars were struggling before Arizona crash. The Economic Times.

Reuters. (19 Mar 2018). Toyota in talks with Uber on self-driving tech. The Economic Times.

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The Race to the Edge of the Network

iot industry 4.0 concept,industrial engineer using software (augmented, virtual reality) in tablet to monitoring machine in real time.Smart factory use Automation robot arm in automotive manufacturing

Edge computing is a distributed, open IT architecture that features decentralized processing power, enabling mobile computing and Internet of Things (IoT) technologies. In edge computing, data is processed by the device itself or by a local computer or server, rather than being transmitted to a data center.

Allowing large amounts of data to be processed near the source, edge computing helps reduce internet bandwidth usage. This efficient data processing both eliminates costs and ensures that applications can be used effectively in remote locations. Plus, the ability to process data without ever putting it into a public cloud adds a useful layer of security for sensitive data.

what is edge computing, how does edge computing work, 5G cloud computing, edge computing conceptDriven by a need to overcome cloud overhead in latency and bandwidth and a demand for more local processing, edge computing is poised to enable billions of new IoT end-points and real-time local artificial intelligence/machine learning (AI/ML) for autonomous systems. Edge computing allows smart applications and devices to respond to data almost instantaneously, as it’s being created, eliminating lag time, which is critical for technologies like self-driving cars.

How Client Devices Will Become Smarter

Robert Cihra, Managing Director and Senior Analyst at Guggenheim Securities, LLC, Research Division, says self-driving cars, smartphones and other client devices will become smarter in order to handle more local processing. According to Cihra, this is how:

  • Making machines smarter via real-time on-board AI/ML
  • Making thin-client smartphones fatter, as they need more processing and storage for on-device ML and virtual/augmented reality (VR/AR)
  • Pushing smartphone configurations/BOM costs and thereby ASPs even higher
  • Enabling more frictionless user interfaces (UIs) headlined by Voice and Vision vs. Keyboard and Screen
  • Enabling data input from devices that increasingly involve no human interaction at all (e.g., cameras, IoT sensors for location, vibration, temperature, etc.)
  • Favoring vertically-integrated vendors (hardware and software) particularly early on (e.g., Apple; Tesla; Google now building hardware; GM’s acquisition of Cruise Automation)

The Self-Driving Car Race

One of the hottest topics in edge computing is self-driving cars, because a self-driving car can’t be programmed to drive, but must think and act for itself, and it certainly cannot rely on the cloud and risk lag time.

The ability to process streams of sensor data and complex neural net pipelines in real-time is crucial. An autonomous car will require 50-100X the processing power and >10X the Dynamic Random Access Memory (DRAM) and Not And (NAND) technology of an Advanced Driver Assistance Systems (ADAS) car today.

Interior of Tesla Model S 90D car. Tesla Motors is an American company that designs manufactures and sells cutting edge electric cars.

Interior of Tesla Model S 90D car.

Cihra thinks Tesla, a pioneer in the American development of electric vehicles, is ahead of the curve in making automobiles an edge computing device. The company has used its connected fleet of customer cars for shared ML and building an in-house model that adds complexity, risk and cost, but also ultimate leverage.

As the perfect edge computing device, the automobile must be fully integrated, in terms of hardware and software development. And that’s why Cihra sees Apple either making a car itself or getting out of the market all together. Right now, Apple is investing in autonomous driving but has not yet committed to a car.

And This is Only the Beginning

Edge computing presents an incredible incremental growth opportunity for IoT development and data processing. To learn more about IoT, check out the IEEE Guide to the Internet of Things, our series of eight training courses designed to give your organization critical foundational knowledge.

Resources

Ray, Tiernan. (2 Mar 2018). Apple, Tesla to Lead ‘Edge’ Computing, Says Gugenheim. Barron’s.

What is Edge Computing? Hewlett Packard Enterprise.

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Is Your Industry Ripe for Artificial Intelligence Disruption?

Health industry using AI artificial intelligence healthcare

Artificial intelligence (AI) is poised to make an indelible mark on how business is done in a variety of fields. The AI industry will have tremendous impact on the way people and programs work together effectively. Here are the industries that are primed to see the most tremendous improvements in efficiency and cost savings this year.

Healthcare

AI is now contributing to the practicality of disease management and empowering people to make better lifestyle choices. It’s also creating a better pathway between patients and their healthcare providers. Plus, in a world that’s increasingly vulnerable to cyber security threats, AI can play a vital role in safeguarding the industry overall. It’s not an overstatement to say that the AI industry is crucial for healthcare.

For medical practitioners and providers, AI has led to a breakthrough in emerging drug discovery platforms. Additionally, many treatment centers are using AI-based diagnostics as a first-tier of clinical diagnostics, leveraging AI for enabling personalized medicine.

According to Mark Michalski, executive director of Massachusetts General Hospital and Brigham and Women’s Center for Clinical Data Science, by the end of 2018, half of the leading healthcare systems could adopt some form of AI within their diagnostic groups. It’s anticipated that 2018 will be “the year AI becomes real for medicine.” (Michalski, Dec 2017).

Automotive artificial intelligence AI industry cars AI car industry auto industryAutomotive

There seems to be a new headline about self-driving vehicles permeating every news cycle as of late. Not only is AI “driving” driver-less cars, it can help build smart cars less expensively, ones that are capable of detecting and self-navigating various people, places, and things while in operation. The AI industry and the autonomous vehicles industry really go hand-in-hand.

The most prevalent of AI applications in the auto world is machine learning, which does much of what it sounds. Machines use data to teach themselves how to make real-time decisions in split seconds, similar to how humans learn and improve over time. Thus far, machine learning has been highly useful in developing advanced driving assistance systems. Outside of the vehicles themselves, machine learning has brought huge improvements to the sales and after service functions of the automobile life cycle.

Real Estate

The real estate industry hasn’t had a major breakthrough in decades, making it ripe for disruption. As Value Walk points out, AI has the ability to “reduce operational costs, improve customer service, improve efficiency, and reduce resource wastage” within real estate. AI bots in particular are revolutionizing other industries, and could be one of the first dominant AI technologies that both agencies and property owners adopt. Largely due to their relative ease of integration as compared to other facets of AI, AI bots are able to field queries about leasing, footage, and other common prospective buyer questions that come up during virtual tours.

While the disruption has already begun, Inc. predicts the largest single change that will come to real estate will be AI replacing a realtor for some people.

Bottom Line

The AI industry is expected to expand exponentially in the coming year, completely transforming these and other industries. Programmers, engineers, and technologists need to understand and implement globally accepted ethical considerations at the heart of AI as it continues its fundamental shift in the way business is done. Potential impediments to successfully using this technology, however, includes the practical applications of AI, as well as ethics in design.

This year, IEEE Continuing Professional Education is offering a two part online course program on the subject: Artificial Intelligence and Ethics in Design.  If you’re interested in group discounts for the AI ethics in design courses for your organization, please contact an IEEE Content Specialist today.

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The Benefits of Smart Cities

The Benefits of Smart Cities: IEEE Innovation at Work

Smart Cities are here, using Internet of Things (IoT) technologies to improve the power grid and other utilities, increasing efficiency and stretching municipal funding.

But that isn’t all.  Imagine you are heading to an event in a city where parking is notoriously difficult.  Don’t worry about parking your car.  Instead drive your autonomous vehicle to the venue (the streetlights will be sure to illuminate as you pass, turning off and saving energy after you’ve driven by.).  Your self-driving car drops you off, and then uses its IoT connection to the city grid and drives itself to available parking.  When it’s time to leave, your car picks you up.

This type of connected experience is not far from the realm of possibility. When municipalities create smart city experiences that pool resources and share data, they create places that residents want to live, and to which businesses flock. And the best part is that these technologies tend to improve efficiencies and save money, paying for themselves within a few years. (Horn, 2016)

How can smart cities technology transform and benefit these communities?

  • Smart cities pool resources and maximize cost savings that translate to better community services. Municipal entities have found cost savings by initiating simple improvements to their planning, resulting in funding for more programs that support more of their residents.
  • Coordinating IoT initiatives have a positive impact on the residents of that community. According to John Horn, CEO of Ingenu,A city that illustrates a commitment to improvement through smart initiatives is more likely to build strong, well-informed, and healthy communities.”
  • Finally, as these communities get recognized for their positive attributes, it attracts more people to the neighborhood.  They will want to live, work, and play in these areas, generating additional revenue for the community. Besides the individual, companies migrate to places that centralize resources, because this reduces the costs of doing business and in turn attracts customers.

Even though the smart city image of self-driving cars isn’t here yet, IoT technology is a cornerstone of tomorrow’s community.

Learn more about the Internet of Things, a crucial component to smart cities; check out IEEE Guide to the Internet of Things.

References

Horn, John. (2016, December 14). 3 benefits a smart city can gain from smart infrastructure. ReadWrite.

Ismail, Nick. (2017, August 29). How Smart Cities will Lay the Way for Autonomous Cars. Information Age.

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Why Your Children Might Never Drive

Self-driving cars are the future of transportationYour children might never drive. Despite the initial shock factor this statement elicits, it doesn’t take long for the truth to sink in. For those that have already learned how to drive, it may be difficult to imagine relinquishing this freedom. But the reality is that self-driving cars, or autonomous vehicles (AVs), are set to stage a technological coup over transportation as we know it.

The shift is already beginning. According to the Gates et al., (2017), “Major automakers have been investing billions in development, while tech players like Uber and Google’s parent company have been testing their versions in American cities.” While much of the technology behind self-driving cars is not yet perfect or complete, studies are proving that AVs will dramatically reduce the number of traffic accidents and deaths (Stewart, 2017). Even though the first fatal self-driving accident with the Tesla Model S last year aroused considerable fear, investigators from the National Highway Traffic Safety Administration (NHSTA) concluded that the Autopilot on the car did not actually cause the passenger’s death (Stewart, 2017). Nevertheless, automakers and tech developers are working on improving safety features to further allay fears.

Some other hurdles that AVs will have to overcome are the threat they pose to numerous jobs and the risks they carry in light of potential hackers (Chopra, 2017). According to Chopra (2017), “Soon technological capability won’t be the greatest impediment to adoption; societal friction will be.” But even among these challenges, few people question or deny that self-driving cars are the future. As Artificial Intelligence (AI) and the Internet of Things (IoT) continue to advance and permeate our lives, AVs are no exception.

Interested in learning more about the Internet of Things for your organization? Check out IEEE Continuing Professional Education’s online training program: IEEE Guide to the Internet of Things.

References:

Chopra, A. (2017, Jul 22). What’s taking so long for driverless cars to go mainstream? Fortune.

Gates, G., Granville, K., Markoff, J., Russell, K., & Singhvi, A. (2017,  Jun 6). The race for self-driving cars. The New York Times.

Stewart, J. (2017, Jan 20). After probing Tesla’s deadly crash, feds say yay to self-driving. Wired.

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