Part 4: Developing IoT-enabled Autos: a tsunami of change and leveraging the IoT

By | 3 minute read | January 11, 2018

In the first three parts of this series we explained the process transformation that is taking place In IoT-enabled autos. I’ve discussed the emergence of model-based systems engineering (MBSE) and the movement toward the Scaled Agile Framework (SAFe) in modern engineering practices. The final component driving automotive development forward is the promise of cognitive systems and how they help at key junctures in the process.

But we haven’t yet talked about the 700-pound gorilla: The most important part of this journey is the ability to leverage the Internet of Things (IoT). That then lets you directly understand how today’s vehicles operate on the roads.

The IoT is now influencing all aspects of driving.

The IoT means time gaps are narrowing

Traditionally, engineers had to wait months after a vehicle’s release to get a detailed view of how it was performing. After new vehicles are sold, it takes time for consumers to recognize issues and take them back to their dealers. Dealers offload vehicle data and then send periodic information back to OEMs. There could easily be a three- to six-month gap before initial data makes its way back to engineers.

And that’s just the vehicles that were taken back to dealers. What about consumers who allow an issue to linger before doing anything about it? What about data from the other cars that weren’t directly problematic?

There’s also the issue of context. When a problem with a vehicle was observed by its driver, what was the weather like in that moment? Or the road conditions? How was the car being driven when the issue occurred? All of this may be lost through current processes where data is only obtained from the subset of cars that their drivers brought in for service.

We can do much better.

Enabling preventive maintenance

As this transformation unfolds, the sensor systems already in cars will be accessed in real time, through IoT platforms and with vehicle-to-cloud connectivity that enables integration to engineering systems. Engineers should then be able to obtain this data from vehicles as soon as they hit the roads. They can aggregate it, analyze it, and diagnose it before those issues even turn up at a dealership. And with much less time than it would take the same information to traverse through the existing process. This video explains IBM’s vision for how IoT systems will work closely with engineering systems.

IBM’s IoT for Automotive solutions enable real-time updates and improved performance.

The ability of engineers to interact with vehicles directly through over-the-air updates is also a game-changer. It allows engineers to remotely update relevant vehicle software. Vehicle issues that can be fixed through software can be resolved while IoT-enabled autos are parked in their garage overnight. Issues remain for automotive OEMs to work out how these over-the-air updates will affect existing dealer networks in servicing vehicles.

Extending vehicles’ lifespan while improving performance

Over-the-air updates also introduce another new and exciting feature to vehicle owners. Vehicle software will be updated to give owners new capabilities and services throughout the life of the car. We’ve practically taken this for granted on our smartphones, but we still have practically no expectation of attaining new vehicle features remotely in our cars. Tesla, for example, not only deployed its Autopilot as an over-the-air update, but during last summer’s Hurricane Irma in Florida, the company provided an extended battery range capability to nervous customers who were stuck in long traffic jams while evacuating from the affected areas. I would imagine those Tesla owners are highly satisfied.

To find more information about all these innovations, visit IBM’s IoT for Automotive solution for connected vehicles as well as IBM’s Continuous Engineering suite.


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