Former rental cars are at the top of every buyer’s wish list. Car accident histories can’t be faked. No, it’s not an alternate universe. It’s our infinitely safer, trustful future with blockchain, IoT, and machine learning, and I test drove it during the recent SAPPHIRE NOW and ASUG Annual Conference.

Car rental demo at SAPPHIRE NOW
The car rental demo at SAPPHIRE NOW revealed how blockchain, IoT, machine learning will disrupt industries.

My challenge was to navigate a miniature, sensor-tagged vehicle through a track designed to reveal my driving habits, for better or worse. Controlled through an iOS app using an iPad, I maneuvered my “car” down to three pit stops, watching as the screen revealed my driving behavior. According to Michael Benirschka, who is responsible for Digitalization and Innovation at SAP Digital Business Services, a much larger business opportunity was brewing behind the gleaming show floor demo.

“Car rental companies and manufacturers are very interested in using this technology that can be applied to any kind of vehicle rental, such as cars, trucks, boats, forklifts and other machinery,” he said. “Combining SAP Leonardo innovations, including IoT, machine learning, and blockchain, on SAP Cloud Platform is valuable to many industries. Companies can capture and analyze real-time data from any object with SAP Vehicle Insights. Using this information, they can provide their customers with new services.”

At the Starting Gate, IoT Benchmarks Journey

Cut back to me poised in front of the starting line. I picked up my iPad and pointed its camera to select my sensor-tagged “vehicle.” After tapping the start button, we were off.  Running on SAP Leonardo Machine Learning Foundation, the algorithm instantly recognized my vehicle, and displayed data from the car’s IoT sensors on my iPad. In a flash, I could see when it was last driven, by how many people, and at what average speed.

Rewarding Low-Risk Drivers

As I revved down the track, the software automatically captured and reported my every move on the screen, using machine learning to analyze data from the IoT sensors in my car. In the real world, the idea would be to monitor someone’s risky driving habits, and reward safe drivers with bonuses. When I paused at the second pit stop, the risk indicator on my iPad revealed my rating (it was low risk), alongside recommendations for improvement and potential rewards.

“Rental companies could award safe drivers with points to redeem for free driving minutes, lower rental or insurance rates, or other special offers, while reducing the wear and tear on cars, and the number of accidents,” said Benirschka. “It’s a new business model that could be applied to organizations in any industry challenged by consumers who may or may not be using their products as intended.”

Used Car Drivers Can Trust in Blockchain

On the third leg of the track, I powered through a gauntlet of obstacles impossible to miss. The track was designed to show how blockchain captures collision data on a trusted, immutable distributed ledger. When my vehicle came to a full stop at the end, my iPad displayed every time it had struck an object, along with other information like the damage done, mileage, and shape of the tires.

“Historically people haven’t wanted to buy rental cars, but with blockchain, companies can prove how well a car has been treated including the number of accidents it’s been involved with, and if it was repaired properly,” said Benirschka. “Having this data allows resellers to calculate the real value of the car, and gives buyers the ability to trust that value.”

Consider the cascading impact of these innovations. Drivers are incented to treat rental cars better. Car dealers and repair shops provide customized maintenance updates based on individual driving habits. People waste less time and money on unnecessary diagnostics and service, and manufacturer and car dealer efficiencies soar. Best of all, drivers can rest easy knowing they can trust that “new” used car in the driveway. Used car salesmen never had it so good.

Follow me at @smgaler.