3 IoT and Edge Computing Use Cases Transforming the Auto Industry

By Tony Velcich
Jun 05, 2022

This article is part of a series exploring use cases and innovative approaches to edge computing and IoT across a range of industries where these technologies are expected to deliver outsize business value.

By 2030, nearly 95 percent of new vehicles sold globally will be connected — sharing Internet access and data with other devices inside and outside of the vehicle — according to a McKinsey & Company report, “Unlocking the full life-cycle value from connected-car data.”

In the much-nearer future, the volume of data transmitted between vehicles and the cloud through sensors and related software will be close to 100 petabytes per month, with connected vehicles generating roughly $150 billion in annual revenue, according to an Automotive Edge Computing Consortium white paper, “General Principle and Vision.”

For the automotive sector — a legacy industry of OEMs, suppliers, and aftermarket players — activating data from commercial and consumer vehicles requires a fundamental transformation of their businesses. Digital native start-ups that are “born in the cloud,” such as the Aurora Driver and MOTER Technologies, are already pushing the industry forward.

The path to mobility

Many companies are becoming “mobility companies.” A mobility company is defined as one that provides technologies and services that enable people and goods to move around freely. This concept isn’t new to the auto industry; it began gathering steam in the mid-2010s, when car makers around the world announced that they wanted to change from being manufacturing companies to mobility service providers. One example of the changes to come was when Volvo introduced Care by Volvo, the first subscription model that bundled a car, maintenance, and insurance into one monthly subscription fee.

A mobility business model addresses the huge change in the ways that people get from point A to point B. Factors driving this change include the increase in urbanization, the uptick in the shared economy (share a ride, share a home, share an office, share an e-bicycle, share electricity), and the surge in on-demand delivery services (food, consumer goods, digital entertainment).

More important is the boom in mobile connectivity and sensor technologies that can be embedded into objects — leading to growth of the Internet of Things (IoT), where data from billions of connected people, devices, and things can be analyzed and monetized.

Data leaders need to transform their businesses to grab opportunities from the edge to the cloud. So which use cases matter to automotive industry data leaders? Which applications of IoT and edge computing are worth the investment and attention? Here are three use cases that are already having an impact.

1. Use case: Business transformation

Not all companies are “born in the cloud.” Incumbent players with decades — if not centuries — of experience are now adopting a high-tech mentality toward innovation in order to remain relevant and compete. Two in particular are Bosch and Denso Corp.

From durable goods to smart sensors

Car sensors have been around for a long time. Initial sensors called MEMS (micro-electro-mechanical systems) were first used in vehicles as pressure sensors and accelerometers. Over time, MEMS sensors were used in consumer electronics, smart phones, and, more recently, have evolved into smart sensor nodes for IoT.

A leader in sensing technology is Bosch. A multinational company known to many for its durable goods products, Bosch has been developing sensors since the 1990s, starting with micromechanical sensors for use in automobiles to measure acceleration, rotation, pressure, and sound. These sensors relay information to electronic control units, letting them know exactly when to inflate an airbag in an accident, for example.

In 2005, Bosch started manufacturing sensors for consumer electronics. Since then, Bosch saw the opportunities being presented by IoT and expanded its lines of business to include IoT, software, new internet-based business models, and data protection. Through its Mobility Products and Services group, for example, Bosch provides sensing solutions to global automotive manufacturers to enable autonomous driving, active safety features, and predictive maintenance, among other solutions. With a continuous flow of data, these automotive sensors can annually create petabytes of data, which need to be analyzed at scale in the cloud to take full advantage of the data contained within and among the sensor network.

For instance, if an automotive manufacturer starts collecting and analyzing data from car sensors, it could share that data with insurance providers to change the way insurance policies are created based on a driver’s behavior. “Pay-as-you-drive” insurance is revolutionizing an industry not known for innovation, until now.

From auto parts to driver safety, starting at the edge

Denso has made the transition from being a hardware manufacturer to being a mobility data company. Denso has a large portfolio of legacy products and services from its initial automotive parts business and, more recently, has become a provider of mobility solutions that connect vehicles with IoT.

Denso’s MaaS Architecture is an onboard edge computing platform for automobiles that connects vehicles to cloud networks to offer new services. The architecture replicates real-life urban environments and traffic conditions in a virtual space; collects the data; and then analyzes it to anticipate traffic issues. The data is then used by service providers, including administrative agencies and service shops, to facilitate repairs and maintenance. In this way, mobility service providers can analyze data and control vehicles safely from the cloud, matching vehicles with the right services and ultimately reducing service times and costs.

Denso believes that the only way to eliminate the number of accidents is to equip all forms of mobility with safety technology — from sensors that can ascertain a situation in and around a vehicle such as traffic patterns, environmental conditions, and even a driver’s health condition to algorithms and control systems that can make split-second decisions.

2. Use case: Product innovation

Sensing the wide open road: Connecting the fleet with driverless trucks

Vehicle sensors are now being used in other modes of transportation such as long-haul trucking. There are a number of cloud-based services, such as Software as a Service, Infrastructure as a Service, and Platform as a Service. Next up is “Driver as a Service,” or DaaS. Founded in 2017, American-based Aurora Innovation, Inc. develops self-driving vehicle technology that can be integrated not only into cars for autonomous driving, but also into commercial trucks.

The company’s technology platform, the Aurora Driver, consists of sensors that perceive the world; software that plans a safe path through it; and the computer that powers and integrates them both with the vehicle. Rather than depending on one type of sensor for the self-driving technology, Aurora combines the strengths of different types of sensors — high-resolution cameras, 4-D imaging radar, and its custom lidar technology that enables trucks to drive farther and travel safely at high speeds — to create a more reliable system. Aurora licenses the technology to self-driving vehicle fleet companies so that Aurora retains the data, analytics, and insights of all the miles driven across all vehicle fleets.

3. Use case: Monetizing car data

Changing the path of its 113-year-old business, one driver at a time

General Motors was perhaps one of the first — if not the first — traditional automaker to collect connected-car data with the introduction of OnStar in 1996. OnStar is a telematics system that can detect when a car equipped with OnStar is involved in an accident; it then automatically dispatches first responders to the scene.

A key byproduct of OnStar is that it provides assorted driver behavioral data that GM can monetize. In 2021, GM reported that it had 20 million connected cars on the road in 47 countries, resulting in enormous amounts of data and potential new revenue opportunities. One such opportunity is OnStar Insurance. Released in 2021, OnStar Insurance is a user-based insurance service specifically for GM owners, as well as for drivers who don’t have OnStar-capable cars.

The service focuses on such things as individual vehicle usage and rewards for safe driving habits — factors that fall within the customer’s control. Using built-in vehicle sensors, OnStar Insurance tracks vehicle usage and driving habits and uses that data to offer discounts and incentives to those drivers who practice safe driving. Ergo group is also pioneering the use of IoT data to evolve both their business model and their suite of insurance products and services.

OnStar Insurance is just one of roughly 20 startups GM has planned in an effort to double annual revenues by 2030. GM projects annual software and services revenue opportunities to be between $20 billion and $25 billion, from a projected 30 million connected vehicles by the end of the decade. The OnStar connectivity platform has more than 16 million connected vehicles on the road today, according to GM, with software and services generating a projected $2 billion in annual revenue. OnStar Insurance is a key part of this growth, as GM projects it to have a potential revenue opportunity of more than $6 billion annually by the end of the decade.

Tips to kickstart mobility initiatives

Deloitte outlined a set of tips to help data leaders lay the foundation for a successful mobility data business model.

Perform “random acts of science.” Don’t focus the organization on one ambition; instead, understand both consumer trends and potential disruptors to uncover winning ideas. Then, set new goals and create a portfolio of value-creation concepts.

Ask questions. As your concepts become tactical plans, ask key questions for each opportunity you identify, including:

1. Which data collection, privacy, and analytical capabilities are required?
2. Where is the value in these activities, such as data standardization, consent management, and anonymization?
3. Which critical technologies are in place and which would have to be built?
4. What should be done in-house versus outsourced to an ecosystem partner?
5. How could a concept be prototyped for validation?
6. What level of investment would be required to scale the concept?

People matter. Work with a cross-functional team that has a high level of innovation and skills, is well-versed in today’s business environment, is enlightened by external research, and is willing to challenge their own thinking.

As the vehicle continues to evolve from being strictly a mode of transportation to a product that offers new services and value through cloud-networking connections, the automotive industry must act fast in order to reap the benefits — revenue, profit, customer retention, and more — of moving data from the edge to the cloud throughout the entire lifecycle of the automotive value chain.

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