IoT platforms: The secret sauce for connected vehicle applications
March 02, 2017
The times they are a changin’. According to the IBM Institute for Business Value study “Automotive 2025: Industry without borders,” the automotive industry is making a drastic change. These...
The times they are a changin’.
According to the IBM Institute for Business Value study “Automotive 2025: Industry without borders,” the automotive industry is making a drastic change. These changes are due to a number of factors, including pervasive disruption and shifting consumer engagement and expectations. Digitization and connectivity are the precipitative elements driving the shift in consumer engagement and expectations. There is strong demand for a seamless connected life, and among some groups a constant social engagement. These drastic changes are resulting in the need to engage a broader ecosystem of stakeholders and partners, and to become more agile. This requires a departure from the closed and siloed methods and solutions of the past.
According to a report by ABI Research, by 2020 telematics will power more than 73 million commercial vehicles; another report estimates that 342 million automotive infotainment systems will ship between the years of 2015 and 2020. If these were the only connected vehicles on the road, this would number about 415 million. This is an incredible figure, and one that illustrates a large potential for captive touchpoints.
Many owners of connected vehicles today are realizing some of the benefits of that connectivity. These benefits include things like safety and security features (for example, roadside assistance and stolen vehicle location assistance); remote access features (like remote door lock/unlock and remote start); and, for some, the ability to incorporate Internet-based infotainment services like Yelp.
I’ve looked at clouds from both sides now
Minimally, an IoT platform is a technology that enables connection and management of devices – this, however, is nothing more than an entry point today. While connectivity is a critical component of the overall architecture, an IoT platform, to be truly useful, must support the management of data in addition to the management of connected devices. And, should an IoT platform wish to be considered comprehensive, it must provide the capability to develop applications and analyze the data it ingests, both in real-time and in batch.
In a recent report on the topic, BI Intelligence broke platforms out into “three buckets”:
- Open, building block platforms – Mainly for developers working on apps at their companies
- Closed, high-end platforms – Primarily for business or government
- Product management platforms – For connecting and managing products provided by a company
While I agree that there are platforms that exist within these three silos, more capable platforms exist that transcend these boundaries. These cross-categorical platforms provide a more well-rounded set of capabilities that enable the expansive ecosystems we see developing in the connected vehicle space. For example, a “closed” product management platform in which personally identifiable information (PII) can be kept secure with an open platform that allows for third-party application development to deliver value-added content to vehicle occupants to improve the user experience.
Dreaming about the things that we could be
In today’s expanding connected vehicle environment, it is critical that our platforms support millions of simultaneously connected vehicles. The gateway provided by the platform must be scalable to support a range of applications. The platforms need to support the ingestion of contextual data, which is the data that exists in the area(s) vehicles operate. Incorporating real-time traffic information, point-of-interest information, as well as real-time weather data can significantly increase the depth and breadth of services that can be provided to the customer. With a platform-based approach, in addition to ingesting the data, it is possible to analyze the data in real-time as it is streaming onto the platform.
Imagine a road hauler with a heavy load, winding its way through the mountains. What had been originally predicted as a mild rainfall quickly begins to show signs of turning into a significant weather event with dangerously high winds. Real-time analysis of the storm trajectory coupled with the knowledge of the truck’s route and current position allow the service provider to make a real-time route update and send it directly to the in-cab navigation system, guiding the driver through a much safer route.
A platform-based approach also provides the ability to more easily aggregate streams of data. For example, imagine the traditional approach of delivering vehicles to market with adaptive cruise control. Information about whether the adaptive cruise feature is active could be captured and stored, and occasionally may even be looked at. If it is looked at, observers may notice that it is not being activated as frequently as expected. While this may be an interesting data point, to what could it be correlated?
In a different part of the company, the marketing organization sees blips come across the corporate feed, “Don’t trust ACC!”; “Been driving for years, I can control my car better than a computer #AccOff.” Once again, interesting data points, but marketing organizations are more concerned about addressing real complaints about vehicle functions and not the “occasional” gripe about a feature.
Now, imagine a platform-based approach where aggregation of not just data but disparate data streams is possible, and on that platform there exist services that can handle the unstructured data that is social media and classify comments while correlating them to actual relevant key performance indicators (KPIs) of interest to the product teams (for example, the enabling and disabling of the new adaptive cruise control feature). Very quickly, the platform dashboard would light up with indicators showing that there was a general lack of “trust” in the new feature.
The ability of the team to respond and take corrective action is improved. Further analysis could also be done on ways to increase trust. Modifications to software could be implemented, built, and deployed from this same platform.
As these various use cases illustrate, development on a platform provides many advantages over traditional development environments. In addition, the presence of a platform in the operational stage of vehicles enables richer engagement with the customers. Whether it’s a new lower latency or more secure protocol, a database with faster access time and transfer rates, new cognitive capabilities, or third-party applications, as new technologies and services become available a platform makes adoption of those technologies easier.
There are other use cases that could be discussed, some well understood and adopted (like usage-based insurance) and others just beginning to emerge. Instead, however, I will leave you to dream of what a connected vehicle could become. Share those dreams with me on Twitter.
1. “Automotive 2025.” IBM Automotive 2025 – United States. February 15, 2017. Accessed March 01, 2017..
2. “Telematics to Power More than 73 Million Commercial Vehicles by 2020 Amidst Cut-throat Competition.” ABI Research. Accessed March 01, 2017..
3. “Over 342 Million Connected Automotive Infotainment Systems to Ship between 2015 and 2020.” ABI Research. Accessed March 01, 2017..
4. Business Insider. Accessed March 01, 2017..