Image Credit: Subaru
The rise of the Internet of Things (IoT) has caused stratospheric growth in the number of connected devices and sensors in enterprises across all industries. It’s estimated that more than 80 “things” per second are connecting to the Internet, and by 2020 there will be a whopping 50 billion things connected to the IoT. Industries such as manufacturing and retail are being dramatically transformed by the IoT, with enterprises adopting technologies like fog computing and advanced analytics, or deploying hundreds of thousands of sensors throughout every aspect of their supply chains to create efficiencies, increase productivity, and gain real-time insights about their customers.
The connected car market today is facing many of the same IoT-related challenges that enterprises in other industries have already encountered and overcome. Here’s my take on some of the best practices and lessons learned along the way — many of which can be applied to the connected car market to help automakers and their partners harness the full potential of the IoT. Because this is such an important topic with many lessons to be learned, we’ll explore it over the course of a two-part series.
In many ways, the connected car can be considered the ultimate “thing” in the IoT. These data centers on wheels are truly the epitome of everyone’s best hopes and greatest challenges when it comes to the IoT.
With often more than 100 onboard computers continuously monitoring location, component performance, driving behavior, and more, experts estimate that highly automated vehicles will generate four terabytes of data per hour! And, as our transportation systems become even more connected through vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication, the amount of data generated is going to shift into overdrive.
As a result, automakers and their partners are beginning to experience many of the same challenges that enterprises in other industries have, including managing an overwhelming number of connected devices and the huge volume of data they generate, as well as challenges related to security, pervasive connectivity, bandwidth optimization, and more.
Lesson #1: Managing mushrooming devices when traditional methods won’t scale
Not long ago, enterprise IT revolved around managing a few large mainframes. Then suddenly, new paradigms emerged, like client-server, distributed, and mobile computing — forcing enterprise IT to evolve. The trend of bring your own device (BYOD — allowing employees to connect their personal devices to the company network) created…