Automotive Industry will always remain the biggest consumer of IoT

Today, M2M / IoT communication is helping automotive OEMs better understand their vehicle’s performance and driving behaviour.

CIOL Bureau
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IoT in Automotive Industry

IoT (Internet of Things) is still considered a new tech on the block, but most people are not aware of the fact that communication between devices in the form of machine-to-machine (M2M) systems dates back to more than a century now. The roots of M2M are buried deep in the development of other technologies, often created for military applications.


In 1845, the Russian army began using M2M systems in their data transmission systems. It was the most basic form of a wired data transfer network then. It was followed by the invention of two-way radio networks in the 1900s. IoT is powered by M2M technology, which uses embedded SIM cards to transmit data wirelessly via a secure mobile network and enables companies to send and receive data in real-time.

While none of the industry sectors remain untouched by the disruption IoT has brought, Automobiles has been one of the biggest consumers of IoT/M2M technology. The first car was invented in 1886 by Karl Benz. It was powered by an internal combustion engine and had three wheels.

Assembly line manufacturing was a ground-breaking development that made automobiles affordable for consumers while simultaneously increasing the volume of its automotive production per day. And this is the era when use of analytics in its most rudimentary form also started by the automobile OEMs.


An average vehicle contains 25,000 or more components and the base parts, sub-assemblies, subsystems and the final vehicle are fundamentally inter-related. From a data perspective, these relationships are hierarchical and can be complex to represent accurately and conveniently.

However, in this era, a lot of time and energy was channelized in manually processing data for understanding the efficiency and proper functioning of the critical components of automobiles and monitor the wear and tear to drive new alloys for endurance.

The next use case for analytics kicked off when automobile giants started paying attention to consumer desires to have it all– the economy of mass production, design options to fit an individual’s taste and needs, and the highest possible quality. The need to offer a greater variety of product models within the limits of mass production gave rise to multiple quality assurance methods to produce standard and exchangeable parts to reduce manufacturing costs. This, in turn, sparked the demand for design reengineering and establishing a better understanding of efficiency and power of the vehicles using data.


The next big move in use of analytics came with the use of analog sensors in cars. In 1950’s, basic sensors for low oil pressure warning lights and charging system warning lights on the instrument panel existed. However, there were no computers during that time to monitor specific conditions of the car. It was only in the early 1970’s that we see examples of electronic fuel control using sensors developed by Bosch and used on brands like Mercedes Benz, VW, Porsche, and Datsun.

Electronically controlled systems using sensors became more popular in the late 70’s and early 80’s in response to U.S. EPA emissions standards requiring the use of catalytic convertors. Most of the first computer controlled automotive systems used sensors primarily to improve fuel control in order to reduce tailpipe emissions.

Now sensors are used to monitor everything from raindrops on the windshield to reminding us when it’s time for an oil change. The data collected from automobiles can be simple sensor-based techniques to record and monitor performance, maintenance and behavior of critical automobile systems, or more sophisticated GPS and satellite-based techniques such as tracking vehicle position and recording external conditions.


Even the data collection techniques for automobiles have gained maturity over the years by using current technology offerings like mobile devices, wearables, Big Data, Business Intelligence, Cloud and Social Media. The major focus of these collection techniques is to improve customer experience and achieve better vehicle health.

Today, M2M/IoT communication is helping automotive OEMs better understand their vehicle’s performance and driving behaviour. The technology has made easy for the OEMs to understand the relation between Man and the Machine with a lot more sophistication. It has also enabled OEMs to develop and evolve relationships by having informed conversations with their customers, dealers, suppliers and deliver new, innovative value-added services, such as infotainment, user-based insurance and even financing.

Even fleet operators, including companies that offer taxi services such as the Uber and Ola, on-demand services like Zipcar, car rental companies like Hertz, and even the commercial enterprises such as the FedEx are getting more connected cars because telematics data can help improve safety, keep assets well-maintained, avoid accidents, improve route-planning, and optimize supply chain logistics, among many other benefits.


Ranjeet Koul Vice President and Country Manager for APAC and MEA Region Aeris Communications Ranjeet Koul Vice President and Country Manager for APAC and MEA Region Aeris Communications

Accenture claims that total business value of connected car services will reach $123 billion by 2020, rising to $618 billion by 2025. A single connected car could deliver as much as $6,188 over its lifetime.

While early adopters are clearly keen to realise the financial advantages, safer drivers and safer roads are also the key driver of M2M/IoT technology. Some analysts predict that the automotive sector will generate up to $199 billion in revenue in 2020 as a result of M2M technology, with the highest growth rates expected in Asia Pacific.


By this time the automotive M2M market is expected to grow to almost 1.3 billion connections, driven predominantly by the need for manufacturers to fit new cars with emergency assistance devices. However, beyond emergency assistance, the data the cars generate can provide a wide range of anonymised traffic information that helps public services better understand motorway networks. Vehicle suspension data collected from cars can also help authorities detect faults in the road before they develop into potholes.

However, one of the biggest issues is cybersecurity. It dominates the connected car industry and must be addressed as part of OEM efforts to shift their business model. Ransomware in 2017 caused serious service outages for several OEMs,

In the nutshell, the adoption of M2M/IoT by the automotive industry is only likely to accelerate with increasing regulatory demands, the opportunity to drive up revenues whilst driving down costs, and the growing customer expectations to be offered the very latest entertainment and support services become more predominant. And without doubt, the automobile sector was and will always remain the most loyal consumer of IoT.

By Ranjeet Koul, Vice President and Country Manager for APAC and MEA Region, Aeris Communications

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