With the speedy digitization of the universe, the automotive industry is poised for gigantic change in coming decade, if not in the next few years. The automobile industry is on the verge of a technological revolution where vehicles are no longer just mechanical engines. The confluence of automotive industry and smart technologies has made the journey of drivers more easier and safer. At the same time vehicles have become more feature rich and advanced in meeting societal needs. IoV (Internet of vehicles) may still be far fetched but undeniably vehicles are becoming biggest data creators, may be next only to humans. They are now mobile data centres, pushing a new wave of storage technology requirements. Significant quantities of data are generated and consumed as cars become more linked and autonomous.
This data, true to its name, is a Big Data which is already giving valuable insights to the automotive industry to improve further in a number of ways by increasing the safety of vehicle, reducing the repair cost and increasing the productivity with predictive analysis and so on.
Smart vehicles contain plenty of data. Most of this vehicle data is of a technical identity and is available temporarily, with very less usefulness locally. The utility of the data within the car which is not stored for a long time is only going to increase in coming years. But certain data even now, is frequently analysed to provide better services, the connected vehicle can provide awareness into driver behaviour, vehicle health and enhance customer confidence in reliability of the vehicle as predictive maintenance replaces traditional approaches to vehicle maintenance.
Automobile data analytics will allow the vehicles to navigate, collaborate and communicate with each other without any human intervention making use of huge amount of data which is being generated by the sensors in the vehicle.
It is just about an autonomous vehicle; data science, artificial intelligence and machine learning technologies which can help in keeping the automobile companies more competitive by improving R&D, design manufacturing and marketing processes.
Machine learning, data science and eventually Artificial Intelligence can improve efficiency in the production of smart vehicles which will enable the companies to cut down their production costs, better customer service and development of futuristic innovative products.
With the help of vehicle data analytics the OEMs, Service Cenrtres, Drivers, customers as well as regulators stand to gain. Some of the Big Data mobile apps like (Tableau, Google Chart, Roambi, Qlik etc.,) collect real-time data about the traffic, transportation, accidents and other problems that may occur on the road. Thanks to these applications, crowdsourcing helps in massive collaboration amongst the users. These apps also help the users in reaching their destinations faster and more safely. The car features like parking assistance, booking of parking space or active driver assistance and many others will soon become common features in the vehicles.
As connected and self-driving cars become more common, the use of vehicle data opens up new revenue streams for OEMs and partners. In all spheres, data is being considered as a new gold and the same is going to be true in automotive sector as vehicle data can be used to make money. Big data is an essential by product for autonomous vehicles to see, hear, and respond to their surroundings. It also acts as a resource for a number of use cases outside of the automotive industry, such as retail, banking, and entertainment.
Newer predictions and patterns in the monetization of collected data are on the horizon. In-car microphones, cameras, and sensors generate vast quantities of data in connected cars. These IoT devices not only provide useful information about the driver’s actions and interests, but they also track passengers and bystanders, vehicle journey locations and time as well. This enables the collection of a large amount of essential and non-essential data along the way but all that have a potential for innovative new streams of products and services through analytics.
The ability to deliver high-quality goods and services faster than rivals would be the differentiator of success for businesses. But as of now the road ahead does not seem to be devoid of breakers. Would consumers, however, be able to share personal information in return for advanced data-driven solutions? The level of willingness varies dramatically between use cases. Customers are more willing to share information if they understand the benefits and are assured that their information is secure. Data access legislation and the ability to provide advanced protection for personal data are important. It is not possible to simply sell gathered data to third parties.
There are challenges in developing data monetisation business models. Customers, in one way or the other, are a barrier to personal data monetisation, as is the businesses’ ability to earn their loyalty. OEMs and their collaborators have to forge a common understanding with the customers and regulators on legal, social, and technological issues related to vehicle data monetisation. Need is to establish norms and solutions that enable them to live more comfortably in the shared data space and focus on developing business models wherein each stake holder perceives a fair share from the gains.
Author:
Anuj Sinha
Deputy CEO & Director
Telematics Wire
Published in Telematics Wire
