The evolution of automotive software traces back to the 1970s. This was the time when cars first leveraged computers, with software-managed basic engine functions and advanced electronics making their way into the automotive industry. In the 1990s and early 2000s, software began to dictate safety, climate control, infotainment, and driver assistance. Today, the automotive industry is on the cusp of a technological revolution, driven by the advent of cloud and digital transformation. As the world becomes increasingly connected, the demand for efficient, intelligent, and sustainable transportation solutions are skyrocketing.  

Let's delve into how the cloud will drive these futuristic technologies in the automotive industry. 

Driving Towards Innovation: The Current State of Automotive Industry

Four well-known technology trends have emerged as key drivers of innovation in the automotive industry: autonomous driving, connectivity, electrification, and shared mobility. 

Driving Towards Innovation

Traditional automotive companies are facing intense competition from tech giants and startups that are disrupting the industry with innovative business models and cutting-edge technologies. Besides, as the autonomy of vehicles increases, so will their insatiable appetite for data generation. Some reports suggest, the modern vehicles churn out a modest 25 gigabytes of data per hour, while their autonomous counterparts are poised to eclipse this figure by over 100 times. Now that's what we call a “tsunami of data”!

This new normal will not only push global networks to their absolute limit, but it would also necessitate the need for a robust, global network of cloud datacenters to manage the influx effectively and diligently. 

Cloud is no longer a luxury but a necessity to meet the ever-evolving demands of modern consumers in this increasingly connected world.

Cloud Steering the Automotive Industry Forward – How?

Predictive Insights and Data-driven Optimization: 

Cloud solutions offer powerful data analytics and machine learning capabilities that can help automakers gain valuable insights from the vast amounts of data generated by connected vehicles. These insights can be used to improve vehicle performance, optimize maintenance schedules, and enhance the overall driving experience.

Now for instance, Mercedes drove a car around the world to capture data on road conditions and driver behaviors in different countries. A cloud-based machine learning model can analyze such data, enabling predictive maintenance and identifying potential issues before they occur, reducing downtime and improving customer satisfaction.

Collaborative Design and Development: 

Distributed teams of engineers, designers, and suppliers can collaborate seamlessly on vehicle development projects, regardless of their geographic location through cloud. Cloud-based tools and platforms facilitate real-time sharing of design files, simulations, and other data, streamlining the development process and accelerating time-to-market.

A global automaker, for example uses a cloud-based product lifecycle management (PLM) system, allowing its teams in different countries to work concurrently on the design and development of a new vehicle models, fostering collaboration and reducing development cycles.

Over-the-Air (OTA) Updates: 

The cloud makes it possible for automotive companies to deliver software updates and new features to vehicles over-the-air (OTA), without requiring customers to visit a service center. With the use of cloud-based software and APIs, manufacturers can remotely update the software and firmware of vehicles, which helps to improve security and ensure that vehicles are running the latest software versions

Elastic Capacity: 

The cloud provides the automotive industry with the ability to scale computing resources as and when needed, ensuring they have the necessary capacity to handle fluctuating demands without over-provisioning or under-provisioning. Whether it's managing vehicle data, running simulations, or deploying software updates, cloud platforms offer the flexibility to provision resources instantly. This elasticity streamlines operations, reduces costs, and fosters innovation in automotive technology.

Expenditure Model Optimization: 

By leveraging cloud, the automotive industry can shift from capital-intensive investments in on-premises infrastructure to an operational expenditure model, with a pay as you go model. This can lead to significant cost savings, especially for computationally intensive workloads like simulations and autonomous driving development.

For instance, instead of building and maintaining a massive on-premises high-performance computing (HPC) cluster for crash simulations, companies can leverage cloud-based HPC resources, paying only for the computing power it needs, when it needs it, resulting in substantial cost savings. 

The Potential of Cloud in Automotive Industry

The Potential of Cloud in Automotive Industry

ReseachGate

Top 15 Use Cases of Cloud in Automotive Industry

1) AI and Autonomous Vehicles: One area where the cloud is poised to make a significant impact is in the development of autonomous vehicles. AI in automotive is essential for creating self-driving cars that can navigate complex environments safely and efficiently. The cloud provides the computational resources and data processing capabilities necessary to train and deploy machine learning models that power autonomous driving systems. 

  • German vehicle manufacturer Volkswagen is one enterprise going the co-creation route, building its own industry cloud for automobile manufacturing in concert with AWS. 

2) Connected Vehicles: The development of linked automobiles, or vehicles that are connected to the internet and other devices, is made possible by cloud. Info such as real-time traffic data, remote diagnostics, and over-the-air updates are just a few of the additional features and services made possible by connectivity.  

3) Vehicle-to-Everything (V2X) Communication: Cloud-based platforms will enable real-time communication between vehicles, infrastructure, and other connected devices, facilitating intelligent traffic management, accident prevention, and optimized navigation.

4) Autonomous Mobility-as-a-Service (AMaaS): Cloud can enable seamless integration and orchestration of autonomous vehicle fleets, providing scalable computing power and real-time data processing capabilities for efficient ridesharing and logistics services.

5) Digital Twin for Vehicle Lifecycle Management: The creation and maintenance of digital twins – virtual replicas of physical vehicles – enabling real-time monitoring, predictive maintenance, and optimized product lifecycle management can be facilitated by cloud solutions. 

6) Automated Vehicle Cybersecurity: Cloud-based cybersecurity solutions employ advanced analytics and machine learning to safeguard connected vehicles from cyber threats. These solutions provide continuous monitoring, threat detection, and prevention, ensuring the security of automated vehicles against evolving cybersecurity risks. 

7) Generative AI for Vehicle Design and Manufacturing: Cloud-based generative AI models are here to change vehicle design and manufacturing processes, enabling rapid iteration, optimization, and customization based on real-time data and consumer preferences.

8) Cloud for Massive Computing Power: The immense computing power required for resource-intensive tasks like autonomous driving simulations, big data analytics, and machine learning model training, is something cloud solutions are known for.

  • For example, a single Jaguar model consumed 36 million CPU hours to support the running of 1.8 million simulations that generated 1,200 terabytes of data. All of the data collected then contributed to meeting around 40% of the car’s design and performance verifications. 

9) Advanced Driver Assistance Systems (ADAS): Cloud-connected ADAS will leverage real-time data from vehicles, traffic conditions, and infrastructure to enhance driver safety with features like predictive collision avoidance, adaptive cruise control, and intelligent traffic signal recognition.

10) 3D Printing On-Demand Parts: Cloud-integrated 3D printing services will enable automotive manufacturers to produce and deliver on-demand replacement parts, custom accessories, and prototype components directly to customers, reducing inventory costs and lead times.

11) App-based Mobility Services: Cloud platforms enable the development and deployment of mobile applications that power services like ride-hailing, car-sharing, and subscription-based vehicle access.

  • Uber's ride-hailing app for instance, is built on a cloud infrastructure, allowing seamless scaling and integration with mapping, payment, and other services.

12) Connected EV Charging Networks: Facilitate the management and optimization of electric vehicle charging networks, cloud-based systems by leveraging real-time data processing and analytics to optimize charging schedules, manage energy consumption, and provide users with information on charging station availability and pricing. 

  • ChargePoint exemplifies this with its cloud-based platform that manages a network of over 108,000 EV charging spots across North America and Europe.

13) In-Vehicle Infotainment and Telematics: Cloud enables the delivery of personalized infotainment, navigation, and telematics services to connected vehicles, leveraging over-the-air updates, real-time data integration, and seamless content streaming for an enhanced driving experience.

  • BMW ConnectedDrive leverages the built-in SIM card, BMW ID, and cloud connectivity to provide a range of intelligent services, like remote vehicle access and control, and seamless integration with smartphones and smart home technologies.

14) Full Self-Driving Vehicles: By processing and analyzing vast amounts of sensor data, mapping information, and real-time traffic data, cloud acts as the central ecosystem for Full Self-Driving (FSD) in autonomous vehicles. Cloud solutions power the development, training, and deployment of autonomous driving systems, facilitating decision-making, and over-the-air software updates for self-driving capabilities across entire fleets.

15) Robotics and Automated Manufacturing: The integration of robotics and automation in vehicle manufacturing processes, enabled by cloud solutions, facilitate tasks like automated vehicle assembly, maintenance, and logistics operations, enhancing efficiency, precision, and safety in automotive manufacturing processes.     

Know How – A Two-wheeler Giant Embraced Fully Managed Cloud Services, For Digital Transformation and Improved Customer Experiences! 
Read the Full Story  

 

Cruising through the Cloudscape: Exploring the Right Cloud Mix for Automotive Innovation

Private Cloud for Automotive Industry: 

Automakers can use private cloud to store and process sensitive data, such as sensitive manufacturing data, proprietary designs and customer information, with enhanced security and control. Example: A luxury car manufacturer uses a private cloud to manage its design and engineering processes, ensuring intellectual property protection.

Public Cloud for Automotive Industry: 

Since public cloud is a shared, multi-tenant computing environment provided by third-party vendors, automakers can leverage public clouds for scaling computing resources or hosting customer-facing applications like car configurators, providing flexibility and accessibility to a wide audience.

Hybrid Cloud for Automotive Industry: 

A carefully considered hybrid strategy lets automakers move applications based on their different needs and environments. In the automotive industry, this setup allows to securely store sensitive data like vehicle designs in private clouds while leveraging public clouds for collaboration across the supply chain. Hybrid cloud simplifies project management, improves communication, and facilitates easier tracking of automotive parts. 

Multi-Cloud for Automotive Industry: 

Multi-cloud strategies are gaining traction in the automotive industry, allowing manufacturers to leverage the strengths of different cloud providers for specific applications. A multi-cloud strategy involves using multiple public or private cloud services from different providers. Automakers can leverage multi-cloud to avoid vendor lock-in, optimize costs, and access best-of-breed services from different cloud providers.  

Done right, a cloud strategy can lead the automotive industry towards a successful digital transformation. 

Cloud4C’s End to End Cloud Managed Services for Automotive Industry

Companies in virtually every enterprise sector today are using the cloud to gain IT agility, control costs and do more with their data. The automotive sector is no different. 

Cutting-edge cloud, communication, and networking innovations are reshaping motor vehicles, into fully connected entities. With robust security measures, vehicles have become versatile platforms for diverse applications, transforming driving and travel experiences. Which means, the automotive industry is benefiting greatly from the use of cloud computing platforms like Azure, GCP, and AWS, offering the necessary infrastructure and tools. This is where Cloud4C steps in the picture!

Enabling the automotive industry's digital transformation risk-free, Cloud4C stands out with our comprehensive suite of multi-cloud services, automation solutions, and robust cybersecurity measures. As a managed cloud services provider, we can help automotive companies migrate and modernize their IT infrastructure to the cloud. From enabling seamless data management, data analytics and AI to facilitating agile development and deployment of automotive applications, our team of experts ensure scalability, efficiency, and security across the automotive value chain, including production, wholesaling, retailing, and maintenance in the automotive industry.

In the race to put cars on the cloud, we can be your trusted partners. To know how, contact us today! 

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Team Cloud4C
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Team Cloud4C

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