Connected mobility and IoT: drivers of automotive innovation

Edge AI and real-time data processing

The introduction of Edge AI is a significant advance in connected mobility. Instead of processing data in the cloud, Edge AI is used directly in the vehicle to minimize latency times and enable real-time decisions. This is particularly important for autonomous driving applications and advanced driver assistance systems (ADAS). OEMs and semiconductor manufacturers are increasingly developing AI chips that are specifically designed for use in vehicles, which enables faster data processing and improved response times.

Current developments in Edge AI

In 2024, we see a clear automotive trend in the increased integration of Edge AI in cars such as the Tesla Model S and the autonomous vehicles from Waymo. These developments show how important fast data processing is for the safety and efficiency of autonomous vehicles.

5G connectivity and its impact

The introduction of 5G networks is a revolutionary step for connected mobility. 5G enables high-speed and low-latency communication, which is necessary for the real-time data exchange between vehicles and infrastructure. The Ericsson Mobility Report predicts that the number of cellular IoT connections will rise to three billion by 2029, which corresponds to an annual growth rate of 12%.

5G as an enabler for autonomous vehicles

With 5G, vehicles can transmit large amounts of data in near real time, which is essential for the implementation of V2X (vehicle-to-everything) technologies. Pilot projects in cities such as San Francisco and Shanghai are already using 5G to support autonomous driving tests.

Digital twins and predictive maintenance

Digital twin technology, which creates virtual replicas of physical objects, is being used more and more frequently in the automotive industry. It enables real-time monitoring and simulation of vehicle performance, resulting in improved maintenance and efficiency. Companies such as Siemens and General Electric use digital twins to monitor and predict the performance of their vehicles. BMW uses digital twins to optimize production lines, and Renault uses this technology to monitor and optimize energy consumption in electric vehicles.

Blockchain for increased security and data protection

Blockchain technology is used to solve security and data protection problems in connected mobility. Its decentralized structure ensures tamper-proof data management and increases the security of vehicle communication and transactions. This is particularly important as the number of networked devices and the amount of data transferred increases.

For example, Volkswagen uses blockchain to ensure the integrity of OTA software updates, and Toyota is improving supply chain transparency through blockchain technology.

Sustainable mobility through IoT

Alongside technological advances, sustainability is another increasingly important issue. IoT applications play a key role in promoting sustainable mobility by optimizing fuel consumption and reducing emissions. Fleet management systems that use IoT technologies enable more efficient route planning and reduce the ecological footprint.

Renault and Nissan use IoT-based systems to optimize the energy consumption of their electric vehicles. Volvo relies on renewable energies in combination with IoT technologies to reduce carbon emissions.

Autonomous vehicles and machine learning

Advances in artificial intelligence and machine learning are crucial for the development of autonomous vehicles. Modern systems analyze extensive data to identify driving patterns and make decisions in real time, which improves traffic safety and efficiency. Waymo and Tesla are increasingly focusing on these electronic technologies to bring the next generation of autonomous vehicles onto the market.

Progress with autonomous vehicles

Waymo is successfully testing its autonomous vehicles in several U.S. cities and is planning to expand. Tesla is continuously improving its Full Self-Driving (FSD) technology with new updates that improve autonomous navigation in urban environments.