The ecosystem of connected cars is becoming more complex

Main visual : The ecosystem of connected cars is becoming more complex

Connected cars are part of 'the Internet of Things', a term used to describe technologies that can be connected to the Internet in an attempt to make things easier for the manufacturer, driver, service center, and businesses that operate fleets of vehicles. Connection is typically achieved though a wireless local area network (WLAN). This form of communication enables the car to share internet access and data with other devices inside and outside the car.

The connected car concept has rapidly become more sophisticated, moving on from the fist innovations introduced ten years ago, when the ability to connect and stream music appeared, and map functionality became in-built. Now both hardware and software can do much more. Examples of new technologies include cellular connectivity, cloud management, data access, and data analytics. This will driven by the maturity of 5G capability, developments with vehicle-to-everything communication (V2X), and the advent of autonomous vehicles. The market for connected cars is also growing, as Lux Research point out in the report "Key Players and Business Models in the Connected Car." Not only does the report predict that the connected car market will hit $12.7 billion by 2030; the report also reveals an ecosystem of growing complexity. The report provides, examples of connected car technology: Entertainment Applications Examples here are streaming media content providers such as Spotify and Pandora. These are provided as native apps in some vehicles and these can mirror on the car's head unit using applications like Android Auto and Apple CarPlay. Diagnostics and Predictive Maintenance Services This relates to the use of onboard sensors, diagnostic codes, or analysis of vibration, noise, and harshness allow users like drivers, or service centers to analyze mechanical issues within a vehicle. Usage-Based Insurance Applications Such technology can be used to analyze driver behavior like aggressiveness or distraction based on sensors in a vehicle or mobile phone. The driver score generated is a factor in determining insurance premium rates. Training Autonomous Vehicles (AV) This relates to the process of building the technology that self-driving vehicles will need in order to upload datasets from sensors and precision maps. In the future, updated maps and machine learning models can then be downloaded by other cars in a fleet. Location-Based Services Applications This refers to technology that uses GPS and map data to provide suggestions on places to eat and refuel, as well as real-time traffic updates for navigation. Over-the-Air (OTA) Updates This is the process of wirelessly updating the software embedded on vehicles, including core safety features or advanced driver assistance systems (ADAS). These examples indicate the expanding ecosystem involved in developing connected cars, from application developers to cloud computing providers; and from mobile network companies to vehicle manufacturers.

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