Automotive IoT - Saudi Arabia

One of the fastest growing Internet of Things’ markets has been the Automotive IoT as more manufacturers are entering the race of delivering the first completely autonomous car available for commercial sales. Technology used for Advanced Driver Assistance Systems (ADAS) has been developed and introduced to newer vehicles, and governments, such as the EU countries, have been introducing legal framework for mandatory ADAS features to improve road safety.

Vehicle telematics have become widely available and affordable, and the advancements in technology including more sophisticated sensors and advanced analytics tools are fueling the demand. The sensors and analytics tool have especially seen a high adoption in fleet telematics as providing real-time tracking and monitoring of vehicles yields great results in improving operational efficiency and reducing costs.

Connected vehicles are also becoming part of smart cities with systems such as the vehicle-to-infrastructure (V2I) and the data communicated helps in improving road safety and reduce congestion. The more vehicles are connected, the better results are.

Data coverage

The data encompasses B2B, B2C and B2G revenues. The revenue only refers to the spending share of the Internet of Things components.

Modeling approach/ Market size:

The segment size is determined through a combination of top-down and bottom-up approaches. We use annual financial reports of the market-leading companies and industry associations, as well as third-party studies and reports to analyze the markets. To estimate the market size for each country individually, we use relevant key market indicators and data from country-specific industry associations, such as consumer spending, internet penetration, 4G coverage, and current and historical developments. This data helps us estimate the market size for each country individually.

Forecasts:

In our forecasts, we apply diverse forecasting techniques but primarily exponential smoothing. The selection of forecasting techniques is based on the behavior of the relevant market. The main drivers are the GDP and the level of digitization.

Additional notes:

The data is modeled using current exchange rates. The market is updated twice a year in case market dynamics change.