Which technology employs edge computing for data analysis?

Self-driving cars utilize edge computing for data analysis primarily due to the need for real-time processing of vast amounts of data generated by various sensors and systems. These vehicles are equipped with multiple sensors, including cameras, radar, and LiDAR, which continuously collect data from their surroundings to make rapid decisions.

Edge computing allows these cars to process this data locally, often within the vehicle itself, rather than relying on sending all the information to a central cloud server. This local processing significantly reduces latency, enabling quicker reactions to changing road conditions, obstacles, and other critical driving factors. For example, if a self-driving car detects a pedestrian suddenly entering its path, it must analyze the data and respond immediately—something that would be hindered by the delays associated with cloud processing.

In contrast, traditional web servers primarily serve content and do not typically analyze real-time data. Mobile applications, while they can utilize cloud services and occasionally employ edge computing, do not necessarily require it for basic functionality. Static websites are designed to deliver fixed content without the need for dynamic data processing or analysis, thus they do not engage in data analysis that would benefit from edge computing.