Description: Data inference is the process of drawing conclusions from a dataset using algorithms and statistical models. This process occurs at the ‘edge’, meaning on devices that are close to the data source, such as sensors and IoT (Internet of Things) devices. Edge inference allows devices to process and analyze data in real-time, reducing latency and the need to send large volumes of data to central servers. This is particularly relevant in applications where response speed is critical, such as in autonomous systems, health monitoring, and industrial automation. Data inference at the edge also contributes to bandwidth efficiency, as only relevant results are sent to the cloud or other systems, rather than transmitting all raw data. In summary, edge data inference is a technique that combines artificial intelligence and real-time data processing, enabling quick and effective decisions based on locally available information.
