Description: Edge capacity refers to the maximum amount of data processing that can occur at the edge of a network, meaning on devices that are closest to the data source. This capacity allows data to be processed locally rather than being sent to a central server or the cloud, reducing latency and improving efficiency. Edge computing has become essential in a world where the amount of data generated by IoT (Internet of Things) devices is constantly increasing. By processing data at the edge, real-time decisions can be made, thus optimizing the performance of critical applications. Additionally, this capacity allows for better bandwidth management, as only the data that truly needs to be stored or analyzed in depth is sent to the cloud. In summary, edge capacity is fundamental for enabling applications that require fast and efficient responses, such as autonomous driving, smart surveillance, and industrial automation.
History: Edge computing began to gain attention in the late 2010s, driven by the exponential growth of IoT devices and the need for more efficient data processing. As networks became more complex and data volumes increased, it became clear that relying solely on the cloud for data processing was not sustainable. In 2014, companies like Cisco and IBM started developing specific solutions for edge computing, highlighting its importance in modern network architecture.
Uses: Edge capacity is used in various applications, including industrial automation, where sensors in factories process data in real-time to optimize production. It is also applied in smart surveillance, where cameras analyze video locally to detect suspicious activities before sending alerts. Additionally, in the healthcare sector, wearable devices can monitor vital signs and process data locally to provide instant information to doctors.
Examples: An example of edge capacity is the use of IoT devices in smart agriculture, where sensors in the field analyze soil and weather conditions to optimize irrigation. Another example is the use of drones that process images in real-time for inspections of infrastructures, such as bridges and buildings, sending only relevant data to operators.
