Description: The edge computing model refers to a conceptual framework that allows understanding how data is processed and managed at the edge of the network, rather than relying solely on centralized data centers. This approach aims to reduce latency and improve efficiency by bringing data processing closer to the source of generation, such as IoT devices, sensors, and other equipment. By performing processing at the edge, the need to send large volumes of data to the cloud is minimized, which not only optimizes bandwidth usage but also enables faster responses and a better user experience. Key features of this model include the ability to operate in real-time, enhanced data security by keeping sensitive information closer to its origin, and the capability to function in environments with limited connectivity. The relevance of edge computing has grown exponentially with the increase in connected devices and the need to process data efficiently and effectively, especially in critical applications such as industrial automation, digital health, and smart cities.
History: The concept of edge computing began to take shape in the late 1990s and early 2000s, when the proliferation of connected devices and the need for real-time data processing became evident. However, it was in the 2010s that the term ‘Edge Computing’ gained popularity, driven by the growth of the Internet of Things (IoT) and the need for solutions that could handle the vast amounts of data generated by these devices. Companies like Cisco and Amazon began developing specific solutions for edge computing, leading to greater adoption across various industries.
Uses: Edge computing is used in a variety of applications, including industrial automation, where sensors and machinery devices process data locally to optimize production. It is also applied in healthcare, enabling real-time patient monitoring through connected devices. Other areas include traffic management in smart cities, where sensor data is processed to improve urban mobility, and in the entertainment sector, where it is used to enhance user experience in streaming services.
Examples: An example of edge computing is the use of smart security cameras that process video locally to detect suspicious movements before sending alerts to the cloud. Another case is the use of health monitoring devices that analyze biometric data in real-time, allowing doctors to receive immediate information about their patients’ status. Additionally, in the automotive industry, connected vehicles use edge computing to process sensor data and make instantaneous driving decisions.
