How Does Edge Computing Improve Disease Surveillance?
Traditional disease surveillance systems often rely on centralized data processing, which can be slow and resource-intensive. Edge computing, on the other hand, enables decentralized data analysis, allowing for quicker detection of disease patterns and anomalies. This can be particularly beneficial in remote or underserved areas where internet connectivity may be limited. Wearable devices and IoT sensors can collect and process health data locally, providing immediate insights that can inform public health decisions.
