In the context of wearable devices for critical patient health monitoring, fog computing (sometimes referred to as "dog" in some contexts due to a misinterpretation, but here taken as fog computing) and edge computing work together in a complementary way to enable real-time health monitoring, medication suggestions, and emergency alerts. Edge computing processes health data locally on or near the wearable device, minimizing latency and enabling rapid responses. This local processing capacity ensures that critical health data can be analyzed immediately without relying on constant communication with remote cloud servers. For example, the wearable device or a nearby edge server can analyze patient vitals in real time to detect anomalies and suggest medications or alert doctors instantly if emergencies arise. Fog computing acts as an intermediate layer between the edge devices and the cloud, providing distributed processing, storage, and communication capabilities closer to the data source than the cloud. It helps manage and process large volumes of health data generated by many IoT devices or wearables within a local network, improving response times and reducing data transmission to remote clouds, which is beneficial for latency-sensitive healthcare applications. Together, edge and fog computing reduce reliance on centralized cloud infrastructure, enable real-time decision-making, improve bandwidth efficiency, and enhance patient data privacy and security by keeping sensitive data closer to the source. These combined technologies allow wearable health devices to constantly monitor patients, suggest medications based on immediate data, and alert healthcare providers rapidly in emergency situations through speedy local processing and networked data handling.