<p>This study introduces a fog-based framework designed to address the rising incidence of heatstroke through efficient, real-time healthcare solutions. By leveraging fog computing(FC), cloud computing (CC), and Internet of Things (IoT) sensors, the framework aims to overcome the limitations of traditional cloud computing in handling real-time IoT data, which often leads to latency and spatial awareness issues. The framework integrates three layers: the IoT sensor layer collects health and other parameters related of heat stroke risk, the fog layer processes this data locally for immediate decision-making and alerts regarding potential level of heatstroke, severe cases, and the cloud layer handles long-term data storage and conducts spatial network analysis (SNA) to identify hot-spots. This setup improves location awareness and service quality, essential for quickly diagnosing and managing heatstroke cases. It provides key benefits like decreased latency and enhanced service quality, crucial for real-time healthcare applications. This fog-based approach aims to streamline heatstroke management, leading to better patient outcomes and reduced strain on healthcare systems. The public health sector can use this framework for early detection and handling the heat stroke related health issue, thereby improving response times and reducing the impact of heatwaves on vulnerable populations.</p>