A Systematic Survey of Industrial and Hospital using FOG-CLOUD Computing based IOT

This paper presents an advanced IOT-based system catering to industrial and healthcare applications. In industry, it maintains optimal conditions through continuous temperature monitoring via IOT sensors and dynamic load management for enhanced energy efficiency. Integration of exhaust fans aids in efficient cooling, ensuring worker comfort and safety. Simultaneously, the healthcare module monitors and transmits vital patient parameters such as heart rate, temperature and oxygen levels to the cloud for remote monitoring. An alert system with a buzzer and mobile app notifications ensures timely healthcare provider intervention for abnormal reading. This integrated cloud architecture allows real time analysis and accessibility, meeting diverse industrial and healthcare needs. Planned enhancements include implementing predictive maintenance algorithms for industrial equipment and expanding healthcare monitoring features, such as integrating wearable devices for continuous patient data collection. By leveraging fog nodes to preprocess data locally before sending essential information to the cloud, the FOG-CLOUD model reduces response time by 30-40% in real-time applications compared to cloud-only approaches. This latency reduction is critical in healthcare for emergency monitoring and in industrial settings for real-time machinery control. Moreover, bandwidth optimization achieved through localized filtering and data compression at the fog level reduces data transmission requirements to the cloud by up to 50%, significantly enhancing system efficiency, especially where high data volumes are typical, such as in hospitals.