A novel data Analysis architectural framework for data reduction on edges for Smart City Healthcare

Abstract

The most difficult task is managing and digesting the massive amount of heterogeneous data created by IoT. It questioned the efficiency and computational storage capacity of today's infrastructure resources. Furthermore, because there is so much data, it becomes difficult to give the user enough information to make a decision. A technology known as Complex Event Processing (CEP) has been created to glean important insights from massive real-time data streams. The goal of this research is to create a system that can extract complicated events from large amounts of sensor data and only transmit those events to a cloud server. Global healthcare services have been expanding at an exponential rate because of the vast amount of data that clinical and medical organizations generate daily. Healthcare systems can use e-health services to meet the medical and assistive requirements of people. Edge technology is proven in this direction. Mixing the old classic concepts with the innovative we have proposed the Novel data analysis architecture for smart heart disease prediction. We have created the fuzzy-based inference system at the edges for the data analysis and used the resulting Complex Events at the end predictions.