Cognitive IoT Integration for Smart Healthcare: Case Study for Heart Disease Detection and Monitoring

with the fast advancement in medical and computer technologies, healthcare systems turns to be an interesting topic for both academia and researchers. Moreover, some of the healthcare systems are not successful in analyzing the emergency circumstances of patients and incapable to offer personalized service resources for patients. To address this crisis, in this investigation, an IoT based Cognitive computing [C-IoT] for smart healthcare system has been anticipated. In the proposed C-IoT method, ECG sensors transmit and record ECG signals from patients. This C-IoT is capable to analyze user's physical health using cognitive computing. It also deals with the cognitive framework for making real time decisions over further activities and transmits the data to Convolutional Neural Network module. The proposed system examines the state of patients with Latent semantic Analysis [LSA]. LSA act as a minimization procedure to identify the severity of patient's condition. The results are provided to the doctors to monitor the patients. The experimental results show better trade off than the conventional deep learning approach. The accuracy of 99.30% and sensitivity of 94% of LSA with CNN method has increased correspondingly.