An internet of things-based automatic brain tumor detection system

Due to the advances in information and communication technologies, usage of internet things (IoT) has reached an evolutionary process development modern health care environment. In recent human analysis system, amount brain tumor patients increased severely placed 10th position leading cause death. Previous state-of-the-art techniques based on magnetic resonance imaging (MRI) faces challenges detection as it requires accurate image segmentation. A wide variety algorithms were developed earlier classify MRI images which are computationally very complex expensive. this paper, a cost-effective stochastic method for automatic tumors using IoT is proposed. The proposed system uses physical activities detect tumors. To track daily activities, portable wrist band named Mi Band 2, temperature, blood pressure monitoring sensors embedded with Arduino-Uno used achieved accuracy 99.3%. Experimental results show effectiveness designed detecting automatically produce better comparison previous approaches.