A Narrative Analysis on Deep Learning in IoT based Medical Big Data Analysis with Future Perspectives

The analysis of health-specific parameters and IoT based health monitoring system become a very challenging research scope to merge them with big data handling capability. This paper proposes an idea describing the possible ways to monitor and analyze health conditions collaborating IoT based medical big data through deep learning algorithm. The recent research trend regarding the concerning field often utilizes the conventional machine learning based algorithms those are not suitable for IoT based big medical data because of their manual feature extraction and less accuracy. On this contrary, this paper widely reviews the different research works regarding the big data handling in deep machine learning approaches and their proposals for health monitoring, applicability on IoT based system, accuracy, and suitability regarding big data analysis. Eventually, this paper focuses on deep learning based IoT system for health monitoring tools and contributes to providing relevant results to the different remote doctors in the area of IoT architecture to ensure propzer knowledge about critical patients. It is an approach to synchronize them in a platform that could be a potential solution for the upcoming researchers to implement a sustainable online based health monitoring system with big data accessing capability. In addition, this research will be effective for medical experts to ensure appropriate healthcare facilities to the mass people in the future.