Towards self-aware heatstroke early-warning system based on healthcare IoT

This paper addresses a preliminary model for self-aware heatstroke early-warning system based on the healthcare internet of things (IoT). Basically, heatstroke is a syndrome caused by human’s body overheating, commonly due to lengthy exposure or physical exertion in excessive temperatures. Now-a-days, heatstroke is one of the most critical issues in human health due to global warming. The major goal of this research is to save valuable lives by proposing a self-aware heatstroke early-warning system by applying an advancement of healthcare IoT and machine learning technique. The proposed system is an easy to wear and cost-effective system that even middle class people can afford it. The system will use real-time sensor data obtained from the users in real-time outdoor and indoor experiment. In this system, we use an Arduino prototype which contains three different types of sensors including (a) temperature sensor, (b) pulse sensor and (c) breath sensor. In addition to this, the usage of analytics here can enhance accuracy and real-time capability, allow in-advance detection, and enable personalization.