Abstract
The Internet of Things has attained rapid growth in the field of the smart healthcare industry in the last decades. Different intelligent heath sensing research has been carried out in the field of vital signs, heart rate monitoring, sleep patterns, and abnormal respirations. This research takes into consideration the cost setup for the tools and equipment, getting the data, training them, and considering different health conditions based on the individuals around the world. Different health sensing approaches are taken into consideration but none of the research achieved a remarkable result. . So, low-cost, and affordable research in the health care industry is the need of the day. In this project, we are implementing a system that takes into consideration the sleep patterns and breathing signals from multiple users. Sleep is one of the pivotal parts of an individual’s life. Sleep Apnea is highly debilitating and can be treated effectively if detected on time. Certain parameters should be taken into considerations when dealing with sleep patterns as it may end up getting into a scenario of Apnea. If the sleep patterns are not considered and taken care of, then it might lead to problematic scenarios for individuals.The system consists of an RFID speedway Reader, Antenna, and Tags (ALN- 9740) which are the building component for detecting the breathing patterns of a person. Data is collected from different people into a collaborated file and furthermore integrates LSTM is applied to the data collected to detect the apnea. The data before performing the experiment on the model is preprocessed using low pass filters and Hampel filter to eliminate the collisions and outliers. Doing this calibration helps us to get a proper balance between the values obtained.