Research Data (Health & Environmental).xlsx

Title: Dataset for IoT-Based Remote Health Monitoring System for Asthma Patients <br> Description: The sensor data from an Internet of Things-based remote health monitoring system created for people with asthma is included in this collection. The information includes both environmental and health factors, giving details on the patients' health and indoor environments. The dataset is a useful tool for researching the efficiency of the monitoring system and examining asthma patients' medical problems. <br> Environmental Data: The file contains measurements of the room's temperature, humidity, and dust density. A DHT11 sensor was used to measure temperature and humidity, while an optical dust sensor was used to measure dust concentration. Over the course of a month, the data was gathered every 15 minutes. <br> Health Data: The dataset also includes health parameters including body temperature, oxygen saturation, and heart rate (measured in beats per minute, or BPM). A MAX30100 sensor was used to measure the heart rate and the amount of oxygen in the blood, while a DS18B20 sensor was used to gauge the body temperature. Over the course of one week, measurements for each of these parameters were conducted at regular intervals on one patient. <br> Data Analysis: A thorough data analysis, including descriptive analysis, graphical representation, and statistical testing, has been performed on the dataset. For both environmental and health factors, descriptive analysis involves computing a number of statistical measures, including mean, standard deviation, minimum, maximum, and percentage of data outside permissible limits. To see the trends and patterns in the data, graphs were created, including line plots, box plots, and time series plots. In order to investigate the variations and importance of health markers throughout various time periods, statistical tests like ANOVA were carried out. <br> Data Reproducibility: Researchers may use the technique described in the corresponding paper to replicate the data. This involves connecting the sensors (DHT11, MAX30100, DS18B20) for data collecting, setting up the IoT-based monitoring system using NodeMCU and Arduino microcontrollers, and employing the relevant software platforms (Blynk, Thingspeak) for real-time monitoring and data visualization. The corresponding author will provide more thorough instructions upon request.