Real-Time Abnormal Detection for Asthma Patients with Internet of Things Technology

Internet of Things (IoT) has gained significant momentum with the developing technology-. Health services are one of the most critical areas of loT that are used in almost every application. Nowadays, one of the most common chronic diseases is asthma. Respiratory rates of asthma patients need to be monitored for specific periods. For this reason, patients need to go to health centers continuously. In this study, we aim to detect respiration in real-time in every environment where asthmatic patients do not go to health centers. Patient breathing rates are calculated using the DHTII temperature sensor. The data from the patient is transferred to the Firebase cloud environment in real-time with the Wemos D1 development card which has ESP8266 Wi-Fi module. The obtained data is processed and sent to the WEKA data mining software for classification. Classification results are reported to the patient by detecting a normal or abnormal condition. Thus, using data mining techniques and loT devices, patients are provided with the opportunity to know their situation in all settings without the help of medical experts.