Internet of Things based Sensor Module for Respiratory Tracking System

• Published in: IEEE sensors journal Vol. 23; no. 16; p. 1
• Main Authors: Bhola, Biswaranjan, Kumar, Raghvendra, Priyadarshini, Ishaani, So-In, Chakchai, Padhy, Tusharkanta, Slowik, Adam, Gandomi, Amir H.
• Format: Journal Article
• Language: English
• Published: New York IEEE 15.08.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Biomedical monitoring; Breathing; Circuit design; Circuit diagrams; Electric potential; Internet of Things; IoT; Lung; Modules; Monitoring; Respiration; Respiratory System; Sensor systems; Sensors; Temperature measurement; Temperature sensors; Thermistors; Tracking systems; Unconsciousness; Voltage
• ISSN: 1530-437X; 1558-1748
• DOI: 10.1109/JSEN.2023.3274585

Respiration is a necessary process for producing energy and maintaining normal bodily functioning in all living organisms. The respiratory system and breathing frequency change per the body's needs in response to different physical activities, such as Running, and to emotional states like joy, and fear. Therefore, this work presents a simulation-based IoT sensor module using thermistors to estimate the respiration rate of a human subject and to compare the temperature at the time of breathing. The circuit diagram of the explained sensor was designed and validated using simulations with Proteus software. The results are presented in the form of graphs, comparing resistance and voltage. Specifically, the resistance varies with the temperature near the thermistor, subsequently changing the voltage, which is converted into a digital value to calculate the respiration rate and length of respiration. The main focus of the proposed work for developing this basic circuit is to observe the breathing pattern of a person. From the breathing pattern, many physical activities can be predicted, Like he is in a consciousness stage or unconsciousness stage, because every physical activity makes an impact on the breathing pattern. The obtained information can be stored and communicated across the cloud, from which the automated respiratory tracking system can manage and monitor accidental situations. In the case of an emergency, the system sends an alert so that necessary steps can be taken to help the user. Finally, we discuss some applications of the proposed module, specifically for reducing accidental deaths.