Herein demonstrated experiment studies two methods, namely convection and body resistance, to approximate human core body temperature. The proposed system is highly energy efficient that consumes only 165 mW power and runs on 5 VDC source. The implemented solution employs an IR thermographic sensor of industry grade along with AT Mega 328 breakout board. Ordinarily, the IR sensor is placed 1.5–30 cm away from human forehead (i.e., non-invasive) and measured the raw data in terms of skin and ambient temperature which is then converted using appropriate approximation formula to find out core body temperature. The raw data is plotted, visualized, and stored instantaneously in a local machine by means of two tools such as Makerplot, and JAVA-JAR. The test is performed when human object is in complete rest and after 10 min of walk. Achieved results are compared with the CoreTemp CM-210 sensor (by Terumo, Japan) which is calculated to be 0.7 °F different from the average value of BCT, obtained by the proposed IR sensor system. Upon a slight modification, the presented model can be connected with a remotely placed Internet of Things cloud service, which may be useful to inform and predict the user’s core body temperature through a probabilistic view. It is also comprehended that such system can be useful as wearable device to be worn on at the hat attachable way.
