SMART monitoring of surface temperature and moisture content using multisensory data fusion

This paper characterizes the practice of Infrared Thermopile array sensor to monitor the surface temperature and also temperatures at different depth levels by employing the thermocouple probes. The increase in moisture content when the surface of the object is in influence with water bath is studied and interpreted. The effect of distances and depth levels between the electrodes on resistance moisture content has been analysed and Gaussian Process based machine learning technique to estimate the moisture content using resistive sensor data is proposed. The paper concludes by discussing the projected method´s potential to augment the monitoring capabilities in sewer environment through multisensory data fusion.