1. Machine Learning-aided Automatic Calibration of Smart Thermal Cameras for Health Monitoring Applications
- Author
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Fiammetta Marulli, Lelio Campanile, Gianfranco Palmiero, Carlo Sanghez, Michele Mastroianni, Campanile, L., Marulli, F., Mastroianni, M., Palmiero, G., Sanghez, C., Campanile, L., Marulli, F., Mastroianni, M., Palmiero, G., and Sanghez, C.
- Subjects
Computer science ,Calibration (statistics) ,Smart Sensor Networks ,Internet of Things ,Real-time computing ,Clinical Evaluation ,Mass Screening Infection ,Health Monitoring ,Machine Learning ,Deep Learning ,Covid-19 Disease ,Thermal ,Internet of Thing - Abstract
In this paper, we introduce a solution aiming to improve the accuracy of the surface temperature detection in an outdoor environment. The temperature sensing subsystem relies on Mobotix thermal camera without the black body, the automatic compensation subsystem relies on Raspberry Pi with Node-RED and TensorFlow 2.x. The final results showed that it is possible to automatically calibrate the camera using machine learning and that it is possible to use thermal imaging cameras even in critical conditions such as outdoors. Future development is to improve performance using computer vision techniques to rule out irrelevant measurements.
- Published
- 2021
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