Real Time Health Monitoring System to Predict Fever, Jaundice and Anemia using Smart Phone Camera

The accurate and timely detection of fever is crucial in environments that require rapid and widespread screening, including healthcare facilities, airports, border checkpoints, and public events. Traditional fever detection methods, particularly contact thermometers, tend to be slow, labor-intensive, and pose an increased risk of disease transmission. This paper introduces an innovative non-contact fever detection system that utilizes grayscale image processing to simulate thermal imaging and estimate temperatures from the inner eye canthi—a region closely associated with core body temperature. Beyond fever detection, the system also analyzes RGB intensity variations in the same area to identify potential signs of jaundice and anemia, thereby broadening its diagnostic capabilities. By focusing on predefined eye regions, the system avoids the need for computationally intensive facial landmark algorithms while maintaining high accuracy. Temperature estimations, along with assessments for jaundice and anemia, are derived from grayscale intensity variations and presented through an intuitive web interface that enables real-time feedback. Despite operating without dedicated thermal cameras or fully calibrated data, the system demonstrates reliable performance, providing a costeffective and scalable solution for practical health screening. Future research will aim to incorporate advanced calibration techniques and expand the system’s diagnostic range to further improve detection accuracy.