Detecting and identifying individuals with high body temperature can be critical for preventing the spread of diseases with high body temperature as a symptom like COVID-19. Thermal cameras or manual temperature inspection methods are widely used to identify elevated body temperature. In this work, we propose a novel method to identify and track people with higher disease risk, including the body temperature change of each person in a specified community and other risk factors like family backgrounds, habits, and social life. Results show that each person's body temperature can be tracked and recorded with the user’s ID number every time the user passes from specific locations equipped with RFID readers. By using an artificial intelligence-supported risk scoring system, a risk factor is evaluated based on the parameters defined accordingly. If the evaluated risk score of the user is above a specific value, the system generates an alarm to isolate the person with a high-risk score. Therefore, isolating any potentially infected individual helps health professionals reduce the spreading speed of infections through isolated communities.