Developing a Universal Identification Model: Integrating AI and IoT Tools with DNAFIDs to Recognize COVID-19 Patients

Abstract

DNA fingerprinting identification systems based on artificial intelligence infuse almost every facet of life. Its impact on various aspects of human health can be seen today. It has also found its importance in the identification of global COVID-19 infections, whether suspected or proven, in patients. Because of the IoT and the application of sophisticated filtering techniques to big data, it’s conceivable. The technology of DNA profiling, which creates detailed profiles of individual characteristics, is a necessity. This can be incredibly helpful in the acquisition process in certain circumstances when paired with other data. Many candidates’ medical and physiological factors are included in the Human Clinical Profile (HCP), as are social profile-related services. The government spends significant tax dollars vetting the physical and medical characteristics of various candidates for clinical care and purposes related to public health response. We propose a technique that may help analyze the physical traits of candidates preemptively and conduct forensic investigation for human identification, which may help reduce the cost of check-ups and other medical processes. This technique combines DNA profiling with artificial intelligence tools to pre-screen candidates for COVID-19 patients who require physical and remote monitoring. Further experiments done in a targeted manner are justification for the hypothesis.