IoT and Blockchain Oriented Gender Determination of Bangladeshi Populations

Abstract

Forensic and medical-legal investigations depend heavily on sex identification. The most precise and trustworthy evidence of a person's identity are regarded to be their fingerprints and sexual identity determination. This test's goal was to find any gender-specific variations in the Gopalganj district of Bangladesh's population between the number of fingerprint ridges between male and female hands. To determine the topological, age demographic, and gender variability inside the number of fingerprints inside the aforementioned population is the purpose of this research. Whether the individual is male or female can be determined with accuracy by our technology. 800 unrelated volunteers, 400 men and 400 women, were fingerprinted. We have discovered through experimentation that the Ridge Density (RD) of humans varies with age. As a result, we divided the population of people into four groups, each consisting of individuals between the ages of 12 and 17; 18 to 36; 37 to 55; and 56 to 73, all of whom were collected from the Gopalganj district of Bangladesh. After conducting an experiment with 200 people from each of two groups (men = 100 and women = 100) totaling 8000 individuals, we determined and set the threshold values to detect humans. For men, we discovered a range of RD from 10 to 15 with a mean equal to 12.75, while for women, we found a range of RD from 15 to 21 with a mean equal to 18.25. As a result, we've established a threshold of 10 to 15 for males and 15 or more for women. Age and sex groups both showed significant disparities. Females have narrower crests and higher RD than males. Age-related decreases in RD levels were also noted. All groups met the RD criterion for sex discrimination, which was determined using Bayes’ theorem, allowing for its use in forensic inquiry.