DEVELOPMENT OF A FACE-MASK DETECTION SOFTWARE USING ARTIFICIAL INTELLIGENCE (AI) IN PYTHON FOR COVID-19 PROTECTION

• Published in: Journal of Management Information and Decision Sciences Vol. 24; no. 6; pp. 1 - 15
• Main Authors: Kabir, Ahmed Imran, Mitra, Sriman, Jakowan, Das, Soumya Suhreed
• Format: Journal Article
• Language: English
• Published: London Allied Business Academies 01.06.2021
• Subjects: Algorithms; Artificial intelligence; Cameras; Coronaviruses; COVID-19; Datasets; Deep learning; Facial recognition technology; Machine learning; Medical research; Neural networks; Programming languages; Qualitative research; Real time; Research methodology; Sensors
• ISSN: 1524-7252; 1532-5806

Infectious diseases like Covid-19 transmits and contaminates via dispersal through aerial medium has become a serious issue nowadays that stimulated increasing the facemask usage. However, in densely populated countries it is very hard for law enforcing organizations to monitor the number of people wearing mask and those who are not wearing any in public. For this reason, a facemask detection model can be developed for security cameras in public places and surveil on people. In this research, researchers developed a prototype of facemask detector using python codes and artificial intelligence. Since Machine cannot understand human language, developers use different types of programming languages for training machine. Here, Python was used with the help of its packages to train models and two separate python files were developed to complete this research; the first one is to develop a mask detector and the other one to combine mask and face detector, combined together to develop facemask detector in real time. Data was collected, analyzed and visualized with python programming language, model was trained using ConvNet (Convolutional Neural Network) and finally an output was received from a raw input, which can detect mask in human face.