Intelligent monitoring system for crowd monitoring and social distancing with mask control

Autor: Najmath Ottakath, Omar Elharrouss, Somaya Al Madeed
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Popis: Due to the current COVID situation, there’s a huge need for crowd control as well as efficient social distancing. Security cameras are everywhere but personnel to monitor it are few. In this project, we use crowd counting and detection along with social distancing monitoring which would enable efficient social distancing and control of the crowd intelligently. The lightening of the cumbersome task of the security professionals to monitor and analyze the crowd is done here making smart decisions on their behalf. In addition, masks are essential instruments to prevent a Corona infection; they are essentials for every individual in a crowd. In this project non-facemask wearing people can be detected at public places and an alert send for that particular individual which further helps control COVID infections. Intelligent system achieved by these two tasks will enable informed decision-making, efficient remote monitoring of crowd, proper social distancing and thus achieving safety at essential infrastructures like transport stations, schools, malls, airports, playground, hospitals etc. where tracking multiple cameras at the same time would be a hassle for security professionals. In this project, we propose a deep learning approach to accurately detect crowd above a certain restriction and make sure the individuals abide by wearing masks and social distancing effectively.
Databáze: OpenAIRE