People Counting and Temperature Recording Using Low-Cost AI MATLAB Solution

Abstract

The adverse impact of coronavirus (COVID-19) has taken a toll on many aspects of our lives. Precautionary safety measures were established to contain and reduce the widespread of the virus. However, in most cases, the global pandemic countermeasures imposed restrictions on physical access to financial, health, educational, shopping, factories, public transportation, and office buildings. In addition, the process of facilitating access based on customary identity verification and temperature collection can be high risk and time-consuming, especially if performed in a close encounter. Today, many surveillance and security companies can provide a practical solution, though with a high cost. The merit of this practice is to utilize Artificial Intelligence to provide 1) remote image recognition accurately with face masks, 2) temperature recording and 3) low-cost solutions altogether. This study is developed in response to a Request for a Proposal by the UAE Ministry of Energy and Infrastructure. The study is directly related to developing low-cost system for people counting and temperature recordings using enhanced Viola-Jones algorithm with cascade objects for detection and tracking. Rudimentary analysis indicates 95% effectiveness of system, with more than 70% cost reduction, and opportunity for global implementation to ensure smoother transitions to new normal.