Augmented Reality Training Systems for Law Enforcement: Design, Challenges and Opportunities
Abstract
The paper describes an augmented reality (AR)based training model of law enforcement agencies that aims at boosting the operational readiness, quality of decisions and situational awareness using immersive and adaptive problems solving environments; the system is designed through the use of real time scenario simulation, the ability to dynamically adjust the level of difficulty, performance analytics and ethical protection, and experimental research indicates significantly better results compared to traditional training design in terms of accuracy, decision time, cognitive efficiency, and the engagement of the trainees, making <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$A R$</tex> a principled and efficient solution to the contemporary limitations in policingrelated issues. In this research paper, the concept of the Augmented Reality Training Systems to the Law Enforcement is studied in terms of their design principles, and issues of implementation, and future possibilities. The study will attempt to give a comprehensive background to the researcher, system designers, and policymakers who want to take advantage of AR as a disruptive means to enhance law enforcement training, functional performance, and citizen confidence.