A Sustainable 3D Cube Surveillance and Pedestrian Monitoring Framework for Green AI Theme Park

Abstract

Recently, the concept of Green AI is expanding its applicability to various academic and industrial fields including surveillance with energy efficiency, maximum reliability, managing traffic flows in smart cities. In particular, it is highly expected that the sustainable 3D cube surveillance is applied to theme park environment with Green AI perspective appropriately. In this paper, we design a sustainable 3D cube framework for surveillance and pedestrian monitoring toward Green AI-enabled theme park environment using mobile robots and smart UAVs. Then, a main research problem is formally defined. To resolve the problem, three different approaches are proposed with 3D zone-based and energy-efficient rearrangement strategies. Moreover, the performance of the proposed schemes is evaluated based on experiment outcomes which are obtained from expansive simulations with various scenarios.