GeoSS: Geographic Segmentation Security Barriers for Virtual Emotion Detection With Discriminative Priorities in Intelligent Cooperative Vehicular System

Abstract

A development of the integrated vehicular system through ground and aerial cooperation using intelligent mobile robots and smart UAVs is required to support various applications including intelligent transportation, secure service, surveillance reinforcement. Also, it is highly anticipated that the applicability of virtual emotion is expanded continuously in smart systems. In this paper, we introduce a geographic segmentation security barrier system for the purpose of secure surveillance through virtual emotion detection in intelligent cooperative vehicular area with mobile robots and UAVs. The proposed system is necessary to provide discriminative priorities in the requested cooperative vehicular area consisting of mobile robots and UAVs with rapid construction. Moreover, with ILP formulation, we formally defined a problem whose goal is to maximize a total number of geographic segmentation security barriers such that the completed establishment of those barriers is done by a specific group of mobile robots and UAVs within the requested various districts where they are divided according to differential security priorities. To solve the problem, we devise novel schemes to return the maximum number of geographic segmentation security barriers so that it pursues the maximization of system lifetime consequently. Then, the proposed approaches are implemented through expansive simulations and their performances based on numerical results are evaluated clearly.