This paper presents a semantic knowledge-based context-aware smart border surveillance system to monitor suspicious activities across the border or nearby red zones and assists in handling hazardous situations using context acquisition, observation, monitoring, and generating alerts without or with minimal human intervention. The proposed formalism has an intelligent decision support mechanism to take decisions intelligently on behalf of the user, infer a plan to prevent the damages caused by the suspicious entities, and adapt itself according to the current context of use. We propose algorithms for a smart border vigilance system to present the system flow on detecting suspicious activities in the red zone and rescuing from hazards. We develop a simple case study of a smart border surveillance system and simulate the agents’ reasoning process using NetLogo simulator to analyze the behaviour in terms of efficiency and efficacy of the system.

本文提出了一种基于语义知识的上下文感知智能边界监控系统，用于监控跨境或附近红区的可疑活动，并在没有或在最少人为干预的情况下通过上下文获取、观察、监控和生成警报来协助处理危险情况。所提出的形式主义具有智能决策支持机制，可以代表用户智能地做出决策，推断防止可疑实体造成的损害的计划，并根据当前的使用环境进行自我调整。我们提出了智能边界警戒系统的算法，以展示检测红色区域中的可疑活动并从危险中救援的系统流程。