In the current scenario of the COVID-19 pandemic and worldwide health emergency, one of the major challenges is to identify and predict the panic health of persons. The management of panic health and on-time evacuation prevents COVID-19 infection incidences in educational institutions and public places. Therefore, a system is required to predict the infection and suggests a safe evacuation path to people that control panic scenarios with mortality. In this paper, a fog-assisted cyber physical system is introduced to control panic attacks and COVID-19 infection risk in public places. The proposed model uses the concept of physical and cyber space. The physical space helps in real time data collection and transmission of the alert generation to the stakeholders. Cyberspace consists of two spaces, fog space, and cloud- space. The fog-space facilitates panic health and COVID-19 symptoms determination with alert generation for risk-affected areas. Cloud space monitors and predicts the person’s panic health and symptoms using the SARIMA model. Furthermore, it also identifies risk-prone regions in the affected place using Geographical Population Analysis. The performance evaluation acknowledges the efficiency related to panic health determination and prediction based on the SARIMA with risks mapping accuracy. The proposed system provides an efficient on time evacuation with priority from risk-affected places that protect people from attacks due to panic and infection caused by COVID-19.

在当前 COVID-19 大流行和全球卫生紧急情况下，主要挑战之一是识别和预测人们的恐慌健康状况。恐慌健康管理和及时疏散可防止教育机构和公共场所发生 COVID-19 感染事件。因此，需要一个系统来预测感染并向人们建议一条安全的疏散路径，以控制死亡的恐慌情景。在本文中，引入了一种雾辅助的网络物理系统来控制公共场所的惊恐发作和 COVID-19 感染风险。拟议的模型使用物理空间和网络空间的概念。物理空间有助于实时收集数据并将警报生成传输给利益相关者。网络空间由两个空间组成，雾空间和云空间。雾空间有助于恐慌健康和 COVID-19 症状确定，并为受风险影响的区域生成警报。云空间使用 SARIMA 模型监测和预测人的恐慌健康和症状。此外，它还使用地理人口分析识别受影响地区的风险易发区域。性能评估承认基于具有风险映射准确性的 SARIMA 的恐慌健康确定和预测相关的效率。拟议的系统提供高效的及时疏散，优先从受风险影响的地方疏散，以保护人们免受因 COVID-19 引起的恐慌和感染而造成的袭击。云空间使用 SARIMA 模型监测和预测人的恐慌健康和症状。此外，它还使用地理人口分析识别受影响地区的风险易发区域。性能评估承认基于具有风险映射准确性的 SARIMA 的恐慌健康确定和预测相关的效率。拟议的系统提供高效的及时疏散，优先从受风险影响的地方疏散，以保护人们免受因 COVID-19 引起的恐慌和感染而造成的袭击。云空间使用 SARIMA 模型监测和预测人的恐慌健康和症状。此外，它还使用地理人口分析识别受影响地区的风险易发区域。性能评估承认基于具有风险映射准确性的 SARIMA 的恐慌健康确定和预测相关的效率。拟议的系统提供高效的及时疏散，优先从受风险影响的地方疏散，以保护人们免受因 COVID-19 引起的恐慌和感染而造成的袭击。