Saleem Kiran, Saleem Misbah, Ahmad Rana Zeeshan, Javed Abdul Rehman, Alazab Mamoun, Gadekallu Thippa Reddy, Suleman Ahmad
School of SoftwareDalian University of Technology Dalian 116024 China.
Institute of Diet and Nutritional Science, University of Lahore Lahore 54590 Pakistan.
IEEE Sens J. 2022 Mar 3;23(2):898-905. doi: 10.1109/JSEN.2022.3156819. eCollection 2023 Jan.
Ambient intelligence plays a crucial role in healthcare situations. It provides a certain way to deal with emergencies to provide the essential resources such as nearest hospitals and emergency stations promptly to avoid deaths. Since the outbreak of Covid-19, several artificial intelligence techniques have been used. However, situation awareness is a key aspect to handling any pandemic situation. The situation-awareness approach gives patients a routine life where they are continuously monitored by caregivers through wearable sensors and alert the practitioners in case of any patient emergency. Therefore, in this paper, we propose a situation-aware mechanism to detect Covid-19 systems early and alert the user to be self-aware regarding the situation to take precautions if the situation seems unlikely to be normal. We provide Belief-Desire-Intention intelligent reasoning mechanism for the system to analyze the situation after acquiring the data from the wearable sensors and alert the user according to their environment. We use the case study for further demonstration of our proposed framework. We model the proposed system by temporal logic and map the system illustration into a simulation tool called NetLogo to determine the results of the proposed system.
环境智能在医疗保健场景中发挥着至关重要的作用。它提供了一种应对紧急情况的方式，能够迅速提供诸如最近的医院和急救站等必要资源，以避免死亡。自新冠疫情爆发以来，已经使用了多种人工智能技术。然而，态势感知是应对任何大流行情况的关键方面。态势感知方法为患者提供了一种常规生活，在此过程中，护理人员通过可穿戴传感器对他们进行持续监测，并在患者出现任何紧急情况时向从业者发出警报。因此，在本文中，我们提出了一种态势感知机制，用于早期检测新冠系统，并在情况似乎不正常时提醒用户自我意识到该情况并采取预防措施。我们为系统提供信念-愿望-意图智能推理机制，以便在从可穿戴传感器获取数据后分析情况，并根据用户的环境向其发出警报。我们通过案例研究进一步演示我们提出的框架。我们用时态逻辑对所提出的系统进行建模，并将系统图示映射到一个名为NetLogo的模拟工具中，以确定所提出系统的结果。
