Situation-Aware BDI Reasoning to Detect Early Symptoms of Covid 19 Using Smartwatch

Area of Science:

• Healthcare technology
• Artificial Intelligence in Medicine
• Pandemic Response

Background:

• Ambient intelligence is vital for emergency healthcare, enabling rapid access to resources.
• The Covid-19 pandemic highlighted the need for advanced situation awareness in healthcare.
• Continuous patient monitoring via wearable sensors is crucial for early emergency detection.

Purpose of the Study:

• To propose a situation-aware mechanism for early detection of Covid-19 symptoms.
• To enhance patient self-awareness and enable proactive health precautions.
• To provide timely alerts to users and healthcare practitioners during health emergencies.

Main Methods:

• Utilizing wearable sensors for continuous patient data acquisition.
• Implementing a Belief-Desire-Intention (BDI) intelligent reasoning mechanism for situation analysis.
• Modeling the proposed system using temporal logic and simulating it in NetLogo.

Main Results:

• Demonstrated the feasibility of the situation-aware mechanism through a case study.
• The system effectively analyzes data from wearable sensors to detect potential Covid-19 symptoms.
• The BDI model provides intelligent alerts based on environmental and patient data.

Conclusions:

• The proposed situation-aware mechanism offers a novel approach to early Covid-19 detection and management.
• Integrating ambient intelligence and AI enhances patient monitoring and emergency response capabilities.
• The system empowers users with self-awareness for timely health precautions during pandemics.