IoT-Based COVID-19 Diagnosing and Monitoring Systems: A Survey

Area of Science:

• Computer Science
• Medical Informatics
• Public Health

Background:

• The COVID-19 pandemic caused by SARS-CoV-2 has led to widespread infections and fatalities globally.
• Current strategies include vaccine development, public health measures, and stringent government interventions.
• Advanced technologies are crucial for effective pandemic management and control.

Purpose of the Study:

• To analyze the application of Internet of Things (IoT) technologies in diagnosing and monitoring COVID-19.
• To explore how IoT can aid in identifying infected individuals and hotspot areas.
• To identify challenges and future research directions for IoT in combating COVID-19.

Main Methods:

• Review and analysis of existing IoT technologies and systems for COVID-19.
• Examination of real-time and intelligent IoT-based diagnostic and monitoring systems.
• Identification of key challenges and future research opportunities in the field.

Main Results:

• Several real-time and intelligent IoT-based systems have been proposed for COVID-19 diagnosis and monitoring.
• IoT technologies show significant potential in tracking infected individuals and mapping outbreak hotspots.
• Machine learning (ML) algorithms integrated with IoT are pivotal in these advancements.

Conclusions:

• IoT technology, combined with ML, presents a promising approach for real-time COVID-19 diagnosis and monitoring.
• Addressing identified challenges is crucial for the widespread adoption and effectiveness of these technologies.
• Further research is needed to optimize and integrate IoT solutions for future pandemic preparedness.