A Community-Based IoT Personalized Wireless Healthcare Solution Trial.

Area of Science:

• Biomedical Engineering
• Internet of Medical Things (IoMT)
• Telemedicine

Background:

• Point-of-care diagnostics are crucial for personalized monitoring.
• Remote healthcare solutions are needed, especially in areas with limited connectivity.
• Existing systems often lack long-range capabilities and robust data transmission.

Purpose of the Study:

• To develop and test an advanced Internet of Things (IoT) point-of-care bio-fluid analyzer.
• To demonstrate the feasibility of long-range, remote diagnostic screening for urinary tract infections (UTIs).
• To evaluate the system's reliability in transmitting diagnostic data to a secure cloud server.

Main Methods:

• Utilized a LoRa/Bluetooth-enabled electronic reader with disposable test 'keys'.
• Developed a companion Android application for data management and transmission.
• Conducted technology trials simulating remote screening for UTIs over distances of 1.1-6.0 Km.

Main Results:

• The LoRaWAN-enabled monitor correctly diagnosed and transmitted all UTI test results to a secure cloud server.
• Tests achieved 100% accuracy in UTI diagnosis based on visual inspection of test strips.
• Data transmission was robust across distances with significant radio path losses (119-141 dB).

Conclusions:

• The developed IoT medical solution provides a robust and simple method for next-generation community-based smart diagnostics.
• This system is particularly beneficial for regions lacking reliable mobile or broadband signals.
• It offers subscription-free, long-range bio-telemetry, reducing the need for frequent clinical visits and potentially lowering healthcare costs.