$GTCH the company's joint Venture GBT Tokenize Corp (“GBT/Tokenize”) has completed its qTerm device prototype and is now in the testing and debugging phase. The testing and debugging phase is targeted to check the device's overall functionality and its sub-systems including BLE (Bluetooth Low Energy), IR heat sensors, oximeter sensors, power management and others. The initial testing provided satisfactory results and all electronic circuitries are fully functional.

Further testing of the complete system will be conducted during the upcoming weeks in order to finalize the device’s functionality. Another aspect is the device's mechanical enclosure, components and sensors placement. The device is assembled based on the most up-to-date SMT (Surface Mount Technology). SMT is a method in which the electronic components (microchips, resistors, capacitors) are mounted directly onto the surface of a printed circuit board (PCB). SMT is an efficient method to create small electronic devices and to increase manufacturing automation which reduces cost and improves quality. It also allows for more electronic components to fit on a given area. qTerm prototype includes a PCB with IR and optical sensors, LEDs for visual feedback, battery and its enclosure. The device firmware, which is a permanent software code that is programmed into an internal read-only memory, provides the machine-level control for a device's specific hardware. qTerm's embedded firmware provides a robust operating environment, performing functions control, monitoring and data manipulation operations. The device will be providing a visual feedback about the results, using colored LEDs and a mobile application information and alerts. A custom mobile application is working with the device to read the data, process it, and provide the results to the user. In addition, the mobile application is an interface to send data to a backend program that is running on a server. The data is planned to be further analyzed by AI algorithms to enable health monitoring, on-going health information and alerts. The mobile app is planned to use location information to provide proximity alerts in order to slow the pandemic spread. The proximity alerts will be based on voluntary, anonymous, private user's participation.