ITS students create Techno Temperature with AI as innovation of COVID-19 temperature detector

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Five students of the Sepuluh Nopember Institute of Technology (ITS) Surabaya created a body detection system in anticipation of the coronavirus (COVID-19) that utilizes Artificial Intelligence (AI) called TT-Techno Temperature.

They are Instrumentation Engineering Department Students who are members of the Instone team.

This idea was lifted from the weaknesses of traditional body temperature measurements that still use humans as implementers or controls and the possibility of technical errors in data collection in the field.

Instone Team Leader Lukman Arif Hadianto explained why the temperature detection protocol should use technology, not humans. “Implementation by making physical contact can potentially endanger the officer, besides the manual data collection process, also slows down the identification of suspects with COVID-19,” he explained, Monday, July 27.

According to Lukman, TT – Techno Temperature itself is a body temperature pattern recognition system using the Longwave Infrared (LWIR) sensor and image processing as a follow up to prevent the spread of COVID-19 integrated with the government and hospitals.

The main component of TT – Techno Temperature uses a FLIR Lepton thermal camera that can measure human body temperature. This camera itself applies the concept of AI in the form of a neural network.

“For its application, the sensor is connected to an application that can display the user interface of the sensor readings,” he explained.

If body temperature is detected above the temperature threshold, the camera automatically takes a picture of a human face and sends the data to the user of this application and sounds an alarm for warning.

Furthermore, the data will be sent to the central or regional government and hospitals for monitoring and follow-up of humans whose body temperature is above normal limits.

For example, by picking up the suspect so that he immediately checked with the nearest hospital and quarantined.

Lukman explained, the advantage of Instone innovation that is integrated with user applications, hospital applications, and government applications.

So according to him, this system is very effective because data of the patient or people that indicated body temperature above the normal limit can be detected quickly and realtime

The five students consisting of Lukman with Ari Wardana, Noor Robbycca Rachmana, Indriani Aramintha Mentari, and Nurfani Arifudin, through this innovation won first prize in the COVID-19 Innovative and Inspirational Application Competition (LAI2-COVID-19) in the Detectors sub-competition organized by the Directorate of ITS Student Affairs.

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