IO, Surabaya – In an effort to anticipate the spread of COVID-19 pandemic, five students of the Department of Instrumentation Engineering, the Faculty of Vocations of Institut Teknologi Sepuluh Nopember (ITS), gathered together in the “Instone team”, have created a temperature detection system that utilizes artificial intelligence on behalf of TT-Techno Temperature. This idea was taken from the weakness of existing body temperature measurements that still require an officer to check people’s temperature and the possibility of technical errors in the logging in the field.
Lukman Arif Hadianto, chairman of the Instone Team, explains why temperature detection protocols should use non-human technology. “The implementation by making physical contact can potentially harm the officer; besides, the process of logging manually also slows down the identification of a suspected COVID-19 sufferer,” he explained, in a release received by Independent Observer, Sunday (7/26/2020).
According to Lukman, TT-Techno Temperature itself is a body temperature pattern recognition system using LWIR sensor and image processing as follow-up prevention of the dissemination of COVID-19, integrated with the government and hospitals. This man, born in 1998, explained how TT-Techno Temperature, using a Flir Lepton thermal camera, can measure the temperature of the human body.
The camera itself implements the concept of artificial intelligence in the form of neural networking. “For implementation, the sensor is connected to an application that can display the user interface of the sensor reading results,” said the student of 2017.
He continued, there is a threshold or a specified minimum temperature. If the body temperature is detected above that threshold, the camera automatically takes a picture of a human face and sends the data to the app’s users and sounds an alarm for the alert. Furthermore, the data will be transmitted to the central or local government and hospitals for monitoring and follow-up, confirming whose body temperature is above the normal limit, detaining the suspected carrier to be checked immediately into the nearest hospital and quarantined.
“This system is very effective because the patient or human data that indicates body temperature above a normal limit can be detected quickly and in real time,” said the student, who was born in Kediri, East Java.
The advantage of Instone innovations is that it is automatically integrated with user applications, hospital applications, and government applications. It will be easier to track people detected by those sensors. “Also, there are notifications about the delivery of information to the sensors, detected in the form of measured body temperature and hospital information, to allow manual checking with a hospital or self-quarantine at home,” said Lukman.
The innovations, initiated by Lukman with Ari Wardana, Noor Robbycca Rachmana, Indriani Aramintha Mentari, and Nurfani Arifudin, managed to win first place in the Innovative And Inspirational Application Contest COVID-19 (LAI2-COVID-19) in national scale on the detector subrace, conducted by ITS Directorate of Student Affairs. Team Instone also faces obstacles like sensor selection, that can detect body temperature quickly and precisely, as well as challenges where the process of discussion and workmanship is done online.
“Nevertheless, this competition is very interesting for those of us who cannot contribute to the forefront, but can contribute to making a new tool and innovation,” he said. (est)