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4th International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2021 ; : 550-555, 2021.
Article in English | Scopus | ID: covidwho-1769645

ABSTRACT

There has been a steep rise of contactless payment during COVID-19. The rapid improvements of miniaturized sensors and biometric recognition systems for face identification, fingerprint, iris, and voice are conducive and fit during this rise of COVID-19. Thus, non-contact interactions are the most effective way to fight against the spread of the virus and any other diseases. One of the most used is iris scanners and speech recognition. The study promotes contactless payments to address the accompanying issues in cash aid distribution particularly in the DSWD 4Ps, where it has a two-Tier biometric security system which is iris recognition and speech recognition. This can provide the same type of service and securities as a normal ATM while removing the worry of getting different kinds of viruses and diseases. Testing the iris recognition system, a False acceptance ratio of 13% and 3% of False Rejection rates were achieved. While for the testing of speech recognition (security questions), a False Acceptance Ratio of 0% and False Rejection Ratio of 12.12% were achieved. Lastly, testing of speech recognition (navigation)a False Acceptance Ratio of 0% and False Rejection Ratio of 3.62% were achieved. Giving the system an 84% accuracy for the iris recognition, 87.88% for the security questions, and 96.36% for the navigation. © 2021 IEEE.

2.
5th International Conference on Electrical, Telecommunication and Computer Engineering, ELTICOM 2021 ; : 78-83, 2021.
Article in English | Scopus | ID: covidwho-1537690

ABSTRACT

Coronavirus Disease (COVID-19) is an infectious disease caused by SARS-CoV-2, a newly discovered coronavirus. Infected people experience mild symptoms such as colds, which would lead to severe respiratory-related diseases that weaken the entire body. As the virus can be transmitted primarily through direct contact with an infected person or by touching surfaces and objects contaminated by respiratory droplets, it is critical to control and cut the transmission routes by exposing individuals under quarantine. In this study, the researchers developed an Arduino-based ankle tracker, associated with an application as the GUI, to implement geofencing to monitor people under home quarantine. The ankle tracker acts as the trigger being monitored within a geofence, a circular virtual perimeter. The system was designed to have a 95% confidence level to filter out inaccurate GNSS location data. It will only accept data that is highly accurate which depends on the PDOP value. The Geo-mapping accuracy of the tracker device was tested and presented in this study. © 2021 IEEE.

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