Implementation of Transfer Learning-based Mask Detector on Smart-Locked Door with Raspberry Pi

The status of covid 19 as a pandemic by WHO has not been revoked, not even downgraded into endemic. The masks and vaccinations are still consider as 'the most effective weapons' against the virus. Using masks indoors is still mandatory. This paper designed a device that turns an ordinary door into a smart door that only gives access to people who wear masks. A camera and monitor is installed in front of the exisiting door and solenoid lock is added as additional keys. TensorFlow and OpenCV on Raspberry Pi are used to detect whether someone is wearing a mask or not. Based on the test results, the effective distance of the device is 2,7 m with 98,11% accuracy. © 2022 IEEE.

The Implementation of Android Application for Online Learning Using Blended Learning System at Sharia and Law Faculty UIN Sunan Gunung Djati Bandung

The online learning system during the Covid-19 pandemic is the best choice in the learning process, however, the quality of learning and knowledge transfer remains the top priority. An android-based blended learning system is used at the Faculty of Sharia and Law which presents the features needed in the online teaching and learning process by combining face-to-face learning using an e-learning system and a two-way communication system, so that maximum quality of learning can be achieved. © 2022 IEEE.

Implementation of Arduino-Based Body Temperature and Olfactory Detector Automatic Door

The serious problem faced by the world now is the pandemic caused by Covid-19. Currently, body temperature and olfactory screening are still important, especially for safety in closed rooms. This study aims to design and build a simple prototype of an automatic door integrated with contactless temperature and olfactory detection devices. This device consists of an MLX 90614 sensor as a temperature detector, an IR FC-51 sensor as a fragrance object detector, an Arduino UNO as a processor, and an LED display that displays instructions and screening results. The door automatically opens if the temperature and smell are normal and vice versa. The implementation results of this prototype provide the best detection distance of up to 2.5 centimeters with 5% error. While the FC-51 sensor is able to detect up to a distance of 5 centimeters. The performance of the MLX 90614 sensor in detecting temperatures is not significantly different from the detection results of the GXGOI thermogun, which is only around 0.17 degrees Celsius. In general, the entire device part works as expected with 100% accuracy. This simple prototype is expected to inspire screening techniques to prevent the spread of Covid19 in closed rooms. © 2022 IEEE.