Low Cost System for Face Mask Detection Based Haar Cascade Classifier Method

In December 2019, there was a pandemic caused by a new type of coronavirus, namely SARS-CoV-2 (Severe Acute Respiratory Syndrome Corona Virus 2) spread almost throughout the world. The World Health Organization (WHO) named it COVID-19 (Coronavirus Disease). To minimize the spread of the COVID-19, the Indonesian government announced a policy for the social distancing of 1-2 meters and wearing a medical mask. In this study, a mask detection system was built using the Haar Cascade Classifier method by detecting the facial areas such as the nose and lips. The study aims to distinguish between using masks and on the contrary. It is expected that the mask detection system can be implemented to provide direct warnings to people who do not wear masks in public areas. The results using the Haar Cascade Classifier method show that the system designed is able to detect faces, noses, and lips at a light intensity of 80-140 lux. The face is detected at a distance of 30-120cm, while the nose is at a distance of 30-60cm, while the lips are at a distance of 30-70cm. The system designed can perform the detection process at a speed of 5 fps. The overall test results obtained a success rate of 88,89%.

Modeling of cooling process of hydroaluminosilicate materials

Porous thermal-insulation materials are widely used in building industry, the advantages of which are cheapness and efficiency. Their commercial appearance is also important in their implementation. Porous thermal-insulation materials to prevent sticking can be packaged only after cooling and after the main thermal processes and classification. The process of cooling porous hydroaluminosilicate materials by the method of modeling with the subsequent check on the laboratory equipment with a fluidized bed is investigated in the work. The main thermal process takes place at a temperature of about 300°C. The cooling time of the porous material to a temperature of 20°C, which is about 20 seconds, is calculated, and the need to ensure this time in its classification is indicated. This model allows you to determine with sufficient accuracy the cooling time for particles of different diameters and temperatures. The process of cooling the obtained thermal insulation material in the production technology occurs simultaneously with its hydrodynamic classification in the cascade classifier of the fluidized bed. It is important to determine the required cooling time of the spherical hydroaluminosilicate material to temperatures close to 20°C and to ensure the presence of particles in the apparatus during this time. Comparison of experimental data with the results of the mathematical model shows the results with an error of 10%. There is a slight increase in the minimum residence time of a single granule obtained experimentally compared with the calculated.

RANCANG BANGUN APLIKASI NEW NORMAL COVID-19 DETEKSI PENGGUNAAN MASKER MENGGUNAKAN HAAR CASCADE CLASSIFIER

During the COVID-19 pandemic, when in public places, it is required to apply the 4M health protocol, namely wearing masks, washing hands, maintaining distance, and avoiding crowds. In its implementation, there are officers who always maintain and remind people not to violate health protocols. Like remembering to wear a mask. The mask detection application is made as a computerized surveillance system that can store images of violations of the use of masks and provide warning sounds. Observations, discussions and literature studies are sources of data in this empirical research. Using Python as a programming language assisted with OpenCV for image processing. After passing through the 4 stages of Waterfall, namely Analysis, Design, Manufacturing and Development and Testing, an application is produced where the Raspberry Pi is a processing tool and images are captured from the camera module with a resolution of 1080x1024 px. This application can detect the use of masks with an accuracy of 90.5% using the Machine Learning Haar Cascade Classifier method. Where the condition of the face is a maximum of 30 degrees turned to the side and looked up