Towards the new normal: A microcontroller-based screening and contact tracing information system aggregated with a web application

Contact tracing is a key point for curbing the transmission of SARS-CoV-2 and reducing COVID-19-associated mortality. In the Philippines, prior entering establishments, individuals are required to have their temperature measurements measured and log their names in contact tracing forms. This study integrates a contact tracing information system and an automated thermal scanner using MLX 90614. The study includes three major components – a database and web server, a web application and an IoT device. The IoT device runs on Raspberry Pi 4B which includes an MLX90614 for thermal measurement and a Rapsberry Pi Camera V2.1 for QR code validation

Vehicle classification through detection and color segmentation of registration plates running on raspberry Pi 3 model B

© BEIESP. Classification of license plates provides useful information regarding the nature of the vehicle, whether it is used for public transport, a privately-owned vehicle, an official vehicle, or a special vehicle. In the Philippines, the registration plates of vehicles are classified by colors. Colors such as red, green blue, black, yellow are used to identify what vehicle classification the plate belongs to. The information is useful to applications in statistics and transport regulation. This paper discusses a convolutional neural network based embedded system that runs on Raspberry Pi 3 Model B. The said system provides a process of classifying vehicles using plate detection using Convolutional Neural Networks and color thresholding of registration plates using the RGB color space. TensorFlow and OpenCV libraries were utilized for the detection and classification