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The study aims the development of a wearable device to combat the onslaughtof covid-19. Likewise, to enhance the regular face shield available in themarket. Furthermore, to raise awareness of the health and safety protocolsinitiated by the government and its affiliates in the enforcement of socialdistancing with the integration of computer vision algorithms. The wearabledevice was composed of various hardware and software components such as atransparent polycarbonate face shield, microprocessor, sensors, camera,thin-film transistor on-screen display, jumper wires, power bank, and pythonprogramming language. The algorithm incorporated in the study was objectdetection under computer vision machine learning. The front camera with OpenCVtechnology determines the distance of a person in front of the user. UtilizingTensorFlow, the target object identifies and detects the image or live feed toget its bounding boxes. The focal length lens requires the determination of thedistance from the camera to the target object. To get the focal length,multiply the pixel width by the known distance and divide it by the known width(Rosebrock, 2020). The deployment of unit testing ensures that the parametersare valid in terms of design and specifications.

Smart Face Shield: A Sensor-Based Wearable Face Shield Utilizing Computer Vision Algorithms