As the human race continues to expand and strengthen, new variations of viruses and diseases also become more prominent; it is imperative to build on existing technology and expand on current knowledge to protect humanity from these life-threatening viruses.
Recently, the world has witnessed a global pandemic caused by the COVID-19 virus. To limit the spread of this virus, enforcing specific measures such as social distancing, hand hygiene and using personal protective equipment (PPE) is highly advised. Face masks are one of the most effective ways to reduce the spread of the COVID-19 virus, and as a result, countries have mandated the use of face masks in many public areas (WHO 2020). However, ensuring compliance with this mandate has proven challenging, ultimately making developing a face mask detection system necessary.
When I began this project, I had a broad understanding of the need for face masks and the basics of neural networks. To connect the need for face masks to computer vision, I focused on how advanced technology can enforce mask-wearing, particularly in hospital and care home environments. To develop my face mask detection system proof of concept, I studied other detection systems and gained insight into what was needed for a successful design.