The patent titled, System and Method for Detecting a Face Mask on the Face of a Person with application number: 562697 by Assistant Professor, Dr Anirban Ghosh and his students from the department Ms J Keerthi Tanvitha, Ms K Poojitha, Ms T Pallavi Sri, has come up with a novel idea that focuses on developing a system and method for detecting face masks on individuals before they enter a gated space. Their research uses image capture, face detection, mask-wearing verification, and temperature sensing to ensure compliance with health and safety protocols.
Brief Abstract
The research focuses on developing a system and method for detecting face masks on individuals before they enter a gated space. The system integrates image capture, face detection, mask-wearing verification, and temperature sensing to ensure compliance with health and safety protocols. It utilizes artificial intelligence and sensor technology to determine whether a person is wearing a mask correctly and allows or denies entry based on preset criteria. The system also includes an aliveness detection module to ensure that a real person is being scanned and prevents tampering or spoofing.
Explanation in Layperson’s Terms
Imagine you are entering a building where you must wear a mask and have your temperature checked. Instead of a security guard manually checking each person, this system does it automatically and without contact.
Here’s how it works:
- A camera captures your face as you approach the entrance.
- A software program checks if you are wearing a mask correctly (covering your nose and mouth).
- A temperature sensor scans your body temperature.
- If your mask is worn properly and your temperature is normal, the door opens and you can enter.
- If you are not wearing a mask correctly or have a high temperature, an alert is triggered, and entry is denied.
This system is especially useful in hospitals, offices, schools, airports, and malls to ensure safety without requiring human intervention.
Practical and Social Implications
This system plays a crucial role in public health by ensuring compliance with mask-wearing protocols, especially in high-traffic areas like hospitals, offices, and airports. By automating the detection process, it reduces reliance on manual checks, minimizing human error and lowering exposure risks for security personnel. Additionally, it streamlines entry procedures, preventing congestion at access points. While the technology enhances safety, it also raises concerns about privacy and data security, making it essential to implement ethical safeguards. Beyond COVID-19, this system can be adapted for future health crises requiring similar preventive measures.
Future Research Plans
Future improvements will focus on enhancing accuracy using AI to recognize different mask types and improve real-time detection. Expanding the system to include biometric health screening, such as cough detection and respiratory analysis, could make it a broader health monitoring tool. Integration with facial recognition and automated access systems will further strengthen security applications. Additionally, optimizing the system with edge computing will enable faster, more efficient processing. As the need for contactless health monitoring grows, refining this technology will ensure its continued relevance beyond COVID-19.