Anurag Sawant
2022
This web application utilizes computer vision to detect whether a person is wearing a mask. If the app detects the absence of a mask, it triggers an alert mechanism
Spycrop is a web application that utilizes computer vision to detect whether a person is wearing a mask. It uses machine learning models to analyze images and identify individuals without masks. If the application detects the absence of a mask, it triggers an alert mechanism, notifying the user and relevant authorities. SpyCrop is designed to be fast, accurate, and user-friendly, with a clean and intuitive interface.
The COVID-19 pandemic has highlighted the importance of wearing masks in public spaces. However, monitoring mask compliance can be challenging, especially in high-traffic areas like airports, hospitals, and schools.
Spycrop uses computer vision and machine learning to detect individuals without masks, helping organizations monitor mask compliance and enforce safety protocols. By providing real-time alerts and notifications, the application helps prevent the spread of COVID-19 and other infectious diseases. It also provides attendance tracking based on facial recognition to track attendance and mask compliance for employees, students, and visitors.
Identify individuals without masks using computer vision and machine learning models.
Trigger alerts and notifications when the application detects the absence of a mask.
Monitor mask compliance in real time and generate reports for analysis.
Track attendance and mask compliance for employees, students, and visitors by facial recognition.
Last Updated on 28th September, 2025, 18:26 PM IST