Cloud Based Attendance Monitoring System Using MobileNet SSD

In order to improve the accuracy of attendance tracking in institutional and workplace settings, a dual authentication system is intended to be implemented. The technology ensures secure and accurate attendance recording by combining facial recognition and One-Time Password (OTP) verification. Users are first verified using facial recognition, and after a successful verification they are given a special OTP for extra security. A new system for detecting and tracking objects in real time using multiple pan-tilt cameras on unmanned platforms is proposed. This system utilizes the MobileNet-SSD algorithm, which enables real time, GPU- free human object identification on mobile platforms. By precisely distinguishing and following articles, the framework can work on the productivity and viability of different applications, like reconnaissance, observing, and search and salvage activities. Moreover, the data storage is done in cloud to enhance the access of images more effectively and efficiently. Furthermore, the framework can be utilized to upgrade participation records by decreasing participation extortion, advancing responsibility in various settings.