Intelligent Farmhouse Attendance Monitoring System Using Deep Learning
J. Jeba Johannah, S. Tephillah · 2023
In large farmhouses, attendance is recorded by the supervisor and the record is maintained manually. It results in an increase in time and manpower. It also suffers from human error, and there may be the possibility of missing paper before reaching the owner of the farm for future reference. Deep learning is one of the most popular and emerging technologies in the digital world today. It has become extraordinary in recent years owing to its many applications. In this proposed work, the face recognition technique is used to design a prototype that handles attendance records automatically without any human intervention. To track the workers' attendance in this project, an intelligent attendance tracking system is created by identifying their facial features using efficient algorithms. It also sends the message automatically to the owner of the farmhouse and mails the report to the officers involved in the administration of the farmhouse. In addition to these features, it is also designed with live monitoring facilities. Also the simulation results prove an increase of 1% to 5% in accuracy of identification with different data sets. This low-cost, robust, and portable technology is also very effective and steady, saving the owners' valuable time.