Automated Attendance Monitoring System for Cattle through CCTV.
Shabina Modi
Abstract
In a period of rapid technological advancement, the traditional methods of taking attendance of cattle after coming from grazing yard is done by normal counting as this have become inefficient and outdated. To overcome this issue, an Automatic Attendance Monitoring System (AAMS) using Closed-Circuit Television (CCTV) technology has been introduced as a solution. These abstracts highlight its key features and benefits. The Automated Attendance Monitoring System through CCTV uses the power of computer vision and machine learning (ML) for attendance monitoring. Using CCTV cameras in big dairy farms cows & buffalos are monitored. This can be also been implemented in grazing yards systems to analyse unique identification of data. That data will be cross-analysed using the database to record the attendance by colour, breed, and most importantly RFID tag. This system analyses accuracy the in-out time of cattle’s using this recognition system. In training data, with multiple images of individual cow or buffalo from all angles & features are captured. Up to 30000-50000 images will be generated with supporting to that closed circuit images of all RFID implanted at ears of cattle. If the image captured by CCTV and the images in the database match, then attendance will be done and the report submitted. To build this system, the Python language was used. For developing systems, software is required, such as PyCharm or Spyder. We also need some libraries, like the OpenCV library and the Cattle Recognition library. The CNN algorithm is used for cattle recognition. Django, HTML, CSS, JavaScript, MySQL, and Bootstrap technologies will be used. In conclusion, the Automatic Attendance Monitoring System through CCTV provides an effective solution for the traditional attendance system. Provides high security and accuracy.