Automated Email and SMS Notification System for Unauthorized Entry using Yolov9

Security breaches present a serious risk in a variety of settings, thus strong detection and alerting systems are required to efficiently reduce risks. This study proposes a novel way for developing an Automated Email and SMS Notification System customized for unauthorized entrance detection using the YOLOv9 object identification model. By utilizing the capabilities of YOLOv9, the system quickly detects unwanted people or things in the monitored areas and sends out automatic emails and SMS notifications to selected stakeholders. Our technology improves security measures by combining cutting-edge machine learning techniques with communication technologies. This allows for the rapid response to possible attacks through real-time notifications. Test results show that the system is effective in identifying unwanted entries and reducing false positives, strengthening security protocols in many contexts.