Real Time Security Monitoring with ML And Sending Alerts

Real Time Security Monitoring with ML And Sending Alerts

Mr. Karthiban R1, Ms. Monika P2, Ms. B M Sahana3, Ms. Sandhiya C4, Ms. Sandhiya S5

1Assistant Professor, Computer Science Engineering (Cyber Security), Sri Shakthi Institute and Engineering and Technology, Coimbatore, India

2IInd Year Student, Computer Science Engineering (Cyber Security), Sri Shakthi Institute and Engineering and Technology, Coimbatore, India

3IInd Year Student, Computer Science Engineering (Cyber Security), Sri Shakthi Institute and Engineering and Technology, Coimbatore, India

4IInd Year Student, Computer Science Engineering (Cyber Security), Sri Shakthi Institute and Engineering and Technology, Coimbatore, India

5IInd Year Student, Computer Science Engineering (Cyber Security), Sri Shakthi Institute and Engineering and Technology, Coimbatore, India

*Mr. Karthiban R

E-Mail Id: rkarthiban@siet.ac.in

ABSTRACT

In the era of increasing security challenges, traditional surveillance systems are often limited by manual monitoring and delayed response. This project, AlertCam, presents a smart security solution that leverages machine learning to enable real-time monitoring and automated threat detection. By using live video feeds and intelligent algorithms such as facial recognition and motion analysis, the system can accurately identify unauthorized access or suspicious behavior. Upon detection, it immediately sends alerts through SMS or cloud-based notifications to ensure swift action. AlertCam is a scalable and efficient security system suitable for campuses, homes, and workplaces, aiming to enhance safety through automation and intelligent decision-making.

Keywords: Real-time Monitoring, AlertCam, Machine Learning, Facial Recognition, Automated Alert, Smart campus security.