NUST Institutions Library Catalogue

As security concerns climb alongside rapid technological advancements, innovative surveillance solutions are becoming increasingly vital. This project dives into the design and deployment of a Deep Learning-powered Smart Security and Surveillance System, aiming to provide efficient monitoring and proactive threat detection. The system boasts a robust wireless network thanks to the LoRa protocol, enabling seamless connections across diverse environments. This enhanced connectivity significantly improves the chances of early threat detection within a protected area. The system leverages various sensors like PIR detectors, microwave sensors, and magnetometers to pick up on potential threats before they escalate. Furthermore, Wi-Fi modules ensure critical information is processed promptly, eliminating delays that could hinder response times. PTZ cameras with operator control offer a wider viewing radius and improved surveillance capabilities, empowering operators to maintain a watchful eye over a larger area. To make this system even more user-friendly, a special Graphical User Interface (GUI) is built using Flutter, allowing for real-time monitoring and supervision. This project will delve into the system's components, its construction and operation, and ultimately assess its effectiveness in bolstering security and surveillance efforts.