Deep Learning Based Smart Security and Surveillance System / (Record no. 611822)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 01889nam a22001697a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | NUST |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 621.382,YOU |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Younis, Hamna |
| 9 (RLIN) | 126074 |
| 245 ## - TITLE STATEMENT | |
| Title | Deep Learning Based Smart Security and Surveillance System / |
| Statement of responsibility, etc. | NC Hamna Younis, NC Muhammad Awais, NC Kanwal Mehreen, PC Jamshaid Ahmad Khan. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | MCS, NUST |
| Name of publisher, distributor, etc. | Rawalpindi |
| Date of publication, distribution, etc. | 2024 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 81 p |
| 505 ## - FORMATTED CONTENTS NOTE | |
| Formatted contents note | 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. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | UG EE Project |
| 9 (RLIN) | 118090 |
| 651 ## - SUBJECT ADDED ENTRY--GEOGRAPHIC NAME | |
| Geographic name | BEE-57 |
| 9 (RLIN) | 125983 |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Supervisor Dr. Yasir Awais Butt |
| 9 (RLIN) | 126075 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | |
| Koha item type | Project Report |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Permanent Location | Current Location | Shelving location | Date acquired | Total Checkouts | Full call number | Barcode | Date last seen | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Military College of Signals (MCS) | Military College of Signals (MCS) | General Stacks | 09/25/2024 | 621.382,YOU | MCSPTC-476 | 09/25/2024 | 09/25/2024 | Project Report |