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Muhammad Abdullah

FAST · 2021 · 17I - 0038
Email
Phone
LinkedIn
GitHub

Academic

Program
BSCS
CGPA
Year
2021
Education
SEECS
Address
DOB

Career

Current role
Target role
Skills
Pytorch, OpenCV, Python 3, Django, Android Studio Java

Verbatim text

The exact text the LLM saw on the page (or the booklet text from the old import). This is what powers semantic search.
Threatify – Threat Detection Using CCTV 
Security is a huge concern in the modern world, since crime is increasing. To prevent crime, CCTVs 
are installed everywhere along with CCTV operators to monitor the screens. This, however, isn’t 
feasible at homes & shops because we cannot have an operator watching the footage 24/7. Having 
CCTVs but still being unable to report crime either not viewing it at that instance or being under the 
influence of gunmen could cause lots of damage. 
We plan to develop a deep learning-based system which is capable of detecting threats the 
moment it occurs and report the crime to the corresponding authorities as fast as possible. This 
could result in minimizing the response time resulting in less damage, such techniques would have 
high demand in this digital world. 
Features include: 
● Threat detection using CCTV feed. 
● Threat classification. (Arson & Explosion, Fighting, Gun-Event) 
● Web application. 
● Android Mobile App 
Notifying and sending location to the client and authorities about the threat.

AI enrichment

Muhammad Abdullah holds a BSCS degree and has developed a deep learning-based threat detection system utilizing CCTV feeds for real-time crime monitoring. The project includes features for threat classification, such as arson and fighting, alongside web and Android mobile applications for instant notifications.
Skills (AI)
["Deep Learning", "Computer Vision", "Threat Detection", "Web Application Development", "Android Development", "CCTV Integration"]
Status: ai_done
Provenance
Source file: Graduate Directory FAST School of Computing 2021 (1st Final) (1).pdf
From job #24 page 238
Created: 1778170890