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Amna Arshad

FAST · 2022 · i18 - 0563

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Phone

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GitHub

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Academic

Program

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CGPA

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Year

2022

Education

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Address

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DOB

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Career

Current role

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Target role

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Skills

Python, Java, Xml, Android Studio, Visual Studio Code, Jupyter Notebook, Raspberry pi, YOLOV5, CNN

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.

Route and Safety Awareness app is being made, whilst keeping the perspective of inexperienced drivers and their safety. There is one view of the app - Driver View - the view is for the drivers to use the features provided by our app to view the detected traffic signboard, check the history of all passed traffic signs, and get the real-time voice alert whenever the signboard is detected. Traffic signboards include 42 signs i.e. warning signs, speed limit signs, and stop signs. Real-time signboard detection is performed using the You Only Look Once i.e. YOLOV5 algorithm and classification using Convolutional Neural Network i.e. CNN. 
Features include:  
- Capture traffic signboards in real-time 
- Detect traffic signboards: including warning signs, speed limit signs, and stop sign 
- Classify traffic signboards: including warning signs, speed limit signs, and stop sign 
- Generate voice alert whenever a  signboard is detected 
- Display the history of all passed signboards to the driver 
 
 
 
 
 
 
 
 
 
Technology Used: 
Python, Java, Xml,  Android Studio, Visual Studio Code,  
Jupyter Notebook, Raspberry pi  
Supervisor Name: 
Mr. Umair Arshad 
Group Members:   
Amna Arshad (i18 - 0563) 
Iram Bashir (i18 - 0456)

AI enrichment

Amna Arshad is a student who developed a Route and Safety Awareness app for inexperienced drivers using Android and Raspberry Pi. The project implements real-time traffic sign detection and classification using YOLOv5 and CNN algorithms to provide voice alerts and history tracking.

Skills (AI)

["Python", "Java", "XML", "Android Studio", "YOLOv5", "CNN", "Raspberry Pi", "Jupyter Notebook", "Computer Vision"]

Status: ai_done

Provenance

Source file: Graduate Directory FAST School of Computing 2022 Final Version (07-06-2022).pdf
From job #25 page 273
Created: 1778170963