Fahad Ahmad Siddiqui · imagine-talent

Email

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Phone

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GitHub

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Academic

Program

BSCS

CGPA

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Year

2022

Education

SEECS

Address

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DOB

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Career

Current role

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Target role

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Skills

Java, Android Studio, Java Spring Suite 4.0, Firebase Database, SQLite, MERN Stack

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.

Accident Detection and Emergency Response System

Almost everyone carries their smartphone with them while driving, and smartphones nowadays
have a lot of sensors present inside them.
Our system makes use of these sensors to detect an accident, and inform relevant authorities about
the exact location of the accident.
The user will sign-up and provide their personal details, along with emergency contacts.
During the trip in case of an accident, it will be detected using the readings on the Accelerometer,
Gyroscope and Microphone present inside the smartphone.
Once an accident has been confirmed, the concerned authorities (helplines and emergency
contacts) will be sent an alert along with the location.
The ambulance portal will be shown the shortest path to the location.
All the people using this app in a nearby radius will be notified of the accident and its location.
The Admin Panel will be able to oversee real-time accidents, along with a history of events.
Statistics will be saved, showing the number of events taken place in particular areas in a given time
selected by Admin user.
The Admin will have access to user’s information to make contact if needed.

Technology Used:

Java, Android Studio, Java Spring Suite 4.0,

Firebase Database, SQLite, MERN Stack

Supervisor Name:

Mr. Bilal Khalid Dar

Group Members:
Fahad Ahmad Siddiqui (I18 – 0590)

Muhammad Saad Minhas (I18 – 0691)

Muntahim Hussain Khan (i18 – 0707)

AI enrichment

Fahad Ahmad Siddiqui is a BSCS graduate who contributed to a group project developing an Accident Detection and Emergency Response System. The application utilized smartphone sensors to detect accidents and notify authorities and nearby users via a MERN stack and Java-based backend.

Skills (AI)

["Java", "Android Studio", "Spring Suite 4.0", "Firebase Database", "SQLite", "MERN Stack", "Mobile Application Development"]

Status: ai_done

Provenance

Source file: Graduate Directory FAST School of Computing 2022 Final Version (07-06-2022).pdf
From job #25 page 211
Created: 1778149999