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  • Deep Learning

AI-Based Elderly Fall Detection & Emergency Alert System

A computer vision-based safety system that detects falls from video feeds and triggers real-time emergency alerts.

Overview

YOLOv8 posture analysis detects fall events from video or image frames, sounds an alarm immediately, and dispatches SMS and automatic voice-call alerts through Twilio or Fast2SMS — logging every event with timestamp and status for later review.

Problem Statement

For an elderly person living alone, the danger after a fall is the time spent on the floor before anyone finds out. Wearable buttons only work if the wearer is conscious and wearing them.

Proposed Solution

Detect the fall from the existing camera feed rather than from a worn device, and escalate automatically through alarm, SMS and voice call without requiring any action from the person who fell.

Key Features

  • YOLOv8-Based Posture Analysis

    Detects fall events from human activity video/image frames.

  • Automated Alarm Trigger

    Sounds an alert immediately upon fall detection.

  • SMS & Voice Call Alerts

    Twilio/Fast2SMS-based emergency notification and automatic emergency calling.

  • Event History Logging

    Stores fall events with timestamp and status for review.

Technologies Used

Computer Vision

  • YOLOv8
  • OpenCV
  • Ultralytics
  • PyTorch

Alerting

  • Twilio
  • Fast2SMS
  • Voice call API

Application

  • Flask
  • SQLite
  • WebSockets

Project Workflow

  1. 1

    Video capture

    A camera feed is processed frame by frame.

  2. 2

    Posture analysis

    YOLOv8 identifies human posture and fall events.

  3. 3

    Alarm

    An audible alert fires immediately on detection.

  4. 4

    Escalation

    SMS and automated voice calls reach caregivers.

  5. 5

    Logging

    The event is stored with timestamp and status.

What You'll Receive

  • Complete, runnable source code with folder structure
  • Project report and technical documentation
  • Ready-to-present PPT content
  • Setup and installation walkthrough
  • Line-by-line project explanation session
  • Viva question bank with answers
  • Bug fixing and troubleshooting help
  • Post-delivery support after submission

Frequently Asked Questions

How much does this project cost?

Every project is quoted individually, because the price depends on the modules you need, your technology stack, your college's format and your deadline. Send us the project name on WhatsApp and we'll share a quote the same day.

Can the project be customised to my college requirements?

Yes. Share your guide's requirements, preferred technology stack and abstract format, and we adapt the modules, dataset or UI accordingly.

Will I be able to explain this project during my viva?

That is the point of the explanation session. We walk you through the architecture, every module, the flow of data and the results, and hand over a viva question bank with answers.

What if the project does not run on my laptop?

We help you with setup end to end — dependencies, environment, database and configuration — over chat or a call until it runs on your machine.

Do I get support after submission?

Yes. Post-delivery support is included, so you can come back for fixes, doubts or demo help even after the project is delivered.

Want This Project?

Get complete source code, documentation, PPT, explanation, and support.

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