Fast and High-Precision Human Fall Detection Using Improved YOLOv8 Model
Objective
The main objectives of this project are to detect human falls quickly and accurately using an improved YOLOv8 model optimized for real-time performance. It focuses on recognizing fall events from video streams with high precision while minimizing false positives.This system enhances safety monitoring, especially for the elderly and patients, enabling timely alerts and emergency response.
Abstract
This project presents a real-time human fall detection system using Raspberry Pi, USB web camera, LCD display, GPS module, buzzer, and the YOLOv8 deep learning model. The camera continuously captures video frames, and the YOLOv8 model detects human falls by analyzing body posture and movement. When a fall is detected, the buzzer alert is activated, and a warning message is displayed on the LCD screen. The GPS module retrieves the user's location, and an automated email containing the fall alert and GPS coordinates is sent to caregivers or emergency contacts. The proposed system provides a fast, accurate, and low-cost solution for improving safety and emergency response in healthcare and elderly monitoring applications.
Keywords: YOLOv8, Human Fall Detection, Raspberry Pi, GPS Tracking, Smart Healthcare.
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
Specifications
Hardware components:
- Raspberry pi
- LCD
- Web camera
- GPS
- Buzzer
- connectors-10
Software requirements:
- Raspbian OS
- Python IDLE
Learning Outcomes
- Raspberry pi pin diagram and architecture
- How to install Raspberrypi / setup software
- Setting up and installation procedure for Raspberrypi
- Introduction to Raspberrypi environment / development setup
- Basic programming in Raspberrypi (Python)
- Basics of Embedded programming using Raspberrypi
- Basics of IoT platforms
- Working of power supply
- About Project Development Life Cycle:
- Planning and Requirement Gathering (software, tools, hardware components, etc.)
- Schematic preparation
- Code development and debugging
- Hardware development and debugging
- Development of the project and output testing
- Practical exposure to:
- Hardware and software tools
- Solution providing for real-time problems
- Working with team/individual
- Work on creative ideas
- Skills developed:
- Project development skills
- Problem analyzing skills
- Problem solving skills
- Creativity and imaginative skills
- Programming skills
- Deployment
- Testing skills
- Debugging skills
- Project presentation skills
- Thesis writing skills
Paper Publishing
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6-2-85/B, Old Maternity Hospital Road, Thyagaraja Nagar, Tirupati, Andhra Pradesh – 517501
+91 9030333433
+91 9393939065
0877-2261612
Disclaimer - Takeoff Edu Group Projects are not associated or affiliated with IEEE in any way. The IEEE Projects mentioned here are mentioned in the context of student projects, whose ideas are derived from IEEE publications, not projects of or by IEEE.
