Intelligent visionbased patient surveillance for realtime abnormal behaviour detection in healthcare environments
Objective
The objective of the Fall Detection System using Raspberry Pi is to develop an intelligent monitoring system that detects human falls and abnormal behaviors in real time using YOLOv8 and a web camera. The system provides immediate alerts through a buzzer, LCD display, and GSM module to enhance safety and support emergency response in elderly care and security applications.
Abstract
This project introduces a Intelligent vision based patient surveillance for realtime abnormal behaviour detection in healthcare environments. Utilizing a Raspberry Pi as the core processing unit, the system employs a USB web camera to capture real-time video, where the YOLO (You Only Look Once) algorithm is implemented for fast and efficient detection of unusual activities such as falls or lack of movement. Upon detecting an abnormal event, the system activates a buzzer for immediate alert, displays a message on the LCD, and sends an SMS notification through the GSM module to caregivers or family members. This solution provides a low-cost, real-time, and non-invasive method for elderly care, offering continuous safety monitoring in residential and assisted living settings.
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
Block Diagram
Specifications
Hardware Components
- Raspberry Pi 3
- Micro SD Card
- USB Web Camera
- GSM Module
- Heartbeat Sensor
- Dallas Temperature Sensor
- MCP3008 ADC Module
- LCD Display
- Buzzer
- 5V Power Supply
- 12V 1A Adapter
- Connectors
Software Components
- Python
- Raspbian OS
Learning Outcomes
- Understand Raspberry Pi architecture and GPIO configuration
- Learn how to install and configure Raspbian OS and required Python libraries
- Interface analog sensors with Raspberry Pi using MCP3008 ADC
- Implement image classification using Artificial Neural Networks
- Develop real-time skin analysis using USB camera input
- Build automated health screening systems with display and alert features
- Integrate temperature and heartbeat monitoring in diagnostic systems
- Analyze and interpret classification output for healthcare applications
- About Project Development Life Cycle:
- Planning and Requirement Gathering (software’s, 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.
- Project development Skills:
- Problem analyzing skills
- Problem solving skills
- Creativity and imaginary skills
- Programming skills
- Deployment
- Testing skills
- Debugging skills
- Project presentation skills
Paper Publishing
Request Call Back
Would you like to receive a free callback now?
Choose the best time for callback:
Leave your message and we will contact you as soon as possible
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.
