Intelligent Fall Detection and Alert System for the Elderly Using Yolov8 and Cloud-Based Analytics

As people age, the frequency and impact of falls among the elderly continue to escalate, presenting significant health and mobility risks. Efficient detection and immediate response are crucial in reducing the severity of injuries and potentially life-threatening complications associated with such falls. This research study introduces a real-time alert system for the elderly by utlilizing the cutting-edge capabilities of YOLO v8, the latest iteration in the You Only Look Once series of models known for its high speed and accuracy in object detection tasks. The system is designed to operate with inputs from a variety of sources, including direct video feeds, RTSP streams from existing CCTV infrastructure, static images, and data from wearable sensors. This multi-source approach ensures that the system is adaptable for use in a wide range of environments, from personal residences to care facilities, providing continuous monitoring with enhanced accuracy. Upon the detection of a fall, the system immediately activates an alert protocol via Amazon Web Services (AWS) Simple Notification Service (SNS), ensuring that caregivers or family members are promptly notified to respond swiftly to the incident. This data-driven approach not only enhances the accuracy and responsiveness of the system over time but also aids caregivers and healthcare providers in understanding fall patterns and potential risk factors associated with specific environments or individuals, effectively addressing the critical challenges in elderly fall prevention and care.