This model is designed to help reduce slip-and-fall accidents in public places, such as shopping centres, airports, and other high-traffic areas. It enables timely intervention and potentially life-saving measures by detecting and alerting to slip and fall incidents in real-time.
The machine learning algorithms are fine-tuned on a comprehensive dataset of slip and fall incidents, ensuring the model provides reliable and accurate predictions in various environments and conditions. A slip-and-fall detection model is an essential tool for improving safety in public places.
It is essential to note that this slip and fall detection model is not designed to replace human monitoring or response. Instead, it is intended to complement human efforts and provide an extra layer of safety in public spaces. This system should not be used as a replacement for human surveillance, and its predictions should always be verified by human personnel.