AI and Cloud for Real-Time Evaluation of Sports Injury Severity and Recovery

This research provides a revolutionary artificial intelligence (AI) and cloud-based system for assessing the severity of sports injuries in real time and tracking healing progress. The objective is to develop an AI and Cloud-based system for evaluating sports injuries in real time, providing accurate severity assessment, recovery tracking, and personalised treatment recommendations with powerful Natural Language Processing (NLP) and image analysis algorithms. The proposed method uses modern NLP and deep learning-based image analysis algorithms to process and analyze data from a variety of sources, such as IoT-enabled wearable devices, medical reports, and athlete feedback. NLP is used to extract useful insights from unstructured text, while image analysis finds damage patterns in medical images. By combining these technologies with cloud computing, the system provides a scalable and economical solution for real-time injury assessment, including personalized rehabilitation programs and predictive modelling. AI enables automated, data-driven decision-making, which reduces human error while increasing diagnostic speed and accuracy. Future study will look at the addition of more AI algorithms, expanding the dataset to include more injury kinds, and improving the system's real-time feedback capability. This method aims to transform sports injury care and recovery optimization.