ASSESSMENT AND MONITORING OF ATHLETES' PHYSICAL FITNESS BASED ON ARTIFICIAL INTELLIGENCE

This scientific paper investigates the application of Artificial Intelligence (AI) and Machine Learning (ML) technologies in evaluating and monitoring athletes' physical fitness, optimizing training loads, and predicting injury risks in real-time. The study explores multimodal data integration strategies from computer vision systems, wearable sensors, and IoT devices. Deep learning architectures, specifically Convolutional Neural Networks (CNNs) and Long Short-Term Memory networks (LSTMs), are evaluated for biomechanical posture recognition and physiological workload assessment. Practical implementation workflows and future directions for smart sports analytics are discussed.