Poor posture has become a common problem in our lives today and causes many health problems such as back pain, headaches, and fatigue. Solving this problem requires new solutions that combine technology and ergonomic principles. Our research paper focuses on the human body to explore the use of revolutionary technology, like YOLOv5 and YOLOv8, to improve body awareness. This study uses personal data to demonstrate and evaluate the effectiveness of these models to accurately identify different individuals. This research aims to overcome the limitations of small data and improve the general knowledge of resources on guidance algorithms by using transfer learning from pretrained models on big data. Research focuses on detecting unhealthy behaviors such as slouching, asymmetrical lifting of heavy objects, and inappropriate use of mobile phones by using computer vision algorithms. By analyzing these behaviors in real time, people can get instant feedback, raise awareness, and implement effective treatments to reduce health problems. The results of this study can contribute to the development of cognitive navigation that can be integrated into modern devices such as smartphones and computers to provide users with employment promotion and health promotion. Finally, the integration of adaptive learning with physical awareness has the potential to transform physical awareness today and improve spine health throughout life.