Biomechanics-inspired utilization 5G multimedia for intelligent title recommendations in low carbon smart libraries through collaborative filtering algorithms

With the popularization of e-readers, electronic reading rooms, digital libraries, and other new ways of reading in libraries and society, libraries have also entered a new stage of development because of “low-carbon” construction. The low-carbon development of intelligent libraries reduces the application of traditional literature carriers, increases the popularity and application of modern equipment, makes the replacement of paper materials, and reduces its own energy consumption. To achieve personalized recommendations in the lending system, this paper, inspired by biomechanical concepts, constructs a tree intelligent recommendation system via a collaborative filtering algorithm. This system functions like a neural network in a biological system, processing and analyzing data to make informed decisions. By verifying the system with actual borrowing data of students, it proves effective, much like how a biomechanical adaptation is tested and validated in nature. This approach offers a valuable reference for intelligent book management in universities, aligning library operations with the principles of efficient resource utilization and adaptation seen in the biomechanical world. book management in universities. In addition to these advancements, integrating biomechanics into the design and operation of smart libraries can enhance user experience and engagement. Understanding the biomechanics of reading—such as posture, hand movements, and eye tracking—can inform the development of ergonomic reading spaces and devices. For instance, optimizing seating arrangements and reading environments based on biomechanical principles can reduce physical strain and improve comfort for users. Moreover, incorporating biomechanical feedback into the recommendation system could personalize user interactions further. By analyzing how different users engage with reading materials—considering factors like reading speed, preferred formats, and physical interactions with devices—libraries can refine their recommendation algorithms. This approach not only enhances the effectiveness of title recommendations but also promotes a healthier reading experience, aligning with the low-carbon goals of reducing physical strain and energy consumption associated with inefficient reading practices.