In recent years, with the constant development and integration of Internet technology, Internet of Things technology, and intelligent terminal technology, to make people’s work and life more comfortable and convenient, these new technologies have been more and more widely used in daily home life such as social education, agricultural production, industrial production, medical, and other fields. However, at present, there are still a lot of room for development in the application of new technologies in the medical and health industry. Especially in the context of hospital information construction and medical difficulties, the functions of fixed information points such as traditional nurse stations and doctor stations no longer meet the growing medical needs of people. Therefore, how to introduce these new technologies and design to a practical and low-cost intelligent medical information management system that realizes the convenient management and efficient management of medical personnel has become a top priority. In view of the problems faced by the hospital, this paper proposes an intelligent medical plan based on NB-IoT technology and develops a smart hospital information management system. Test results indicate that patients can easily and conveniently register their appointments through the Android mobile client. Through checking medical records and hospital news updates, medical staff can more easily complete their work. Comparison results of performance variance between the common server and adaptive algorithm web server demonstrate that an adaptive load balancing algorithm can achieve a more accurate allocation of the load. Therefore, the web smart medical information management platform can manage hospitals more comprehensively.

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In this paper, a phase-shifted full-bridge current-doubler synchronous rectifying converter (PSFB-CDSRC) based on IGBT and its control strategies are studied. In the main circuit, a current doubling synchronous rectifying circuit based on IGBT is presented to further reduce the power loss of power devices. Moreover, in the control strategy, in view of the existing researches, the basic BP neural network PID control performance of the rectifying converter still can be further improved. Therefore, this paper combines the quasi-Newton algorithm and traditional GA to propose an improved GA-BP (IGA-BP) neural network to further improve PID control performance. The simulation results demonstrate that the maximum efficiency of 5 V/500 A rectifying converter based on the proposed circuit scheme can reach 94.1%, and the rectifying converter has a good performance of excellent waveform and wide range of load. IGA-BP neural network PID control responds fast and reaches the stable state quickly in comparison with that controlled by the GA-BP neural network control strategy, and the steady-state time can be reduced by 10.5% through using IGA-BP neural network control strategy. This study can provide a valuable guidance and reference, not only in circuit scheme but also in the optimal PID control strategy for design of the high-efficiency DC/DC rectifying converter with higher power in the future.

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