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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.

In this paper, achieving minimum energy consumption in the copper electrowinning process is taken as the research objective. In the traditional production process, sulfate ion concentration, copper ion concentration, and current density are carried out according to the empirical value, which cannot ensure the energy consumption reaching the optimal level. Therefore, this paper proposes a BP neural network model to optimize energy consumption according to the relationship between current density, sulfate ion concentration, copper ion concentration, electrolytic tank voltage, and current efficiency, and the established BP neural network model is trained by using real data from the enterprise. The simulation results show that there is a definite error between the predicted electrolytic tank voltage and current efficiency and corresponding to predict electrolytic tank voltage and current efficiency measured at the production site. The BP neural network improved by GA is proposed to further improve the prediction accuracy of the BP neural network. Simulation results indicate that the prediction error of electrolytic tank voltage and current efficiency is greatly reduced that meets the accuracy requirements, and then the minimum energy consumption can be calculated. On the premise of guaranteeing the quality of copper electrowinning, the current density, sulfate ion concentration, and copper ion concentration corresponding to the minimum energy consumption accurately predicted by this method can be respectively adjusted in real time, which realizes the optimization of energy consumption in the process of copper electrowinning under the background of low carbon and environmental protection.

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In order to better track the planned trajectory of Delta high-speed parallel robot, this paper proposes a dynamics control strategy for Delta high-speed parallel robots based on the linear active disturbance rejection control (LADRC) strategy which realizes decoupling control through observing and compensating the coupling and internal and external disturbances between the three joints. Firstly, the structure and dynamics model of the Delta high-speed parallel robot are analyzed, respectively. Secondly, the control scheme of the Delta high-speed parallel robot dynamic LADRC strategy is constructed, and then, the system stability is analyzed. Taking a representative 8-shaped space helical variance trajectory as a given input of the system and a triangular wave as an external disturbance as given disturbance input of the system, simulations are carried out to demonstrate the effectiveness of the proposed LADRC strategy; results indicate that the system with the LADRC strategy has a good quick and precise real-time trajectory tracking and strong robustness.