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Energy consumption is important to consume less power, reducing toxic fumes released by plants, preserving natural resources, and protecting ecosystems against damage. The challenging characteristics in energy supply include lack of renewable energy adoption, and policy and energy management are 0considered essential factors. An artificial intelligent building with a multi-energy planning method (AIBMEM) has been proposed to design multi-energy systems to achieve the best policy and energy management techniques. The intelligent construction problem with multi-energy is framed as a predictive energy model to minimize the overall utilization of energy levels. The normal distribution with the artificial intelligent model is introduced to solve the problem of renewable energy. The experimental results based on reliability, effectiveness, preservation, energy consumption, and control systems show that the suggested model is better than existing models, producing good performance analysis results.

Smart wearable is expected to give the elderly more peace of mind and experience in a comfortable home environment. This not only satisfies their desire to live relatively independently, but also avoids the waste of resources caused by the lack of timely detection and feedback of aging and health problems, and contributes to the sustainable development of society. In order to meet the current demand for high development of smart wearable products for the elderly at home, and to lay out the limited design resources on the key design factors so as to enhance the consumer experience, a design element system is constructed from a sustainable perspective. The textual measures of academic literature and product evaluations are used to analyze the relevant theoretical foundations and the current state of the market category products. Based on this, the user’s needs at the instinctive, behavioral and reflective levels are captured through expert panel interviews, and the initial requirement importance is calculated. The QFD quality house model is used to translate the needs into design factors and score them based on the relationship degree of the needs, and finally construct the design factor system of smart wearable for the elderly at home in a sustainable perspective.

The aim of this chapter is to apply Systems Theory – Systems Science – to Ontologies. The subject matter is given a modern context. The chapter contains a brief description of Systems Theory, which today has become what is known as Systems Science. Subsequently, Systems Science and systems are defined, as well as the links that are responsible for the correct function of a system, known as vectors. Ontologies will be discussed, along with their various definitions and characteristics. This chapter will be based on the premise that Ontology is a complex, conceptual, empirical classification system. An Ontology is structured like a system in which the principal and primary node is the word. A summary will be made of how this system should be constructed, concentrating on the vectors that help the system function. This will be illustrated with an example.

Firstly, the theory and techniques of the CET4 Diagnostic Practice System were analyzed. Secondly, the architecture and development mode of the system has been determined and the main functional modules has been designed detailedly. Last, the implementation of system architecture has been elaborated on the basis of the development environment and tools. This system is a kind of deep practice and innovation on CET-4, aimed at learners can receive personalized learning guidance and targeted diagnostic evaluation according to their characteristics, thus improving the standard of English learners and learning ability, so it has a wide range of prospect and practical value.