Research On The Design Of Intelligent Products For The Old Based On Household Behavior Prediction

Recent years,with the rapid development of artificial intelligence technology and 5G(fifth generation communication technology),information technology and AI technology have gradually provided service support for various systems in society,and also provided new The idea has gradually become a powerful means to solve the problem of aging society.However,a high degree of intelligence brings a certain convenience to the daily life of the elderly,but also brings a series of negative effects.Therefore,how to measure the "smart scale" of the product so that the intelligent product can better serve the daily life of the elderly Life service has become the focus of attention in the design field today.This project uses behavior prediction as a basic theory to study the behavioral characteristics of the elderly,and through the regularity of them,build a smart product usage model suitable for the life of the elderly.The study takes home behavior prediction as the starting point,uses scene theory and activity theory and other related design theories to build a smart home behavior prediction system for the elderly,draws corresponding design principles and strategies,and conducts a series of design practices.The project firstly classifies the characteristics of the elderly and their home behaviors.It summarizes the behavioral characteristics of the elderly at home through literature reviews,user surveys and comparative analysis.It is divided into four types according to their characteristics: regular behaviors and accidental behaviors.,Sudden behavior and gradual behavior,lay the foundation for the system's classification processing;introduce behavior prediction theory into the research of smart old product design methods,and use scene theory and activity theory to build elderly homes through the coupling relationship between the Scene-activity model,and on this basis,using the human-computer two-way learning process,summaries the human-computer interaction model of the smart home system;taking the basic framework of the traditional behavior prediction system as the starting point,it proposes four levels of acquisition layer,interaction layer,transmission layer and service layer,which combines the technical advantages of AI and 5G to complete The construction of the smart home behavior prediction system for the elderly;on this basis,the "moderate" smart principles and design strategies of the old smart home products are proposed,and related product design practices and design evaluations are carried out.The research proposes a multi-level design method for smart products suitable for the elderly,which provides new solutions for the elderly at home,and makes the intelligent products provide high-quality services and guarantees for the happy life of the elderly to the greatest extent.