Key result
A proposed smart home healthcare system based on middleware and a counter neural network model demonstrated efficiency in simulations.
Why the study?
Smart medical treatment emerged to address hospital workload burdens and doctor-patient relationship imbalances in China.
Proposes a smart home healthcare system based on middleware and counter neural networks to address healthcare imbalances in China.
Smart home health systems may aid monitoring; leaves open need for rigorous cardiovascular trials before adoption.
In recent years, with the upsurge of the smart city construction, smart communities and smart medical services have also witnessed rapid development. The development of smart home has achieved remarkable results. The new term of smart home medical treatment is also accompanied by intelligent home into people’s lives. Smart home health is to improve the smart home to bring new experiences of the public life, combined with the wisdom of the medical under another kind of human considerations. The emergence of smart medical treatment is accompanied by smart home and in an attempt to solve the current imbalance in the relationship between doctors and also patients in China, especially the common medical sanitation in hospitals with high sanction, and the heavy workload of hospitals and the contradiction between doctor-patient relationships. Under this general background, this paper proposes smart home healthcare system based on the middleware and counter neural network model. The simulation proves the efficiency.
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Shao et al. (2020) studied this question. Smart home healthcare system based on middleware and counter neural network model was evaluated on System efficiency. A proposed smart home healthcare system based on middleware and a counter neural network model demonstrated efficiency in simulations.
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