Self-learning sleep optimization system for ai-driven mattresses

A self-learning sleep optimization system for AI-driven mattresses, comprising:

• a multi-sensor data acquisition module configured to collect real-time physiological data of a user during sleep, comprising pressure, temperature, humidity, heart rate, and breathing rate, wherein the module comprises a plurality of sensors distributed across different areas of the mattress;
• an artificial intelligence algorithm module connected to the multi-sensor data acquisition module, comprising deep learning models and reinforcement learning algorithms, configured to analyse the collected data and generate optimized adjustment strategies based on the user's physiological characteristics and sleeping habits;
• a multifunctional adjustment device comprising electric airbags, an air pump, control valves, and temperature control devices, configured to execute the optimized adjustment instructions and facilitate real-time regional adjustment of the mattress, independently adjust the height, softness, and temperature of the mattress in different areas according to the optimized adjustment strategies;
• a self-learning database and remote communication module configured to store the user's long-term sleep data and adjustment records, and to synchronize with a cloud database for data interaction and management across multiple devices;
• and
• wherein the artificial intelligence algorithm module further comprises a deep learning acceleration module utilizing FPGA or ASIC architecture to expedite the operation of deep learning models, and a strategy generation acceleration module to accelerate the reinforcement learning algorithm for real-time mattress adjustment.