1. Scheme Introduction

The core requirement of sleep health monitoring is to accurately capture key data such as sleep cycle, body movements, and abnormal behaviors without interfering with sleep state, so as to provide support for sleep quality assessment and health risk warning. Dark-light full-color technology relies on self-developed AI ISP chip and deep learning algorithm, breaks through the bottleneck of traditional night vision technology relying on light supplement, fuzzy imaging and no color information, and can realize low noise, high-fidelity full-color imaging in 0.001Lux extremely low-light environment, without additional light source to restore sleep scene details. This solution deeply integrates the technology with sleep monitoring scenes to create an integrated solution of "non-sense monitoring + accurate analysis + intelligent response", which adapts to the needs of multiple scenes such as family, medical treatment and pension, provides professional sleep health management services for users, and provides efficient and reliable monitoring tools for the institutional side.

2. user value

Individual users: Obtain non-sensitive and accurate sleep monitoring services, clearly grasp their own sleep status, obtain personalized improvement suggestions, and improve sleep quality

Medical institutions: improve the efficiency and accuracy of diagnosis and treatment of sleep disorders, simplify the monitoring process, reduce the workload of medical staff, and provide data support for the optimization of scientific research and diagnosis and treatment programs.

Elderly care institutions: reduce the labor cost of night care, improve the response speed of abnormal situations, reduce safety risks, and provide data basis for personalized care, improve service quality

Equipment manufacturers: relying on dark full-color technology to create differentiated products, break through the bottleneck of traditional sleep monitoring equipment, expand the home, medical, pension multi-scene market, enhance product competitiveness.