This paper proposes a sleep quality monitoring system based on artificial intelligence, whose basic idea is to collect the relevant data during sleep through the sensors installed in the intelligent devices and analyze the sleep characteristics, which include the data of body movement, respiratory data, snoring, etc. Then, under the synergy of this system, we propose a strategy to regulate sleep disorders by combining “artificial intelligence + physical exercise”. Then, under the synergy of this system, we propose a sleep disorder regulation strategy combining “artificial intelligence + physical exercise”. A total of 500 college students in the freshman and sophomore years of X University were selected as research subjects, and the Pittsburgh Sleep Quality Index (PSQI) and Physical Activity Rating Scale (PARS) were used to investigate the current status of the college students’ sleep quality and physical activity and to explore the specific effects of this control strategy. The results showed that the detection rate of PSQI score ≥8 was 179 (35.80%), and the average PSQI score of college students who participated in physical exercise was 8.31±2.34, which was significantly lower than that of college students who didn’t participate in physical exercise, which was 10.21±3.84. Under the combination of the “Artificial Intelligence + Physical Activity” sleep disorder regulation strategy, after the regulation of sleep quality and physical activity, the results were significantly lower than those of college students who didn’t participate in physical activity, which was significantly lower than those of college students who didn’t participate in physical activity. Under the combination of “artificial intelligence + physical exercise”, the average PSQI score after modulation (8.06±2.84) was also significantly lower than the average PSQI score before modulation (14.39±4.18).
