This application relates to the field of fire early warning technology, and in particular to an intelligent fire early warning method and device for student dormitories. The method includes: collecting
smoke concentration data,
gas concentration data,
flame signal data, and human movement status data; determining whether human movement exists based on the human movement status data; if no human movement exists, performing a
fire risk assessment based on comparisons between
smoke concentration data and preset
smoke thresholds, comparisons between
gas concentration data and preset gas thresholds, and whether the
flame signal data is non-zero; if human movement exists, performing a
fire risk assessment based on comparisons between
flame signal data and preset flame thresholds, and whether the flame signal data is continuously rising. Therefore, this method is applicable to situations involving
spontaneous combustion or electrical fires in student dormitories, avoiding false alarms caused by student activities, proactively identifying when students ignite other substances with candles or lighters, and avoiding false alarms due to dust or smog caused by heavy
fog or dormitory cleaning.