Aiming at problem that heat generated by equipment in longterm high-load working condition in machine room is liable to cause failure and accident

a distributed event-triggered temperature anomaly monitoring and alarm system based on wireless sensor networks（ WSNs） is designed. In the system

use a distributed temperature anomaly monitoring methods

collect sample data of equipment under various temperature anomalies

and extract waveform characteristics of sample temperature curve

and use Bayesian classifer to determine abnormal species

if temperature is abnormal

it alarms. Experimental results show that the system has high accuracy and real-time performance.