The invention relates to a user behavior
analysis method and device for burglary prevention of mobile equipment in an exhibition hall, and the method comprises the steps: carrying out the collection and preprocessing of
Bluetooth signal intensity data, acceleration,
angular velocity data, geomagnetic sensor data and ambient light sensor data, and taking the sampling rate of the preprocessed acceleration and
angular velocity data as reference time; mapping the preprocessed
Bluetooth signal intensity data, geomagnetic sensor data and ambient light sensor data to the same
timestamp; constructing a user behavior
database according to the defined user behaviors; a user
behavior recognition result is obtained through the trained CNN-LSTM
hybrid recognition model by means of multi-
modal sensor data collected in real time; a comprehensive
score is calculated by distributing weights for the user
behavior recognition result and the
Bluetooth signal strength distance; and judging whether the comprehensive
score exceeds a preset threshold, and if the comprehensive
score exceeds the preset threshold, triggering an anti-theft alarm. The problems that in an existing
mobile phone display anti-theft
system, the
false alarm rate is high, and a single sensor is prone to being interfered are solved.