Synchronous Head Movement as a Crowd-Behavior-Based Security System

Individuals react in response to internal or external stimuli, whether visual, auditory, gustatory, olfactory, cutaneous, kinesthetic, vestibular. This behavior is not fully utilized infer possible security incidents taking place about take a defined geographical area outside of the range field-of-view systems. Sensors are form human senses. If these natural sensors together with advances deep learning technology, researchers will be equipped build advanced solutions. In this paper, we propose system based on crowd synchronous head movement (SHMOV). The provides an alert incident if occurs among specific by analyzing video stream from camera. We assessed proposed SHMOV using experiment 20 participants and olfactory settings. demonstrated technology’s potential, 100%, 80% detection accuracy alerts issued 9, 24, 47 seconds after start each incident, respectively.