Design and Implementation of a Smart Scenic Area Tourist Behavior Safety Monitoring System based on HiSilic
DOI:
https://doi.org/10.54097/hy7qwb90Keywords:
HiSilicon, Tourist Behavior Monitoring, Crowd Flow Statistics, Edge-cloud Collaboration, Edge ComputingAbstract
Inspired by the technical capability of the HiSilicon Hi3516DV300 camera to efficiently run the YOLOv3-tiny model on embedded devices, this solution offers significant advantages of high accuracy, low latency, and low power consumption, providing a valuable reference for the application of lightweight edge intelligence devices in scenic area monitoring. This study analyzes and designs a smart scenic area tourist behavior safety monitoring system based on an “edge-cloud” collaborative architecture. The hardware terminal adopts the HiSilicon Hi3516DV300 smart camera, equipped with an optimized YOLOv3-tiny lightweight object detection model accelerated by TensorRT, to achieve local real-time detection of human bodies and key targets within the scenic area. Simple tracking and trajectory analysis are combined to complete crowd flow statistics and density warning. The model is also tailored for head/body detection and deployed at the edge for real‑time counting. On the cloud side, the Alibaba Cloud IoT platform provides device management, data storage, visual analytics, and remote interaction functionalities.
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